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While BRAF inhibitor combinations with EGFR and/or MEK inhibitors have improved clinical efficacy in BRAFV600E colorectal cancer (CRC), response rates remain low and lack durability. Preclinical data suggest that BRAF/MAPK pathway inhibition may augment the tumor immune response. We performed a proof-of-concept single-arm phase 2 clinical trial of combined PD-1, BRAF and MEK inhibition with sparatlizumab (PDR001), dabrafenib and trametinib in 37 patients with BRAFV600E CRC. The primary end point was overall response rate, and the secondary end points were progression-free survival, disease control rate, duration of response and overall survival. The study met its primary end point with a confirmed response rate (24.3% in all patients; 25% in microsatellite stable patients) and durability that were favorable relative to historical controls of BRAF-targeted combinations alone. Single-cell RNA sequencing of 23 paired pretreatment and day 15 on-treatment tumor biopsies revealed greater induction of tumor cell-intrinsic immune programs and more complete MAPK inhibition in patients with better clinical outcome. Immune program induction in matched patient-derived organoids correlated with the degree of MAPK inhibition. These data suggest a potential tumor cell-intrinsic mechanism of cooperativity between MAPK inhibition and immune response, warranting further clinical evaluation of optimized targeted and immune combinations in CRC. ClinicalTrials.gov registration: NCT03668431.

Introduction The conect4children (c4c) consortium was setup to facilitate the development of new drugs and therapies for paediatric populations and address key challenges associated with paediatric clinical trials. Two of the major adopting principles for c4c were academia-industry partnership and data harmonisation and interoperability through common eCRF definitions. To understand the challenges arising out of these principles, the c4c team at Newcastle University conducted semi-structured interviews with four c4c industry partners. Methods Each partner was asked 10 questions about the data standards used in their company, management and maintenance of data dictionaries, how they dealt with paediatric-specific issues, major knowledge gaps and how academia could aid in bridging these gaps. Thematic analysis was performed to identify patterns in their answers. Results All companies use the Clinical Data Interchange Standards Consortium (CDISC) standards but face problems when certain terminology is not included in CDISC (e.g., paediatric-specific terminologies). All companies were committed to interoperability and had strict policies about how additional terminology could be added to their dictionaries. Three of the four companies maintained a single dictionary but also had lighter versions for specific usage. The two major knowledge gaps identified from the interviews were handling of non-CDISC terminology and maintenance of normal lab ranges in dictionaries. Discussion To address these gaps, c4c has been working on a four-point plan including the development of a cross-cutting paediatric dictionary and a paediatric user guide in collaboration with CDISC.

Contains fulltext : 232104.pdf (Publisher’s version ) (Open Access) The need for information about new and existing drugs used in children was recognized in the European Union (EU) with the implementation of the Paediatric Regulation in 2007. In 2017, the 10-year review of the Paediatric Regulation identified barriers to the conduct of clinical trials, including delays in setting up and completing paediatric trials. Across Europe, the difficulties with clinical research are compounded by variation within countries and between countries. Ethics and regulatory review have national specificities. This paper describes the Collaborative Network for European Clinical Trials for Children (conect4children, c4c), which addresses selected difficulties in the design and conduct of paediatric clinical trials. c4c is a time-limited public-private consortium funded by the Innovative Medicines Initiative (IMI2). The elements of c4c are as follows: expert advice providing input on study design and/or paediatric development programmes (including patient involvement activities); a network of sites following harmonised procedures coordinated by National Hubs and a single point of contact for Europe; a facility for education and training for sites and trial teams; and support for managing data used by the network and a common paediatric data dictionary. c4c does not sponsor trials. c4c is taking a phased approach with careful piloting through industry and non-industry studies intended to demonstrate the viability of the network (proof-of-viability studies). c4c uses a co-design approach involving industry and academics within a clearly defined scope. A sustainable, successor organization open to all potential service users will be open for business before the end of IMI2 funding in 2024.

Liquid biopsy, particularly the analysis of circulating tumor DNA (ctDNA), has demonstrated considerable promise for numerous clinical intended uses. Successful validation and commercialization of novel ctDNA tests have the potential to improve the outcomes of patients with cancer. The goal of the Blood Profiling Atlas Consortium (BloodPAC) is to accelerate the development and validation of liquid biopsy assays that will be introduced into the clinic. To accomplish this goal, the BloodPAC conducts research in the following areas: Data Collection and Analysis within the BloodPAC Data Commons; Preanalytical Variables; Analytical Variables; Patient Context Variables; and Reimbursement. In this document, the BloodPAC’s Analytical Variables Working Group (AV WG) attempts to define a set of generic analytical validation protocols tailored for ctDNA-based Next-Generation Sequencing (NGS) assays. Analytical validation of ctDNA assays poses several unique challenges that primarily arise from the fact that very few tumor-derived DNA molecules may be present in circulation relative to the amount of nontumor-derived cell-free DNA (cfDNA). These challenges include the exquisite level of sensitivity and specificity needed to detect ctDNA, the potential for false negatives in detecting these rare molecules, and the increased reliance on contrived samples to attain sufficient ctDNA for analytical validation. By addressing these unique challenges, the BloodPAC hopes to expedite sponsors’ presubmission discussions with the Food and Drug Administration (FDA) with the protocols presented herein. By sharing best practices with the broader community, this work may also save the time and capacity of FDA reviewers through increased efficiency.

