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Background and AimsThe microbiome has long been suspected of a role in colorectal cancer (CRC) tumorigenesis. The mutational signature SBS88 mechanistically links CRC development with the strain ofEscherichia coliharboring thepksisland that produces the genotoxin colibactin, but the genomic, pathological and survival characteristics associated with SBS88-positive tumors are unknown.MethodsSBS88-positive CRCs were identified from targeted sequencing data from 5,292 CRCs from 17 studies and tested for their association with clinico-pathological features, oncogenic pathways, genomic characteristics and survival.ResultsIn total, 7.5% (398/5,292) of the CRCs were SBS88-positive, of which 98.7% (392/398) were microsatellite stable/microsatellite instability low (MSS/MSI-L), compared with 80% (3916/4894) of SBS88 negative tumors (p=1.5×10-28). Analysis of MSS/MSI-L CRCs demonstrated that SBS88 positive CRCs were associated with the distal colon (OR=1.84, 95% CI=1.40-2.42, p=1×10-5) and rectum (OR=1.90, 95% CI=1.44-2.51, p=6×10-6) tumor sites compared with the proximal colon. The top seven recurrent somatic mutations associated with SBS88-positive CRCs demonstrated mutational contexts associated with colibactin-induced DNA damage, the strongest of which was theAPC:c.835-8A>G mutation (OR=65.5, 95%CI=39.0-110.0, p=3×10-80). Large copy number alterations (CNAs) including CNA loss on 14q and gains on 13q, 16q and 20p were significantly enriched in SBS88- positive CRCs. SBS88-positive CRCs were associated with better CRC-specific survival (p=0.007; hazard ratio of 0.69, 95% CI=0.52-0.90) when stratified by age, sex, study, and by stage.ConclusionSBS88-positivity, a biomarker of colibactin-induced DNA damage, can identify a novel subtype of CRC characterized by recurrent somatic mutations, copy number alterations and better survival. These findings provide new insights for treatment and prevention strategies for this subtype of CRC.

Background Obesity is an established risk factor for colorectal cancer (CRC), but the evidence for the association is inconsistent across molecular subtypes of the disease. Methods We pooled data on body mass index (BMI), tumor microsatellite instability status, CpG island methylator phenotype status, BRAF and KRAS mutations, and Jass classification types for 11 872 CRC cases and 11 013 controls from 11 observational studies. We used multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for covariables. Results Higher BMI was associated with increased CRC risk (OR per 5 kg/m2 = 1.18, 95% CI = 1.15 to 1.22). The positive association was stronger for men than women but similar across tumor subtypes defined by individual molecular markers. In analyses by Jass type, higher BMI was associated with elevated CRC risk for types 1-4 cases but not for type 5 CRC cases (considered familial-like/Lynch syndrome microsatellite instability-H, CpG island methylator phenotype-low or negative, BRAF-wild type, KRAS-wild type, OR = 1.04, 95% CI = 0.90 to 1.20). This pattern of associations for BMI and Jass types was consistent by sex and design of contributing studies (cohort or case-control). Conclusions In contrast to previous reports with fewer study participants, we found limited evidence of heterogeneity for the association between BMI and CRC risk according to molecular subtype, suggesting that obesity influences nearly all major pathways involved in colorectal carcinogenesis. The null association observed for the Jass type 5 suggests that BMI is not a risk factor for the development of CRC for individuals with Lynch syndrome.

Background: Fusobacterium nucleatum (F. nucleatum) activates oncogenic signaling pathways and induces inflammation to promote colorectal carcinogenesis. Methods: We characterized F. nucleatum and its subspecies in colorectal tumors and examined associations with tumor characteristics and colorectal cancer–specific survival. We conducted deep sequencing of nusA, nusG, and bacterial 16s rRNA genes in tumors from 1,994 patients with colorectal cancer and assessed associations between F. nucleatum presence and clinical characteristics, colorectal cancer–specific mortality, and somatic mutations. Results: F. nucleatum, which was present in 10.3% of tumors, was detected in a higher proportion of right-sided and advanced-stage tumors, particularly subspecies animalis. Presence of F. nucleatum was associated with higher colorectal cancer–specific mortality (HR, 1.97; P = 0.0004). This association was restricted to nonhypermutated, microsatellite-stable tumors (HR, 2.13; P = 0.0002) and those who received chemotherapy [HR, 1.92; confidence interval (CI), 1.07–3.45; P = 0.029). Only F. nucleatum subspecies animalis, the main subspecies detected (65.8%), was associated with colorectal cancer–specific mortality (HR, 2.16; P = 0.0016), subspecies vincentii and nucleatum were not (HR, 1.07; P = 0.86). Additional adjustment for tumor stage suggests that the effect of F. nucleatum on mortality is partly driven by a stage shift. Presence of F. nucleatum was associated with microsatellite instable tumors, tumors with POLE exonuclease domain mutations, and ERBB3 mutations, and suggestively associated with TP53 mutations. Conclusions: F. nucleatum, and particularly subspecies animalis, was associated with a higher colorectal cancer–specific mortality and specific somatic mutated genes. Impact: Our findings identify the F. nucleatum subspecies animalis as negatively impacting colorectal cancer mortality, which may occur through a stage shift and its effect on chemoresistance.

Carriers of germline biallelic pathogenic variants in the MUTYH gene have a high risk of colorectal cancer. We test 5649 colorectal cancers to evaluate the discriminatory potential of a tumor mutational signature specific to MUTYH for identifying biallelic carriers and classifying variants of uncertain clinical significance (VUS). Using a tumor and matched germline targeted multi-gene panel approach, our classifier identifies all biallelic MUTYH carriers and all known non-carriers in an independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence interval 99.87–100%)). All monoallelic MUTYH carriers are classified with the non-MUTYH carriers. The classifier provides evidence for a pathogenic classification for two VUS and a benign classification for five VUS. Somatic hotspot mutations KRAS p.G12C and PIK3CA p.Q546K are associated with colorectal cancers from biallelic MUTYH carriers compared with non-carriers (p = 2 × 10−23 and p = 6 × 10−11, respectively). Here, we demonstrate the potential application of mutational signatures to tumor sequencing workflows to improve the identification of biallelic MUTYH carriers.

