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PDF file, 80K, Supplementary Tables 4-8: 4. LOH patterns in three cohorts, 5A&B. FLOH and chemotherapy resistance in three cohorts, 6. BRCA mutations in the AOCS, 7. Univariate and multivariate analysis of platinum resistantce, 8. PFS in LOH subclusters and patients with BRCA mutations.

XLS file, 509K, supplementary Tables 1-3: 1. Information from the Boston cohort, 2. Information from AOCS cohort, 3. Information from TCGA.

PDF file, 366K, Supplementary Figures 1-9: 1. LOH patterns on different array platforms, 2. Allelic imbalance in LOH clusters, 3. LOH clustering breast cancer, 4. LOH and copy number prevalence in breast cancer, 5. Chemotherapy resistance and FLOH in three cohorts, 6. Chemotherapy resistance and FLOH with or without BRCA mutations, 7. PFS regardless of stage and residual disease, 8. PFS with or without BRCA mutations, 9. BRCA1 expression and FLOH.

Purpose: High-grade serous cancer (HGSC) is the most common cancer of the ovary and is characterized by chromosomal instability. Defects in homologous recombination repair (HRR) are associated with genomic instability in HGSC, and are exploited by therapy targeting DNA repair. Defective HRR causes uniparental deletions and loss of heterozygosity (LOH). Our purpose is to profile LOH in HGSC and correlate our findings to clinical outcome, and compare HGSC and high-grade breast cancers.Experimental Design: We examined LOH and copy number changes using single nucleotide polymorphism array data from three HGSC cohorts and compared results to a cohort of high-grade breast cancers. The LOH profiles in HGSC were matched to chemotherapy resistance and progression-free survival (PFS).Results: LOH-based clustering divided HGSC into two clusters. The major group displayed extensive LOH and was further divided into two subgroups. The second group contained remarkably less LOH. BRCA1 promoter methylation was associated with the major group. LOH clusters were reproducible when validated in two independent HGSC datasets. LOH burden in the major cluster of HGSC was similar to triple-negative, and distinct from other high-grade breast cancers. Our analysis revealed an LOH cluster with lower treatment resistance and a significant correlation between LOH burden and PFS.Conclusions: Separating HGSC by LOH-based clustering produces remarkably stable subgroups in three different cohorts. Patients in the various LOH clusters differed with respect to chemotherapy resistance, and the extent of LOH correlated with PFS. LOH burden may indicate vulnerability to treatment targeting DNA repair, such as PARP1 inhibitors. Clin Cancer Res; 18(20); 5806–15. ©2012 AACR.

Background: Checkpoint inhibitors have revolutionized the treatment of metastatic melanoma, yielding long-term survival in a considerable proportion of the patients. Yet, 40–60% of patients do not achieve a long-term benefit from such therapy, emphasizing the urgent need to identify biomarkers that can predict response to immunotherapy and guide patients for the best possible treatment. Here, we exploited an unsupervised machine learning approach to identify potential inflammatory cytokine signatures from liquid biopsies, which could predict response to immunotherapy in melanoma. Methods: We studied a cohort of 77 patients diagnosed with unresectable advanced-stage melanoma undergoing treatment with first-line nivolumab plus ipilimumab or pembrolizumab. Baseline and on-treatment plasma samples were tested for levels of PD-1, PD-L1, IFNγ, IFNβ, CCL20, CXCL5, CXCL10, IL6, IL8, IL10, MCP1, and TNFα and analyzed by Uniform Manifold Approximation and Projection (UMAP) dimension reduction method and k-means clustering analysis. Results: Interestingly, using UMAP analysis, we found that treatment-induced cytokine changes measured as a ratio between baseline and on-treatment samples correlated significantly to progression-free survival (PFS). For patients treated with nivolumab plus ipilimumab we identified a group of patients with superior PFS that were characterized by significantly higher baseline-to-on-treatment increments of PD-1, PD-L1, IFNγ, IL10, CXCL10, and TNFα compared to patients with worse PFS. Particularly, a high PD-1 increment was a strong individual predictor for superior PFS (HR = 0.13; 95% CI 0.034–0.49; p = 0.0026). In contrast, decreasing levels of IFNγ and IL6 and increasing levels of CXCL5 were associated with superior PFS in the pembrolizumab group, although none of the cytokines were individually predictors for PFS. Conclusions: In short, our study demonstrates that a high increment of PD-1 is associated with superior PFS in advanced-stage melanoma patients treated with nivolumab plus ipilimumab. In contrast, decreasing levels of IFNγ and IL6, and increasing levels of CXCL5 are associated with response to pembrolizumab. These results suggest that using serial samples to monitor changes in cytokine levels early during treatment is informative for treatment response.