In the context of cancer, clonal hematopoiesis of indeterminate potential (CHIP) is associated with the development of therapy-related myeloid neoplasms and shorter overall survival. Cell-free DNA (cfDNA) sequencing is becoming widely adopted for genomic screening of cancer patients but has not been used extensively to determine CHIP status due to a requirement for matched blood and tumor sequencing. Here we present an accurate machine learning approach to determine clonal hematopoiesis (CH) status from cfDNA sequencing alone and apply our model to 4,096 oncology clinical cfDNA samples. Using this method, we determine that 26% of patients in this cohort have evidence of CH and CH is most common in lung cancer patients. Matched RNAseq data shows signals of increased inflammation, especially neutrophil activation, within the tumor microenvironment of CH-positive patients. Additionally, CH patients showed evidence of neutrophil activation systemically, pointing to a potential mechanism of action for the worse outcomes associated with CH status. Neutrophil activation may be one of many mechanisms however, as estrogen positive breast cancer patients harboring TET2 frameshift mutations had worse outcomes but similar neutrophil levels to CH-negative patients.One Sentence SummaryWe train an accurate machine learning model to detect clonal hematopoiesis in cancer and characterize associated changes in the tumor microenvironment.

Background For the advancement of cancer research, the collection of tissue specimens from drug‐resistant tumors after targeted therapy is crucial. Although patients with lung cancer are often provided targeted therapy, post‐therapy specimens are not routinely collected due to the risks of collection, limiting the study of targeted therapy resistance mechanisms. Posthumous rapid tissue donation (RTD) is an expedient collection process that provides an opportunity to understand treatment‐resistant lung cancers. Methods Consent to participate in the thoracic RTD protocol was obtained during patient care. When death occurred, tumor and paired non‐tumor, cytology, and blood specimens were collected within 48 hours and preserved as formalin‐fixed and frozen specimens. Tissue sections were evaluated with hematoxylin and eosin staining and immunohistochemistry (IHC) against multiple biomarkers, including various programmed death ligand 1 (PD‐L1) clones. Next‐generation sequencing was performed on 13 specimens from 5 patients. Results Postmortem specimens (N = 180) were well preserved from 9 patients with lung cancer. PD‐L1 IHC revealed heterogeneity within and between tumors. An AGK‐BRAF fusion was newly identified in tumor from a donor with a known echinoderm microtubule‐associated protein‐like 4 to anaplastic lymphoma kinase (EML4‐ALK) fusion and history of anaplastic lymphoma kinase (ALK) inhibitor therapy. RNA expression analysis revealed a clonal genetic origin of metastatic cancer cells. Conclusions Post‐therapy specimens demonstrated PD‐L1 heterogeneity and an acyl glycerol kinase to B‐rapidly accelerated fibrosarcoma (AGK‐BRAF) fusion in a patient with an EML4‐ALK–positive lung adenocarcinoma as a potential resistance mechanism to ALK inhibitor therapy. Rapid tissue donation collection of postmortem tissue from lung cancer patients is a novel approach to cancer research that enables studies of molecular evolution and drug resistance., We collected high‐quality primary and metastatic lung cancer specimens from donors after death by rapid collection in the community. Protein analysis of this tissue revealed discordant programmed death ligand 1 (PD‐L1) results at different cancer sites from the same patient; genetic analysis identified anaplastic lymphoma kinase (ALK) and B‐rapidly accelerated fibrosarcoma (BRAF) gene fusions in a patient with a history of ALK inhibitor therapy and a clonal genetic origin of metastatic cancer cells.