Introduction: Male breast cancer (BCa) is a rare disease accounting for less than 1% of all breast cancers (BC) and 1% of all cancers in males. The clinical management is largely extrapolated from female BCa. Few studies have examined the genomic landscape of male BCas, with six male BCas included in The Cancer Genome Atlas (TCGA). Familial studies of male BCas have shown genomic changes similar to female BCa, while a larger targeted sequencing study of 59 male breast cancers identified recurrent mutations affecting PIK3CA and GATA3. To date, there is still limited information regarding the genomic landscape of male BCas; particularly in the context of identifying targeted treatments. To reveal genomic changes that characterize male BCas in the context of known cancer driver genes linked to prognosis and targeted agents, we performed a targeted sequencing study on 248 male BCas from the International Male Breast Cancer Program. Methods: 248 primary M0, ER+ve, HER2-ve male BCas enrolled in the Part 1 (retrospective joint analysis) International Male Breast Cancer Program of 1483 patients diagnosed between 1990-2010 (Cardoso et al. Annals of Oncology, 2018) were processed for nucleic acid extraction from formalin-fixed paraffin embedded (FFPE) tissues. Using the Thermo Fisher Scientific Oncomine Comprehensive Assay v3 (OCAv3), a validated targeted sequencing panel currently used in the NCI-MATCH trial (NCT02465060), we evaluated mutational and copy number variations (CNVs) of genes that are prognostic or predictive to targeted therapies currently in use in the clinic or late-stage clinical trials. The OCAv3 DNA pan-cancer panel assays 115 genes for determining mutational status (48 full coding and 67 hotspot) as well as copy-number assessment in 43 genes. The OCAv3 uses Ampliseq-based technology linked to the Oncomine NGS workflow to identify actionable mutations and CNVs Results: Of the 248 samples assayed, 216 passed strict quality control parameters (87.1%). Using the Oncomine NGS workflow, actionable mutations at ≥5% variant allele frequency (VAF) were most frequently identified in PIK3CA (29.2%), BRCA2 (11.1%), NF1 (11.6%), indels in TP53 (10.6%), ATR (5.6%), ATRX (5.1%), indel BRCA2 (5.1%), TP53 point mutations (4.6%), MET (4.6%), ATM (4.6%), NOTCH2 (4.6%), CHEK1 (4.2%), FANCI (4.2%), PTEN (3.2%) with a number of additional genes identified at lower frequencies. Gene amplifications were most frequently detected in MYC (24.5%), FGFR1 (14.8%), CCND1 (12%), FGF3 (9.7%), FGF19 (9.7%), MDM2 (6.5%), CDK4 (1.4%), FGFR3, MDM4, ERBB2 (0.9% each), and FLT3, AR, MYCL, CDK6, IGF1R, FGFR4, KRAS, AKT3 and ESR1 (0.5% each). Although the results here describe the mutations and copy-number changes deemed to be actionable, further analysis of all non-actionable somatic mutations and CNVs will be presented and compared to female BCas previously assayed using the same panel. Conclusion: In this targeted sequencing study of the largest series of male BCas to our knowledge, we have revealed that PIK3CA continues to be a frequently altered gene in both male and female BCas. However, there is an enrichment of mutations in genes related to DNA repair in male BCs. Interestingly, while MYC is commonly amplified in female BCa, a higher frequency of amplified cases were seen in male BCas, in contrast to female BCas. Together with our previously generated transcriptional profiling data in this data set, we believe that both common and unique biological processes comprising male and female BCas will ultimately improve their clinical management and move towards the goal of precision medicine. This work has been funded by the Breast Cancer Research Foundation (BCRF). Citation Format: Jane Bayani, Coralie Poncet, Cheryl Crozier, Quang M Trinh, Megan Hopkins, Aime Lambert Uwimana, Tammy Piper, Carrie Cunningham, Monika Sobol, Stefan Aebi, Kim Benstead, Oliver Bogler, Lissandra Dal Lago, Florentine Hilbers, Ingrid Hedenfalk, Larissa Korde, Barbro Linderholm, John Martens, Lavinia Middleton, Melissa Murray, Catherine Kelly, Cecilia Nilsson, Monika Nowaczyk, Stephanie Peeters, Aleksandra Peric, Peggy Porter, Carolien Schröder, Isabel T Rubio, Kathryn J Ruddy, Christi van Asperen, Danielle Van Den Weyngaert, Carolien HM van Deurzen, Elise van Leeuwen-Stok, Joanna Vermeij, Eric Winer, Lincoln D Stein, Sharon H Giordano, Fatima Cardoso, John MS Bartlett. The genomic landscape of male breast cancers using the oncomine comprehensive assay for actionable mutations [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-03.

Due to breast screening, ductal carcinoma in situ (DCIS) accounts for approximately 25% of all newly diagnosed breast neoplasms. Believed to be a precursor to invasive carcinoma, a significant number of patients diagnosed with DCIS are effectively managed by surgery alone or in conjunction with radiotherapy and endocrine therapy. In general, there is an 8-11% relative risk for a subsequent invasive carcinoma over a period of 10 year, with 98% breast cancer-specific survival after 10 years of follow up. Although mastectomy, breast conserving surgery, and radiotherapy can reduce the risk of recurrence, there are ongoing lifetime consequences of treatment. Thus, there is a clinical need to identify those patients who are at risk of an invasive recurrence from those who might not recur or experience a subsequent DCIS recurrence. In this study, 60 patients with pure primary DCIS, treated with only with breast conserving therapy, across three different clinical outcome groups were examined: patients who did not experience a recurrence within 5 years (n=20); patients who experienced a recurrent DCIS within 5 years (n=20); and patients that recurred with an invasive cancer within 5 years (n=20). Pure primary DCIS lesions, as well as the matched DCIS recurrence or invasive recurrence, were macrodissected from formalin fixed paraffin embedded tissues and subjected to nucleic acid extraction. All samples were profiled using Thermo Fisher Scientific’s validated targeted sequencing panel, the Oncomine Comprehensive Assay v3.0 (OCAv3.0). This assay is comprised of common cancer driver genes shown to be prognostic and predictive to targeted therapies in use or in late-phase clinical trials, and is currently being used in the NCI-MATCH trial (NCT02465060). While the OCA panel and accompanying Oncomine Knowledgebase Reporter provides information regarding the targeted treatments linked to known actionable mutations, this study utilized all somatic mutations and copy number changes to reveal the genomic landscape of DCIS and their matched recurrences across these pan-cancer driver genes Amongst all primary DCIS samples across the three different clinical outcome groups, PIK3CA, was frequently found to be affected by SNV and Indels (32.8%) in addition to TP53 (26.2%), NF1 (21.3%), CREBBP (16.4%), ATM (14.8%), PALB2 (14.8%). DNA repair genes, including CHEK1, RAD50, RAD51B, MRE11A, BRCA1 and BRCA2, were found to be frequently subject to mutation in these primary DCIS samples ranging from 5%-15%. Similarly, copy number gains were frequently detected in HER2 (26.2%), CDK12 (18%), FGFR1 (4.9%), GNAS (4.9%), MYC, CCNE1, AR, RAD51C and RNF43 (1.6% each), and loses at H3F3A and KNSTRN (each 1.6%). Matched primary DCIS and their recurrent DCIS or invasive lesions exhibited similar changes with invasive cancers suggesting that in some cases, the primary DCIS gives rise to the invasive cancer. We will present the preliminary findings mapping the mutational and copy-number landscape of primary DCIS and matched recurrences to identify putative genomic changes defining these clinical outcome groups and to investigate the genomic progression of DCIS to invasive carcinoma. Citation Format: Jane Bayani, Quang M Trinh, Mary Anne Quintayo, Cheryl Crozier, Ilinca Lungu, Dan Dion, Joema Felipe-Lima, Giancarlo Pruneri, Jonas Bergh, Fredrik Warnberg, Giuseppe Viale, Lincoln D Stein, John MS Bartlett. The mutational landscape of cancer driver genes in matched primary ductal carcinoma in situ and recurrent ductal carcinoma in situ or recurrent invasive cancers [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-08-22.

PURPOSE Hormone receptor–positive breast cancer remains an ongoing therapeutic challenge, despite optimal anti-endocrine therapies. In this study, we assessed the prognostic ability of genomic signatures to identify patients at risk for recurrence after endocrine therapy. Analysis was performed on the basis of an a priori hypothesis related to molecular pathways, which might predict response to existing targeted therapies. PATIENTS AND METHODS A subset of patients from the Tamoxifen Versus Exemestane Adjuvant Multinational trial ( ClinicalTrials.gov identifiers: NCT00279448 and NCT00032136, and NCT00036270) pathology cohort were analyzed to determine the prognostic ability of mutational and copy number aberration biomarkers that represent the cyclin D/cyclin-dependent kinase (CCND/CDK), fibroblast growth factor receptor/fibroblast growth factor (FGFR/FGF), and phosphatidylinositol 3-kinase/protein kinase B (PI3K/ATK) pathways to inform the potential choice of additional therapies to standard endocrine treatment. Copy number analysis and targeted sequencing was performed. Pathways were identified as aberrant if there were copy number aberrations and/or mutations in any of the predetermined pathway genes: CCND1/CCND2/CCND3/CDK4/CDK6, FGFR1/FGFR2/FGFR2/FGFR4, and AKT1/AKT2/PIK3CA/PTEN. RESULTS The 390 of 420 samples that passed quality control were analyzed for distant metastasis–free survival between groups. Patients with no changes in the CCND/CDK pathway experienced a better distant metastasis–free survival (hazard ratio, 1.94; 95% CI, 1.45 to 2.61; P < .001) than those who possessed aberrations. In the FGFR/FGF and PI3K/AKT pathways, a similar outcome was observed (hazard ratio, 1.43 [95% CI, 1.07 to 1.92; P = .017] and 1.34 [95% CI, 1.00 to 1.81; P = .053], respectively). CONCLUSION We show that aberrations of genes in these pathways are independently linked to a higher risk of relapse after endocrine treatment. Improvement of the clinical management of early breast cancers could be made by identifying those for whom current endocrine therapies are sufficient, thus reducing unnecessary treatment, and secondly, by identifying those who are at high risk for recurrence and linking molecular features that drive these cancers to treatment with targeted therapies.

