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Trifluridine/tipiracil is available on the Australian Pharmaceutical Benefits Scheme for the treatment of patients with metastatic colorectal cancer (mCRC) previously treated with, or not considered candidates for, fluoropyrimidine-, oxaliplatin- and irinotecan-based chemotherapies, anti-vascular endothelial growth factor agents and anti-epidermal growth factor receptor agents. This article reviews trifluridine/tipiracil clinical data and presents practical information on its use in the management of refractory mCRC in Australia. Whereas the primary mechanism of action of fluoropyrimidines such as fluorouracil (5-FU) and capecitabine is enzyme inhibition of nucleotide synthesis, trifluridine/tipiracil primarily acts by incorporation into DNA, resulting in DNA dysfunction. Trifluridine/tipiracil has activity in patients with 5-FU-resistant tumors and can be considered in patients with prior intolerance or toxicity to 5-FU. In the pivotal phase III RECOURSE trial evaluating trifluridine/tipiracil in chemotherapy-refractory mCRC, efficacy benefits were observed across all a priori prognostic subgroups including those defined by age (≥65 and ≥75 years), geographical origin, primary tumor site or KRAS status. Trifluridine/tipiracil therapy benefits appropriately selected patients who have an ECOG performance status of 0 or 1, with no more than mild hepatic impairment or mild-to-moderate renal impairment, and who are capable of adhering to oral therapy safely. Appropriate dosing, monitoring for adverse events and effective management of side effects are essential.

Introduction Pancreatic cancer remains a challenging malignancy due to the high proportion of patients diagnosed at advanced stages and the limited treatment options. This article discusses recent evidence in the management of both localised and advanced pancreatic cancer and offers an expert opinion on current best practice. Areas covered For patients with localised disease, the evidence for adjuvant chemotherapy is discussed as well as emerging neoadjuvant approaches for resectable, borderline resectable and locally advanced disease. Advances in metastatic disease are discussed including cytotoxic chemotherapy, targeted therapies and the role of genomic testing to identify patients with molecular alterations. Reviewed literature included; journal publications, abstracts presented at major international oncology meetings and ongoing clinical trials databases. Expert opinion Pancreatic cancer is a devastating diagnosis and despite recent advances has a very poor prognosis. Only a minority of patients, 20%, are diagnosed with potentially curable disease. The shifting paradigm towards neoadjuvant therapy may improve resectability and survival rates however robust evidence is required. Thus far, there has only been limited progress in advanced stage disease. Genomic testing may potentially identify more treatment targets although limited to small subgroups.

Background Among patients with non-metastatic pancreatic cancer, 80% have high-risk, borderline resectable or locally advanced cancer, with a 5-year overall survival of 12%. MASTERPLAN evaluates the safety and activity of stereotactic body radiotherapy (SBRT) in addition to chemotherapy in these patients. Methods and design MASTERPLAN is a multi-centre randomised phase II trial of 120 patients with histologically confirmed potentially operable pancreatic cancer (POPC) or inoperable pancreatic cancer (IPC). POPC includes patients with borderline resectable or high-risk tumours; IPC is defined as locally advanced or medically inoperable pancreatic cancer. Randomisation is 2:1 to chemotherapy + SBRT (investigational arm) or chemotherapy alone (control arm) by minimisation and stratified by patient cohort (POPC v IPC), planned induction chemotherapy and institution. Chemotherapy can have been commenced ≤28 days prior to randomisation. Both arms receive 6 × 2 weekly cycles of modified FOLFIRINOX (oxaliplatin (85 mg/m2 IV), irinotecan (150 mg/m2), 5-fluorouracil (2400 mg/m2 CIV), leucovorin (50 mg IV bolus)) plus SBRT in the investigational arm. Gemcitabine+nab-paclitaxel is permitted for patients unsuitable for mFOLFIRINOX. SBRT is 40Gy in five fractions with planning quality assurance to occur in real time. Following initial chemotherapy ± SBRT, resectability will be evaluated. For resected patients, adjuvant chemotherapy is six cycles of mFOLFIRINOX. Where gemcitabine+nab-paclitaxel was used initially, the adjuvant treatment is 12 weeks of gemcitabine and capecitabine or mFOLFIRINOX. Unresectable or medically inoperable patients with stable/responding disease will continue with a further six cycles of mFOLFIRINOX or three cycles of gemcitabine+nab-paclitaxel, whatever was used initially. The primary endpoint is 12-month locoregional control. Secondary endpoints are safety, surgical morbidity and mortality, radiological response rates, progression-free survival, pathological response rates, surgical resection rates, R0 resection rate, quality of life, deterioration-free survival and overall survival. Tertiary/correlative objectives are radiological measures of nutrition and sarcopenia, and serial tissue, blood and microbiome samples to be assessed for associations between clinical endpoints and potential predictive/prognostic biomarkers. Interim analysis will review rates of locoregional recurrence, distant failure and death after 40 patients complete 12 months follow-up. Fifteen Australian and New Zealand sites will recruit over a 4-year period, with minimum follow-up period of 12 months. Discussion MASTERPLAN evaluates SBRT in both resectable and unresectable patients with pancreatic ductal adenocarcinoma. Trial registration Australia New Zealand Clinical Trials Registry ACTRN12619000409178, 13/03/2019. Protocol version: 2.0, 19 May 2019

BACKGROUND Advanced biliary tract cancer (ABTC) is a highly aggressive malignancy, with a 5-year overall survival of

The aim of CATS (Cardiotoxicity of Adjuvant Trastuzumab Study) was to prospectively assess clinical, biochemical, and genomic predictors of trastuzumab-related cardiotoxicity (TRC).Cardiac dysfunction is a common adverse effect of trastuzumab. Studies to identify predictive biomarkers for TRC have enrolled heterogeneous populations and yielded mixed results.A total of 222 patients with early-stage human epidermal growth factor receptor 2-positive breast cancer scheduled to receive adjuvant anthracyclines followed by 12 months of trastuzumab were prospectively recruited from 17 centers. Left ventricular ejection fraction (LVEF), troponin T, and N-terminal prohormone of brain natriuretic peptide were measured at baseline, post-anthracycline, and every 3 months during trastuzumab. Germline single-nucleotide polymorphisms in ERBB2, FCGR2A, and FCGR3A were analyzed. TRC was defined as symptomatic heart failure; cardiac death, arrhythmia, or infarction; a decrease in LVEF of15% from baseline; or a decrease in LVEF of10% to 50%.TRC occurred in 18 of 217 subjects (8.3%). Lower pre-anthracycline LVEF and greater interval decline in LVEF from pre- to post-anthracycline were each associated with TRC on multivariate analyses (odds ratio: 3.9 [p = 0.0001] and 7.9 [p 0.0001] for a 5% absolute change in LVEF). Higher post-anthracycline N-terminal prohormone of brain natriuretic peptide level was associated with TRC on univariate but not multivariate analyses. There were no associations between troponin T or ERBB2/FGCR polymorphisms and TRC. Baseline LVEF and LVEF change post-anthracycline were used to generate a "low-risk TRC score" to identify patients with low TRC incidence.Low baseline LVEF and greater LVEF decline post-anthracycline were both independent predictors of TRC. The other biomarkers did not further improve the ability to predict TRC. (Cardiotoxicity of Adjuvant Trastuzumab [CATS]; NCT00858039).

Objective We aimed to define preoperative clinical and molecular characteristics that would allow better patient selection for operative resection. Background Although we use molecular selection methods for systemic targeted therapies, these principles are not applied to surgical oncology. Improving patient selection is of vital importance for the operative treatment of pancreatic cancer (pancreatic ductal adenocarcinoma). Although surgery is the only chance of long-term survival, 80% still succumb to the disease and approximately 30% die within 1 year, often sooner than those that have unresected local disease. Method In 3 independent pancreatic ductal adenocarcinoma cohorts (total participants = 1184) the relationship between aberrant expression of prometastatic proteins S100A2 and S100A4 and survival was assessed. A preoperative nomogram based on clinical variables available before surgery and expression of these proteins was constructed and compared to traditional measures, and a postoperative nomogram. Results High expression of either S100A2 or S100A4 was independent poor prognostic factors in a training cohort of 518 participants. These results were validated in 2 independent patient cohorts (Glasgow, n = 198; Germany, n = 468). Aberrant biomarker expression stratified the cohorts into 3 distinct prognostic groups. A preoperative nomogram incorporating S100A2 and S100A4 expression predicted survival and nomograms derived using postoperative clinicopathological variables. Conclusions Of those patients with a poor preoperative nomogram score, approximately 50% of patients died within a year of resection. Nomograms have the potential to improve selection for surgery and neoadjuvant therapy, avoiding surgery in aggressive disease, and justifying more extensive resections in biologically favorable disease.

Background The Irinotecan Cetuximab Evaluation and Cetuximab Response Evaluation (ICECREAM) study assessed the efficacy of cetuximab monotherapy compared with cetuximab combined with chemotherapy for quadruple wild-type (KRAS, NRAS, BRAF, or P13KCA exon 20) metastatic colorectal cancer. Patients and Methods Patients were enrolled in an open-label, multicenter, phase II trial and randomly assigned to cetuximab 400 mg/m2, then 250 mg/m2 cetuximab weekly, with or without irinotecan 180 mg/m2 every 2 weeks. The primary endpoint was 6-month progression-free survival; secondary endpoints were response rate, overall survival, toxicity, and quality of life. Results From 2012 to 2016, 48 patients were recruited. Two were ineligible, and 2 were not evaluable for response. Characteristics were balanced, except gender (male, 62% vs. 72%) and primary sidedness (left, 95% vs. 68%). For cetuximab compared with cetuximab-irinotecan, progression-free survival was 14% versus 41% (hazard ratio, 0.39; 95% confidence interval, 0.20-0.78; P = .008); response rate was 10% (2 partial responses) versus 38% (1 complete, 8 partial); P = .04. Grade 3 to 4 toxicities were less with cetuximab monotherapy (23% vs. 50%); global and specific quality of life scores did not differ. Conclusion In comparison with cetuximab alone, cetuximab plus irinotecan increases the response rate and delays progression in irinotecan-resistant RAS wild-type colorectal cancer. This echoes data from molecularly unselected patients.

Background & Aims Continuing recalcitrance to therapy cements pancreatic cancer (PC) as the most lethal malignancy, which is set to become the second leading cause of cancer death in our society. The study aim was to investigate the association between DNA damage response (DDR), replication stress, and novel therapeutic response in PC to develop a biomarker-driven therapeutic strategy targeting DDR and replication stress in PC. Methods We interrogated the transcriptome, genome, proteome, and functional characteristics of 61 novel PC patient–derived cell lines to define novel therapeutic strategies targeting DDR and replication stress. Validation was done in patient-derived xenografts and human PC organoids. Results Patient-derived cell lines faithfully recapitulate the epithelial component of pancreatic tumors, including previously described molecular subtypes. Biomarkers of DDR deficiency, including a novel signature of homologous recombination deficiency, cosegregates with response to platinum (P < .001) and PARP inhibitor therapy (P < .001) in vitro and in vivo. We generated a novel signature of replication stress that predicts response to ATR (P < .018) and WEE1 inhibitor (P < .029) treatment in both cell lines and human PC organoids. Replication stress was enriched in the squamous subtype of PC (P < .001) but was not associated with DDR deficiency. Conclusions Replication stress and DDR deficiency are independent of each other, creating opportunities for therapy in DDR-proficient PC and after platinum therapy., Graphical abstract

Pancreatic ductal adenocarcinoma (PDAC) can be divided into transcriptomic subtypes with two broad lineages referred to as classical (pancreatic) and squamous. We find that these two subtypes are driven by distinct metabolic phenotypes. Loss of genes that drive endodermal lineage specification, HNF4A and GATA6, switch metabolic profiles from classical (pancreatic) to predominantly squamous, with glycogen synthase kinase 3 beta (GSK3β) a key regulator of glycolysis. Pharmacological inhibition of GSK3β results in selective sensitivity in the squamous subtype; however, a subset of these squamous patient-derived cell lines (PDCLs) acquires rapid drug tolerance. Using chromatin accessibility maps, we demonstrate that the squamous subtype can be further classified using chromatin accessibility to predict responsiveness and tolerance to GSK3β inhibitors. Our findings demonstrate that distinct patterns of chromatin accessibility can be used to identify patient subgroups that are indistinguishable by gene expression profiles, highlighting the utility of chromatin-based biomarkers for patient selection in the treatment of PDAC.