BackgroundCheckpoint inhibitors have significantly improved treatment of metastatic melanoma. Yet, 40–60% of the patients do not achieve a long-term benefit from such immunotherapy. Thus, there is an urgent need to identify biomarkers that can predict response to immunotherapy to guide patients for the best possible treatment. Here, we evaluate an unsupervised machine learning approach to identify potential cytokine signatures from liquid biopsies that predict response to immunotherapy in melanoma.MethodsBlood samples were drawn from 74 patients diagnosed with unresectable advanced-stage melanoma undergoing treatment with first-line nivolumab/ipilimumab or pembrolizumab between August 2017 – July 2019 at Aarhus University Hospital, Denmark. Blood samples were tested for plasma levels of PD-1, PD-L1, IFN-beta, IFN-gamma, CCL20, CXCL5, CXCL10, IL6, IL8, IL10, MCP1, and TNF-alpha by Meso Scale ELISA assays. Healthy controls were used to compare general cytokine levels in plasma. A bioinformatic workflow consisting of Uniform Manifold Approximation and Projection (UMAP) dimension reduction method and k-means clustering analysis was applied to define clusters based on the cytokine profile, followed by survival analysis of the clusters.ResultsUMAP analysis demonstrated that the cytokine profile at baseline was similar for healthy controls and patients, regardless of treatment. Upon treatment initiation, the cytokine profile changed in a treatment-dependent way to be significantly different between patient groups. Clustering defined by the cytokine profile measured early during treatment in nivolumab/ipilimumab treated patients identified two clusters associated with superior progression-free survival (PFS) (log-rank p=0.018). We identified that these cluster were characterized by significantly higher levels of PD-1, CXCL10, and TNF-alpha. UMAP analysis of the cytokine level as fold change over baseline level, confirmed that nivolumab/ipilimumab patients with superior PFS were characterized by higher levels of PD-1, CXCL10, and TNF-alpha. Cox regression analysis revealed high fold change of PD-1 as a strong predictor for superior PFS (HR=0.29; 95% CI 0.12–0.66; p=0.0032). However, a similar cytokine profile was not associated to superior PFS in patients receiving pembrolizumab, suggesting that the cytokine signature is specific for nivolumab/ipilimumab treatment.ConclusionsUsing unsupervised machine learning we identified a cytokine signature of high PD-1, CXCL10, and TNF-alpha to be associated with superior PFS in advanced-stage melanoma patients treated with nivolumab/ipilimumab but not pembrolizumab, with high fold change of PD-1 being a strong individual predictor for PFS.AcknowledgementsWe thank the medical laboratory technicians who collected blood samples and the patients who participated in the study.Ethics ApprovalThe study was approved by Central Denmark Region Committees on Biomedical Research Ethics, approval number 1-10-72-374-15.

Approximately 50% of patients with early-stage non-small-cell lung cancer (NSCLC) who undergo surgery with curative intent will relapse within 5 years1,2. Detection of circulating tumor cells (CTCs) at the time of surgery may represent a tool to identify patients at higher risk of recurrence for whom more frequent monitoring is advised. Here we asked whether CellSearch-detected pulmonary venous CTCs (PV-CTCs) at surgical resection of early-stage NSCLC represent subclones responsible for subsequent disease relapse. PV-CTCs were detected in 48% of 100 patients enrolled into the TRACERx study3, were associated with lung-cancer-specific relapse and remained an independent predictor of relapse in multivariate analysis adjusted for tumor stage. In a case study, genomic profiling of single PV-CTCs collected at surgery revealed higher mutation overlap with metastasis detected 10 months later (91%) than with the primary tumor (79%), suggesting that early-disseminating PV-CTCs were responsible for disease relapse. Together, PV-CTC enumeration and genomic profiling highlight the potential of PV-CTCs as early predictors of NSCLC recurrence after surgery. However, the limited sensitivity of PV-CTCs in predicting relapse suggests that further studies using a larger, independent cohort are warranted to confirm and better define the potential clinical utility of PV-CTCs in early-stage NSCLC.

Introduction: Immunotherapy is regarded as one of the major breakthroughs in cancer treatment. Despite its success, only a subset of patients responds-urging the quest for predictive biomarkers. We hypothesize that artificial intelligence (AI) algorithms can automatically quantify radiographic characteristics that are related to and may therefore act as noninvasive radiomic biomarkers for immunotherapy response.Patients and methods: In this study, we analyzed 1055 primary and metastatic lesions from 203 patients with advanced melanoma and non-small-cell lung cancer (NSCLC) undergoing anti-PD1 therapy. We carried out an AI-based characterization of each lesion on the pretreatment contrast-enhanced CT imaging data to develop and validate a noninvasive machine learning biomarker capable of distinguishing between immunotherapy responding and nonresponding. To define the biological basis of the radiographic biomarker, we carried out gene set enrichment analysis in an independent dataset of 262 NSCLC patients.Results: The biomarker reached significant performance on NSCLC lesions (up to 0.83 AUC, P < 0.001) and borderline significant for melanoma lymph nodes (0.64 AUC, P = 0.05). Combining these lesion-wide predictions on a patient level, immunotherapy response could be predicted with an AUC of up to 0.76 for both cancer types (P < 0.001), resulting in a 1-year survival difference of 24% (P = 0.02). We found highly significant associations with pathways involved in mitosis, indicating a relationship between increased proliferative potential and preferential response to immunotherapy.Conclusions: These results indicate that radiographic characteristics of lesions on standard-of-care imaging may function as noninvasive biomarkers for response to immunotherapy, and may show utility for improved patient stratification in both neoadjuvant and palliative settings.

Background: Colorectal cancer is responsible for 9.4% of cancer-related deaths worldwide. Early detection of the disease has the potential to improve patient outcomes, therefore, developing an efficient and minimally invasive method for carrying out surveillance has been a clinically relevant effort in recent years. Circulating tumour DNA has garnered interest as a marker for early cancer detection, however, deeper understanding of the underlying biology of ctDNA release is needed in order to maximize its utility in clinical practice. In this project, we aimed to investigate whether a phenotype conductive to ctDNA shedding can be defined in a colorectal cancer cohort, including transcriptomic, genomic and clinical data collected from stage I to stage IV colon cancer patients at Aarhus University Hospital. Methods: Transcriptomic data from 102 patients and whole exome sequencing data from 60 patients were analyzed. Differential gene expression and differential pathway enrichment analyses between ctDNA positive and ctDNA negative patients were conducted by performing Student’s t-test. The resulting p-values were adjusted according to the Benjamini-Hochberg method. The genes in the transcriptomic analyses were assigned to pathways with regard to the MSigDB Hallmark gene sets and pathway enrichment was assessed using Gene Set Variation Analysis (GSVA). Using an extended cohort of 537 patients, we performed Wilcoxon’s signed rank test to investigate the association between tumour size, histological subtypes and ctDNA shedding behavior. Additionally, we modelled the expected ctDNA fraction as a function of birth rate, death rate and tumour mass. Results: In colon cancer, ctDNA release is primarily associated with tumour size, molecular subtypes and proliferative transcriptomic signatures. A moderate but significant correlation was observed between the tumour’s largest diameter and the detected ctDNA fraction. Furthermore, molecular subtypes associated with less aggressive disease tended to shed lower amounts of ctDNA. Notably, we have found that pathways associated with proliferation are enriched in the ctDNA positive subgroup. Conclusions: Our results demonstrate that enhanced proliferative capacity in connection with tumour size and molecular subtypes may contribute to a higher ctDNA release rate. We anticipate our study to be a starting point for further investigation of ctDNA shedding dynamics in colorectal cancer. Citation Format: Judit Kisistok, Tenna Vesterman Henriksen, Jesper Bertram Bramsen, Thomas Reinert, Trine Block Mattesen, Nicolai Juul Birkbak, Claus Lindbjerg Andersen. Exploring the biology of ctDNA release in colon cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3398.