Sonic hedgehog medulloblastoma encompasses a clinically and molecularly diverse group of cancers of the developing central nervous system. Here, we use unbiased sequencing of the transcriptome across a large cohort of 250 tumors to reveal differences among molecular subtypes of the disease, and demonstrate the previously unappreciated importance of non-coding RNA transcripts. We identify alterations within the cAMP dependent pathway (GNAS, PRKAR1A) which converge on GLI2 activity and show that 18% of tumors have a genetic event that directly targets the abundance and/or stability of MYCN. Furthermore, we discover an extensive network of fusions in focally amplified regions encompassing GLI2, and several loss-of-function fusions in tumor suppressor genes PTCH1, SUFU and NCOR1. Molecular convergence on a subset of genes by nucleotide variants, copy number aberrations, and gene fusions highlight the key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma and open up opportunities for therapeutic intervention., Sonic Hedgehog medulloblastoma (Shh-MB) comprises four subtypes each with distinct clinical traits. Here the authors characterize the genome, transcriptome, and methylome of Shh-MB subtypes, revealing a complex fusion landscape and the molecular convergence of MYCN and cAMP signaling pathways.

Hormone receptor positive breast cancer remains an ongoing therapeutic challenge. Despite optimal anti-endocrine therapies, most breast cancer deaths follow a diagnosis of early luminal cancer. Data describing molecular events in breast cancer has yet to be translated into actionable information to inform medical management and benefit patients. To understand the impact of multiple aberrations in the context of current therapy, we assessed the prognostic ability of genomic signatures as a putative stratification tool to targeted therapies. The analysis was performed based on an a priori hypothesis relating to molecular pathways which might predict response to targeted therapies currently under evaluation in late-stage clinical trials. In a case-control fashion, 420 patients from the Tamoxifen vs Exemstane Adjuvant Multinational Trial (TEAM) pathology cohort, were analysed to determine the prognostic, ability for these mutational and copy-number biomarkers representing the CCND/CDK, FGFR/FGF and AKT/PIK3CA to inform potential response to therapies targeting these pathways. Copy number analysis was performed using the Affymetrix Oncoscan™ Assay. Targeted sequencing was performed in a subset of samples for genes based on signaling cassettes mined from the ICGC. Pathways were identified as aberrant if there were copy number aberrations (CNAs) and/or mutations in any of the predetermined pathway genes: 1) CCND1/CCND2/CCND3/CDK4/CDK6 2) FGFR1/FGFR2/FGFR2/FGFR4 and 3) AKT1/AKT2/PIK3CA/PTEN. Kaplan Meier and log rank analyses were used for DRFS between groups. Hazard ratios were calculated using the Cox proportional hazard models adjusted for age, tumour size, grade, lymph node and HER2 status. 390/420 samples passed informatics QC filters. For the CCND/CDK pathway, patients with no CNA changes experienced a better DRFS (HR=1.94, 95% CI 1.45-2.61, p< 0.001). For the FGFR/FGF pathway, a similar outcome is seen among patients without CNAs (HR = 1.43, 95% CI 1.07-1.92 p=0.017). For AKT/PIK3CA, a decrease in DRFS was seen in those with aberrations (H=1.34, 95% CI 1.00-1.81, p=0.053). We demonstrated that CNAs of genes within CDK4/CCND, PIK3CA/AKT and FGFR pathways are independently linked to high risk of relapse following endocrine treatment. In this way, improving the clinical management of early breast cancers could be made, firstly by identifying those patients for whom current endocrine therapies are sufficient, thus reducing unnecessary treatment; and secondly, identifying those patients who are at high-risk for recurrence despite optimal endocrine therapy and the linking molecular features driving these cancers to treatment with targeted therapies. Citation Format: Bayani J, Kornaga EN, Crozier C, Jang GH, Kalatskaya I, Trinh QM, Yao CQ, Livingstone J, Hasenburg A, Kieback DG, Markopoulos C, Dirix L, Boutros PC, Spears M, Stein LD, Rea D, Bartlett JMS. Copy-number and targeted sequencing analyses to identify distinct prognostic groups: Implications for patient selection to targeted therapies amongst anti-endocrine therapy resistant early breast cancers [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD4-11.

Background The use of chemotherapies such as anthracyclines and taxanes have improved overall and disease free survival in breast cancer. For all patients, anthracyclines can have significant toxicities including cardiotoxicity and leukemia. It is therefore essential to select the subset of patients who will receive the optimal overall benefit from anthracycline therapy and to identify molecular pathways driving resistance. To fully understand the impact of mutations in the context of current breast cancer therapy, requires a comprehensive mapping of key molecular events in the context of treatment. We sequenced 101 genes, that were prioritized based on not only gene frequency, but also taking into account the importance of amino acid substitution, type of mutation and network connectivity, in 692 primary tumours to both identify driver genes and pathway cassettes and to understand their clinical significance in response to anthracycline treatment. Methods We performed targeted sequencing in patients from the BR9601 (n=374) and CCTG MA.5 (n=703) clinical trials. The BR9601 and MA.5 clinical trials examined the effectiveness of combination chemotherapy consisting of CMF (cyclophosphamide, methotrexate and 5-fluorouracil) with or without epirubicin. DNA was extracted, samples were sequenced using AmpliSeq Technology adapted to Illumina and somatic mutations were called using a novel mutation calling pipeline (ISOWN). A priori analyses were performed using distant recurrence free survival (DRFS) as the primary endpoint. Results: In 692 successfully analysed samples 509 (73.6%) samples exhibited at least one single nucleotide mutation (range 0-54). 94/101 genes were mutated in at least one patient. Only variants in PIK3CA, TP53, CDH1, TLE6, MLL3 and USH2A were detected in 5% or more of samples. TSC22D1, RB1 and ZNF565 were associated with increased risk of distant relapse in multivariate analyses corrected for clinic-pathological variables. No single genes were predictive of anthracycline treatment compared to CMF in multivariate analyses corrected for clinic-pathological variables. Signaling cassettes/modules were designed based on the pathway database, Reactome. Within the signaling cassettes one module was predictive of anthracycline failure. Patients with one or more mutations in this module had an increased risk of distant relapse (HR 0.52, 95% CI 0.29-0.95, p=0.034) when treated with an anthracycline containing chemotherapy regimen compared to CMF (HR 1.34 95% CI 1.05-1.72, p=0.019). Conclusions: We successfully performed a signaling pathway-based targeted sequencing analysis within predefined signaling modules. We identified a single signaling cassette linked to anthracycline resistance in early breast cancer. However, further work to validate this study in a separate clinical trial is warranted. Citation Format: Spears M, Kalatskaya I, Trinh QM, Liao L, Chong TM, Crozier C, Dion D, Heisler L, Timms L, Stein LD, Pritchard KI, Levine MN, Shepherd L, Twelves CJ, Bartlett JMS. Targeted sequencing in early breast cancer: Identification of novel candidate mutations predictive of anthracycline benefit [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-10-04.

Colorectal cancer (CRC) is a biologically heterogeneous disease. To characterize its mutational profile, we conduct targeted sequencing of 205 genes for 2,105 CRC cases with survival data. Our data shows several findings in addition to enhancing the existing knowledge of CRC. We identify PRKCI, SPZ1, MUTYH, MAP2K4, FETUB, and TGFBR2 as additional genes significantly mutated in CRC. We find that among hypermutated tumors, an increased mutation burden is associated with improved CRC-specific survival (HR = 0.42, 95% CI: 0.21–0.82). Mutations in TP53 are associated with poorer CRC-specific survival, which is most pronounced in cases carrying TP53 mutations with predicted 0% transcriptional activity (HR = 1.53, 95% CI: 1.21–1.94). Furthermore, we observe differences in mutational frequency of several genes and pathways by tumor location, stage, and sex. Overall, this large study provides deep insights into somatic mutations in CRC, and their potential relationships with survival and tumor features., Large scale sequencing study is of paramount importance to unravel the heterogeneity of colorectal cancer. Here, the authors sequenced 205 cancer genes in more than 2000 tumours and identified additional mutated driver genes, determined that mutational burden and specific mutations in TP53 are associated with survival odds.