MC3 Working Group: Rehan Akbani21, Pavana Anur22, Matthew H. Bailey1,2,3, Alex Buchanan9, Kami Chiotti9, Kyle Covington12,23, Allison Creason9, Li Ding1,2,3,20, Kyle Ellrott9, Yu Fan21, Steven Foltz1,2, Gad Getz8,14,15,16, Walker Hale12, David Haussler24,25, Julian M. Hess8,26, Carolyn M. Hutter27, Cyriac Kandoth28, Katayoon Kasaian29,30, Melpomeni Kasapi27, Dave Larson1 , Ignaty Leshchiner8, John Letaw31, Singer Ma32, Michael D. McLellan1,3,20, Yifei Men32, Gordon B. Mills33,34, Beifang Niu35, Myron Peto22, Amie Radenbaugh24, Sheila M. Reynolds36, Gordon Saksena8, Heidi Sofia27, Chip Stewart8, Adam J. Struck31, Joshua M. Stuart24,37, Wenyi Wang21, John N. Weinstein38, David A. Wheeler12,13, Christopher K. Wong24,39, Liu Xi12 & Kai Ye40,41 21Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 22Molecular and Medical Genetics, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 23Castle Biosciences Inc, Friendswood, TX 77546, USA. 24UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 25Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 26Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02114, USA. 27National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA. 28Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. 29Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada. 30Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada. 31Computational Biology Program, School of Medicine, Oregon Health and Science University, Portland, OR 97239, USA. 32DNAnexus Inc, Mountain View, CA 94040, USA. 33Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA. 34Precision Oncology, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 35Computer Network Information Center, Chinese Academy of Sciences, Beijing, China. 36Institute for Systems Biology, Seattle, WA 98109, USA. 37Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 38Department of Bioinformatics and Computational Biology and Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 39Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 40School of Elect, PCAWG novel somatic mutation calling methods working group: Matthew H. Bailey1,2,3, Beifang Niu35, Matthias Bieg42,43, Paul C. Boutros6,44,45,46, Ivo Buchhalter43,47,48, Adam P. Butler49, Ken Chen50, Zechen Chong51, Li Ding1,2,3,20, Oliver Drechsel52,53, Lewis Jonathan Dursi6,7, Roland Eils47,48,54,55, Kyle Ellrott9, Shadrielle M. G. Espiritu6, Yu Fan21, Robert S. Fulton1,3,20, Shengjie Gao56, Josep L. l. Gelpi57,58, Mark B. Gerstein5,18,19, Gad Getz8,14,15,16, Santiago Gonzalez59,60, Ivo G. Gut52,61, Faraz Hach62,63, Michael C. Heinold47,48, Julian M. Hess8,26, Jonathan Hinton49, Taobo Hu64, Vincent Huang6, Yi Huang65,66, Barbara Hutter43,67,68, David R. Jones49, Jongsun Jung69, Natalie Jäger47, Hyung-Lae Kim70, Kortine Kleinheinz47,48, Sushant Kumar5,19, Yogesh Kumar64, Christopher M. Lalansingh6, Ignaty Leshchiner8, Ivica Letunic71, Dimitri Livitz8, Eric Z. Ma64, Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Michael D. McLellan1,3,20, Andrew Menzies49, Ana Milovanovic57, Morten Muhlig Nielsen73, Stephan Ossowski52,53,74, Nagarajan Paramasivam43,47, Jakob Skou Pedersen73,75, Marc D. Perry76,77, Montserrat Puiggròs57, Keiran M. Raine49, Esther Rheinbay8,14,72, Romina Royo57, S. Cenk Sahinalp62,78,79, Gordon Saksena8, Iman Sarrafi62,78, Matthias Schlesner47,80, Jared T. Simpson6,17, Lucy Stebbings49, Chip Stewart8, Miranda D. Stobbe52,61, Jon W. Teague49, Grace Tiao8, David Torrents57,81, Jeremiah A. Wala8,14,82, Jiayin Wang1,40,66, Wenyi Wang21, Sebastian M. Waszak60, Joachim Weischenfeldt60,83,84, Michael C. Wendl1,10,11, Johannes Werner47,85, Zhenggang Wu64, Hong Xue64, Sergei Yakneen60, Takafumi N. Yamaguchi6, Kai Ye40,41, Venkata D. Yellapantula20,86, Christina K. Yung76 & Junjun Zhang76, PCAWG Consortium: Lauri A. Aaltonen87, Federico Abascal49, Adam Abeshouse88, Hiroyuki Aburatani89, David J. Adams49, Nishant Agrawal90, Keun Soo Ahn91, Sung-Min Ahn92, Hiroshi Aikata93, Rehan Akbani21, Kadir C. Akdemir50, Hikmat Al-Ahmadie88, Sultan T. Al-Sedairy94, Fatima Al-Shahrour95, Malik Alawi96,97, Monique Albert98, Kenneth Aldape99,100, Ludmil B. Alexandrov49,101,102, Adrian Ally30, Kathryn Alsop103, Eva G. Alvarez104,105,106, Fernanda Amary107, Samirkumar B. Amin108,109,110, Brice Aminou76, Ole Ammerpohl111,112, Matthew J. Anderson113, Yeng Ang114, Davide Antonello115, Pavana Anur22, Samuel Aparicio116, Elizabeth L. Appelbaum1,117, Yasuhito Arai118, Axel Aretz119, Koji Arihiro93, Shun-ichi Ariizumi120, Joshua Armenia121, Laurent Arnould122, Sylvia Asa123,124, Yassen Assenov125, Gurnit Atwal6,126,127, Sietse Aukema112,128, J. Todd Auman129, Miriam R. Aure130, Philip Awadalla6,126, Marta Aymerich131, Gary D. Bader126, Adrian Baez-Ortega132, Matthew H. Bailey1,2,3, Peter J. Bailey133, Miruna Balasundaram30, Saianand Balu134, Pratiti Bandopadhayay8,135,136, Rosamonde E. Banks137, Stefano Barbi138, Andrew P. Barbour139,140, Jonathan Barenboim6, Jill Barnholtz-Sloan141,142, Hugh Barr143, Elisabet Barrera59, John Bartlett98,144, Javier Bartolome57, Claudio Bassi115, Oliver F. Bathe145,146, Daniel Baumhoer147, Prashant Bavi148, Stephen B. Baylin149,150, Wojciech Bazant59, Duncan Beardsmore151, Timothy A. Beck152,153, Sam Behjati49, Andreas Behren154, Beifang Niu35, Cindy Bell155, Sergi Beltran52,61, Christopher Benz156, Andrew Berchuck157, Anke K. Bergmann158, Erik N. Bergstrom101,102, Benjamin P. Berman159,160,161, Daniel M. Berney162, Stephan H. Bernhart163,164,165, Rameen Beroukhim8,14,82, Mario Berrios166, Samantha Bersani167, Johanna Bertl73,168, Miguel Betancourt169, Vinayak Bhandari6,44, Shriram G. Bhosle49, Andrew V. Biankin133,170,171,172, Matthias Bieg42,43, Darell Bigner173, Hans Binder163,164, Ewan Birney59, Michael Birrer72, Nidhan K. Biswas174, Bodil Bjerkehagen147,175, Tom Bodenheimer134, Lori Boice176, Giada Bonizzato177, Johann S. De Bono178, Arnoud Boot179,180, Moiz S. Bootwalla166, Ake Borg181, Arndt Borkhardt182, Keith A. Boroevich183,184, Ivan Borozan6, Christoph Borst185, Marcus Bosenberg186, Mattia Bosio52,53,57, Jacqueline Boultwood187, Guillaume Bourque188,189, Paul C. Boutros6,44,45,46, G. Steven Bova190, David T. Bowen49,191, Reanne Bowlby30, David D. L. Bowtell103, Sandrine Boyault192, Rich Boyce59, Jeffrey Boyd193, Alvis Brazma59, Paul Brennan194, Daniel S. Brewer195,196, Arie B. Brinkman197, Robert G. Bristow44,198,199,200,201, Russell R. Broaddus99, Jane E. Brock202, Malcolm Brock203, Annegien Broeks204, Angela N. Brooks8,24,37,82, Denise Brooks30, Benedikt Brors67,205,206, Søren Brunak207,208, Timothy J. C. Bruxner113,209, Alicia L. Bruzos104,105,106, Alex Buchanan9, Ivo Buchhalter43,47,48, Christiane Buchholz210, Susan Bullman8,82, Hazel Burke211, Birgit Burkhardt212, Kathleen H. Burns213,214, John Busanovich8,215, Carlos D. Bustamante216,217, Adam P. Butler49, Atul J. Butte218, Niall J. Byrne76, Anne-Lise Børresen-Dale130,219, Samantha J. Caesar-Johnson220, Andy Cafferkey59, Declan Cahill221, Claudia Calabrese59,60, Carlos Caldas222,223, Fabien Calvo224, Niedzica Camacho178, Peter J. Campbell49,225, Elias Campo226,227, Cinzia Cantù177, Shaolong Cao21, Thomas E. Carey228, Joana Carlevaro-Fita229,230,231, Rebecca Carlsen30, Ivana Cataldo167,177, Mario Cazzola232, Jonathan Cebon154, Robert Cerfolio233, Dianne E. Chadwick234, Dimple Chakravarty235, Don Chalmers236, Calvin Wing Yiu Chan47,237, Kin Chan238, Michelle Chan-Seng-Yue148, Vishal S. Chandan239, David K. Chang133,170, Stephen J. Chanock240, Lorraine A. Chantrill170,241, Aurélien Chateigner76,242, Nilanjan Chatterjee149,243, Kazuaki Chayama93, Hsiao-Wei Chen114,121, Jieming Chen218, Ken Chen50, Yiwen Chen21, Zhaohong Chen244, Andrew D. Cherniack8,82, Jeremy Chien245, Yoke-Eng Chiew246,247, Suet-Feung Chin222,223, Juok Cho8, Sunghoon Cho248, Jung Kyoon Choi249, Wan Choi250, Christine Chomienne251, Zechen Chong51, Su Pin Choo252, Angela Chou170,246, Angelika N. Christ113, Elizabeth L. Christie103, Eric Chuah30, Carrie Cibulskis8, Kristian Cibulskis8, Sara Cingarlini253, Peter Clapham49, Alexander Claviez254, Sean Cleary148,255, Nicole Cloonan256, Marek Cmero257,258,259, Colin C. Collins62, Ashton A. Connor255,260, Susanna L. Cooke133, Colin S. Cooper178,196,261, Leslie Cope149, Vincenzo Corbo138,177, Matthew G. Cordes1,262, Stephen M. Cordner263, Isidro Cortés-Ciriano264,265,266, Kyle Covington12,23, Prue A. Cowin267, Brian Craft24, David Craft8,268, Chad J. Creighton269, Yupeng Cun270, Erin Curley271, Ioana Cutcutache179,180, Karolina Czajka272, Bogdan Czerniak99,273, Rebecca A. Dagg274, Ludmila Danilova149, Maria Vittoria Davi275, Natalie R. Davidson276,277,278,279,280, Helen Davies49,281,282, Ian J. Davis283, Brandi N. Davis-Dusenbery284, Kevin J. Dawson49, Francisco M. De La Vega216,217,285, Ricardo De Paoli-Iseppi211, Timothy Defreitas8, Angelo P. Dei Tos286, Olivier Delaneau287,288,289, John A. Demchok220, Jonas Demeulemeester290,291, German M. Demidov52,53,74, Deniz Demircioğlu292,293, Nening M. Dennis221, Robert E. Denroche148, Stefan C. Dentro49,290,294, Nikita Desai76, Vikram Deshpande72, Amit G. Deshwar295, Christine Desmedt296,297, Jordi Deu-Pons298,299, Noreen Dhalla30, Neesha C. Dhani300, Priyanka Dhingra301,302, Rajiv Dhir303, Anthony DiBiase304, Klev Diamanti305, Li Ding1,2,3,20, Shuai Ding306, Huy Q. Dinh159, Luc Dirix307, HarshaVardhan Doddapaneni12, Nilgun Donmez62,78, Michelle T. Dow244, Ronny Drapkin308, Oliver Drechsel52,53, Ruben M. Drews223, Serge Serge49, Tim Dudderidge150,221, Ana Dueso-Barroso57, Andrew J. Dunford8, Michael Dunn309, Lewis Jonathan Dursi6,7, Fraser R. Duthie133,310, Ken Dutton-Regester311, Jenna Eagles272, Douglas F. Easton312,313, Stuart Edmonds314, Paul A. Edwards223,315, Sandra E. Edwards178, Rosalind A. Eeles178,221, Anna Ehinger316, Juergen Eils54,55, Roland Eils47,48,54,55, Adel El-Naggar99,273, Matthew Eldridge223, Kyle Ellrott9, Serap Erkek60, Georgia Escaramis53,317,318, Shadrielle M. G. Espiritu6, Xavier Estivill53,319, Dariush Etemadmoghadam103, Jorunn E. Eyfjord320, Bishoy M. Faltas280, Daiming Fan321, Yu Fan21, William C. Faquin72, Claudiu Farcas244, Matteo Fassan322, Aquila Fatima323, Francesco Favero324, Nodirjon Fayzullaev76, Ina Felau220, Sian Fereday103, Martin L. Ferguson325, Vincent Ferretti76,326, Lars Feuerbach205, Matthew A. Field327, J. Lynn Fink57,113, Gaetano Finocchiaro328, Cyril Fisher221, Matthew W. Fittall290, Anna Fitzgerald329, Rebecca C. Fitzgerald282, Adrienne M. Flanagan330, Neil E. Fleshner331, Paul Flicek59, John A. Foekens332, Kwun M. Fong333, Nuno A. Fonseca59,334, Christopher S. Foster335,336, Natalie S. Fox6, Michael Fraser6, Scott Frazer8, Milana Frenkel-Morgenstern337, William Friedman338, Joan Frigola298, Catrina C. Fronick1,262, Akihiro Fujimoto184, Masashi Fujita184, Masashi Fukayama339, Lucinda A. Fulton1 , Robert S. Fulton1,3,20, Mayuko Furuta184, P. Andrew Futreal340, Anja Füllgrabe59, Stacey B. Gabriel8, Steven Gallinger148,255,260, Carlo Gambacorti-Passerini341, Jianjiong Gao121, Shengjie Gao56, Levi Garraway82, Øystein Garred342, Erik Garrison49, Dale W. Garsed103, Nils Gehlenborg8,343, Josep L. l. Gelpi57,58, Joshy George110, Daniela S. Gerhard344, Clarissa Gerhauser345, Jeffrey E. Gershenwald346,347, Mark B. Gerstein5,18,19, Moritz Gerstung59,60, Gad Getz8,14,15,16, Mohammed Ghori49, Ronald Ghossein348, Nasra H. Giama349, Richard A. Gibbs12, Anthony J. Gill170,350, Pelvender Gill351, Dilip D. Giri348, Dominik Glodzik49, Vincent J. Gnanapragasam352,353, Maria Elisabeth Goebler354, Mary J. Goldman24, Carmen Gomez355, Santiago Gonzalez59,60, Abel Gonzalez-Perez298,299,356, Dmitry A. Gordenin357, James Gossage358, Kunihito Gotoh359, Ramaswamy Govindan3, Dorthe Grabau360, Janet S. Graham133,361, Robert C. Grant148,260, Anthony R. Green315, Eric Green27, Liliana Greger59, Nicola Grehan282, Sonia Grimaldi177, Sean M. Grimmond362, Robert L. Grossman363, Adam Grundhoff97,364, Gunes Gundem88, Qianyun Guo75, Manaswi Gupta8, Shailja Gupta365, Ivo G. Gut52,61, Marta Gut52,61, Jonathan Göke292,366, Gavin Ha8, Andrea Haake111, David Haan37, Siegfried Haas185, Kerstin Haase290, James E. Haber367, Nina Habermann60, Faraz Hach62,63, Syed Haider6, Natsuko Hama118, Freddie C. Hamdy351, Anne Hamilton267, Mark P. Hamilton368, Leng Han369, George B. Hanna370, Martin Hansmann371, Nicholas J. Haradhvala8,72, Olivier Harismendy102,372, Ivon Harliwong113, Arif O. Harmanci5,373, Eoghan Harrington374, Takanori Hasegawa375, David Haussler24,25, Steve Hawkins223, Shinya Hayami376, Shuto Hayashi375, D. Neil Hayes134,377,378, Stephen J. Hayes379,380, Nicholas K. Hayward211,311, Steven Hazell221, Yao He381, Allison P. Heath382, Simon C. Heath52,61, David Hedley300, Apurva M. Hegde38, David I. Heiman8, Michael C. Heinold47,48, Zachary Heins88, Lawrence E. Heisler152, Eva Hellstrom-Lindberg383, Mohamed Helmy384, Seong Gu Heo385, Austin J. Hepperla134, José María Heredia-Genestar386, Carl Herrmann47,48,387, Peter Hersey211, Julian M. Hess8,26, Holmfridur Hilmarsdottir320, Jonathan Hinton49, Satoshi Hirano388, Nobuyoshi Hiraoka389, Katherine A. Hoadley134,390, Asger Hobolth75,168, Ermin Hodzic78, Jessica I. Hoell182, Steve Hoffmann163,164,165,391, Oliver Hofmann392, Andrea Holbrook166, Aliaksei Z. Holik53, Michael A. Hollingsworth393, Oliver Holmes209,311, Robert A. Holt30, Chen Hong205,237, Eun Pyo Hong385, Jongwhi H. Hong394, Gerrit K. Hooijer395, Henrik Hornshøj73, Fumie Hosoda118, Yong Hou56,396, Volker Hovestadt397, William Howat352, Alan P. Hoyle134, Ralph H. Hruban149, Jianhong Hu12, Taobo Hu64, Xing Hua240, Kuan-lin Huang1,398, Mei Huang176, Mi Ni Huang179,180, Vincent Huang6, Yi Huang65,66, Wolfgang Huber60, Thomas J. Hudson272,399, Michael Hummel400, Jillian A. Hung246,247, David Huntsman401, Ted R. Hupp402, Jason Huse88, Matthew R. Huska403, Barbara Hutter43,67,68, Carolyn M. Hutter27, Daniel Hübschmann48,54,404,405,406, Christine A. Iacobuzio-Donahue348, Charles David Imbusch205, Marcin Imielinski407,408, Seiya Imoto375, William B. Isaacs409, Keren Isaev6,44, Shumpei Ishikawa410, Murat Iskar397, S. M. Ashiqul Islam244, Michael Ittmann411,412,413, Sinisa Ivkovic284, Jose M. G. Izarzugaza414, Jocelyne Jacquemier415, Valerie Jakrot211, Nigel B. Jamieson133,172,416, Gun Ho Jang148, Se Jin Jang417, Joy C. Jayaseelan12, Reyka Jayasinghe1 , Stuart R. Jefferys134, Karine Jegalian418, Jennifer L. Jennings419, Seung-Hyup Jeon250, Lara Jerman60,420, Yuan Ji421,422, Wei Jiao6, Peter A. Johansson311, Amber L. Johns170, Jeremy Johns272, Rory Johnson230,423, Todd A. Johnson183, Clemency Jolly290, Yann Joly424, Jon G. Jonasson320, Corbin D. Jones425, David R. Jones49, David T. W. Jones426,427, Nic Jones428, Steven J. M. Jones30, Jos Jonkers204, Young Seok Ju49,249, Hartmut Juhl429, Jongsun Jung69, Malene Juul73, Randi Istrup Juul73, Sissel Juul374, Natalie Jäger47, Rolf Kabbe47, Andre Kahles276,277,278,279,430, Abdullah Kahraman431,432,433, Vera B. Kaiser434, Hojabr Kakavand211, Sangeetha Kalimuthu148, Christof von Kalle405, Koo Jeong Kang91, Katalin Karaszi351, Beth Karlan435, Rosa Karlić436, Dennis Karsch437, Katayoon Kasaian29,30, Karin S. Kassahn113,438, Hitoshi Katai439, Mamoru Kato440, Hiroto Katoh410, Yoshiiku Kawakami93, Jonathan D. Kay117, Stephen H. Kazakoff209,311, Marat D. Kazanov441,442,443, Maria Keays59, Electron Kebebew444,445, Richard F. Kefford446, Manolis Kellis8,447, James G. Kench170,350,448, Catherine J. Kennedy246,247, Jules N. A. Kerssemakers47, David Khoo273, Vincent Khoo221, Narong Khuntikeo115,449, Ekta Khurana301,302,450,451, Helena Kilpinen117, Hark Kyun Kim452, Hyung-Lae Kim70, Hyung-Yong Kim415, Hyunghwan Kim250, Jaegil Kim8, Jihoon