Metastatic disease is responsible for 90% of all cancer deaths. Understanding the process of how primary tumors achieve metastatic potential is of great importance and paramount to the development of precision medicine that may limit the aggressive distant spread of metastatic cancer. It is hypothesized that during cancer evolution, cells within the primary tumor obtain metastatic potential through acquisition of specific somatic alterations. However, the defining ability that allows metastasis remains unknown. By comparing genomic profiles of primary and metastatic cancers we wish to investigate if potential metastatic gate-keeper mutations exist, defined as alterations to individual genes or pathways that are required to facilitate metastatic dissemination.Here, we analyzed panel-based DNA sequencing datasets from the GENIE (Genomics Evidence Neoplasia Information Exchange) project, version 9.0. Analyses were performed on 174 shared cancer genes selected to include as many patients as possible while analyzing as many genes as possible. In total 39,036 patients had mutations or copy number alterations in one or more of the 174 shared genes across 25 different cancer types. Using bioinformatic tools, we compared genomic alterations in primary versus metastatic samples. Metastatic samples harbor a higher tumor mutation burden and increased levels of chromosomal instability. However, while we found a higher total level of driver mutations in metastatic samples, these appear primarily driven by a higher mutation burden, and corrected for this, we found a significantly lower level of drivers compared to primary. Overall, phylogenetic analysis showed that primary and metastatic samples clustered together by cancer type. Comparing two logistic regressions models, which was corrected for tumor mutation burden and genomic instability, we found that despite most genes show a relatively low difference in frequency between primary and metastatic disease, 55 of the 174 genes in this panel showed a small but significant overrepresentation in at least one cancer type in either primary or metastatic disease.With this analysis we demonstrate how the power of large datasets can be utilized to make novel inferences on cancer biology. We observed significant enrichment in overall mutation counts and copy number alterations in metastatic samples. However, we found limited genomic differences between primary and metastatic cancer within the same cancer types. This might suggest that acquisition of cancer driver mutations are initially mostly shaped by the tissue of origin where specific cancer driver mutations define the developing primary tumor, while acquisition of driver mutations that contribute to metastatic disease are less specific. It might indicate that the metastatic process is driven less by newly acquired metastatic features, but more by non-cancer features such as inflammation in the surrounding tissue. Citation Format: Ditte Sigaard Christensen, Johanne Ahrenfeldt, Mateo Sokač, Judit Kisistók, Nicholas McGranahan, Nicolai Juul Birkbak. Distinct aggressive biology drives the evolution of metastatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2186.

The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials., Multiple molecular profiling methods are required to study urothelial non-muscle-invasive bladder cancer (NMIBC) due to its heterogeneity. Here the authors integrate multi-omics data of 834 NMIBC patients, identifying a molecular subgroup associated with multiple alterations and worse outcomes.

Chromosomal instability in cancer consists of dynamic changes to the number and structure of chromosomes(1,2). The resulting diversity in somatic copy number alterations (SCNAs) may provide the variation necessary for tumour evolution(1,3,4). Here we use multi-sample phasing and SCNA analysis of 1,421 samples from 394 tumours across 22 tumour types to show that continuous chromosomal instability results in pervasive SCNA heterogeneity. Parallel evolutionary events, which cause disruption in the same genes (such asBCL9, MCL1,ARNT(also known asHIF1B),TERTandMYC) within separate subclones, were present in 37% of tumours. Most recurrent losses probably occurred before whole-genome doubling, that was found as a clonal event in 49% of tumours. However, loss of heterozygosity at the human leukocyte antigen (HLA) locus and loss of chromosome 8p to a single haploid copy recurred at substantial subclonal frequencies, even in tumours with whole-genome doubling, indicating ongoing karyotype remodelling. Focal amplifications that affected chromosomes 1q21 (which encompassesBCL9, MCL1andARNT), 5p15.33 (TERT), 11q13.3 (CCND1), 19q12 (CCNE1) and 8q24.1 (MYC) were frequently subclonal yet appeared to be clonal within single samples. Analysis of an independent series of 1,024 metastatic samples revealed that 13 focal SCNAs were enriched in metastatic samples, including gains in chromosome 8q24.1 (encompassingMYC) in clear cell renal cell carcinoma and chromosome 11q13.3 (encompassingCCND1) in HER2(+)breast cancer. Chromosomal instability may enable the continuous selection of SCNAs, which are established as ordered events that often occur in parallel, throughout tumour evolution.Chromosomal instability enables the continuous selection of somatic copy number alterations, which are established as ordered events that often occur in parallel, throughout tumour evolution and metastasis.

In the version of this article initially published, the list of members and affiliations for The TRACERx Consortium was provided as a Supplementary Note. The list should have been provided in the online version. Also, an incorrect version of Fig. 2b was published. The correct version is provided below. The errors have been corrected in the HTML and PDF versions of the article.