Colorectal cancer (CRC) is a heterogenous disease that develops through somatic mutations in driver genes, leading to activation of diverse neoplastic pathways. To systematically examine if somatically mutated genes and pathways impact survival, we sequenced tumor and normal DNA samples for 4,512 CRC cases using a targeted panel. We performed Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for associations of disease-specific (DS)-survival with somatically mutated genes and pathways, adjusting for age and sex, and stratifying baseline hazards by study population. We assessed statistical significance using Bonferroni p-value thresholds to account for multiple testing of 214 genes (2.34x10-4) and 6 key CRC pathways (8.3x10-3). We limited analyses to non-silent mutations. We observed that DS-survival was significantly more favorable among individuals with hypermutated (HM) tumors, primarily consisting of microsatellite unstable and POLE-mutated tumors, as compared to those with non-hypermutated (NHM) tumors (HR=0.4, 95% CI: 0.3-0.5, p=1.2x10-17). BRAF V600E mutations were associated with poorer survival (HR=2.0, 95% CI: 1.6-2.5, p=1.6x10-10). This association was more pronounced among NHM tumors (HR=2.3, 95% CI: 1.8-2.9, p=4.3x10-12). We identified suggestive associations (p-values < 5.0x10-3 in overall or stratified analyses) between DS-survival and mutations in B2M, TP53, and SMAD4. Mutations in B2M may provide more favorable prognosis for survival (HR=0.5, 95% CI: 0.3-0.8, p=4.4x10-3), with similar effect sizes in HM and NHM tumors. Poorer survival may be associated with mutations in TP53 (HR=1.2, 95% CI:1.2-1.4, p=9.3x10-4) and SMAD4 (HR=1.3, 95% CI:1.1-1.6, p=3.2x10-3) in NHM tumors. We further observed statistically significant associations between survival and three mutated pathways: TP53/ATM (HR=1.2, 95% CI:1.1-1.4, p=9.0x10-4), receptor tyrosine kinases (RTK) and RAS (HR=1.3, 95% CI:1.1-1.5, p=4.5x10-5), and TGF-beta (HR=1.3, 95% CI:1.1-1.5, p=2.9x10-4). Findings for TP53/ATM and RTK/RAS were primarily due to mutations in one gene within each pathway (TP53 and BRAF, respectively). However, the TGF-beta pathway finding, which was more pronounced in NHM tumors, included two genes with p-values less than 0.05 (SMAD4 p=3.2x10-3 and TGFBR2 p=0.01). Despite our large sample size, relatively few somatically mutated genes were significantly associated with DS-survival. It may be that pathway-level testing affords more power for analyses and that larger sample sizes are needed. It is of interest that non-silent mutations in B2M, whose product is a component of the class I major histocompatibility complex, was associated with improved DS-survival, though our finding was not statistically significant after multiple testing correction so further exploration and replication is needed. Citation Format: Tabitha A. Harrison, Syed H. Zaidi, Conghui Qu, Amanda I. Phipps, Robert S. Steinfelder, Quang M. Trinh, Sonja I. Berndt, Daniel D. Buchanan, Peter T. Campbell, Andrew T. Chan, Kim F. Doheny, David A. Drew, Jane C. Figueiredo, Steven J. Gallinger, Marios Giannakis, Andrea Gsur, Marc J. Gunter, Michael Hoffmeister, Wen-Yi Huang, Paul J. Limburg, Victor Moreno, Polly A. Newcomb, Shuji Ogino, Ross L. Prentice, Tameka Shelford, Wei Sun, Stephen N. Thibodeau, Li Hsu, Ulrike Peters. Associations of somatically mutated genes and pathways with colorectal cancer specific survival in 4,500 colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB090.

We recognize that many cancers are highly complex mixtures of sub-populations of cells, which are also influenced by their microenvironment. This heterogeneity explains in part, why the majority of current therapeutic approaches for cancer work best when multiple agents are combined. Therefore, in an era of targeted therapeutics it becomes critical to understand the complexity of tumors both at diagnosis and over the course of therapy, including measures of heterogeneity. Here we present genomic, transcriptomic and in situ proteomic profiling of a cohort of breast cancer (BCa) lumpectomies to reveal the extent of heterogeneity in pathologically defined unifocal and multifocal cancers. Integration of molecular profiling, phylogenetic analyses and radiomics has the potential to significantly improve BCa clinical management and stratification to targeted therapies that are already available in the clinic. In this study, lumpectomies with imaging data were processed as whole mounts with serial blocks reviewed. Tissue cores were taken from at least three different regions through the lumpectomy for nucleic acid extraction and tissue microarray (TMA) construction, focusing on morphologic/histological differences in addition to the spatial orientation of the sampled region within the lumpectomy. Targeted sequencing using the Oncomine Comprehensive Assay v3 (OCAv3); transcriptional profiling using the NanoString Breast Cancer 360 Panel; in situ profiling by multiplex fluorescence immunohistochemistry (MxIF) and Digital Spatial Profiling (see abstract Spears et al) were performed. From this cohort of 60 patients, we present a subset of patients demonstrating integration of the molecular profiling to reveal the phylogenetic relationship between the multiple samplings and the impact on clinical decision making in BCa. Briefly, we identified differences in the molecular subtypes between the different sample regions from the same unifocal cancer as well as differences in the predicted responses to anti-PDL1 therapy by transcriptional profiling; while targeted sequencing of driver mutations suggested the likelihood of an ancestral tumor cell giving rise to the lesions in pathologically defined multifocal cancers. However it was evident that genes and pathways found to be aberrant in these different lesions from the same cancer could impact the response to standard BCa treatment, or the selection of targeted therapies. In situ proteomics demonstrated differences in the expression of standard BCa markers ER, PgR, HER2 and Ki67 in addition to immune markers in the tumor and tumor microenvironment. While there are clinically validated transcriptional risk test available for BCa, we have demonstrated that transcriptomics or genomics alone is insufficient for a rational stratification of patients to currently available targeted therapies; therefore supporting the need for an integrative approach. Citation Format: Jane Bayani, Quang M. Trinh, Mary Anne Quintayo, Cheryl Crozier, Megan Hopkins, Jingping Qiao, Alison Cheung, James Mainprize, Quaid Morris, Melanie Spears, Martin Yaffe, Lincoln Stein, John M. Bartlett. Tumour spatial heterogeneity in breast cancer and the impact on clinical management [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3131.

Availability of lung cancer models that closely mimic human tumors remains a significant gap in cancer research, as tumor cell lines and mouse models may not recapitulate the spectrum of lung cancer heterogeneity seen in patients. We aimed to establish a patient-derived tumor xenograft (PDX) resource from surgically resected non-small cell lung cancer (NSCLC). Fresh tumor tissue from surgical resection was implanted and grown in the subcutaneous pocket of non-obese severe combined immune deficient (NOD SCID) gamma mice. Subsequent passages were in NOD SCID mice. A subset of matched patient and PDX tumors and non-neoplastic lung tissues were profiled by whole exome sequencing, single nucleotide polymorphism (SNP) and methylation arrays, and phosphotyrosine (pY)-proteome by mass spectrometry. The data were compared to published NSCLC datasets of NSCLC primary and cell lines. 127 stable PDXs were established from 441 lung carcinomas representing all major histological subtypes: 52 adenocarcinomas, 62 squamous cell carcinomas, one adeno-squamous carcinoma, five sarcomatoid carcinomas, five large cell neuroendocrine carcinomas, and two small cell lung cancers. Somatic mutations, gene copy number and expression profiles, and pY-proteome landscape of 36 PDXs showed greater similarity with patient tumors than with established cell lines. Novel somatic mutations on cancer associated genes were identified but only in PDXs, likely due to selective clonal growth in the PDXs that allows detection of these low allelic frequency mutations. The results provide the strongest evidence yet that PDXs established from lung cancers closely mimic the characteristics of patient primary tumors.