In spinal muscular atrophy (SMA), degeneration of motor neurons causes progressive muscular weakness, which is caused by homozygous deletion of the SMN1 gene. Available epidemiological data on SMA are scarce, often outdated, and limited to relatively small regions or populations. Combining data from different sources including genetic laboratories and patient registries may provide better insight of the disease epidemiology. To investigate the incidence of genetically confirmed SMA, and the number of patients who are able and approachable to participate in new clinical trials and observational research, we used both genetic laboratories, the TREAT-NMD Global SMA Patient Registry and the Care and Trial Sites Registry (CTSR). In Europe, 4653 patients were genetically diagnosed by the genetic laboratories in the 5-year period 2011 to 2015, with 992 diagnosed in 2015 alone. The data provide an estimated incidence of SMA in Europe of 1 in 3900–16,000 live births. Patient numbers in the national patient registries and CTSR were considerably lower. By far, most patients registered in the national patient registries and the CTSR live in Europe and are reported to have SMA type II. Considerable differences between countries in patient participation in the registries were observed. Our findings indicate that not all patients with SMA are accessed by specialist healthcare services and these patients may not have access to research opportunities and optimal care. Electronic supplementary material The online version of this article (doi:10.1007/s00415-017-8549-1) contains supplementary material, which is available to authorized users.

Circulating tumor DNA (ctDNA) fraction has been shown to be a prognostic factor of treatment response in patients with metastatic cancers. However, algorithms that accurately determine ctDNA fraction across purity ranges are still lacking. Commonly used liquid biopsy gene panels (~70 genes) often approximate the ctDNA fraction in a sample by using somatic variant allele frequencies, resulting in large confidence intervals due to the scarcity of somatic mutations detected per sample and uncertainty of their clonality and copy number. Genome wide signatures such as nucleosome positioning, measured by windowed protection scores (WPS), have been shown to reflect genomic and epigenomic abnormalities specific to cancer and proposed as biomarkers for cancer detection. However, genome wide assays sacrifice somatic mutation detection due to low sequencing coverage and in clinical practice a second assay is required to find actionable mutations. We leverage data from ~6,000 cell-free DNA samples to develop methods for accurately estimating the ctDNA fraction in clinical samples sequenced with a 554-gene panel covering 3MB of genomic content. First, we use Gradient Boosting and 17 features extracted from standard variant calling, copy number and QC pipelines. This approach has been shown to be highly accurate in samples of high ctDNA fraction and therefore provide reliable training labels for those samples. We suggest that more sophisticated methods, using genome wide signatures, can increase prediction accuracies in samples of lower ctDNA fraction. Second, we develop a deep learning model for predicting ctDNA fraction using base pair resolution WPS over the genomic territory covered by the gene panel. Using Morlet wavelet, we transformed each autosomal WPS unidimensional representation into a two-dimensional image. A 22 channels image per sample was generated and used as input to a Convolutional Neural Network (22-CNN) model. The 22-CNN was trained to predict the ctDNA fraction and to classify if a sample was from a ctDNA shedder (ctDNA fraction >0) or not. The dataset was equally divided into training and test sets of ~2800 samples each. We used five-fold cross-validation (CV) during training and evaluated each model in the unseen test dataset. The Mean Square Error of the 22-CNN ctDNA prediction model on the testing set was 0.0072 +- 0.0013 [0.006-0.009] and the accuracy of the classification model on the testing set was 0.79 +- 0.006 [0.78-0.79]. In this work, we present both machine learning and deep learning models to reliably estimate the ctDNA fraction in plasma samples from cancer patients. These methods address a key challenge in the field and are applicable to other liquid biopsy assays. Citation Format: Aamna M. Al-Shehhi, Chintan Parmar, Ben Gustafson, Angad Singh, Rebecca Leary, Markus Riester, O. Alejandro Balbin. Accurate quantification of tumor DNA in liquid biopsies using deep learning [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PR-08.

Racial/ethnic disparities in breast cancer mortality continue to widen but genomic studies rarely interrogate breast cancer in diverse populations. Through genome, exome, and RNA sequencing, we examined the molecular features of breast cancers using 194 patients from Nigeria and 1037 patients from The Cancer Genome Atlas (TCGA). Relative to Black and White cohorts in TCGA, Nigerian HR + /HER2 − tumors are characterized by increased homologous recombination deficiency signature, pervasive TP53 mutations, and greater structural variation—indicating aggressive biology. GATA3 mutations are also more frequent in Nigerians regardless of subtype. Higher proportions of APOBEC-mediated substitutions strongly associate with PIK3CA and CDH1 mutations, which are underrepresented in Nigerians and Blacks. PLK2, KDM6A, and B2M are also identified as previously unreported significantly mutated genes in breast cancer. This dataset provides novel insights into potential molecular mechanisms underlying outcome disparities and lay a foundation for deployment of precision therapeutics in underserved populations., Research on racial and ethnic influence on breast cancer mortality is stymied by a lack of genomic studies in diverse populations. Here, the authors genomically interrogate 194 Nigerian breast cancers, unveiling molecular features that could explain the high mortality rate from breast cancer in an indigenous African population.

Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

Resistance to cancer therapies presents a significant clinical challenge. Recent studies have revealed intratumoral heterogeneity as a source of therapeutic resistance. However, it is unclear whether resistance is driven predominantly by pre-existing or de novo alterations, in part because of the resolution limits of next-generation sequencing. To address this, we developed a high-complexity barcode library, ClonTracer, which enables the high-resolution tracking of more than 1 million cancer cells under drug treatment. In two clinically relevant models, ClonTracer studies showed that the majority of resistant clones were part of small, pre-existing subpopulations that selectively escaped under therapeutic challenge. Moreover, the ClonTracer approach enabled quantitative assessment of the ability of combination treatments to suppress resistant clones. These findings suggest that resistant clones are present before treatment, which would make up-front therapeutic combinations that target non-overlapping resistance a preferred approach. Thus, ClonTracer barcoding may be a valuable tool for optimizing therapeutic regimens with the goal of curative combination therapies for cancer.

We identified genetic mutations in CD19 and loss of heterozygosity at the time of CD19- relapse to chimeric antigen receptor (CAR) therapy. The mutations are present in the vast majority of resistant tumor cells and are predicted to lead to a truncated protein with a nonfunctional or absent transmembrane domain and consequently to a loss of surface antigen. This irreversible loss of CD19 advocates for an alternative targeting or combination CAR approach.

Translational research in Europe for the assessment and treatment of neuromuscular disorders (TREAT-NMD) is a global network of world-class experts within the neuromuscular community whose mission is to support all stages of therapy development and improve the health and quality of life of people around the world with neuromuscular disorders (NMD). Since 2007, TREAT-NMD has played a central role in bringing together the right experts, patients, advocacy organizations, scientists, healthcare professionals, and pharmaceutical companies. By uniting these experts within the neuromuscular community, TREAT-NMD has supported preclinical research in animal and cell models that has raised the potential for clinical trials. TREAT-NMD has successfully developed several key resources, including cell and animal standard operating protocols (preclinical research), global patient registries, ethical framework and care guidelines, and family guides, to help develop and extend translation research in the field, thereby making the field ready for clinical trials. This review aims to highlight key achievements of the network, which spans a decade and the successful partnership with our stakeholders who have enabled the field to identify and address challenges to therapeutic development and standard of care for patients. This review will also outline future perspectives.

Racial/ethnic disparities in breast cancer mortality continue to widen but genomic studies rarely interrogate breast cancer in diverse populations. Through genome, exome, and RNA sequencing, we examined the molecular features of breast cancers using 194 patients from Nigeria and 1037 patients from The Cancer Genome Atlas (TCGA). Relative to Black and White cohorts in TCGA, Nigerian HR + /HER2 - tumors are characterized by increased homologous recombination deficiency signature, pervasive TP53 mutations, and greater structural variation-indicating aggressive biology. GATA3 mutations are also more frequent in Nigerians regardless of subtype. Higher proportions of APOBEC-mediated substitutions strongly associate with PIK3CA and CDH1 mutations, which are underrepresented in Nigerians and Blacks. PLK2, KDM6A, and B2M are also identified as previously unreported significantly mutated genes in breast cancer. This dataset provides novel insights into potential molecular mechanisms underlying outcome disparities and lay a foundation for deployment of precision therapeutics in underserved populations.