Kim453, Jong K. Kim454, Youngwook Kim455,456, Tari A. King457,458,459, Wolfram Klapper128, Kortine Kleinheinz47,48, Leszek J. Klimczak460, Stian Knappskog49,461, Michael Kneba437, Bartha M. Knoppers424, Youngil Koh462,463, Jan Komorowski305,464, Daisuke Komura410, Mitsuhiro Komura375, Gu Kong415, Marcel Kool426,465, Jan O. Korbel59,60, Viktoriya Korchina12, Andrey Korshunov465, Michael Koscher465, Roelof Koster466, Zsofia Kote-Jarai178, Antonios Koures244, Milena Kovacevic284, Barbara Kremeyer49, Helene Kretzmer164,165, Markus Kreuz467, Savitri Krishnamurthy99,468, Dieter Kube469, Kiran Kumar8, Pardeep Kumar221, Sushant Kumar5,19, Yogesh Kumar64, Ritika Kundra114,121, Kirsten Kübler8,14,72, Ralf Küppers470, Jesper Lagergren383,471, Phillip H. Lai166, Peter W. Laird472, Sunil R. Lakhani473, Christopher M. Lalansingh6, Emilie Lalonde6, Fabien C. Lamaze6, Adam Lambert351, Eric Lander8, Pablo Landgraf474,475, Luca Landoni115, Anita Langerød130, Andrés Lanzós230,231,423, Denis Larsimont476, Erik Larsson477, Mark Lathrop189, Loretta M. S. Lau478, Chris Lawerenz55, Rita T. Lawlor177, Michael S. Lawrence8,72,183, Alexander J. Lazar99,108, Xuan Le479, Darlene Lee30, Donghoon Lee5, Eunjung Alice Lee480, Hee Jin Lee417, Jake June-Koo Lee264,266, Jeong-Yeon Lee481, Juhee Lee482, Ming Ta Michael Lee340, Henry Lee-Six49, Kjong-Van Lehmann276,277,278,279,430, Hans Lehrach483, Dido Lenze400, Conrad R. Leonard209,311, Daniel A. Leongamornlert49,178, Ignaty Leshchiner8, Louis Letourneau484, Ivica Letunic71, Douglas A. Levine88,485, Lora Lewis12, Tim Ley486, Chang Li56,396, Constance H. Li6,44, Haiyan Irene Li30, Jun Li21, Lin Li56, Shantao Li5, Siliang Li56,396, Xiaobo Li56,396, Xiaotong Li5, Xinyue Li56, Yilong Li49, Han Liang21, Sheng-Ben Liang234, Peter Lichter68,397, Pei Lin8, Ziao Lin8,487, W. M. Linehan488, Ole Christian Lingjærde489, Dongbing Liu56,396, Eric Minwei Liu88,301,302, Fei-Fei Liu201,490, Fenglin Liu381,491, Jia Liu492, Xingmin Liu56,396, Julie Livingstone6, Dimitri Livitz8, Naomi Livni221, Lucas Lochovsky5,19,110, Markus Loeffler467, Georgina V. Long211, Armando Lopez-Guillermo493, Shaoke Lou5,19, David N. Louis72, Laurence B. Lovat117, Yiling Lu38, Yong-Jie Lu162,494, Youyong Lu495,496,497, Claudio Luchini167, Ilinca Lungu144,148, Xuemei Luo152, Hayley J. Luxton117, Andy G. Lynch223,315,498, Lisa Lype36, Cristina López111,112, Carlos López-Otín499, Eric Z. Ma64, Yussanne Ma30, Gaetan MacGrogan500, Shona MacRae501, Geoff Macintyre223, Tobias Madsen73, Kazuhiro Maejima184, Andrea Mafficini177, Dennis T. Maglinte166,502, Arindam Maitra174, Partha P. Majumder174, Luca Malcovati232, Salem Malikic62,78, Giuseppe Malleo115, Graham J. Mann211,246,503, Luisa Mantovani-Löffler504, Kathleen Marchal505,506, Giovanni Marchegiani115, Elaine R. Mardis1,193,507, Adam A. Margolin31, Maximillian G. Marin37, Florian Markowetz223,315, Julia Markowski403, Jeffrey Marks508, Tomas Marques-Bonet61,81,386,509, Marco A. Marra30, Luke Marsden351, John W. M. Martens332, Sancha Martin49,510, Jose I. Martin-Subero81,511, Iñigo Martincorena49, Alexander Martinez-Fundichely301,302,451 Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Charlie E. Massie223, Thomas J. Matthew37, Lucy Matthews178, Erik Mayer221,512, Simon Mayes513, Michael Mayo30, Faridah Mbabaali272, Karen McCune514, Ultan McDermott49, Patrick D. McGillivray19, Michael D. McLellan1,3,20, John D. McPherson148,272,515, John R. McPherson179,180, Treasa A. McPherson260, Samuel R. Meier8, Alice Meng516, Shaowu Meng134, Andrew Menzies49, Neil D. Merrett115,517, Sue Merson178, Matthew Meyerson8,14,82, William U. Meyerson4,5, Piotr A. Mieczkowski518, George L. Mihaiescu76, Sanja Mijalkovic284, Ana Mijalkovic Mijalkovic-Lazic284, Tom Mikkelsen519, Michele Milella253, Linda Mileshkin103, Christopher A. Miller1 , David K. Miller113,170, Jessica K. Miller272, Gordon B. Mills33,34, Ana Milovanovic57, Sarah Minner520, Marco Miotto115, Gisela Mir Arnau267, Lisa Mirabello240, Chris Mitchell103, Thomas J. Mitchell49,315,352, Satoru Miyano375, Naoki Miyoshi375, Shinichi Mizuno521, Fruzsina Molnár-Gábor522, Malcolm J. Moore300, Richard A. Moore30, Sandro Morganella49, Quaid D. Morris127,490, Carl Morrison523,524, Lisle E. Mose134, Catherine D. Moser349, Ferran Muiños298,299, Loris Mularoni298,299, Andrew J. Mungall30, Karen Mungall30, Elizabeth A. Musgrove133, Ville Mustonen525,526,527, David Mutch528, Francesc Muyas52,53,74, Donna M. Muzny12, Alfonso Muñoz59, Jerome Myers529, Ola Myklebost461, Peter Möller530, Genta Nagae89, Adnan M. Nagrial170, Hardeep K. Nahal-Bose76, Hitoshi Nakagama531, Hidewaki Nakagawa184, Hiromi Nakamura118, Toru Nakamura388, Kaoru Nakano184, Tannistha Nandi532, Jyoti Nangalia49, Mia Nastic284, Arcadi Navarro61,81,386, Fabio C. P. Navarro19, David E. Neal223,352, Gerd Nettekoven533, Felicity Newell209,311, Steven J. Newhouse59, Yulia Newton37, Alvin Wei Tian Ng534, Anthony Ng535, Jonathan Nicholson49, David Nicol221, Yongzhan Nie321,536, G. Petur Nielsen72, Morten Muhlig Nielsen73, Serena Nik-Zainal49,281,282,537, Michael S. Noble8, Katia Nones209,311, Paul A. Northcott538, Faiyaz Notta148,539, Brian D. O’Connor76,540, Peter O’Donnell541, Maria O’Donovan282, Sarah O’Meara49, Brian Patrick O’Neill542, J. Robert O’Neill543, David Ocana59, Angelica Ochoa88, Layla Oesper544, Christopher Ogden221, Hideki Ohdan93, Kazuhiro Ohi375, Lucila Ohno-Machado244, Karin A. Oien523,545, Akinyemi I. Ojesina546,547,548, Hidenori Ojima549, Takuji Okusaka550, Larsson Omberg551, Choon Kiat Ong552, Stephan Ossowski52,53,74, German Ott553, B. F. Francis Ouellette76,554, Christine P’ng6, Marta Paczkowska6, Salvatore Paiella115, Chawalit Pairojkul523, Marina Pajic170, Qiang Pan-Hammarström56,555, Elli Papaemmanuil49, Irene Papatheodorou59, Nagarajan Paramasivam43,47, Ji Wan Park385, Joong-Won Park556, Keunchil Park557,558, Kiejung Park559, Peter J. Park264,266, Joel S. Parker518, Simon L. Parsons124, Harvey Pass560, Danielle Pasternack272, Alessandro Pastore276, Ann-Marie Patch209,311, Iris Pauporté251, Antonio Pea115, John V. Pearson209,311, Chandra Sekhar Pedamallu8,14,82, Jakob Skou Pedersen73,75, Paolo Pederzoli115, Martin Peifer270, Nathan A. Pennell561, Charles M. Perou129,518, Marc D. Perry76,77, Gloria M. Petersen562, Myron Peto22, Nicholas Petrelli563, Robert Petryszak59, Stefan M. Pfister426,465,564, Mark Phillips424, Oriol Pich298,299, Hilda A. Pickett478, Todd D. Pihl565, Nischalan Pillay566, Sarah Pinder567, Mark Pinese170, Andreia V. Pinho568, Esa Pitkänen60, Xavier Pivot569, Elena Piñeiro-Yáñez95, Laura Planko533, Christoph Plass345, Paz Polak8,14,15, Tirso Pons570, Irinel Popescu571, Olga Potapova572, Aparna Prasad52, Shaun R. Preston573, Manuel Prinz47, Antonia L. Pritchard311, Stephenie D. Prokopec6, Elena Provenzano574, Xose S. Puente499, Sonia Puig176, Montserrat Puiggròs57, Sergio Pulido-Tamayo505,506, Gulietta M. Pupo246, Colin A. Purdie575, Michael C. Quinn209,311, Raquel Rabionet52,53,576, Janet S. Rader577, Bernhard Radlwimmer397, Petar Radovic284, Benjamin Raeder60, Keiran M. Raine49, Manasa Ramakrishna49, Kamna Ramakrishnan49, Suresh Ramalingam578, Benjamin J. Raphael579, W. Kimryn Rathmell580, Tobias Rausch60, Guido Reifenberger475, Jüri Reimand6,44, Jorge Reis-Filho348, Victor Reuter348, Iker Reyes-Salazar298, Matthew A. Reyna579, Sheila M. Reynolds36, Esther Rheinbay8,14,72, Yasser Riazalhosseini189, Andrea L. Richardson323, Julia Richter111,128, Matthew Ringel581, Markus Ringnér181, Yasushi Rino582, Karsten Rippe405, Jeffrey Roach583, Lewis R. Roberts349, Nicola D. Roberts49, Steven A. Roberts584, A. Gordon Robertson30, Alan J. Robertson113, Javier Bartolomé Rodriguez57, Bernardo Rodriguez-Martin104,105,106, F. Germán Rodríguez-González83,332, Michael H. A. Roehrl44,123,148,234,585,586, Marius Rohde587, Hirofumi Rokutan440, Gilles Romieu588, Ilse Rooman170, Tom Roques262, Daniel Rosebrock8, Mara Rosenberg8,72, Philip C. Rosenstiel589, Andreas Rosenwald590, Edward W. Rowe221,591, Romina Royo57, Steven G. Rozen179,180,592, Yulia Rubanova17,127, Mark A. Rubin423,593,594,595,596, Carlota Rubio-Perez298,299,597, Vasilisa A. Rudneva60, Borislav C. Rusev177, Andrea Ruzzenente598, Gunnar Rätsch276,277,278,279,280,430, Radhakrishnan Sabarinathan298,299,599, Veronica Y. Sabelnykova6, Sara Sadeghi30, S. Cenk Sahinalp62,78,79, Natalie Saini357, Mihoko Saito-Adachi440, Gordon Saksena8, Adriana Salcedo6, Roberto Salgado600, Leonidas Salichos5,19, Richard Sallari8, Charles Saller601, Roberto Salvia115, Michelle Sam272, Jaswinder S. Samra115,602, Francisco Sanchez-Vega114,121, Chris Sander276,603,604, Grant Sanders134, Rajiv Sarin605, Iman Sarrafi62,78, Aya Sasaki-Oku184, Torill Sauer489, Guido Sauter520, Robyn P. M. Saw211, Maria Scardoni167, Christopher J. Scarlett170,606, Aldo Scarpa177, Ghislaine Scelo194, Dirk Schadendorf68,607, Jacqueline E. Schein30, Markus B. Schilhabel589, Matthias Schlesner47,80, Thorsten Schlomm84,608, Heather K. Schmidt1 , Sarah-Jane Schramm246, Stefan Schreiber609, Nikolaus Schultz121, Steven E. Schumacher8,323, Roland F. Schwarz59,403,405,610, Richard A. Scolyer211,448,602, David Scott428, Ralph Scully611, Raja Seethala612, Ayellet V. Segre8,613, Iris Selander260, Colin A. Semple434, Yasin Senbabaoglu276, Subhajit Sengupta614, Elisabetta Sereni115, Stefano Serra585, Dennis C. Sgroi72, Mark Shackleton103, Nimish C. Shah352, Sagedeh Shahabi234, Catherine A. Shang329, Ping Shang211, Ofer Shapira8,323, Troy Shelton271, Ciyue Shen603,604, Hui Shen615, Rebecca Shepherd49, Ruian Shi490, Yan Shi134, Yu-Jia Shiah6, Tatsuhiro Shibata118,616, Juliann Shih8,82, Eigo Shimizu375, Kiyo Shimizu617, Seung Jun Shin618, Yuichi Shiraishi375, Tal Shmaya285, Ilya Shmulevich36, Solomon I. Shorser6, Charles Short59, Raunak Shrestha62, Suyash S. Shringarpure217, Craig Shriver619, Shimin Shuai6,126, Nikos Sidiropoulos83, Reiner Siebert112,620, Anieta M. Sieuwerts332, Lina Sieverling205,237, Sabina Signoretti202,621, Katarzyna O. Sikora177, Michele Simbolo138, Ronald Simon520, Janae V. Simons134, Jared T. Simpson6,17, Peter T. Simpson473, Samuel Singer115,458, Nasa Sinnott-Armstrong8,217, Payal Sipahimalani30, Tara J. Skelly390, Marcel Smid332, Jaclyn Smith622, Karen Smith-McCune514, Nicholas D. Socci276, Heidi J. Sofia27, Matthew G. Soloway134, Lei Song240, Anil K. Sood623,624,625, Sharmila Sothi626, Christos Sotiriou244, Cameron M. Soulette37, Paul N. Span627, Paul T. Spellman22, Nicola Sperandio177, Andrew J. Spillane211, Oliver Spiro8, Jonathan Spring628, Johan Staaf181, Peter F. Stadler163,164,165, Peter Staib629, Stefan G. Stark277,279,618,630, Lucy Stebbings49, Ólafur Andri Stefánsson631, Oliver Stegle59,60,632, Lincoln D. Stein6,126, Alasdair Stenhouse633, Chip Stewart8, Stephan Stilgenbauer634, Miranda D. Stobbe52,61, Michael R. Stratton49, Jonathan R. Stretch211, Adam J. Struck31, Joshua M. Stuart24,37, Henk G. Stunnenberg396,635, Hong Su56,396, Xiaoping Su99, Ren X. Sun6, Stephanie Sungalee60, Hana Susak52,53, Akihiro Suzuki89,636, Fred Sweep637, Monika Szczepanowski128, Holger Sültmann67,638, Takashi Yugawa617, Angela Tam30, David Tamborero298,299, Benita Kiat Tee Tan639, Donghui Tan518, Patrick Tan180,532,592,640, Hiroko Tanaka375, Hirokazu Taniguchi616, Tomas J. Tanskanen641, Maxime Tarabichi49,290, Roy Tarnuzzer220, Patrick Tarpey642, Morgan L. Taschuk152, Kenji Tatsuno89, Simon Tavaré223,643, Darrin F. Taylor113, Amaro Taylor-Weiner8, Jon W. Teague49, Bin Tean Teh180,592,640,644,645, Varsha Tembe246, Javier Temes104,105, Kevin Thai76, Sarah P. Thayer393, Nina Thiessen30, Gilles Thomas646, Sarah Thomas221, Alan Thompson221, Alastair M. Thompson633, John F. Thompson211, R. Houston Thompson647, Heather Thorne103, Leigh B. Thorne176, Adrian Thorogood424, Grace Tiao8, Nebojsa Tijanic284, Lee E. Timms272, Roberto Tirabosco648, Marta Tojo106, Stefania Tommasi649, Christopher W. Toon170, Umut H. Toprak48,650, David Torrents57,81, Giampaolo Tortora651,652, Jörg Tost653, Yasushi Totoki118, David Townend654, Nadia Traficante103, Isabelle Treilleux655,656, Jean-Rémi Trotta61, Lorenz H. P. Trümper469, Ming Tsao124,539, Tatsuhiko Tsunoda183,657,658,659, Jose M. C. Tubio104,105,106, Olga Tucker660, Richard Turkington661, Daniel J. Turner513, Andrew Tutt323, Masaki Ueno376, Naoto T. Ueno662, Christopher Umbricht151,213,663, Husen M. Umer305,664, Timothy J. Underwood665, Lara Urban59,60, Tomoko Urushidate616, Tetsuo Ushiku339, Liis Uusküla-Reimand666,667, Alfonso Valencia57,81, David J. Van Den Berg166, Steven Van Laere307, Peter Van Loo290,291, Erwin G. Van Meir668, Gert G. Van den Eynden307, Theodorus Van der Kwast123, Naveen Vasudev137, Miguel Vazquez57,669, Ravikiran Vedururu267, Umadevi Veluvolu518, Shankar Vembu490,670, Lieven P. C. Verbeke506,671, Peter Vermeulen307, Clare Verrill351,672, Alain Viari177, David Vicente57, Caterina Vicentini177, K. Vijay Raghavan365, Juris Viksna673, Ricardo E. Vilain674, Izar Villasante57, Anne Vincent-Salomon635, Tapio Visakorpi190, Douglas Voet8, Paresh Vyas311,351, Ignacio Vázquez-García49,86,675,676, Nick M. Waddell209, Nicola Waddell209,311, Claes Wadelius677, Lina Wadi6, Rabea Wagener111,112, Jeremiah A. Wala8,14,82, Jian Wang56, Jiayin Wang1,40,66, Linghua Wang12, Qi Wang465, Wenyi Wang21, Yumeng Wang21, Zhining Wang220, Paul M. Waring523, Hans-Jörg Warnatz483, Jonathan Warrell5,19, Anne Y. Warren352,678, Sebastian M. Waszak60, David C. Wedge49,294,679, Dieter Weichenhan345, Paul Weinberger680, John N. Weinstein38, Joachim Weischenfeldt60,83,84, Daniel J. Weisenberger166, Ian Welch681, Michael C. Wendl1,10,11, Johannes Werner47,85, Justin P. Whalley61,682, David A. Wheeler12,13, Hayley C. Whitaker117, Dennis Wigle683, Matthew D. Wilkerson518, Ashley Williams244, James S. Wilmott211, Gavin W. Wilson6,148, Julie M. Wilson148, Richard K. Wilson1,684, Boris Winterhoff685, Jeffrey A. Wintersinger17,127,384, Maciej Wiznerowicz686,687, Stephan Wolf688, Bernice H. Wong689, Tina Wong1,30, Winghing Wong690, Youngchoon Woo250, Scott Wood209,311, Bradly G. Wouters44, Adam J. Wright6, Derek W. Wright133,691, Mark H. Wright217, Chin-Lee Wu72, Dai-Ying Wu285, Guanming Wu692, Jianmin Wu170, Kui Wu56,396, Yang Wu179,180, Zhenggang Wu64, Liu Xi12, Tian Xia693, Qian Xiang76, Xiao Xiao66, Rui Xing497, Heng Xiong56,396, Qinying Xu209,311, Yanxun Xu694, Hong Xue64, Shinichi Yachida118,695, Sergei Yakneen60, Rui Yamaguchi375, Takafumi N. Yamaguchi6, Masakazu Yamamoto120, Shogo Yamamoto89, Hiroki Yamaue376, Fan Yang490, Huanming Yang56, Jean Y. Yang696, Liming Yang220, Lixing Yang697, Shanlin Yang306, Tsun-Po Yang270, Yang Yang369, Xiaotong Yao408,698, Marie-Laure Yaspo483, Lucy Yates49, Christina Yau156, Chen Ye56,396, Kai Ye40,41, Venkata D. Yellapantula20,86, Christopher J. Yoon249, Sung-Soo Yoon463, Fouad Yousif6, Jun Yu699, Kaixian Yu700, Willie Yu701, Yingyan Yu702, Ke Yuan223,510,703, Yuan Yuan21, Denis Yuen6, Takashi Yugawa617, Christina K. Yung76, Olga Zaikova704, Jorge Zamora49,104,105,106, Marc Zapatka397, Jean C. Zenklusen220, Thorsten Zenz67, Nikolajs Zeps705,706, Cheng-Zhong Zhang8,707, Fan Zhang381, Hailei Zhang8, Hongwei Zhang494, Hongxin Zhang121, Jiashan Zhang220, Jing Zhang5, Junjun Zhang76, Xiuqing Zhang56, Xuanping Zhang66,369, Yan Zhang5,708,709, Zemin Zhang381,710, Zhongming Zhao711, Liangtao Zheng381, Xiuqing Zheng381, Wanding Zhou615, Yong Zhou56, Bin Zhu240, Hongtu Zhu700,712, Jingchun Zhu24, Shida Zhu56,396, Lihua Zou713, Xueqing Zou49, Anna deFazio246,247,714, Nicholas van As221, Carolien H. M. van Deurzen715, Marc J. van de Vijver523, L. van’t Veer716 & Christian von Mering433,717, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