Many cancers are highly complex mixtures of many sub-populations of cells, also influenced by their microenvironment. This heterogeneity explains, in part, why the majority of current therapeutic approaches for cancer work best when multiple agents are combined. Therefore, in an era of targeted therapeutics it becomes critical to understand the complexity of tumours both at diagnosis and over the course of therapy, including measures of heterogeneity. Here we present genomic, transcriptomic and in situ proteomic profiling of a cohort of breast cancer (BCa) lumpectomies with associated imaging data to reveal the extent of heterogeneity in pathologically defined unifocal and multifocal cancers. Integration of molecular profiling, phylogenetic analyses and radiomics has the potential to significantly improve BCa clinical management and stratification to targeted therapies that are already available in the clinic. In this study, lumpectomies were processed as whole mounts with serial blocks reviewed. Tissue cores were taken from at least three different regions throughout the lumpectomy for nucleic acid extraction and tissue microarray (TMA) construction, focusing on morphologic/histological differences in addition to the spatial orientation of the sampled region within the lumpectomy. Targeted sequencing using the Oncomine Comprehensive Assay v3 (OCAv3); transcriptional profiling using the NanoString Breast Cancer 360 Panel; and in situ profiling by multiplex fluorescence immunohistochemistry (MxIF) performed (see abstract Cheung et al). From this cohort of 60 patients, we present a subset of patients demonstrating integration of the molecular profiling to reveal the phylogenetic relationship between the multiple samplings and the potential impact on clinical decision making in BCa. We identified differences in the molecular subtypes between the different sample regions from the same unifocal cancer as well as differences in the predicted responses to anti-PDL1 therapy by transcriptional profiling. Targeted sequencing of driver mutations suggested the likelihood of an ancestral tumour cell giving rise to the lesions in pathologically defined multifocal cancers; however it was evident that genes and pathways found to be aberrant in these different lesions from the same cancer could impact the response to standard BCa treatment, or the selection of targeted therapies. In situ proteomics demonstrated differences in the expression of standard BCa markers ER, PgR, HER2 and Ki67, in addition to immune markers in the tumour and its microenvironment. While there are clinically validated transcriptional risk tests available for BCa, we have demonstrated that transcriptomics or genomics alone is insufficient for a rational stratification of patients to currently available targeted therapies, therefore, supporting the need for an integrative approach. Citation Format: Jane Bayani, Quang M. Trinh, Mary Anne Quintayo, Cheryl Crozier, Megan Hopkins, Jingping Qiao, Alison Cheung, James G Mainprize, Quaid Morris, Melanie Spears, Martin J. Yaffe, Lincoln D. Stein, John M.S. Bartlett. Revealing tumour spatial heterogeneity in breast cancer and the impact on clinical management [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-002.

Noonan syndrome (NS) is a relatively common genetic disorder, characterized by typical facies, short stature, developmental delay, and cardiac abnormalities. Known causative genes account for 70-80% of clinically diagnosed NS patients, but the genetic basis for the remaining 20-30% of cases is unknown. We performed next-generation sequencing on germ-line DNA from 27 NS patients lacking a mutation in the known NS genes. We identified gain-of-function alleles in Ras-like without CAAX 1 (RIT1) and mitogen-activated protein kinase kinase 1 (MAP2K1) and previously unseen loss-of-function variants in RAS p21 protein activator 2 (RASA2) that are likely to cause NS in these patients. Expression of the mutant RASA2, MAP2K1, or RIT1 alleles in heterologous cells increased RAS-ERK pathway activation, supporting a causative role in NS pathogenesis. Two patients had more than one disease-associated variant. Moreover, the diagnosis of an individual initially thought to have NS was revised to neurofibromatosis type 1 based on an NF1 nonsense mutation detected in this patient. Another patient harbored a missense mutation in NF1 that resulted in decreased protein stability and impaired ability to suppress RAS-ERK activation; however, this patient continues to exhibit a NS-like phenotype. In addition, a nonsense mutation in RPS6KA3 was found in one patient initially diagnosed with NS whose diagnosis was later revised to Coffin-Lowry syndrome. Finally, we identified other potential candidates for new NS genes, as well as potential carrier alleles for unrelated syndromes. Taken together, our data suggest that next-generation sequencing can provide a useful adjunct to RASopathy diagnosis and emphasize that the standard clinical categories for RASopathies might not be adequate to describe all patients.

Item does not contain fulltext In acute myeloid leukaemia (AML), the cell of origin, nature and biological consequences of initiating lesions, and order of subsequent mutations remain poorly understood, as AML is typically diagnosed without observation of a pre-leukaemic phase. Here, highly purified haematopoietic stem cells (HSCs), progenitor and mature cell fractions from the blood of AML patients were found to contain recurrent DNMT3A mutations (DNMT3A(mut)) at high allele frequency, but without coincident NPM1 mutations (NPM1c) present in AML blasts. DNMT3A(mut)-bearing HSCs showed a multilineage repopulation advantage over non-mutated HSCs in xenografts, establishing their identity as pre-leukaemic HSCs. Pre-leukaemic HSCs were found in remission samples, indicating that they survive chemotherapy. Therefore DNMT3A(mut) arises early in AML evolution, probably in HSCs, leading to a clonally expanded pool of pre-leukaemic HSCs from which AML evolves. Our findings provide a paradigm for the detection and treatment of pre-leukaemic clones before the acquisition of additional genetic lesions engenders greater therapeutic resistance.

A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case-control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10(-5)). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways.

Colorectal cancer (CRC), a common malignancy, is a biologically heterogeneous disease. Next-generation sequencing (NGS) has enabled CRC characterization by identifying somatically mutated genes which now allow us to better define colorectal tumor subtypes (e.g. by mutated pathways). However, the relationship of such CRC subtypes to patient survival and genetic and lifestyle risk factors has not been comprehensively studied. To identify somatic mutations in CRC cases, we designed a targeted AmpliSeq panel of CRC related genes and genomic regions informed by whole exome sequencing data from ~1,200 CRC cases. The sequencing was conducted on Illumina HiSeq 2500 with a mean coverage of 740x and 240x for DNA extracted from FFPE tumor tissues and matched normal samples, respectively. Strelka, MuTect, VarDict, and Varscan2 were used to identify somatic single nucleotide variants and indels. Sanger sequencing was performed to validate a subset of variants. To date, we have sequenced ~2,400 CRC tumors and matched control tissues from four studies participating in the Colon Cancer Family Registry (CCFR) and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). In most tumors, we identified non-silent mutations in genes belonging to the WNT (77%), p53 (44%), IGF2/PI3K (22%), RTK-RAS (47%), and TGF-beta (26%) signaling pathways. Among the 15% of tumors that could be classified as hypermutated, based on the number of mutations, 39% exhibited non-silent mutations in MLH1, MLH3, MSH2, MSH6, and PMS2 and 41% exhibited non-silent mutations in POLE and POLD1. In a subset of studies with available survival data, we used Cox regression to assess the association of hypermutation status and the presence of non-silencing mutations in key signaling pathways with overall (OS) and disease-specific (DSS) survival. OS and DSS were significantly more favorable in cases with hypermutated vs. non-hypermutated CRC (HR=0.77, 95% CI: 0.60-0.98, p=0.04 and HR=0.35, 95% CI: 0.22-0.57, p=2x10-5, respectively); these associations were most pronounced for POLE/POLD1 mutated hypermutated CRC (HR=0.69, 95% CI: 0.46-1.02, p=0.06, HR=0.21, 95% CI: 0.08-0.56, p=2x10-3, respectively). There was no significant association of mutations in WNT, p53, IGF2/PI3K, RTK-RAS, or TGF-beta pathways with survival (p>0.05). The comprehensive molecular characterization of this large panel of CRC cases will support further studies of molecular subtypes of CRC with clinical, lifestyle, and environmental factors. A better understanding of molecular mechanisms of CRC will be valuable in developing strategies for prevention, diagnosis, and treatment of this life-threatening disease. Citation Format: Syed Zaidi, Amanda Phipps, Tabitha Harrison, Catherine Grasso, Robert Steinfelder, Quang Trinh, Charles Connolly, Barbara Banbury, Adilya Rafikova, Philipp Hofer, Stefanie Brezina, Marios Giannakis, Xinmeng Jasmine Mu, Michael Quist, Charles Fuchs, Levi Garraway, Li Hsu, Lincoln Stein, Andrea Gsur, Shuji Ogino, Steven Gallinger, Polly Newcomb, Peter Campbell, Wei Sun, Thomas Hudson, Ulrike Peters. Deep targeted tumor sequencing of colorectal cancer cases to study associations of molecular subtypes with clinical, genetic, and lifestyle risk factors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1224.