Background: The sensitivity of plasma-based oncological assays is influenced by the amount of tumor DNA shed into the circulation (ctDNA fraction). Higher ctDNA fraction has been shown to correlate with later-stage cancers and poorer overall survival (Bettegowda C, et al. Sci Transl Med. 2014; Dawson SJ, et al. N Engl J Med. 2014). Other factors affecting ctDNA fraction are poorly understood. We present results from three large Phase III breast cancer studies (MONALEESA-2, -3, and -7) to evaluate correlations between ctDNA fraction and clinical characteristics and impact on progression-free survival (PFS) and best overall tumor response. Methods: Baseline plasma samples were collected from patients (pts) in the MONALEESA-2, -3, and -7 studies, which are Phase III registration trials testing ribociclib, a cyclin-dependent kinase 4/6 inhibitor, in hormone receptor–positive, human epidermal growth factor receptor 2–negative advanced breast cancer. For each trial, cell-free DNA was extracted from plasma and sequenced using a validated next-generation sequencing assay targeting approximately 550 genes. ctDNA fraction was estimated by analyzing short-read sequences using PureCN (Riester M, et al. Source Code Biol Med. 2016) and tested for correlations with various tumor characteristics (size at baseline, Ki67 expression, number and type of metastatic sites, hormone receptor status) and pt characteristics (type of prior therapy, line of therapy, ECOG performance status, age, body mass index, race, histological grade, menopausal status). We also evaluated the prognostic value of ctDNA fraction on PFS and best overall response. To evaluate the prognostic effect on PFS, ctDNA fraction was binned into 3 categories (not detectable; low, 0.5%-10%; high, > 10%). Results: Higher ctDNA fractions were observed in pts with more metastatic sites (P < 0.0001), larger tumor diameter (P < 0.0001), higher Ki67 expression (P = 0.0001), higher lactate dehydrogenase levels (P < 0.0001), higher-grade tumors (P = 0.0004), worse ECOG performance status (P < 0.0001), progesterone receptor–negative tumors (P = 0.01), presence of liver metastases (P < 0.0001), and shorter disease-free intervals (P < 0.0001). ctDNA fractions were also higher in younger pts (continuous variable; P < 0.0001) and pts with lower BMI (P = 0.0003), prior chemotherapy (P = 0.002), and prior endocrine therapy (P = 0.01). Lower ctDNA fractions were observed in pts with better overall response (P < 0.0001), with median ctDNA fractions lowest in pts with complete responses followed by partial response, stable disease, and progressive disease. Pts with low (0.5%-10%) ctDNA fractions had longer PFS than pts with high (> 10%) ctDNA fractions (HR [95% CI], 0.63 [0.48-0.82], 0.64 [0.51-0.80], and 0.67 [0.52-0.86] in the MONALEESA-2, -3, and -7 trials, respectively). A more pronounced effect on PFS was observed in pts with undetectable levels of ctDNA vs pts with higher ctDNA fractions (HR [95% CI], 0.35 [0.23-0.52], 0.34 [0.21-0.55], and 0.31 [0.21-0.47] in the MONALEESA-2, -3, and -7 trials, respectively). Conclusions: Generally, higher ctDNA fraction was associated with more aggressive tumor characteristics and prior exposure to therapy. Lower ctDNA fraction was associated with longer PFS and better overall response. Together these data suggest that ctDNA fraction is a robust prognostic factor. Citation Format: Nadia Solovieff, Faye Su, Rebecca Leary, Alejandro Balbin, Arunava Chakravartty, Karen Rodriguez Lorenc, Tetiana Taran, Naveen Babbar. Association of tumor DNA in circulation with clinical characteristics and treatment response in HR+/HER2− advanced breast cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A031. doi:10.1158/1535-7163.TARG-19-A031

Importance Focal cortical dysplasia (FCD), hemimegalencephaly, and megalencephaly constitute a spectrum of malformations of cortical development with shared neuropathologic features. These disorders are associated with significant childhood morbidity and mortality. Objective To identify the underlying molecular cause of FCD, hemimegalencephaly, and diffuse megalencephaly. Design, Setting, and Participants Patients with FCD, hemimegalencephaly, or megalencephaly (mean age, 11.7 years; range, 2-32 years) were recruited from Pediatric Hospital A. Meyer, the University of Hong Kong, and Seattle Children’s Research Institute from June 2012 to June 2014. Whole-exome sequencing (WES) was performed on 8 children with FCD or hemimegalencephaly using standard-depth (50-60X) sequencing in peripheral samples (blood, saliva, or skin) from the affected child and their parents and deep (150-180X) sequencing in affected brain tissue. Targeted sequencing and WES were used to screen 93 children with molecularly unexplained diffuse or focal brain overgrowth. Histopathologic and functional assays of phosphatidylinositol 3-kinase–AKT (serine/threonine kinase)–mammalian target of rapamycin (mTOR) pathway activity in resected brain tissue and cultured neurons were performed to validate mutations. Main Outcomes and Measures Whole-exome sequencing and targeted sequencing identified variants associated with this spectrum of developmental brain disorders. Results Low-level mosaic mutations ofMTORwere identified in brain tissue in 4 children with FCD type 2a with alternative allele fractions ranging from 0.012 to 0.086. Intermediate-level mosaic mutation ofMTOR(p.Thr1977Ile) was also identified in 3 unrelated children with diffuse megalencephaly and pigmentary mosaicism in skin. Finally, a constitutional de novo mutation ofMTOR(p.Glu1799Lys) was identified in 3 unrelated children with diffuse megalencephaly and intellectual disability. Molecular and functional analysis in 2 children with FCD2a from whom multiple affected brain tissue samples were available revealed a mutation gradient with an epicenter in the most epileptogenic area. When expressed in cultured neurons, allMTORmutations identified here drive constitutive activation of mTOR complex 1 and enlarged neuronal size. Conclusions and Relevance In this study, mutations ofMTORwere associated with a spectrum of brain overgrowth phenotypes extending from FCD type 2a to diffuse megalencephaly, distinguished by different mutations and levels of mosaicism. These mutations may be sufficient to cause cellular hypertrophy in cultured neurons and may provide a demonstration of the pattern of mosaicism in brain and substantiate the link between mosaic mutations ofMTORand pigmentary mosaicism in skin.