Whereas genomic aberrations in the SLIT-ROBO pathway are frequent in pancreatic ductal adenocarcinoma (PDAC), their function in the pancreas is unclear. Here we report that in pancreatitis and PDAC mouse models, epithelial Robo2 expression is lost while Robo1 expression becomes most prominent in the stroma. Cell cultures of mice with loss of epithelial Robo2 (Pdx1Cre;Robo2F/F) show increased activation of Robo1+ myofibroblasts and induction of TGF-β and Wnt pathways. During pancreatitis, Pdx1Cre;Robo2F/F mice present enhanced myofibroblast activation, collagen crosslinking, T-cell infiltration and tumorigenic immune markers. The TGF-β inhibitor galunisertib suppresses these effects. In PDAC patients, ROBO2 expression is overall low while ROBO1 is variably expressed in epithelium and high in stroma. ROBO2low;ROBO1high patients present the poorest survival. In conclusion, Robo2 acts non-autonomously as a stroma suppressor gene by restraining myofibroblast activation and T-cell infiltration. ROBO1/2 expression in PDAC patients may guide therapy with TGF-β inhibitors or other stroma /immune modulating agents., SLIT-ROBO alterations arise in pancreatic ductal adenocarcinoma (PDAC), but their role in the pancreas is unclear. Here, the authors use mouse models to show that loss of epithelial Robo2 activates the neighbouring stroma via TGF-β signalling; findings are relevant to PDAC patients, where ROBO expression correlates with survival outcomes.