The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identified four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provided independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations were significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration was associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirmed the higher infiltration of class 2b tumors and demonstrated an association between higher immune cell infiltration and lower recurrence rates. Finally, a single-sample classification tool was built and the independent prognostic value of the transcriptomic classes was documented in 1306 validation samples. The classifier provides a framework for novel biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.

BRCA1/2 help maintain genomic integrity by stabilizing stalled forks for repair and thus act as tumor suppressors. Duan et al. identify the E3 ligase RFWD3 as a novel modulator of stalled fork stability in BRCA2-deficient cells and show that blocking fork degradation by depleting MRE11 is not sufficient for full fork recovery., BRCA1/2 help maintain genomic integrity by stabilizing stalled forks. Here, we identify the E3 ligase RFWD3 as an essential modulator of stalled fork stability in BRCA2-deficient cells and show that codepletion of RFWD3 rescues fork degradation, collapse, and cell sensitivity upon replication stress. Stalled forks in BRCA2-deficient cells accumulate phosphorylated and ubiquitinated replication protein A (ubq-pRPA), the latter of which is mediated by RFWD3. Generation of this intermediate requires SMARCAL1, suggesting that it depends on stalled fork reversal. We show that in BRCA2-deficient cells, rescuing fork degradation might not be sufficient to ensure fork repair. Depleting MRE11 in BRCA2-deficient cells does block fork degradation, but it does not prevent fork collapse and cell sensitivity in the presence of replication stress. No such ubq-pRPA intermediate is formed in BRCA1-deficient cells, and our results suggest that BRCA1 may function upstream of BRCA2 in the stalled fork repair pathway. Collectively, our data uncover a novel mechanism by which RFWD3 destabilizes forks in BRCA2-deficient cells.

International audience; Although thousands of solid tumors have been sequenced to date, a fundamental under-sampling bias isinherent in current methodologies. This is caused by a tissue sample input of fixed dimensions (e.g., 6 mmbiopsy), which becomes grossly under-powered as tumor volume scales. Here, we demonstrate representative sequencing (Rep-Seq) as a new method to achieve unbiased tumor tissue sampling. Rep-Seq uses fixed residual tumor material, which is homogenized and subjected to next-generation sequencing. Analysis of intratumor tumor mutation burden (TMB) variability shows a high level of misclassification using current single-biopsy methods, with 20% of lung and 52% of bladder tumors having at least one biopsy with high TMB butlow clonal TMB overall. Misclassification rates by contrast are reduced to 2% (lung) and 4% (bladder) when a more representative sampling methodology is used. Rep-Seq offers an improved sampling protocol for tumor profiling, with significant potential for improved clinical utility and more accurate deconvolution of clonal structure.

BackgroundIntra-tumor heterogeneity (ITH) of colorectal cancer (CRC) complicates molecular tumor classification, such as transcriptional subtyping. Differences in cellular states, biopsy cell composition, and tumor microenvironment may all lead to ITH. Here we analyze ITH at the transcriptomic and proteomic levels to ascertain whether subtype discordance between multiregional biopsies reflects relevant biological ITH or lack of classifier robustness. Further, we study the impact of tumor location on ITH.MethodsMultiregional biopsies from stage II and III CRC tumors were analyzed by RNA sequencing (41 biopsies, 14 tumors) and multiplex immune protein analysis (89 biopsies, 29 tumors). CRC subtyping was performed using consensus molecular subtypes (CMS), CRC intrinsic subtypes (CRIS), and TUMOR types. ITH-scores and network maps were defined to determine the origin of heterogeneity. A validation cohort was used with one biopsy per tumor (162 tumors).ResultsOverall, inter-tumor transcriptional variation exceeded ITH, and subtyping calls were frequently concordant between multiregional biopsies. Still, some tumors had high transcriptional ITH and were classified discordantly. Subtyping of proximal MSS tumors were discordant for 50% of the tumors, this ITH was related to differences in the microenvironment. Subtyping of distal MSS tumors were less discordant, here the ITH was more cancer-cell related. The subtype discordancy reflected actual molecular ITH within the tumors. The relevance of the subtypes was reflected at protein level where several inflammation markers were significantly increased in immune related transcriptional subtypes, which was verified in an independent cohort (Wilcoxon rank sum test; pConclusionOur transcriptomic and proteomic analyses show that the tumor location along the colorectum influence the ITH of CRC, which again influence the concordance of subtyping.

Metastatic cancer is a major cause of death and remains largely incurable. A better understanding of metastasis is therefore desperately needed to improve prognosis for late-stage disease. Here we survey the landscape of studies exploring the genomics of metastatic cancer. We consider evidence for genomic drivers of metastasis and explore studies investigating modes of metastatic spread.

Circulating tumour DNA (ctDNA) refers to the fraction of cell-free DNA in a patient's blood that originates from a tumour. Advances in DNA sequencing technologies and our understanding of the molecular biology of tumours have resulted in increased interest in exploiting ctDNA as a tool to facilitate earlier detection of cancer and thereby improve therapeutic outcomes by enabling early intervention. ctDNA analysis might also have utility in the adjuvant therapeutic setting by enabling the identification of patients at a high risk of disease recurrence on the basis of the detection of post-surgical minimal (or molecular) residual disease (MRD). This approach could provide the capability to adapt clinical trials in the adjuvant setting in order to optimize risk stratification, and we argue that this objective is achievable with current technologies. Herein, we evaluate contemporary next-generation sequencing (NGS) approaches to ctDNA detection with a focus on non-small-cell lung cancer. We explain the technical and analytical challenges to low-frequency mutation detection using NGS-based ctDNA profiling and evaluate the feasibility of ctDNA profiling in both screening and MRD assessment contexts.