137 Background: The adoptive transfer of autologous T cells genetically modified to express a CD19-specific, 4-1BB/CD3ζ-signaling CAR (CTL019) has shown remarkable activity and induces long-term remissions in a subset of patients with relapsed/refractory chronic lymphocytic leukemia (CLL) and acute lymphoblastic leukemia (ALL). In ALL, CTL019 induces a complete response (CR) in over 90% of patients while in CLL 25% of patients obtain a CR. It is not fully understood why only certain patients respond to therapy. Methods: We employed next generation sequencing of RNA (RNAseq) to identify predictive indicators of response to CTL019. We performed RNAseq on leukapheresis and manufactured product T cells prior to re-infusion from 35 CLL and 7 pediatric ALL patients with heavily pre-treated and high-risk disease. To characterize potency, we performed RNAseq on the infusion product after stimulation with the CAR. Results: We find that durable remission in CLL is associated with gene expression signatures of early memory and T-effector cells, while T cells from non-responding patients are enriched in signatures of T-regulatory cells, terminal differentiation, and exhaustion. In following the results from CLL, we find that pediatric ALL manufactured T cells are significantly enriched for an early memory, naïve T cell state and all achieved a CR. In parallel in vitro experiments, stimulation of the infusion product further demonstrated that CTL019 cells from CRs have an increased capacity for activation upon stimulation. We tested if we could extend these observations to identify a phenotype of T cells that is predictive of response prior to CTL019 manufacturing and find that the signatures predictive of response at the pre-infusion stage are also observed at the earlier leukapheresis time point. Conclusions: These findings suggest that intrinsic T cell fitness dictates response to CAR T cells. These gene expression signatures, along with additional immunological biomarkers, may be used to identify which patients are most likely to respond to adoptive transfer strategies and suggest manufacturing modifications that might potentiate the generation of maximally efficacious infusion products. Clinical trial information: NCT01029366, NCT01747486, NCT01626495.

Objectives: Paucity of data on populations of African Ancestry in clinical trials continues to limit our ability to design and implement innovative solutions to narrow the breast cancer survival gap amongst Africans, African Americans, and European Americans. We have developed a cross-continent research infrastructure to examine the spectrum of genomic alterations in breast tumors from West Africa and subsequently, to compare them to tumors from African American women and women of European Ancestry in The Cancer Genome Atlas (TCGA) database. Methods: Consecutive women with breast cancer presenting for treatment at the University College Hospital, Ibadan and at Lagos State University Teaching Hospital, Lagos, Nigeria gave informed consent and were recruited to the West African Breast Cancer Study (WABCS) between 2013-2016. Tumor-normal pairs were subjected to exome and/or high-depth (90x) genome sequencing. High confidence somatic mutations (substitutions, insertions/deletions and structural variants) were obtained by using multiple variant callers. Furthermore, 1,089 exomic and 80 genomic breast tumor-normal pairs from TCGA were harmonized with WABCS samples, resulting in a cohort of 147 West Africans (147 exome; 40 genome), 154 African Americans (154 exome; 31 genome), and 776 Caucasians (776 exome; 43 genome). Results: Across the exomes, genes commonly altered in breast cancer in TCGA are also altered in women of African ancestry, but the mutational spectrum is quite different, demonstrating overrepresentation of tumors with aggressive phenotypes. Overall, TP53 (65%), ERBB2 (27%), and GATA3 (17%) showed statistically significant higher alteration frequencies in West Africans and African Americans. In contrast, PIK3CA (24%) was less frequently mutated. Of note, GATA3 mutation was statistically significantly more frequent in Nigerians (39%) and African Americans (16.7%) compared to Caucasians (10.5%), in ER-positive cancers. Analysis on Structural Variants (SV), on the other hand, has shown that the genome-wide SV counts among three populations are comparable in ER-negative cancers, while Nigerians have significantly more SV counts compared to African Americans (P=0.0013) or European Americans (P=2.9x10-5) in ER-positive cancers. Similarly, genome-wide substitution patterns in ER+ and ER- cancers varied widely by race/ethnicity. In ER- cases, West Africans carried the highest proportion of canonical APOBEC-associated substitutions, particularly C>T transitions. Conversely, European Americans with ER+ disease showed a higher proportion of C>T than both West Africans (Welch t-test P = 0.044) and African Americans (Welch t-test P = 0.011). Mutation signature analyses highlighted multiple APOBEC signatures, with notable contribution differences across ancestry and ER status. A signature likely corresponding to DNA damage repair correlated with the proportion of genetic ancestry, being most prevalent in European Americans and least common in Nigerians, particularly in ER-negative cancers, with African Americans showing a degree of this signature's contribution in between the two populations (linear model adjusted for age, P=1.0x10-10). Conclusions: Overall, our data suggests mutation spectra differences in across race/ethnicity and geography. Identification of molecular characteristics such as higher rates of HER2 enriched tumors and higher rates of GATA3 mutations in ER positive tumors are beginning to reveal the genomic basis of race-associated phenotypes and outcomes in breast cancer. Population differences in frequency and spectrum of mutations should now inform the design of innovative clinical trials that improve health equity and accelerate Precision Oncology care in diverse populations. Citation Format: Olopade OI, Pitt JJ, Riester M, Odetunde A, Yoshimatsu T, Labrot E, Ademola A, Sanni A, Okedere B, Mahan S, Nwosu I, Leary R, Ajani M, Johnson RS, Sveen E, Zheng Y, Wang S, Fitzgerald DJ, Grundstad J, Tuteja J, Clayton W, Khramtsova G, Oludara M, Omodele F, Benson O, Adeoye A, Morhason-Bello O, Ogundiran T, Babalola C, Popoola A, Morrissey M, Chen L, Huo D, Falusi A, Winckler W, Obafunwa J, Papoutsakis D, Ojengbede O, White KP, Ibrahim N, Oluwasola O, Barretina J. Comparative analysis of the genomic landscape of breast cancers from women of African and European ancestry [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD8-05.