Metastatic pancreatic ductal adenocarcinoma (mPDAC) is a lethal disease with a poor 5-year survival. Systemic treatments can be used to control symptoms and prolong life. Cytotoxic chemotherapies are commonly administered, with combination treatments, such as fluorouracil, folinic acid, irinotecan and oxaliplatin (FOLFIRINOX) or nab-paclitaxel and gemcitabine showing the largest clinical benefits. Newer genomic classifications of PDAC may provide a rationale for targeted therapies or immunotherapies, although at present these remain largely experimental. This review discusses the evidence behind the currently used regimens, while introducing the potential future of pancreatic cancer care.

Despite recent progress, the outlook for most patients with pancreatic cancer remains poor. There is variation in how patients are managed globally due to differing interpretations of the evidence, partly because studies in this disease are challenging to undertake. This article collates the evidence upon which current best practice is based and offers an expert opinion from an international faculty on how latest developments should influence current treatment paradigms. Areas covered: Optimal chemotherapy for first and subsequent lines of therapy; optimal management of locally advanced, non-metastatic cancer including the role of neoadjuvant chemo(radio)therapy, current evidence for adjuvant chemotherapy, major advances in pancreatic cancer genomics and challenges in supportive care particularly relevant to patients with pancreatic cancer. For each section, literature was reviewed by comprehensive search techniques, including clinical trial websites and abstracts from international cancer meetings. Expert commentary: For each section, a commentary is provided. Overall the challenges identified were: difficulties in diagnosing pancreatic cancer early, challenges for performing randomised clinical trials in all stages of the disease, some progress in systemic therapy with new agents and in identifying molecular subtypes that may be clinically relevant and move towards personalized therapy, but still, pancreatic cancer remains a very poor prognosis cancer with significant palliative care needs.

Background The return of research results (RoR) remains a complex and well-debated issue. Despite the debate, actual data related to the experience of giving individual results back, and the impact these results may have on clinical care and health outcomes, is sorely lacking. Through the work of the Australian Pancreatic Cancer Genome Initiative (APGI) we: (1) delineate the pathway back to the patient where actionable research data were identified; and (2) report the clinical utilisation of individual results returned. Using this experience, we discuss barriers and opportunities associated with a comprehensive process of RoR in large-scale genomic research that may be useful for others developing their own policies. Methods We performed whole-genome (n = 184) and exome (n = 208) sequencing of matched tumour-normal DNA pairs from 392 patients with sporadic pancreatic cancer (PC) as part of the APGI. We identified pathogenic germline mutations in candidate genes (n = 130) with established predisposition to PC or medium–high penetrance genes with well-defined cancer associated syndromes or phenotypes. Variants from candidate genes were annotated and classified according to international guidelines. Variants were considered actionable if clinical utility was established, with regard to prevention, diagnosis, prognostication and/or therapy. Results A total of 48,904 germline variants were identified, with 2356 unique variants undergoing annotation and in silico classification. Twenty cases were deemed actionable and were returned via previously described RoR framework, representing an actionable finding rate of 5.1%. Overall, 1.78% of our cohort experienced clinical benefit from RoR. Conclusion Returning research results within the context of large-scale genomics research is a labour-intensive, highly variable, complex operation. Results that warrant action are not infrequent, but the prevalence of those who experience a clinical difference as a result of returning individual results is currently low. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0430-4) contains supplementary material, which is available to authorized users.

ObjectiveExtensive molecular heterogeneity of pancreatic ductal adenocarcinoma (PDA), few effective therapies and high mortality make this disease a prime model for advancing development of tailored therapies. The p16-cyclin D-cyclin-dependent kinase 4/6-retinoblastoma (RB) protein (CDK4) pathway, regulator of cell proliferation, is deregulated in PDA. Our aim was to develop a novel personalised treatment strategy for PDA based on targeting CDK4.DesignSensitivity to potent CDK4/6 inhibitor PD-0332991 (palbociclib) was correlated to protein and genomic data in 19 primary patient-derived PDA lines to identify biomarkers of response. In vivo efficacy of PD-0332991 and combination therapies was determined in subcutaneous, intrasplenic and orthotopic tumour models derived from genome-sequenced patient specimens and genetically engineered model. Mechanistically, monotherapy and combination therapy were investigated in the context of tumour cell and extracellular matrix (ECM) signalling. Prognostic relevance of companion biomarker, RB protein, was evaluated and validated in independent PDA patient cohorts (>500 specimens).ResultsSubtype-specific in vivo efficacy of PD-0332991-based therapy was for the first time observed at multiple stages of PDA progression: primary tumour growth, recurrence (second-line therapy) and metastatic setting and may potentially be guided by a simple biomarker (RB protein). PD-0332991 significantly disrupted surrounding ECM organisation, leading to increased quiescence, apoptosis, improved chemosensitivity, decreased invasion, metastatic spread and PDA progression in vivo. RB protein is prevalent in primary operable and metastatic PDA and may present a promising predictive biomarker to guide this therapeutic approach.ConclusionThis study demonstrates the promise of CDK4 inhibition in PDA over standard therapy when applied in a molecular subtype-specific context.

TPS4172 Background: Eighty per cent of patients with non-metastatic pancreatic cancer have high-risk, borderline resectable (BRPC) or locally advanced pancreas cancer (LAPC), conferring a 5-year overall survival of only 12%. MASTERPLAN evaluates the safety and activity of stereotactic body radiotherapy (SBRT) added to neoadjuvant chemotherapy in these patient cohorts. Methods: MASTERPLAN is an investigator-initiated prospective multi-centre randomized phase II trial. Inclusion criteria include histologically confirmed high-risk, BRPC or LAPC. High risk is defined as tumour > 4cm, extrapancreatic extension or node positive. Randomisation is 2:1 to chemotherapy + SBRT (investigational arm) or chemotherapy (control arm) by minimisation with stratification by operability (potentially operable - high risk; BRPC versus inoperable – LAPC; medically inoperable), planned chemotherapy and institution. Both treatment arms receive 6 x 2 weekly cycles of modified FOLFIRINOX (mFOLFIRINOX). Gemcitabine and nab-paclitaxel is permitted if mFOLFIRINOX is unsuitable. The investigational arm receives SBRT (40Gy in 5 fractions) with real time quality assurance. Resectability will be evaluated following initial chemotherapy +/- SBRT. Adjuvant chemotherapy is 6 cycles (12 weeks) of mFOLFIRINOX, or the same duration of gemcitabine and capecitabine (GEMCAP) if neoadjuvant gemcitabine/ nab-paclitaxel given. SBRT adverse events (AEs) will be recorded until study cessation. The primary endpoint is 12-month locoregional control. Secondary endpoints: safety, surgical morbidity and mortality, radiological response rate, progression free survival, pathological response rate, surgical resection rate, R0 resection rate, quality of life, deterioration free survival and overall survival. Biospecimens are collected for translational research for potential prognostic/predictive biomarkers of clinical endpoints and include serial tumour tissue collection from patients undergoing fiducial marker insertion and/or surgery, biopsy at disease progression, serial blood collection and serial buccal and faecal sample collection. An interim analysis will review locoregional failure, distant metastasis and rate of death on the first 40 patients after completion of 12 months follow up. The sample size is 120 patients (80 intervention:40 control), balanced for BRPC/LAPC (60 in each cohort). The minimum follow up is 12 months. The first site opened in October 2019 and 10 patients have been recruited from five sites at 17 Feb 2021. Overall 15 sites in Australia and New Zealand are planned to open to recruitment. Australian Clinical Trials Registry Number: ACTRN12619000409178. Clinical trial information: ACTRN12619000409178.

TPS271 Background: Pan added to combination chemotherapy is established first-line therapy for RAS and BRAF wild type mCRC. Elderly patients are not well represented in clinical trials and may be more suited to treatment protocols with lower toxicity risks; FU plus bevacizumab (bev) is commonly used. Treatment related efficacy, toxicity, impact on quality of life and other outcomes of pan based regimens in an elderly population have not been well studied. Methods: A prospective non-comparative randomized phase 2 study. Australian Clinical Trials Registry Number: ACTRN 12618000233224. Main inclusion criteria include: Untreated patients aged 70 years or older; RAS and BRAF wild type; ECOG performance 0-2. Randomisation 1:1, stratified by primary tumour side, performance status, number of metastatic sites; to pan 6mg/kg 2 weekly or panitumumab plus FU 400 mg/m² bolus; leucovorin 200mg/m²; FU 2400mg/m² 48 hour infusion 2 weekly. Primary endpoint is 6-month progression-free survival (PFS). Sample size is 80 patients based on expected 6-month PFS rate of 73% with FU and bev. Using the method of Metha-Cain, if 24 or more patients are progression free at 6 months, the one sided 95% confidence interval includes 73% and we declare similar activity. Secondary endpoints include overall survival; toxicity and overall treatment utility, a composite measure of treatment benefit based on radiology, clinical progress, toxicity and patient reflection of the impact of treatment on their daily lives. Patients undergo a comprehensive health assessment at baseline and limited health assessment at 4 months. Physical activity trackers are worn for 2 weeks at treatment commencement and again at week 16. Tumour tissue and blood samples (at baseline, cycle 3 day 1 and at 24 weeks) will be collected for translational research. First site opened in June 2018. Twelve patients have been recruited to date from 9 sites in Australasia. Eighteen sites were open as at September 2019. Clinical trial information: 12618000233224.