Jung Soh1, Andrei L Turinsky1, Quang M Trinh1, Jasmine Chang1, Ajay Sabhaney1, et al1Sun Center of Excellence for Visual Genomics, University of Calgary, Calgary, AB, Canada; 2Department of Biological Sciences, University of Alberta, Edmonton, AB, CanadaAbstract: We have developed a computational framework for spatiotemporal integration of molecular and anatomical datasets in a virtual reality environment. Using two case studies involving gene expression data and pharmacokinetic data, respectively, we demonstrate how existing knowledge bases for molecular data can be semantically mapped onto a standardized anatomical context of human body. Our data mapping methodology uses ontological representations of heterogeneous biomedical datasets and an ontology reasoner to create complex semantic descriptions of biomedical processes. This framework provides a means to systematically combine an increasing amount of biomedical imaging and numerical data into spatiotemporally coherent graphical representations. Our work enables medical researchers with different expertise to simulate complex phenomena visually and to develop insights through the use of shared data, thus paving the way for pathological inference, developmental pattern discovery and biomedical hypothesis testing.Keywords: anatomical atlas, gene expression, pharmacokinetics, biomedical data integration, CAVEman, virtual reality in medicine

The nematode Caenorhabditis briggsae is a model for comparative developmental evolution with C. elegans. Worldwide collections of C. briggsae have implicated an intriguing history of divergence among genetic groups separated by latitude, or by restricted geography, that is being exploited to dissect the genetic basis to adaptive evolution and reproductive incompatibility. And yet, the genomic scope and timing of population divergence is unclear. We performed high-coverage whole-genome sequencing of 37 wild isolates of the nematode C. briggsae and applied a pairwise sequentially Markovian coalescent (PSMC) model to 703 combinations of genomic haplotypes to draw inferences about population history, the genomic scope of natural selection, and to compare with 40 wild isolates of C. elegans. We estimate that a diaspora of at least 6 distinct C. briggsae lineages separated from one another approximately 200 thousand generations ago, including the ???Temperate??? and ???Tropical??? phylogeographic groups that dominate most samples from around the world. Moreover, an ancient population split in its history 2 million generations ago, coupled with only rare gene flow among lineage groups, validates this system as a model for incipient speciation. Low versus high recombination regions of the genome give distinct signatures of population size change through time, indicative of widespread effects of selection on highly linked portions of the genome owing to extreme inbreeding by self-fertilization. Analysis of functional mutations indicates that genomic context, owing to selection that acts on long linkage blocks, is a more important driver of population variation than are the functional attributes of the individually encoded genes.

Accurate identification of somatic mutations is an essential first step for many cancer studies. It is usually done by comparing the genome of the tumour to the reference genome sequence derived from a normal tissue taken from the same donor. However, there are a number of possible scenarios in which matched normal tissues might be not available for comparisons. It is most commonly encountered when performing analysis on retrospective studies with human tissues from clinical trials or pathology archives when normal samples were not collected in the first place or patient consent precludes examination of normal tissue or germline variants. Another common scenario is the use of a cancer cell line as an experimental model, many of which have no information on the donor’s normal genome. In this work, we describe an algorithm to identify somatic single nucleotide variants (SNVs) in Next Generation Sequencing (NGS) data in the absence of normal samples using a machine learning approach. Our algorithm was evaluated using a family of supervised learning classifications across six different cancer types and ~1,600 samples, including cell lines, fresh frozen tissues, and formalin-fixed paraffin-embedded (FFPE) tissues. In addition, our algorithm was tested with both deep targeted sequencing and whole exome sequencing strategies. The algorithm correctly classified between 95% and 98% of somatic mutations with F1-measure ranges from 75.9% to 98.6% depending on the tumour type. We have released the algorithm as a software package called ISOWN (Identification of SOmatic mutations Without matching Normal tissues), which is available as Open Source under Apache License 2.0 from https://github.com/ikalatskaya/ISOWN. Citation Format: Irina Kalatskaya, Quang Trinh, Melanie Spears, John Bartlett, Lincoln Stein. Precise somatic mutation prediction in the absence of matching normal DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3571. doi:10.1158/1538-7445.AM2017-3571

The Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) in collaboration with the Colorectal Cancer Family Registry (CCFR) aims to identify genetic variants and environmental risk factors that impact colorectal cancer (CRC). Over 30 studies from North America, Europe, and Australia participate in GECCO. These studies have collected clinical, epidemiological, and survival data, as well as blood and tumor biospecimens, for over 80,000 CRC cases and controls. The current study aims to conduct targeted deep sequencing of tumors and matching normal DNA to identify recurrent and novel somatic and germline variants in 4,200 CRC cases. To achieve this goal, an AmpliSeq targeted sequencing panel of 1.12 Mbp was constructed to sequence the coding regions of 190 significantly mutated genes identified from whole exome sequencing datasets generated by the Nurses’ Health Study and Health Professional’s Follow-up Study, and The Cancer Genome Atlas. The panel also covers coding regions of 15 genes with germline high penetrance mutations in CRC, 54 regions to detect CRC-related copy number alterations (CNAs), and microsatellite and homopolymer repeat regions to identify defective DNA mismatch repair. Primers were also included to detect Fusobacterium nucleatum DNA in tumor biopsies, as F. nucleatum is thought to promote CRC carcinogenesis. Sequencing of the DNA libraries on Illumina HiSeq 2500 produced a mean coverage of greater than 500X for tumor DNA and 100X for normal DNA, with >85% of the bases covered at the target at 50x. So far, targeted sequencing of >1,500 DNA samples from CRC tumors and normal tissues has identified recurrent and novel somatic mutations, germline genetic variants, and hypermutation status of the tumors due to defective DNA mismatch repair or pathogenic mutations in the POLE gene. Targeted sequencing has also allowed quantification of the F. nucleatum DNA in tumor biopsies; the results were validated by a multiplex QPCR assay. At the AACR annual meeting, we will present targeted sequencing results generated from the first two GECCO-participating studies (n=1,300 cases). These data will be valuable for future association testing of somatic mutations, CNAs, hypermutation status, and F. nucleatum with germline genetic variants, lifestyle, and environmental risk factors and survival. This large study will allow development of better strategies for diagnosis, treatment, and prevention of CRC. Citation Format: Syed H. Zaidi, Wei Sun, Jeroen Huyghe, Catherine S. Grasso, Quang Trinh, Charles Connolly, Amy French, Jasmine Mu, Marios Giannakis, Eve Shinbrot, Ivan Borozan, Michael J. Quist, Hermann Brenner, Daniel Buchanan, Peter Campbell, Andrew Chan, Jenny Chang-Claude, Vincent Ferretti, Charles Fuchs, Andrea Gsur, Marc Gunter, Tabitha Harrison, Michael Hoffmeister, Wen-Yi Huang, Paul Krzyzanowski, Stephen Lee, Mathieu Lemire, Jessica Miller, Danielle Pasternack, Cherie Teney, Elaine Mardis, Polly Newcomb, Lincoln Stein, Lee Timms, David Wheeler, Christina Yung, Niha Zubair, Levi Garraway, Shuji Ogino, Li Hsu, Steven Gallinger, Stephen Thibodeau, Thomas Hudson, Ulrike Peters. Targeted deep sequencing of colorectal tumor tissues to study associations of tumor subtypes with germline genetic, lifestyle, and environmental risk factors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1286. doi:10.1158/1538-7445.AM2017-1286