Objectives: Of all ethnic/racial groups, age-standardized mortality rate from breast cancer is highest for African American women in the US for reasons that remain understudied. The paucity of genomic studies of breast tumors across the African Diaspora further restricts our understanding of the biology of breast cancer in underserved populations. To gain a better understanding of the genomic landscape of breast cancer in women of African Ancestry, we have developed a cross continent translational research infrastructure to examine the spectrum of genetic alterations in breast tumors from West Africa compared to the spectrum of alterations observed in tumors from African-American and other women who are predominantly white in The Cancer Genome Atlas (TCGA) dataset. Methods: Peripheral blood and breast cancer biopsy tissues were collected from 214 patients enrolled in the West Africa Breast Cancer Study (WABCS) at the University of Ibadan/University College Hospital (UI/UCH) and at Lagos State University Teaching Hospital (LASUTH). Blood DNA as well as breast cancer tissue DNA and RNA were extracted at the Novartis Institutes for Biomedical Research (NIBR), UI/UCH, and LASUTH using a modified protocol of PAXgene Tissue DNA and RNA extraction method. Whole-exome (WES) and transcriptome (RNA-seq) sequencing were performed on the Illumina HiSeq2000 platform at NIBR. Single Nucleotide Variants (SNVs) and insertions/deletions (indels) were called using MuTect and Pindel, while Copy Number Alterations (CNAs) were called using an in-house implementation of the ABSOLUTE method. Observed mutations were compared against those reported in the TCGA dataset. ER, PR and HER2 status were determined by immunohistochemistry (IHC) at UI/UCH, LASUTH and UChicago. Results: WES data for 95 tumors have been analyzed thus far. Genes commonly mutated in breast cancer in TCGA are also mutated in WABCS but the mutational spectrum is vastly different. TP53 (64%), MYC (31%), and GATA3 (26%), showed significantly higher alteration frequencies in WABCS and African Americans. In contrast, PIK3CA (20%), CDH1 (2%), and MAP3K1 (2%) were less frequently mutated in women of African ancestry. In addition to the high proportion with TP53 mutations, the proportion with HER2 positive subtype of 42.1% and triple-negative subtype of 37.9% suggest that tumors with the most aggressive features are overrepresented in breast cancer patients in West Africa. Conclusions: In the first study of its kind, high throughput genomic analysis of the largest cohort of women of African ancestry has uncovered alterations in cancer genes, some of which may be amenable to treatment with targeted therapies. Furthermore, we provide evidence that population differences in frequency and spectrum of mutations should drive the design and deployment of precision medicine initiatives. Only then can we develop innovative interventions to reduce the unacceptably high rates of mortality from breast cancer in underserved and under resourced populations. Citation Format: Olopade OI, Odetunde A, Riester M, Yoshimatsu T, Labrot E, Ademola A, Sanni A, Okedere B, Mahan S, Nwosu I, Leary R, Ajani M, Johnson RS, Sveen E, Zheng Y, Clayton W, Khramtsova G, Oludara M, Omodele F, Benson O, Adeoye A, Morhason-Bello O, Ogundiran T, Babalola C, Popoola A, Morrissey M, Huo D, Falusi A, Winckler W, Obafunwa J, Papoutsakis D, Ojengbede O, Ibrahim N, Oluwasola O, Barretina J. Genomic landscape of breast cancers from women of African ancestry across the diaspora. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-03-17.