Background Information on the risks of herpes zoster (zoster) preceding a cancer diagnosis and the role of cancer treatment on risk is limited. Methods This was a prospective cohort of 241497 adults, with mean age 62.0 years at recruitment (2006-2009), linked to health datasets from 2006 to 2015. The relation between cancer diagnosis, treatment, and zoster risk was analyzed using time-varying proportional hazards models. Results Over 1760 481 person-years of follow-up, 20286 new cancer diagnoses and 16350 zoster events occurred. Participants with hematological and solid cancer had higher relative risks of zoster than those without cancer (adjusted hazard ratio [aHR], 3.74 [95% confidence interval {CI}, 3.11-4.51] and 1.30 [95% CI, 1.21-1.40], respectively). Compared to those without cancer, zoster risk was also elevated prior to a hematological cancer diagnosis (aHR for 1-2 years prior, 2.01 [95% CI, 1.31-3.09]), but this was not the case for solid cancers (aHR for 1-2 years prior, 0.90 [95% CI, .75-1.07]). Compared to those without cancer, zoster risk among participants with solid cancers receiving chemotherapy was greater than in those without a chemotherapy record (aHR, 1.83 [95% CI, 1.60-2.09] and 1.16 [95% CI, 1.06-1.26], respectively). Conclusions For hematological cancer, increases in zoster risk are apparent in the 2 years preceding diagnosis and treatment; for solid organ cancers, the increased risk appears to be largely associated with receipt of chemotherapy.

Background: \ud Pancreatic cancer (PC) is a highly lethal disease with few effective treatment options. Over the past few decades, many anti-cancer therapies have been tested in the locally advanced and metastatic setting, with mixed results. This review attempts to synthesise all the randomised data available to help better inform patient and clinician decision-making when dealing with this difficult disease.\ud \ud Objectives: \ud To assess the effect of chemotherapy, radiotherapy or both for first-line treatment of advanced pancreatic cancer. Our primary outcome was overall survival, while secondary outcomes include progression-free survival, grade 3/4 adverse events, therapy response and quality of life.\ud \ud Search methods: \ud We searched for published and unpublished studies in CENTRAL (searched 14 June 2017), Embase (1980 to 14 June 2017), MEDLINE (1946 to 14 June 2017) and CANCERLIT (1999 to 2002) databases. We also handsearched all relevant conference abstracts published up until 14 June 2017.\ud \ud Selection criteria: \ud All randomised studies assessing overall survival outcomes in patients with advanced pancreatic ductal adenocarcinoma. Chemotherapy and radiotherapy, alone or in combination, were the eligible treatments.\ud \ud Data collection and analysis: \ud Two review authors independently analysed studies, and a third settled any disputes. We extracted data on overall survival (OS), progression-free survival (PFS), response rates, adverse events (AEs) and quality of life (QoL), and we assessed risk of bias for each study.\ud \ud Main results: \ud We included 42 studies addressing chemotherapy in 9463 patients with advanced pancreatic cancer. We did not identify any eligible studies on radiotherapy.\ud \ud We did not find any benefit for chemotherapy over best supportive care. However, two identified studies did not have sufficient data to be included in the analysis, and many of the chemotherapy regimens studied were outdated.\ud \ud Compared to gemcitabine alone, participants receiving 5FU had worse OS (HR 1.69, 95% CI 1.26 to 2.27, moderate-quality evidence), PFS (HR 1.47, 95% CI 1.12 to 1.92) and QoL. On the other hand, two studies showed FOLFIRINOX was better than gemcitabine for OS (HR 0.51 95% CI 0.43 to 0.60, moderate-quality evidence), PFS (HR 0.46, 95% CI 0.38 to 0.57) and response rates (RR 3.38, 95% CI 2.01 to 5.65), but it increased the rate of side effects. The studies evaluating CO-101, ZD9331 and exatecan did not show benefit or harm when compared with gemcitabine alone.\ud \ud Giving gemcitabine at a fixed dose rate improved OS (HR 0.79, 95% CI 0.66 to 0.94, high-quality evidence) but increased the rate of side effects when compared with bolus dosing.\ud \ud When comparing gemcitabine combinations to gemcitabine alone, gemcitabine plus platinum improved PFS (HR 0.80, 95% CI 0.68 to 0.95) and response rates (RR 1.48, 95% CI 1.11 to 1.98) but not OS (HR 0.94, 95% CI 0.81 to 1.08, low-quality evidence). The rate of side effects increased. Gemcitabine plus fluoropyrimidine improved OS (HR 0.88, 95% CI 0.81 to 0.95), PFS (HR 0.79, 95% CI 0.72 to 0.87) and response rates (RR 1.78, 95% CI 1.29 to 2.47, high-quality evidence), but it also increased side effects. Gemcitabine plus topoisomerase inhibitor did not improve survival outcomes but did increase toxicity. One study demonstrated that gemcitabine plus nab-paclitaxel improved OS (HR 0.72, 95% CI 0.62 to 0.84, high-quality evidence), PFS (HR 0.69, 95% CI 0.58 to 0.82) and response rates (RR 3.29, 95% CI 2.24 to 4.84) but increased side effects. Gemcitabine-containing multi-drug combinations (GEMOXEL or cisplatin/epirubicin/5FU/gemcitabine) improved OS (HR 0.55, 95% CI 0.39 to 0.79, low-quality evidence), PFS (HR 0.43, 95% CI 0.30 to 0.62) and QOL.\ud \ud We did not find any survival advantages when comparing 5FU combinations to 5FU alone.\ud \ud Authors' conclusions: \ud Combination chemotherapy has recently overtaken the long-standing gemcitabine as the standard of care. FOLFIRINOX and gemcitabine plus nab-paclitaxel are highly efficacious, but our analysis shows that other combination regimens also offer a benefit. Selection of the most appropriate chemotherapy for individual patients still remains difficult, with clinicopathological stratification remaining elusive. Biomarker development is essential to help rationalise treatment selection for patients.

BACKGROUND:Best practise care optimises survival and quality of life in patients with pancreatic cancer (PC), but there is evidence of variability in management and suboptimal care for some patients. Monitoring practise is necessary to underpin improvement initiatives. We aimed to develop a core set of quality indicators that measure quality of care across the disease trajectory. METHODS:A modified, three-round Delphi survey was performed among experts with wide experience in PC care across three states in Australia. A total of 107 potential quality indicators were identified from the literature and divided into five areas: diagnosis and staging, surgery, other treatment, patient management and outcomes. A further six indicators were added by the panel, increasing potential quality indicators to 113. Rated on a scale of 1-9, indicators with high median importance and feasibility (score 7-9) and low disagreement (

Background: Adjuvant therapy for HER2-positive breast cancer (HBC) often comprises anthracyclines (A) followed by trastuzumab (T). Trastuzumab-related cardiotoxicity (TRC) is T’s primary toxicity, and led 15% of patients in NSABP-B31 to stop T early. Earlier detection of TRC might enable timely therapeutic intervention, lowering the number of patients ceasing T prematurely. Small, retrospective, unvalidated studies have proposed various markers as predictors for TRC. The Cardiotoxicity of Adjuvant Trastuzumab Study (CATS) aims to assess a panel of clinical, biochemical, and genomic/immunologic markers as predictors for TRC. Methods: HBC patients with a left ventricular ejection fraction (LVEF) ≥ 50% scheduled to receive adjuvant A followed by 12 months’ T were eligible. Serum N-terminal pro-B type natriuretic peptide (NT pro-BNP) and troponin I were measured centrally at baseline (T1), at completion of A (T2), and after 3 and 6 months of T. LVEF was measured at T1, T2, and then 3-monthly until completion of T. Germline SNPs in ERBB2 (V655I), FCGR2A (H131R), and FCGR3A (V158F) were assessed. TRC was defined as: cardiac death, NYHA class 3/4 heart failure, grade 3/4 arrhythmia/ischemia, drop in LVEF >15% from baseline, or drop in LVEF of >10% to Results: 17 centers enrolled 222 patients (217 evaluable). Patient characteristics are shown. Baseline characteristicsAge [median (range), yrs]52 (28-77)Baseline LVEF [median (range)]64% (50-82%)Left-sided tumors [n(%)]105 (48%)History of hypertension [n(%)]48 (22%)Doxorubicin [n(%), median total dose]80 (37%), 242mg/m2Epirubicin [n(%), median total dose]137 (63%), 300mg/m2Concurrent taxane with T [n(%)]217 (100%) TRC occurred in 33 patients (15.2%). In multivariate models, lower baseline LVEF (OR 3.23 for a 5% lower LVEF, [95% CI 1.96-5.33], p Conclusion: This is the largest prospective study analyzing predictors for TRC, and the first studying immune-related SNPs in this context. Consistent with the literature, lower LVEF at baseline increases risk of TRC. Previously unreported, the absolute decrease in LVEF after A is also predictive for TRC. The persistent elevation of troponin I 6 months after completing A demonstrates chronic cardiac stress during therapy. Ongoing modeling analyses (to be presented at the meeting) will determine whether longitudinal changes in serum biomarkers can predict subsequent development of TRC. Citation Format: Shom Goel, Hao Guo, William Barry, Bronwyn Murray, Jodi Lynch, Patricia Bastick, Lorraine Chantrill, Belinda Kiely, Richard Bell, Ehtesham Abdi, Josie Rutovitz, Ray Asghari, Anne Sullivan, Michelle Harrison, Maija Kohonen-Corish, Jane Beith. Clinical, biochemical, and genomic predictors of trastuzumab-related cardiotoxicity: Results of CATS [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-15-02.

Metastatic pancreatic ductal adenocarcinoma (mPDAC) is a lethal disease with a poor 5-year survival. Systemic treatments can be used to control symptoms and prolong life. Cytotoxic chemotherapies are commonly administered, with combination treatments, such as fluorouracil, folinic acid, irinotecan and oxaliplatin (FOLFIRINOX) or nab-paclitaxel and gemcitabine showing the largest clinical benefits. Newer genomic classifications of PDAC may provide a rationale for targeted therapies or immunotherapies, although at present these remain largely experimental. This review discusses the evidence behind the currently used regimens, while introducing the potential future of pancreatic cancer care.

Pancreatic cancer is molecularly diverse, with few effective therapies. Increased mutation burden and defective DNA repair are associated with response to immune checkpoint inhibitors in several other cancer types. We interrogated 385 pancreatic cancer genomes to define hypermutation and its causes. Mutational signatures inferring defects in DNA repair were enriched in those with the highest mutation burdens. Mismatch repair deficiency was identified in 1% of tumors harboring different mechanisms of somatic inactivation of MLH1 and MSH2. Defining mutation load in individual pancreatic cancers and the optimal assay for patient selection may inform clinical trial design for immunotherapy in pancreatic cancer.

Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies.

METHODS: Clinicopathologic features were assessed in a cohort of 766 patients who had been diagnosed with pancreatic ductal adenocarcinoma (PC). Patients were classified with FPC if they had ≥1 affected first-degree relatives; otherwise, they were classified with sporadic PC (SPC).