The first genomic scar-based homologous recombination deficiency (HRD) measures were produced using SNP arrays. As array-based technology has been largely replaced by next generation sequencing approaches, it has become important to develop algorithms that derive the same type of genomic scar scores from next generation sequencing (whole exome “WXS”, whole genome “WGS”) data. In order to perform this analysis, we introduce here the scarHRD R package and show that using this method the SNP array-based and next generation sequencing-based derivation of HRD scores show good correlation (Pearson correlation between 0.73 and 0.87 depending on the actual HRD measure) and that the NGS-based HRD scores distinguish similarly well between BRCA mutant and BRCA wild-type cases in a cohort of triple-negative breast cancer patients of the TCGA data set.

Introduction: Metastatic disease is responsible for 90% of all cancer death. Understanding the process of how primary tumors achieve metastatic potential is of great importance and paramount to the development of precision medicine that may limit the aggressive distant spread of metastatic cancer. It is hypothesized that during cancer evolution, cells within the primary tumor obtain metastatic potential through acquisition of specific somatic alterations. However, the defining ability that allows metastasis remains unknown. By comparing genomic profiles of primary and metastatic cancers we wish to investigate if potential metastatic gate-keeper mutations exist, defined as alterations to individual genes or pathways that are required to facilitate metastatic dissemination. Material and methods: Here, we analyzed panel-based DNA sequencing datasets from the GENIE (Genomics Evidence Neoplasia Information Exchange) project. Analyses were performed on 123 shared genes from the 6 most common panels, selected to include as many patients as possible while analyzing as many genes as possible. In total 43,323 patients had mutations in one or more of the 123 shared genes across 37 different cancer types. Using bioinformatic tools, we compared genomic alterations in primary versus metastatic samples. Results: Out of the 123 genes we found 26 significantly enriched genes and 30 significantly depleted genes in metastatic disease in at least one cancer type. Overall, TP53 was the most mutated gene across all cancer types and the most enriched gene with significant enrichment in metastatic prostate cancer, non-small cell lung cancer and soft tissue sarcoma. Out of the 30 depleted genes we identified CTNBB1 as significantly depleted in four different cancer types and PIK3CA significantly depleted in two. PIK3CA is one of the most commonly mutated cancer genes, and a target of several precision therapies. Finding of the gene being depleted may indicate a less significant role in the development of metastatic disease. Additionally, we found a higher tumor mutation burden and increased levels of chromosomal instability for metastatic samples compared to primary. Conclusions: With this analysis we demonstrate how the power of large datasets can be utilized to make novel inferences on cancer biology. We observed significant enrichment in overall mutation counts and copy number alterations. Furthermore, we identified both enrichments and depletions of specific alterations in metastatic disease potentially revealing how certain driver gene combinations associate with cancer progression more commonly than others. Citation Format: Ditte Sigaard Christensen, Johanne Ahrenfeldt, Nicolai Juul Birkbak. Understanding metastatic cancer biology [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 2859.

A widespread approach to modern cancer therapy is to identify a single oncogenic driver gene and target its mutant-protein product (for example, EGFR-inhibitor treatment in EGFR-mutant lung cancers). However, genetically driven resistance to targeted therapy limits patient survival. Through genomic analysis of 1,122 EGFR-mutant lung cancer cell-free DNA samples and whole-exome analysis of seven longitudinally collected tumor samples from a patient with EGFR-mutant lung cancer, we identified critical co-occurring oncogenic events present in most advanced-stage EGFR-mutant lung cancers. We defined new pathways limiting EGFR-inhibitor response, including WNT/β-catenin alterations and cell-cycle-gene (CDK4 and CDK6) mutations. Tumor genomic complexity increases with EGFR-inhibitor treatment, and co-occurring alterations in CTNNB1 and PIK3CA exhibit nonredundant functions that cooperatively promote tumor metastasis or limit EGFR-inhibitor response. This study calls for revisiting the prevailing single-gene driver-oncogene view and links clinical outcomes to co-occurring genetic alterations in patients with advanced-stage EGFR-mutant lung cancer.

Intra-tumour genetic heterogeneity (ITH) fosters drug resistance and is a critical hurdle to clinical treatment. ITH can be well-measured using multi-region sampling but this is costly and challenging to implement. There is therefore a need for tools to estimate ITH in individual samples, using standard genomic data such as SNP-arrays, that could be implemented routinely. We designed two novel scores S and R, respectively based on the Shannon diversity index and Ripley’s L statistic of spatial homogeneity, to quantify ITH in single SNP-array samples. We created in-silico and in-vitro mixtures of tumour clones, in which diversity was known for benchmarking purposes. We found significant but highly-variable associations of our scores with diversity in-silico (p in–vitro (p = 0.015 and p = 0.085). Our scores were also correlated to previous ITH estimates from sequencing data but heterogeneity in the fraction of tumour cells present across samples hampered accurate quantification. The prognostic potential of both scores was moderate but significantly predictive of survival in several tumour types (corrected p = 0.03). Our work thus shows how individual SNP-arrays reveal intra-sample clonal diversity with moderate accuracy.

Next-generation deep genome sequencing has only recently allowed us to quantitatively dissect the extent of heterogeneity within a tumour, resolving patterns of cancer evolution. Intratumour heterogeneity and natural selection contribute to resistance to anticancer therapies in the advanced setting. Recent evidence has also revealed that cancer evolution might be constrained. In this review, we discuss the origins of intratumour heterogeneity and subsequently focus on constraints imposed upon cancer evolution. The presence of (1) parallel evolution, (2) convergent evolution and (3) the biological impact of acquiring mutations in specific orders suggest that cancer evolution may be exploitable. These constraints on cancer evolution may help us identify cancer evolutionary rule books, which could eventually inform both diagnostic and therapeutic approaches to improve survival outcomes.