Introduction: Cell free DNA (cfDNA) has become a promising approach for non-invasive assessment of the tumor genome. Many cfDNA assays target hotspot alterations in a focused set of genes, but do not provide a broad characterization of the cancer. We have developed and optimized a large next generation sequencing (NGS) panel covering the coding regions of over 500 genes. Using this panel, we sequenced cell free DNA from plasma and matched tumor DNA in patients with early stage breast cancer, late stage breast cancer and late stage lung cancer. Methods: Plasma was collected from patients with cancer using a double spin protocol and, when available, matched archival tumor tissue (representing different time interval with blood collection) was obtained. Next generation sequencing libraries were generated from cell free DNA isolated from 70 plasma samples and genomic DNA from 58 matched tumor samples. The NGS libraries were enriched for the gene panel of interest and were sequenced to a targeted depth of 1,000X for plasma and 300X for matched tumors. We optimized parameters of standard bioinformatics tools to robustly call low allelic fraction events, detecting single nucleotide variants down to 1%, as well as indels and copy number alterations. Results: We identified 8 PIK3CA hotspot alterations in plasma from late stage breast and lung cancers, in addition to many alterations across driver genes such as AKT1, EGFR, IDH2, NRAS, PTEN and TP53. In plasma samples from patients with late stage breast cancer, we found 4 ESR1 mutations exclusive to the plasma samples, of which 3 are known resistance mutations to endocrine therapy. Copy number alterations in EGFR, CCND1 and KRAS were also identified in patient plasma. When comparing the number of alterations across tumor stages, we found that late stage breast (mean = 12.5 variants) and lung cancers (mean = 12.5 variants) had a larger number of alterations present in plasma than early stage breast cancers (mean = 4.5 variants). We compared somatic mutations calls in plasma and matched tumor samples and found a concordance of 53%-67% at the variant level across patients with late stage cancers (N = 37 pairs). Higher variant level concordance was observed among plasma-tumor pairs collected less than a year apart (N = 11 pairs; 76%-84%) versus more than 5 years apart (N = 8 pairs; 41%-50%). Conclusion: We have developed and optimized a 500+ gene panel for direct sequencing of cfDNA, and we demonstrate that this broad assessment of circulating tumor DNA can be used for non-invasive characterization of the cancer genome landscape. The number of alterations identified in patient plasma is consistent with higher levels of ctDNA being present in late stage disease than in early stage disease. The time dependent degree of concordance between plasma and tumor collection suggests that cell free DNA assays may provide a more accurate characterization of the current tumor mutational landscape than an archival tumor sample. The identification of plasma specific ESR1 alterations highlights the importance of cfDNA in the context of identifying mechanisms of resistance, particularly for metastatic disease when tumor tissue collection may not be feasible. In addition, a broad NGS panel provides the opportunity to identify lesions unevaluated by targeted assays and to discover resistance mutations. Citation Format: Nadia Solovieff, Matt Hims, Rebecca Leary, Derek Chiang, Caroline Germa, Cristian Massacesi, Samit Hirawat, Stefan J. Scherer, Michael Morrissey, Wendy Winckler, Emmanuelle di Tomaso. Profiling cell free DNA in breast cancer and non-small cell lung cancer using broad NGS assessment. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr LB-A05.

Melanoma is the most lethal skin cancer and approximately 50% of the cases harbor mutations in the BRAF oncogene, with the mutation V600E representing 80-90% of all BRAF mutations in this indication. BRAF inhibitors as Vemurafenib and Dabrafenib have shown improved overall and progression free survival; however, the long term efficacy of these compounds is limited by the emergence of resistance. Several mechanisms of resistance to BRAF inhibitors have been already described, such as BRAF overexpression, increased ERBB3 signaling, expression of BRAF alternative isoforms, secondary mutations in BRAF or MEK1 and recently BRAF amplifications, among others. A fundamental aspect on devising optimal therapeutic regimes that overcome resistance is to develop preclinical models that resemble the genetic makeup of clinical patients who become resistance during the course of treatment to BRAF inhibitors. To this end, melanoma primary tumor xenografts (PTX) harboring BRAF V600E mutations were subject to treatment with BRAF inhibitors and response data was collected for a maximum of 180 days. Vehicle and treated samples were then sequenced using a targeted next generation sequencing approach in order to characterize their mutational landscape. Raw sequencing data was aligned to the human genome and potential mouse contamination was filter out before downstream analysis. Comparing SNV and copy number calls between treated and control samples revealed that focal amplifications of BRAF and de-novo mutations in the MEK1 gene were frequent genetic aberrations found in the PTX models that developed resistance. In summary, our results indicate that the genetic mechanisms of resistance observed in primary tumor xenograft models closely resemble what is observed in the clinical setting, making these models a valuable research tool for designing optimal therapeutic strategies. Citation Format: Alejandro Balbin, Angad Singh, Joshua Korn, Hui Gao, Darrin Stuart, John Green, Andrew Crenshaw, Scott Mahan, Nathan Houde, Alina Raza, Rebecca Leary, Derek Chiang, Michael Morrissey, Wendy Winckler, Sellers William. Modeling genetic mechanisms of resistance in melanoma primary tumor xenografts. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr B36.