524 Background: Hormone receptor positive breast cancer is a therapeutic challenge. Despite optimal anti-endocrine therapies, most breast cancer deaths follow a diagnosis of early luminal cancer. To understand the impact of multiple aberrations in the context of current therapy, we assessed the prognostic ability of genomic signatures as a putative stratification tool to targeted therapies. Methods: This a priori study is based on molecular pathways which might predict response to targeted therapies. DNA from 420 patients from the phase III TEAM pathology cohort were used. Patients with a distant recurrence within 5 years were matched by clinical variables to those disease-free at follow up. Copy number analysis was performed using the Affymetrix Oncoscan Assay. Targeted sequencing was performed in a subset of samples for genes based on signaling cassettes mined from the ICGC. Pathways were identified as aberrant if there were copy number variations (CNVs) and/or mutations in any of the pre-determined pathway genes: 1) CCND1/CCND2/CCND3/CDK4/CDK6; 2) FGFR1/FGFR2/FGFR2/FGFR4; and 3) AKT1/AKT2/PIK3CA/PTEN. Kaplan-Meier and log-rank analyses were used for DFS between groups. Hazard ratios were calculated using the Cox proportional hazard models adjusted for age, tumour size, grade, lymph node and HER2 status. Results: 390/420 samples passed informatics QC filters. For the CCND/CDK pathway, patients with no CNV changes experienced a better DFS (HR = 1.7, 95% CI 1.3-2.3, p < 0.001). For the FGFR/FGF pathway, a similar outcome is seen among patients without CNVs (HR = 1.5, 95% CI 1.1-2.0; p = 0.005). For AKT/PIK3CA, a decrease in DFS was seen in those with aberrations (HR = 1.4, 95% CI 1.0-1.8, p = 0.03). Conclusions: We demonstrated that CNVs of genes within CDK4/CCND, PIK3CA/AKT and FGFR pathways are independently linked to high risk of relapse following endocrine treatment, with implications for identifying those patients who are at high-risk for recurrence despite optimal anti-endocrine therapy and linking molecular features driving these cancers to targeted therapies.

505 Background: The International Cancer Genome Consortium and The Cancer Genome Atlas have had a global transformative impact on our understanding of cancer. These programs have mapped the genomic landscape of common and rare tumors setting the scene for a comprehensive change in the approach to cancer diagnosis and treatment. However, the task remains incomplete until these mutational events are linked to clinical outcomes in the context of current therapeutic intervention to drive future stratified medicine approaches. Methods: We performed targeted sequencing in patients from the Tamoxifen Exemestane Adjuvant Multicentre trial. DNA was extracted and a 101 gene panel analysed using a novel mutation calling pipeline. Both a priori and machine learning analyses were performed using distant recurrence free survival as the primary endpoint. Results: In 1,491 successfully analyzed samples 1,070 (71.76%) samples exhibited at least one single nucleotide mutation (range 0-94, 1.828+/-0.133, mean+/-s.e.). 98/101 genes were mutated in at least one patient. Only variants in PIK3CA, TP53, MLL3, CDH1 were detected in 5% or more of samples. Twenty genes were associated with increased risk of recurrence in multivariate analyses corrected for clinic-pathological variables, 50% of these genes were involved in transcriptional regulation or RNA/protein processing. In a multivariate analysis, two combined signalling modules were independently prognostic for residual risk following hormone therapy (HRvalidation 3.10 95%CI 1.78-5.40 and HRvalidation 2.70 95%CI 1.57-4.64). Conclusions: We successfully performed a signalling pathway-based targeted sequencing analysis within predefined signalling modules. In supervised and unsupervised analyses we identified multiple signalling cassettes linked to poor outcome in patients with ER+ve breast cancers treated with modern endocrine therapy in the context of a phase III clinical trial. These results identify novel candidates as targets to treat endocrine refractory breast cancers.

The nematode Caenorhabditis briggsae is a model for comparative developmental evolution with C. elegans. Worldwide collections of C. briggsae have implicated an intriguing history of divergence among genetic groups separated by latitude, or by restricted geography, that is being exploited to dissect the genetic basis to adaptive evolution and reproductive incompatibility; yet, the genomic scope and timing of population divergence is unclear. We performed high-coverage whole-genome sequencing of 37 wild isolates of the nematode C. briggsae and applied a pairwise sequentially Markovian coalescent (PSMC) model to 703 combinations of genomic haplotypes to draw inferences about population history, the genomic scope of natural selection, and to compare with 40 wild isolates of C. elegans. We estimate that a diaspora of at least six distinct C. briggsae lineages separated from one another approximately 200,000 generations ago, including the “Temperate” and “Tropical” phylogeographic groups that dominate most samples worldwide. Moreover, an ancient population split in its history approximately 2 million generations ago, coupled with only rare gene flow among lineage groups, validates this system as a model for incipient speciation. Low versus high recombination regions of the genome give distinct signatures of population size change through time, indicative of widespread effects of selection on highly linked portions of the genome owing to extreme inbreeding by self-fertilization. Analysis of functional mutations indicates that genomic context, owing to selection that acts on long linkage blocks, is a more important driver of population variation than are the functional attributes of the individually encoded genes.

Summary: Several semantic Web Services clients for Bioinformatics have been released, but to date no support systems for service providers have been described. We have created a framework (‘MobyServlet’) that very simply allows an existing Java application to conform to the MOBY-S semantic Web Services protocol. Using an existing Java program for codon-pair bias determination as an example, we enumerate the steps required for MOBY-S compliance. With minimal programming effort, such a deployment has the advantages of: (1) wider exposure to the user community by automatic inclusion in all MOBY-S client programs and (2) automatic interoperability with other MOBY-S services for input and output. Complex on-line analysis will become easier for biologists as more developers adopt MOBY-S. Availability: The framework and documentation are freely available from the Java developer's section of http://www.biomoby.org/. Contact: gordonp@ucalgary.ca

CORRIGENDUM: InterMOD: integrated data and tools for the unification of model organism research

Motivation: Copy number variations (CNVs) are a major source of genomic variability and are especially significant in cancer. Until recently microarray technologies have been used to characterize CNVs in genomes. However, advances in next-generation sequencing technology offer significant opportunities to deduce copy number directly from genome sequencing data. Unfortunately cancer genomes differ from normal genomes in several aspects that make them far less amenable to copy number detection. For example, cancer genomes are often aneuploid and an admixture of diploid/non-tumor cell fractions. Also patient-derived xenograft models can be laden with mouse contamination that strongly affects accurate assignment of copy number. Hence, there is a need to develop analytical tools that can take into account cancer-specific parameters for detecting CNVs directly from genome sequencing data. Results: We have developed WaveCNV, a software package to identify copy number alterations by detecting breakpoints of CNVs using translation-invariant discrete wavelet transforms and assign digitized copy numbers to each event using next-generation sequencing data. We also assign alleles specifying the chromosomal ratio following duplication/loss. We verified copy number calls using both microarray (correlation coefficient 0.97) and quantitative polymerase chain reaction (correlation coefficient 0.94) and found them to be highly concordant. We demonstrate its utility in pancreatic primary and xenograft sequencing data. Availability and implementation: Source code and executables are available at https://github.com/WaveCNV. The segmentation algorithm is implemented in MATLAB, and copy number assignment is implemented Perl. Contact: lakshmi.muthuswamy@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Background Funded by the National Institutes of Health (NIH), the aim of the Mod el Organism ENC yclopedia o f D NA E lements (modENCODE) project is to provide the biological research community with a comprehensive encyclopedia of functional genomic elements for both model organisms C. elegans (worm) and D. melanogaster (fly). With a total size of just under 10 terabytes of data collected and released to the public, one of the challenges faced by researchers is to extract biologically meaningful knowledge from this large data set. While the basic quality control, pre-processing, and analysis of the data has already been performed by members of the modENCODE consortium, many researchers will wish to reinterpret the data set using modifications and enhancements of the original protocols, or combine modENCODE data with other data sets. Unfortunately this can be a time consuming and logistically challenging proposition. Results In recognition of this challenge, the modENCODE DCC has released uniform computing resources for analyzing modENCODE data on Galaxy (https://github.com/modENCODE-DCC/Galaxy), on the public Amazon Cloud (http://aws.amazon.com), and on the private Bionimbus Cloud for genomic research (http://www.bionimbus.org). In particular, we have released Galaxy workflows for interpreting ChIP-seq data which use the same quality control (QC) and peak calling standards adopted by the modENCODE and ENCODE communities. For convenience of use, we have created Amazon and Bionimbus Cloud machine images containing Galaxy along with all the modENCODE data, software and other dependencies. Conclusions Using these resources provides a framework for running consistent and reproducible analyses on modENCODE data, ultimately allowing researchers to use more of their time using modENCODE data, and less time moving it around.