Chronic pancreatitis predisposes to pancreatic cancer development and both diseases share a common etiology. A central role has been proposed for the digestive enzyme-secreting acinar cell that can undergo ductal metaplasia in the inflammatory environment of pancreatitis. This metaplastic change is now a recognised precursor of pancreatic cancer. Inflammatory molecules also foster tumour growth through autocrine and paracrine effects in the epithelium and the stroma. These insights have raised new opportunities such as the manipulation of inflammation as a preventive and/or therapeutic strategy for pancreatic cancer. Finally, we address the need for an in-depth study of the pancreatic acinar cells.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis, being predicted to become the second leading cause of cancer-related death by 2030. Chronic pancreatitis is a risk factor for PDAC and both diseases are characterized by a strong desmoplastic response, comprised of activated myofibroblasts and immune cell infiltrates. Genomic aberrations in the SLIT-ROBO pathway are frequent in PDAC. Nevertheless, their role in the pancreas is unclear. We have used an integrative approach combining the study of murine models and PDAC patients with the objective of unraveling the function of the SLIT-ROBO signaling pathway in pancreatic disease. RNA expression of SLIT-ROBO genes was analyzed in murine normal pancreas, pancreatitis and PDAC. Primary cell cultures and experimental pancreatitis were studied using pancreas-specific Robo2 (Pdx1-Cre;Robo2F/F) and whole-body Slit1 (Slit1-/-) knockout mice. Gene and protein expression were assessed in a cohort of PDAC patients (n=109). In mouse pancreatitis and PDAC, epithelial Robo2 expression is lost while Robo1 expression becomes most prominent in the stroma. Pdx1Cre;Robo2F/F pancreatic cell cultures showed increased activation of Robo1-positive myofibroblasts and induction of TGF-β and Wnt pathways. Likewise, induction of pancreatitis in Pdx1Cre;Robo2F/F mice enhanced myofibroblast activation, collagen crosslinking, T-cell infiltration and tumorigenic immune markers. Similar results were obtained using Slit1-/- animals. Moreover, TGF-β inhibition using galunisertib treatment suppressed Robo2-mediated effects in the microenvironment. In patients, ROBO2 expression is overall low in PDAC, while ROBO1 is variably expressed in epithelium and high in the stroma. ROBO1 expression is correlated with markers of activated stroma, Wnt and TGF-β pathways. ROBO2low;ROBO1high subpopulation of patients present the poorest survival rates. In conclusion, Robo2 acts nonautonomously as a stroma suppressor gene by restraining myofibroblast activation and inflammation in the pancreatic microenvironment. ROBO1/2 expression is prognostic in PDAC patients and may guide therapy with TGF-β inhibitors or immunotherapies, currently being tested in clinical trials for advanced pancreatic cancer. Citation Format: Andreia V. Pinho, Mathias Van Bulck, Lorraine Chantrill, Mehreen Arshi, David Herrmann, Claire Vennin, APGI - Australian Pancreatic Cancer Genome Initiative, Anthony Gill, Paul Timpson, Andrew Biankin, Jianmin Wu, Ilse Rooman. ROBO2 is a stroma suppressor gene in the pancreas through regulation of TGF-β [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr A100.

background: Adjuvant chemotherapy improves survival for patients with resected pancreatic cancer. Elderly patients are under-represented in Phase III clinical trials, and as a consequence the efficacy of adjuvant therapy in older patients with pancreatic cancer is not clear. We aimed to assess the use and efficacy of adjuvant chemotherapy in older patients with pancreatic cancer.\ud methods: We assessed a community cohort of 439 patients with a diagnosis of pancreatic ductal adenocarcinoma who underwent operative resection in centres associated with the Australian Pancreatic Cancer Genome Initiative.\ud results: The median age of the cohort was 67 years. Overall only 47% of all patients received adjuvant therapy. Patients who received adjuvant chemotherapy were predominantly younger, had later stage disease, more lymph node involvement and more evidence of perineural invasion than the group that did not receive adjuvant treatment. Overall, adjuvant chemotherapy was associated with prolonged survival (median 22.1 vs 15.8 months; P\ud conclusion: Patients aged greater than or equal to70 are less likely to receive adjuvant therapy although it is associated with improved outcome. Increased use of adjuvant therapy in older individuals is encouraged as they constitute a large proportion of patients with pancreatic cancer.

Background Survival times of women starting first-line chemotherapy for metastatic breast cancer (MBC) in routine clinical practice were determined and compared with those from a systematic review of randomised clinical trials. Methods We identified women with MBC starting first-line chemotherapy from June 2003 to February 2011 and recorded their demographics, tumour and treatment characteristics, and survival times from the start of chemotherapy. Their survival distribution was summarised by the following percentiles (represented scenarios for survival): 90th (worst-case), 75th (lower-typical), 25th (upper-typical) and 10th (best-case), which were compared with the same percentiles from our systematic review of first-line chemotherapy trials. Results The 273 women had a median age of 56 years, and a median time from diagnosis of MBC of 3 months. Eastern Cooperative Oncology Group performance status was 0–1 in 80%. Tumours were hormone receptor positive in 69%, human epidermal growth factor receptor 2 (HER2)-positive in 27% and triple negative in 13%. Survival times in months in routine clinical practice (vs the systematic review) were: 90th percentile 4 (6); 75th percentile 9 (12); median 20 (22); 25th percentile 36 (36) and 10th percentile 61 (56). Independent predictors of overall survival included HER2-positive disease (hazard ratio (HR) 0.49, P = 0.0002), hormone receptor positive disease (HR 0.51, P = 0.0004), Eastern Cooperative Oncology Group performance status 0–1 (HR 0.36, P < 0.0001) and adjuvant chemotherapy (HR 1.86, P = 0.0002). Conclusion Median and better survival times in routine practice were similar to those from randomised clinical trials; however, survival times worse than the median were shorter, likely reflecting patient selection in trials. Oncologists should adjust trial-based survival estimates for patients not meeting typical trial eligibility criteria.

The emerging standard of care for patients with inoperable pancreatic cancer is a combination of cytotoxic drugs gemcitabine and Abraxane, but patient response remains moderate. Pancreatic cancer development and metastasis occur in complex settings, with reciprocal feedback from microenvironmental cues influencing both disease progression and drug response. Little is known about how sequential dual targeting of tumor tissue tension and vasculature before chemotherapy can affect tumor response. We used intravital imaging to assess how transient manipulation of the tumor tissue, or "priming," using the pharmaceutical Rho kinase inhibitor Fasudil affects response to chemotherapy. Intravital Forster resonance energy transfer imaging of a cyclin-dependent kinase 1 biosensor to monitor the efficacy of cytotoxic drugs revealed that priming improves pancreatic cancer response to gemcitabine/Abraxane at both primary and secondary sites. Transient priming also sensitized cells to shear stress and impaired colonization efficiency and fibrotic niche remodeling within the liver, three important features of cancer spread. Last, we demonstrate a graded response to priming in stratified patient-derived tumors, indicating that fine-tuned tissue manipulation before chemotherapy may offer opportunities in both primary and metastatic targeting of pancreatic cancer. Refereed/Peer-reviewed

Background Patients with metastatic colorectal cancer whose disease has progressed on oxaliplatin- and irinotecan-containing regimens may benefit from EGFR-inhibiting monoclonal antibodies if they do not contain mutations in the KRAS gene (are “wild type”). It is unknown whether these antibodies, such as cetuximab, are more efficacious in refractory metastatic colorectal cancer as monotherapy, or in combination with irinotecan. Lack of mutation in KRAS, BRAF and PIK3CA predicts response to EFGR-inhibitors. The ICECREAM trial examines the question of monotherapy versus combination with chemotherapy in two groups of patients: those with a “quadruple wild type” tumour genotype (no mutations in KRAS, NRAS, PI3KCA or BRAF genes) and those with the specific KRAS mutation in codon G13D, for whom possibly EGFR-inhibitor efficacy may be equivalent. Methods and design ICECREAM is a randomised, phase II, open-label, controlled trial comparing the efficacy of cetuximab alone or with irinotecan in patients with “quadruple wild type” or G13D-mutated metastatic colorectal cancer, whose disease has progressed on, or who are intolerant of oxaliplatin- and fluoropyrimidine-based chemotherapy. The primary endpoint is the 6-month progression-free survival benefit of the treatment regimen. Secondary endpoints are response rate, overall survival, and quality of life. The tertiary endpoint is prediction of outcome with further biological markers. International collaboration has facilitated recruitment in this prospective trial of treatment in these infrequently found molecular subsets of colorectal cancer. Discussion This unique trial will yield prospective information on the efficacy of cetuximab and whether this is further enhanced with chemotherapy in two distinct populations of patients with metastatic colorectal cancer: the “quadruple wild type”, which may ‘superselect’ for tumours sensitive to EGFR-inhibition, and the rare KRAS G13D mutated tumours, which are also postulated to be sensitive to the drug. The focus on establishing both positive and negative predictive factors for the response to targeted therapy is an attempt to improve outcomes, reduce toxicity and contain treatment costs. Tissue and blood will yield a resource for molecular studies. Recruitment, particularly of patients with the rare G13D mutation, will demonstrate the ability for international collaboration to run prospective trials in small colorectal cancer molecular subgroups. Trial registration Australian and New Zealand Clinical Trials Registry: ACTRN12612000901808, registered 16 August 2012.

Purpose RAS mutations predict lack of response to epidermal growth factor receptor monoclonal antibody therapy in patients with metastatic colorectal cancer (mCRC), but preclinical studies and retrospective clinical data suggest that patients with tumors harboring the exon 2 KRAS G13D mutation may benefit from cetuximab. We aimed to assess cetuximab monotherapy and cetuximab plus irinotecan in patients with molecularly selected (G13D mutation) chemotherapy-refractory mCRC in a randomized phase II trial of this rare molecular subtype. Patients and Methods Patients with chemotherapy-refractory KRAS G13D mutation–positive mCRC who had progressed within 6 months of irinotecan therapy were randomly assigned to cetuximab 400 mg/m2 loading dose and then 250 mg/m2 once per week with or without irinotecan 180 mg/m2 once every 2 weeks. The primary end point was 6-month progression-free survival; secondary end points were response rate, overall survival, quality of life, and toxicity. Results Fifty-one of 53 patients recruited over 2 years were eligible. The 6-month progression-free survival rate was 10% (95% CI, 2% to 26%) for cetuximab versus 23% (95% CI, 9% to 40%) for cetuximab plus irinotecan with a hazard ratio of 0.74 (95% CI, 0.42 to 1.32). Response and stable disease rates were 0% and 58% for monotherapy versus 9% and 70% for combination treatment, respectively. Overall survival and quality of life were similar; toxicities were higher with combination therapy. Conclusion In patients with G13D-mutated chemotherapy-refractory mCRC, there was no statistically significant improvement in disease control at 6 months with either cetuximab monotherapy or cetuximab plus irinotecan. No responses were seen with single-agent cetuximab. The responses observed with the combination of cetuximab and irinotecan may reflect true drug synergy or persistent irinotecan sensitivity. The ICECREAM (Irinotecan Cetuximab Evaluation and Cetuximab Response Evaluation Among Patients with a G13D Mutation) study demonstrates the need to prospectively evaluate hypotheses that were previously supported by retrospective analyses and exemplifies the value of international collaboration in trials of rare molecular subtypes.

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

Background: Current staging methods for pancreatic cancer (PC) are inadequate, and biomarkers to aid clinical decision making are lacking. Despite the availability of the serum marker carbohydrate antigen 19.9 (CA19.9) for over two decades, its precise role in the management of PC is yet to be defined, and as a consequence, it is not widely used.\ud \ud Methods: We assessed the relationship between perioperative serum CA19.9 levels, survival and adjuvant chemotherapeutic responsiveness in a cohort of 260 patients who underwent operative resection for PC.\ud \ud Results By specifically assessing the subgroup of patients with detectable CA19.9, we identified potential utility at key clinical decision points. Low postoperative CA19.9 at 3 months (median survival 25.6 vs 14.8 months, P = 0.0052) and before adjuvant chemotherapy were independent prognostic factors. Patients with postoperative CA 19.9 levels >90 U/ml did not benefit from adjuvant chemotherapy (P = 0.7194) compared with those with a CA19.9 of ≤90 U/ml median 26.0 vs 16.7 months, P = 0.0108). Normalization of CA19.9 within 6 months of resection was also an independent favorable prognostic factor (median 29.9 vs 14.8 months, P = 0.0004) and normal perioperative CA19.9 levels identified a good prognostic group, which was associated with a 5-year survival of 42%.\ud \ud Conclusions: Perioperative serum CA19.9 measurements are informative in patients with detectable CA19.9 (defined by serum levels of of >5 U/ml) and have potential clinical utility in predicting outcome and response to adjuvant chemotherapy. Future clinical trials should prioritize incorporation of CA19.9 measurement at key decision points to prospectively validate these findings and facilitate implementation.

Background Bevacizumab is an antiangiogenic mAb with efficacy against several cancers, but it is associated with risk of arterial thromboembolism (ATE). Further data are needed to determine the safety of bevacizumab. Patients and methods We recorded grade 3, 4, or 5 ATE events and other data (including age, baseline cardiovascular risk factors, history of ATE, and aspirin use) from 471 patients with metastatic colorectal cancer in the MAX (Mitomycin, Avastin, Xeloda) trial of capecitabine monotherapy versus capecitabine with bevacizumab with or without mitomycin C. Results Bevacizumab-treated patients had 12 grade 3, 4, or 5 ATEs (3.8% incidence). ATEs occurred in 2.1% of patients >65 years, 5% of those with a history of ATE, and 5% of those with cardiac risk factors. Age, history of ATE, or vascular risk factors did not increase risk. Aspirin users had a higher incidence than nonusers (8.9% versus 2.7%) but had higher rates of vascular risk factors. Conclusions Bevacizumab was associated with a modestly higher risk of ATE, but safety was not significantly worse in older patients or patients with a history of ATE or vascular risk factors. The effect of aspirin in preventing ATE in patients receiving bevacizumab could not be determined from this study.