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.

Whole genome doubling (WGD) is a prevalent macro-evolutionary event in cancer, involving a doubling of the entire chromosome complement. However, despite its prevalence and clinical prognostic relevance, the evolutionary selection pressures for WGD have not been investigated. Here, we explored whether WGD may act to mitigate the irreversible, inexorable ratchet-like, accumulation of deleterious mutations in essential genes. Utilizing 1050 tumor regions from 816 non-small cell lung cancers (NSCLC), we temporally dissect mutations to determine their temporal acquisition in relation to WGD. We find evidence for strong negative selection against homozygous loss of essential cancer genes prior to WGD. However, mutations in essential genes occurring after duplication were not subject to significant negative selection, consistent with WGD providing a buffering effect, decreasing the likelihood of homozygous loss. Finally, we demonstrate that loss of heterozygosity and temporal dissection of mutations can be exploited to identify signals of positive selection in lung, breast, colorectal cancer and other cancer types, enabling the elucidation of novel tumour suppressor genes and a deeper characterization of known cancer genes.

Somatic mutations together with immunoediting drive extensive heterogeneity within non-small-cell lung cancer (NSCLC). Herein we examine heterogeneity of the T cell antigen receptor (TCR) repertoire. The number of TCR sequences selectively expanded in tumors varies within and between tumors and correlates with the number of nonsynonymous mutations. Expanded TCRs can be subdivided into TCRs found in all tumor regions (ubiquitous) and those present in a subset of regions (regional). The number of ubiquitous and regional TCRs correlates with the number of ubiquitous and regional nonsynonymous mutations, respectively. Expanded TCRs form part of clusters of TCRs of similar sequence, suggestive of a spatially constrained antigen-driven process. CD8+ tumor-infiltrating lymphocytes harboring ubiquitous TCRs display a dysfunctional tissue-resident phenotype. Ubiquitous TCRs are preferentially detected in the blood at the time of tumor resection as compared to routine follow-up. These findings highlight a noninvasive method to identify and track relevant tumor-reactive TCRs for use in adoptive T cell immunotherapy.

An aim of molecular biomarkers is to stratify patients with cancer into disease subtypes predictive of outcome, improving diagnostic precision beyond clinical descriptors such as tumor stage1. Transcriptomic intratumor heterogeneity (RNA-ITH) has been shown to confound existing expression-based biomarkers across multiple cancer types2–6. Here, we analyze multi-region whole-exome and RNA sequencing data for 156 tumor regions from 48 patients enrolled in the TRACERx study to explore and control for RNA-ITH in non-small cell lung cancer. We find that chromosomal instability is a major driver of RNA-ITH, and existing prognostic gene expression signatures are vulnerable to tumor sampling bias. To address this, we identify genes expressed homogeneously within individual tumors that encode expression modules of cancer cell proliferation and are often driven by DNA copy-number gains selected early in tumor evolution. Clonal transcriptomic biomarkers overcome tumor sampling bias, associate with survival independent of clinicopathological risk factors, and may provide a general strategy to refine biomarker design across cancer types. TRACERx Lung: Intratumoral transcriptional heterogeneity, which often hinders the development of clinically useful RNA-expression-biased biomarkers for cancer, can now be overcome with an approach for the identification of clonal expression biomarkers.

While hundreds of thousands of solid tumors have been sequenced to date, a fundamental under-sampling bias is inherent in current methodologies. This is caused by a tissue sample input of fixed dimensions (e.g. 6mm punch) from a single spatial location, which becomes grossly under-powered as tumor volume scales. Indeed our analysis of current clinical and research practice shows that existing protocols sample from only 0.0005% to 2.0% of the total tumor mass, raising the prospect of considerable sampling bias. Failure to address this bias risks undermining the clinical utility of genomic medicine in cancer; through lack of sensitivity to detect actionable mutations, miss-assignment of subclonal variants as clonal, and unreliable estimate of tumor mutational burden (TMB). Here we demonstrate Representative Sequencing (Rep-Seq), as a novel method to achieve unbiased sampling of solid tumor tissue. The Rep-Seq protocol comprises homogenization of all residual tumor material not taken for pathology into a well-mixed solution, coupled with next generation sequencing. Rep-Seq was implemented on a proof of concept basis, and benchmarked against current methods across multiple solid tumor types including renal cell carcinoma, lung cancer, melanoma, breast and colorectal cancer. Analysis of intra-tumor TMB variability showed a high level of misclassification with current single biopsy methods, with 20% of lung tumors, and 52% of bladder tumors, having ≥1 biopsy with high-TMB, but low clonal TMB overall (based on 10.0 mutations/Mb threshold for immune checkpoint inhibitor therapy (CPI)). Misclassification rates by contrast were reduced to 2% (lung) and 4% (bladder) when a more representative sampling frame was used. Clonal clustering analysis revealed rapid convergence of cancer cell fraction estimates in Rep-Seq towards true values, as validated in >60 biopsies, and >5ctDNA samples, taken from a single tumor. As a consequence 100% of variants were correctly classified as clonal by Rep-Seq, compared to ~85% in single biopsy sequencing. In terms of subclonal mutation detection, Rep-Seq achieved a greater sensitivity to detect variants, as compared to single-biopsy sequencing at equivalent depth (p=6.6x10-11). Finally, in a rapid autopsy setting Rep-Seq was able to accurately reconstruct the clonal phylogeny of advanced stage disease, correctly identifying polyclonal metastases, whereas single biopsy sequencing predicted monoclonal disease. Clinically this case showed lack of response to three lines of immune CPI therapy, which was observed in the context of a heterogeneous subclonal neoantigen repertoire. In conclusion, Rep-Seq effectively implements an unbiased tumor sampling approach, drawing DNA molecules from a well-mixed solution of the entire tumor mass, hence removing spatial bias inherent in current approaches. As a result Rep-Seq detects more mutations, achieves greater accuracy in determining clonal from subclonal variants. Rep-Seq offers an improved sampling protocol for tumor profling, with the same equivalent sequencing costs as current methods (single biopsy sequencing), but with significant potential for improved clinical utility.