Model organisms are widely used for understanding basic biology and have significantly contributed to the study of human disease. In recent years, genomic analysis has provided extensive evidence of widespread conservation of gene sequence and function amongst eukaryotes, allowing insights from model organisms to help decipher gene function in a wider range of species. The InterMOD consortium is developing an infrastructure based around the InterMine data warehouse system to integrate genomic and functional data from a number of key model organisms, leading the way to improved cross-species research. So far including budding yeast, nematode worm, fruit fly, zebrafish, rat and mouse, the project has set up data warehouses, synchronized data models and created analysis tools and links between data from different species. The project unites a number of major model organism databases, improving both the consistency and accessibility of comparative research, to the benefit of the wider scientific community.

We sequenced 11 germline exomes from five families with familial pancreatic cancer (FPC). One proband had a germline nonsense variant in ATM with somatic loss of the variant allele. Another proband had a nonsense variant in PALB2 with somatic loss of the variant allele. Both variants were absent in a relative with FPC. These findings question the causal mechanisms of ATM and PALB2 in these families and highlight challenges in identifying the causes of familial cancer syndromes using exome sequencing.

The completion of The Cancer Genome Atlas (TCGA) project for colorectal cancer (CRC) has enabled a new, focused phase of sequencing tumor samples for which genome-wide genetic, epidemiological, clinical and lifestyle data have been collected. By combining somatic mutational profiles with these aforementioned data, we may identify and report effective prevention and treatment approaches for a broader population of individuals. The advent of targeted deep sequencing approaches using DNA obtained from formalin fixed paraffin embedded tissues has made possible the genetic characterization of the large numbers of patients needed to make such an effort relevant. As a first step, we describe a custom gene panel designed from large-scale studies for targeted deep sequencing, and its application to over 4,200 CR tumors, collected by the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). This study is designed to identify recurrent somatic mutations and copy number alterations (CNAs) for association testing with germline genetic and lifestyle and environmental risk factors for CRC, and thereby identify relevant approaches to impact cancer prevention. The targeted CRC panel includes 205 genes. Genes were primarily selected as significantly mutated genes identified from the Nurses’ Health Study and Health Professional's Follow-up Study (n = 700), and TCGA (n = 525). We also included 15 genes associated with high penetrance germline mutations and augmented the list to include genes in pathways of somatically altered genes, identified by literature review, from public databases and known to be associated with loss of heterozygosity. For these 205 genes, amplification primers were designed to include all coding regions of transcripts that are listed in the UCSC Genome Browser. For regions with CNAs, the TCGA dataset was analyzed to include regions with greater than or equal to 2 copy focal gains or losses that were found in more than 4 or 3 tumors, respectively. Candidate genes in regions with significant CNAs from the TCGA CRC publication (Nature 2012) were also included. For CNAs, 6 to 12 amplicons were designed for each of the 56 selected regions (32 gains and 24 losses). Additional target regions include: 1) 25 microsatellite loci previously used to identify defective DNA mismatch repair and 212 homoploymer repeats. These include microsatellite loci recommended by the NCI Consensus Panel for identifying MSI; 2) amelogenin (for gender); and 3) Fusobacterium to detect a putative CRC-associated pathogen in tumor biopsies. At the AACR annual meeting, we expect to present results for deep sequencing (∼1,000X) of the first 1,000 CR tumors, including any preliminarily identified pathways and subtypes that may provide the basis for association testing with germline genetic and lifestyle and environmental risk factors needed for inferring better approaches to prevention and treatment of CRC. Citation Format: Syed H. Zaidi, Catie Grasso, Jasmine Mu, Eve Shinbrot, Marios Giannakis, Charles Connolly, Ivan Borozan, Hermann Brenner, Peter Campbell, Andrew Chan, Jenny Chang-Claude, Mengmeng Du, Vincent Ferretti, Amy French, Charles Fuchs, Steven Gallinger, Levi Garraway, Andrea Gsur, Marc Gunter, Tabitha Harrison, Michael Hoffmeister, Li Hsu, Wen-Yi Huang, Jeroen Huyghe, Mathieu Lemire, Elaine Mardis, John McPherson, Polly Newcomb, Lincoln Stein, Wei Sun, Lee Timms, Quang Trinh, David Wheeler, Christina Yung, Niha Zubair, Shuji Ogino, Stephen Thibodeau, Ulrike Peters, Thomas Hudson. Linking the molecular profile of colorectal tumors to germline genetic and environmental risk factors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5221.

Mutations in human induced pluripotent stem cells (iPSCs) pose a risk for their clinical use due to preferential reprogramming of mutated founder cell and selection of mutations during maintenance of iPSCs in cell culture. It is unknown, however, if mutations in iPSCs are due to stress associated with oncogene expression during reprogramming. We performed whole exome sequencing of human foreskin fibroblasts and their derived iPSCs at two different passages. We found that in vitro passaging contributed 7% to the iPSC coding point mutation load, and ultradeep amplicon sequencing revealed that 19% of the mutations preexist as rare mutations in the parental fibroblasts suggesting that the remaining 74% of the mutations were acquired during cellular reprogramming. Simulation suggests that the mutation intensity during reprogramming is ninefold higher than the background mutation rate in culture. Thus the factor induced reprogramming stress contributes to a significant proportion of the mutation load of iPSCs.

The authors have created a software system called the CAVEman, for the visual integration and exploration of heterogeneous anatomical and biomedical data. The CAVEman can be applied for both education and research tasks. The main component of the system is a three-dimensional digital atlas of the adult male human anatomy, structured according to the nomenclature of Terminologia Anatomica. The underlying data-indexing mechanism uses standard ontologies to map a range of biomedical data types onto the atlas. The CAVEman system is now used to visualize genetic processes in the context of the human anatomy and to facilitate visual exploration of the data. Through the use of Javatrade mark software, the atlas-based system is portable to virtually any computer environment, including personal computers and workstations. Existing Java tools for biomedical data analysis have been incorporated into the system. The affordability of virtual-reality installations has increased dramatically over the last several years. This creates new opportunities for educational scenarios that model important processes in a patient's body, including gene expression patterns, metabolic activity, the effects of interventions such as drug treatments, and eventually surgical simulations.

Most large-scale heterogeneous distributed computing systems, such as grids, rely on service oriented architectures (SOA) to interact with others in different platforms and computing languages. However, we still need to solve the semantic heterogeneity problem of data; we must interpret the data from different systems in some semantically related ways. Ontologies are the most common and well-accepted methodology to handle this problem at multiple levels of granularities across different systems. Nevertheless, using ontologies in a dynamic environment, such as a grid, to share some common concepts is still a challenge. It is difficult to keep a static mapping between ontologies; the corresponding semantic mapping changes must occur consistently. Therefore, we adopt the concept of tuple space and propose a flexible approach for managing ontologies in a grid. It enables systems and users to interoperate semantically and dynamically by sharing and managing the concepts and semantic ontology mappings in a flexible approach.

This paper describes a framework that uses the Semantic Web infrastructure to address semantic interoperability between relational database systems in large-scale environments and at multiple levels of granularities. Given a relational database system, we describe a formal algorithm to use the relational database Rs meta-data and structural constraints to construct its OWL ontology while preserving the structural constraints of the underlying relational database system. The generated ontology is described using and conforming to a set of vocabularies defined in an ontology that describes relational database systems on the web. Using this set of vocabularies guarantee that applications on the web can work with data instances that conformed to a set of known vocabularies and structures. Finally, we describe our prototype and how semantic conflicts are resolved between multiple relational database systems using the generated ontologies.

Nature 506, 328–333 (2014); doi:10.1038/nature13038 Author Fouad Yousif (of the Ontario Institute for Cancer Research, Toronto, Canada) should have been included in the author list after Andrew M. K. Brown with affiliation number 7 and listed in the Author Contributions as performing and analysing targeted sequencing; these omissions have been corrected in the online versions of this Article.