TPS548 Background: Neuroendocrine carcinomas (NEC WHO grade 3) are rare and aggressive cancers. There are no randomised trials to date to establish standard therapy for advanced gastrointestinal (GI) NECs. Extrapolating from small cell lung cancer data, standard practice is to treat GI-NECs with etoposide and carboplatin. Paclitaxel is also active in NECs however there is no data on the role of nab-paclitaxel. NABNEC aims to establish if the carboplatin and nab-paclitaxel combination is an effective and tolerable treatment for advanced GI-NECs and to enhance our understanding of the biology and imaging characteristics of NECs. Methods: Design: Randomised, non-comparative, stratified, multicentre phase 2 trial. Primary endpoint (n=70): objective response rate (RR) by RECIST 1.1 at 6 months. Secondary endpoints: progression free survival, overall survival, adverse events by NCI-CTCAE V4.03 and quality of life (EORTC QLQC30, QLQ-GINET21 questionnaires). Translational endpoints include 1) blood and tissue biomarkers (prognostic and/or predictive) correlated with clinical endpoints including circulating tumour cells, mutation profile (whole exome sequencing), DNA methylation profile; 2) correlation of 18-fluoro-deoxyglucose positron emission tomography (FDG-PET) to early response and other clinical endpoints. Sample Size: 70 patient’s gives 80% power and 95% confidence to rule out a 30% RR in favour of a clinically relevant RR of 50% at 6 months. Population: Adults with advanced or metastatic non-resectable GI-NEC (includes small cell and large cell NEC). Treatment: Randomisation 2:1 to Arm A IV nab-paclitaxel 100 mg/m2 on Day (D) 1 weekly and IV carboplatin AUC=5 on D1, 3 weekly; and Arm B IV etoposide 100mg/m2 on D1-3, and IV carboplatin AUC=5 on D1, 3 weekly to continue until disease progression or unacceptable toxicity. Assessments: 68Ga Octreotate PET at baseline, CT scan at baseline and every 9 weeks, FDG PET at baseline, 9 weeks then every 18 weeks and QOL questionnaires every 9 weeks until disease progression. NABNEC is enrolling patients at 12/20 planned study sites in Australia and New Zealand. ANZCTR #. Clinical trial information: 12616000958482.

Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.

Purpose: Personalized medicine strategies using genomic profiling are particularly pertinent for pancreas cancer. The Individualized Molecular Pancreatic Cancer Therapy (IMPaCT) trial was initially designed to exploit results from genome sequencing of pancreatic cancer under the auspices of the International Cancer Genome Consortium (ICGC) in Australia. Sequencing revealed small subsets of patients with aberrations in their tumor genome that could be targeted with currently available therapies. Experimental Design: The pilot stage of the IMPaCT trial assessed the feasibility of acquiring suitable tumor specimens for molecular analysis and returning high-quality actionable genomic data within a clinically acceptable timeframe. We screened for three molecular targets: HER2 amplification; KRAS wild-type; and mutations in DNA damage repair pathways (BRCA1, BRCA2, PALB2, ATM). Results: Tumor biopsy and archived tumor samples were collected from 93 patients and 76 were screened. To date 22 candidate cases have been identified: 14 KRAS wild-type, 5 cases of HER2 amplification, 2 mutations in BRCA2, and 1 ATM mutation. Median time from consent to the return of validated results was 21.5 days. An inability to obtain a biopsy or insufficient tumor content in the available specimen were common reasons for patient exclusion from molecular analysis while deteriorating performance status prohibited a number of patients from proceeding in the study. Conclusions: Documenting the feasibility of acquiring and screening biospecimens for actionable molecular targets in real time will aid other groups embarking on similar trials. Key elements include the need to better prescreen patients, screen more patients, and offer more attractive clinical trial options. Clin Cancer Res; 21(9); 2029–37. ©2015 AACR.

Adenocarcinoma of the pancreas is an aggressive malignancy with poor prognosis. Pancreatic neuroendocrine tumours (PNET) comprise ~3% of primary pancreatic neoplasms and they are more heterogeneous in their histological character and outcome. This is the case report of a 73-year-old female patient with synchronously diagnosed pancreatic adenocarcinoma and PNET, which is likely associated with a pathogenic partner and localizer of breast cancer 2, early onset (PALB2) mutation. The potential pathogenic significance of PALB2 and its association with various malignancies were investigated and the potential role of PALB2 in conferring sensitivity to chemotherapeutic agents, such as mitomycin C and cisplatin, was discussed. This case report highlights the significance of ongoing research into the molecular pathogenesis of pancreatic cancer, which may help guide the selection of optimal treatments for this disease, as well as the need for ongoing study of PALB2 as a possible predictive marker of response to DNA-damaging agents.

Sirtuin 1 is a protein deacetylase that regulates a large number of proteins often functionally implicated in tumor development and progression. Its pleiotropic function has turned SIRT1 into an attractive chemotherapeutic target, underscored by very promising preclinical results with SIRT1 inhibitors in the treatment of chronic myeloid leukemia. Here, we revisit the studies on SIRT1 as an emerging target for therapy in pancreatic cancer, a tumor with dismal outcomes for which currently few therapeutic options are available. We highlight those potential SIRT1 target genes that are commonly affected in pancreatic cancer according to recent genomic analyses.

To investigate the safety and efficacy of adding bevacizumab to first-line chemotherapy in metastatic colorectal cancer patients with peritoneal disease.We compared rates of gastrointestinal perforation in patients with metastatic colorectal cancer and peritoneal disease receiving first-line chemotherapy with and without bevacizumab in three distinct cohorts: (1) the AGITG MAX trial (Phase III randomised clinical trial comparing capecitabine vs capecitabine and bevacizumab vs capecitabine, bevacizumab and mitomycinC); (2) the prospective Treatment of Recurrent and Advanced Colorectal Cancer (TRACC) registry (any first-line regimen ± bevacizumab); and (3) two cancer centres in New South Wales, Australia [Macarthur Cancer Therapy Centre and Liverpool Cancer Therapy Centre (NSWCC) from January 2005 to Decenber 2012, (any first-line regimen ± bevacizumab). For the AGITG MAX trial capecitabine was compared to the other two arms (capecitabine/bevacizumab and capecitabine/bevacizumab/mitomycinC). In the AGITG MAX trial and the TRACC registry rates of gastrointestinal perforation were also collected in patients who did not have peritoneal metastases. Secondary endpoints included progression-free survival, chemotherapy duration, and overall survival. Time-to-event outcomes were estimated using the Kaplan-Meier method and compared using the log-rank test.Eighty-four MAX, 179 TRACC and 69 NSWCC patients had peritoneal disease. There were no gastrointestinal perforations recorded in either the MAX subgroup or the NSWCC cohorts. Of the patients without peritoneal disease in the MAX trial, 4/300 (1.3%) in the bevacizumab arms had gastrointestinal perforations compared to 1/123 (0.8%) in the capecitabine alone arm. In the TRACC registry 3/126 (2.4%) patients who had received bevacizumab had a gastrointestinal perforation compared to 1/53 (1.9%) in the chemotherapy alone arm. In a further analysis of patients without peritoneal metastases in the TRACC registry, the rate of gastrointestinal perforations was 9/369 (2.4%) in the chemotherapy/bevacizumab group and 5/177 (2.8%) in the chemotherapy alone group. The addition of bevacizumab to chemotherapy was associated with improved progression-free survival in all three cohorts: MAX 6.9 m vs 4.9 m, HR = 0.64 (95%CI: 0.42-1.02); P = 0.063; TRACC 9.1 m vs 5.5 m, HR = 0.61 (95%CI: 0.37-0.86); P = 0.009; NSWCC 8.7 m vs 6.8 m, HR = 0.75 (95%CI: 0.43-1.32); P = 0.32. Chemotherapy duration was similar across the groups.Patients with peritoneal disease do not appear to have an increased risk of gastrointestinal perforations when receiving first-line therapy with bevacizumab compared to systemic therapy alone.

Locally advanced rectal cancer is regularly treated with trimodality therapy consisting of neoadjuvant chemoradiation, surgery and adjuvant chemotherapy. There is a need for biomarkers to assess treatment response, and aid in stratification of patient risk to adapt and personalise components of the therapy. Currently, pathological stage and tumour regression grade are used to assess response. Experimental markers include proteins involved in cell proliferation, apoptosis, angiogenesis, the epithelial to mesenchymal transition and microsatellite instability. As yet, no single marker is sufficiently robust to have clinical utility. Microarrays that screen a tumour for multiple promising candidate markers, gene expression and microRNA profiling will likely have higher yield and it is expected that a combination or panel of markers would prove most useful. Moving forward, utilising serial samples of circulating tumour cells or circulating nucleic acids can potentially allow us to demonstrate tumour heterogeneity, document mutational changes and subsequently measure treatment response.

Nature 543, 65–71 (2017); doi:10.1038/nature21063 It has been brought to our attention that in Fig. 2d of this Article, an incorrect Sanger trace was used to represent the breakpoint of the EWSR1 and FLI1 type 2 fusion. This was due to an error during manuscript preparation, when we inadvertently inserted the electrophoretic trace referring to EWSR1 splicing variants.

3572 Background: Cetuximab (cet) increases survival in RAS wild-type (WT) metastatic colorectal cancer (mCRC) in first-line and chemorefractory patients (pts). Adding irinotecan (iri) to cet in refractory pts who had progressed on iri increased response and delayed progression in the BOND trial, which was conducted prior to recognition that RAS mutations are predictive of EGFR-inhibitor (EGFR-I) resistance. Subsequent trials in chemorefractory pts used single agent EGFR-I as standard. In the era of biomarker selection, the benefit of continuing iri versus single agent EGFR-I had not been resolved. Methods: ICECREAM is a randomised phase II trial evaluating cet v cet + iri in chemotherapy-refractory mCRC, stratified for KRAS G13D mutation (previously reported) or no mutations in KRAS, NRAS, BRAF and PI3KCA (Quad WT ). EGFR-I naïve, ECOG PS 0-1 pts, progressing within 6 months of iri and refractory (or intolerant) to fluoropyrimidine and oxaliplatin were randomised to cet 400mg/m2 IV loading then 250mg/m2 weekly +/- iri 180mg/m2q2 wks. The primary endpoint was progression-free survival at 6 months (6m PFS); secondary endpoints were response rate (RR), overall survival (OS), toxicity and quality of life (QOL). Results: From Nov 2012 to June 2016, 48 Quad WT pts were recruited: 2 ineligible (not iri-refractory, BRAF mutation) wre not included for analyses and a further 2 not evaluable for response. Characteristics were balanced between cet (n = 21) v cet-iri (n = 25), except for sex (male 62 v 72%) and primary site (left 95 v 68%). 6m PFS rate was 14% v 41%; HR 0.39 (95% CI: 0.20–0.78, p = 0.008). RR was 10% (2 PR) v 36% (1 CR, 8 PR); p = 0.04. Toxicities were higher with cet-iri; at least one grade 3/4 adverse event in 50 v 23%. No differences in global or specific QOL were seen. Conclusions: The AGITG ICECREAM trial confirms a significant synergy for the addition of iri to cet and improved PFS in Quad WT chemorefractory mCRC, echoing data in molecularly unselected pts. Clinical trial information: ACTRN12612000901808.

e15759 Background: PC is a highly lethal disease which metastasises early. The sequencing efforts of the Australian Pancreatic Cancer Genome Initiative (APGI) identified ROCK-1 as a target of interest. The Rho/ROCK pathway is essential in cellular movement, metastasis, vasculogenesis and stromal signaling. Fasudil (F) is a ROCK inhibitor which has been shown to be safe for human use. Using unique, patient derived models, we have previously shown that F plus gemcitabine (G) does not reduce cellular proliferation in vitro but reduces tumour size and improves overall survival (OS) in subcutaneous patient-derived xenografts (PDX). However, PDXs are critisised for not fully recapitulating the human condition. Here we aimed to generate a patient-derived orthotopic xenograft (O-PDX) which could be used to assess the effects of F + G on metastasis formation and OS. Methods: One patient-derived cell line (PDCL) was labled with firefly luciferase. This was injected into the pancreas of NOD/Shi- scid/IL-2Rγnull (NSG) mice to generate the O-PDX model. The O-PDX was imaged weekly with the IVIS imaging system. The O-PDXs were treated with saline control (S) (n = 8), gemcitabine (G) (n = 10) fasudil (F) (n = 6) or gemcitabine + fasudil (GF) (n = 10). Mice were culled once radiographic or clinical evidence of ascites was detected. Metastasis free (MFS) and OS were recorded. Vessel quantification was performed via CD-31 staining. Results: Metastases seen (spleen, liver, lung, ovary) on imaging were confirmed using GFP stains on immunohistochemistry. F prolonged MFS but not OS when compared with S. GF significantly prolonged MFS (33.5 versus 43 days; p = 0.0339) and OS (51.5 versus 64 days; p = 0.0035). CD-31 staining showed that treatment with F resulted in increased vascularity in the liver metastases and normal liver tissue but not in the pancreas tumour. Conclusions: The addition of Fasudil to gemcitabine improves MFS and OS in an orthotopic model of PC and is a promising new therapeutic option. The increase in vascularity of the metastases and normal liver tissue suggest that changes in vascularity are important and may result in improved delivery of gemcitabine.