An unbiased genome-scale screen for unmutated genes that drive cancer growth when overexpressed identified methyl cytosine-guanine dinucleotide (CpG) binding protein 2 (MECP2) as a novel oncogene. MECP2 resides in a region of the X-chromosome that is significantly amplified across 18% of cancers, and many cancer cell lines have amplified, overexpressed MECP2 and are dependent on MECP2 expression for growth. MECP2 copy-number gain and RAS family member alterations are mutually exclusive in several cancer types. The MECP2 splicing isoforms activate the major growth factor pathways targeted by activated RAS, the MAPK and PI3K pathways. MECP2 rescued the growth of a KRASG12C-addicted cell line after KRAS downregulation, and activated KRAS rescues the growth of an MECP2-addicted cell line after MECP2 downregulation. MECP2 binding to the epigenetic modification 5-hydroxymethylcytosine is required for efficient transformation. These observations suggest that MECP2 is a commonly amplified oncogene with an unusual epigenetic mode of action. Significance: MECP2 is a commonly amplified oncogene in human malignancies with a unique epigenetic mechanism of action. Cancer Discov; 6(1); 45–58. ©2015 AACR. This article is highlighted in the In This Issue feature, p. 1

Introduction Minimal residual disease (MRD) detection in solid tumors describes isolation of circulating tumor DNA (ctDNA) molecules in plasma following definitive treatment of a cancer. Detection of MRD following surgical tumor excision categorizes patients as high risk for disease recurrence. Establishing an MRD approach to treating early-stage NSCLC will facilitate escalation of standard of care (SoC) treatment only in patients destined to relapse from their cancer and overcome challenges associated with conventional adjuvant drug-trial design. Here, we present data from the lung TRACERx study where patients with early-stage NSCLC underwent phylogenetic ctDNA profiling following resection. Methods Patient specific anchored-multiplex PCR (AMP) enrichment panels were generated for 78 lung TRACERx patients who underwent surgery for stage I-III NSCLC; 608 plasma samples were analyzed. Extensive patient-specific cfDNA enrichment panels targeted a median of 196 (range 72 to 482) clonal and subclonal variants detected in primary tumor tissue by multi-region exome sequencing. A novel MRD-caller controlled and estimated background sequencing error to maximize ctDNA detection at low mutant allele frequencies (MAFs). Analytical validation experiments benchmarked assay performance. Results Analytical validation of a 50-variant AMP-MRD assay demonstrated a sensitivity of 89% for mutant DNA at a MAF of 0.008% (with 25ng of DNA input into the assay), specificity was 100% experimentally and 99.9% (95% CI: 99.67 to 99.99%) modelled in-silico. 45 patients suffered relapse of their primary NSCLC; ctDNA was detected at or before clinical relapse in 37 of 45 patients. In these 37 patients the median ctDNA lead-time (time from ctDNA detection to clinical relapse) was 151 days (range 0 to 984 days) and the median time to relapse from surgery was 413 days (range 41 to 1242 days). In 10 of 10 patients who developed second primary cancers during follow-up no ctDNA was detected, reflecting specificity of the MRD assay toward the primary tumor. In 23 patients who remained relapse-free during a median of 1184 days of study follow-up, ctDNA was detected in 1 of 199 time-points analyzed. Analysis of SoC adjuvant surveillance imaging (CT, PET-CT or MRI, 220 encounters) revealed examples of MRD positive patients where SoC radiological surveillance was negative for impending relapse. Through application of large cfDNA enrichment panels targeting up to 483 variants per patient we observed dynamic changes in clonal composition and copy-number status prior to NSCLC relapse, categorized relapse as monoclonal or polyclonal and identified distinct subclonal dynamics during systemic intervention for disease recurrence. Conclusions ctDNA is an adjuvant biomarker capable of both detecting MRD following surgery and defining the clonality of relapsing disease. These data pave the way for clinical trials predicated on escalation of adjuvant standard of care in NSCLC patients who exhibit MRD positive status following surgery. Citation Format: Chris Abbosh, Alexander Frankell, Aaron Garnett, Thomas Harrison, Morgan Weichert, Abel Licon, Selvaraju Veeriah, Bob Daber, Mike Moreau, Adrian Chesh, Kevin Litchfield, Emilia Lim, Daniel Cooke, Clare Puttick, Maise Al Bakir, Fabio Gomes, Akshay Patel, Lizi Manzano, Ariana Huebner, Nicolas Carey, Joan Riley, Paula Roberts, Todd Druley, Jacqui A. Shaw, Nicholas McGranahan, Mariam Jamal-Hanjani, Nicolai Birkbak, Josh Stahl, Charles Swanton, Lung TRACERx consortium. Phylogenetic tracking and minimal residual disease detection using ctDNA in early-stage NSCLC: A lung TRACERx study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT023.

Cell-in-cell (CIC) structures are commonly seen in tumours. Their biological significance remains unclear, although they have been associated with more aggressive tumours. Here we report that mutant p53 promotes CIC via live cell engulfment. Engulfed cells physically interfere in cell divisions of host cells and for cells without p53 this leads to host cell death. In contrast, mutant p53 host cells survive, display aberrant divisions, multinucleation and tripolar mitoses. In xenograft studies, CIC-rich p53 mutant/null co-cultures show enhanced tumour growth. Furthermore, our results show that CIC is common within lung adenocarcinomas, is an independent predictor of poor outcome and disease recurrence, is associated with mutant p53 expression and correlated to measures of heterogeneity and genomic instability. These findings suggest that pro-tumorigenic entotic engulfment activity is associated with mutant p53 expression, and the two combined are a key factor in genomic instability., Cell-in-cell (CIC) structures are frequently observed in cancers; however, it is unclear how their formation contributes to tumorigenesis. Here, the authors show that the high frequency of CIC is linked to mutant p53 status and CIC containing p53 mutant cancer cells are pro-tumorigenic due to enhanced genomic instability.

Cell-in-cell (CIC) structures are commonly seen in tumours. Their biological significance remains unclear, although they have been associated with more aggressive tumours. Here we report that mutant p53 promotes CIC via live cell engulfment. Engulfed cells physically interfere in cell divisions of host cells and for cells without p53 this leads to host cell death. In contrast, mutant p53 host cells survive, display aberrant divisions, multinucleation and tripolar mitoses. In xenograft studies, CIC-rich p53 mutant/null co-cultures show enhanced tumour growth. Furthermore, our results show that CIC is common within lung adenocarcinomas, is an independent predictor of poor outcome and disease recurrence, is associated with mutant p53 expression and correlated to measures of heterogeneity and genomic instability. These findings suggest that pro-tumorigenic entotic engulfment activity is associated with mutant p53 expression, and the two combined are a key factor in genomic instability.

Background: Platinum based therapy is an effective treatment for a subset of triple negative breast cancer and ovarian cancer patients. In order to increase response rate and decrease unnecessary use, robust biomarkers that predict response to therapy are needed. Patients and methods: We performed an integrated genomic approach combining differential analysis of gene expression and DNA copy number in sensitive compared to resistant triple negative breast cancers in two independent neoadjuvant cisplatin treated cohorts. Functional relevance of significant hits was investigated in vitro by overexpression, knockdown and targeted inhibitor treatment. Results: We identified two genes, the Bloom helicase (BLM) and Fanconi anemia complementation group I (FANCI), that have both increased DNA copy number and gene expression in the platinum sensitive cases. Increased level of expression of these two genes was also associated with platinum but not with taxane response in ovarian cancer. As a functional validation, we found that overexpression of BLM promotes DNA damage and induces sensitivity to cisplatin, but has no effect on paclitaxel sensitivity. Conclusions: A biomarker based on the expression levels of the BLM and FANCI genes is a potential predictor of platinum sensitivity in triple negative breast cancer and ovarian cancer. Short description: Through integrated analysis of gene expression and copy number data from two independent clinical trials in triple negative breast cancer, we identify two genes, BLM and FANCI, involved in double-strand DNA repair where increased expression is related to sensitivity to platinum induced DNA damage. Further functional validation reveals that overexpression of BLM alone promotes DNA damage.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with > 10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance. We thank Aida Murra, Naheed Shaikh, Justine Korteweg, Jeremy Tai, Eleanor Carlyle, Leonora Conneely, KimEdmonds, Karla Lingard, Karen O'Meara, Helen Breeze, Sarah Sarker, Lesley Cooper, Linda Shephard, Susie Slater, and Catherine Rogers for study support. We thank the patients and their families. S.T. and H.X. are funded by Cancer Research UK (CRUK) (C50947/A18176). S.T., T.C., J.L., and M.G. are funded by the National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at the Royal Marsden Hospital and Institute of Cancer Research (A109). J.I.L. is funded by the Ministerio de Economia y Competitividad (MINECO, SAF2016-79847-R). M.S., A.S., J. Lynch, R.F., L.A., and L.S. are funded by the Royal Marsden Cancer Charity. K.L. is funded by UK Medical Research Council (MR/P014712/1). T.B.K.W. is funded by the European Union Seventh Framework Programme (FP7-People-2013-ITN). M.J.-H. is funded by the NIHR. N.M.L. is a Winton Group Leader in recognition of the Winton Charitable Foundation's support towards the establishment of The Francis Crick Institute. N.M.L. is additionally funded by a Wellcome Trust Joint Investigator Award (103760/Z/14/Z) and the MRC eMedLab Medical Bioinformatics Infrastructure Award (MR/L016311/1). M.K. is funded by the Danish Cancer Society grant (R90-A6213). P.C. is funded by the Wellcome Trust (WT088340MA). N.M. receives funding from CRUK, Rosetrees, and the NIHR BRC at University College London Hospitals. C.S. is a Royal Society Napier Research Professor. C.S. is funded by Cancer Research UK (TRACERx and CRUK Cancer Immunotherapy Catalyst Network), the CRUK Lung Cancer Centre of Excellence, Stand Up 2 Cancer (SU2C), the Rosetrees and Stoneygate Trusts, NovoNordisk Foundation (THESEUS), Marie Curie Network PloidyNet, the NIHR BRC at University College London Hospitals, and the CRUK University College London Experimental Cancer Medicine Centre. C.S., O.P., D.R., I.C., and Z.S. are funded by NovoNordisk Foundation (16584). O.P., D.R., and I.C. are funded by the National Research, Development and Innovation Office of Hungary (NVKP_16-1-20160004). This work was supported by CRUK (Clinical Scientist Fellowship to S.T., C50947/A18176), The Francis Crick Institute, which receives its core funding from Cancer Reseach UK (FC010110), the UK Medical Research Council (FC010110), the Wellcome Trust (FC010110), and NIHR BRC at the Royal Marsden Hospital and Institute of Cancer Research (A109). High-performance computing was supported by eMedLab. The results published here are in whole or part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/.

A significant proportion of triple negative breast cancers (TNBC) carry defects in DNA repair including Homologous Recombination (HR) defects and are sensitive to therapies that target these pathways. Several clinical trials have demonstrated improvement in pathologic response with the addition of platinum to standard of care neoadjuvant regimens but at a cost of increased toxicities. Recently three DNA based metrics (LOH, Abkevich et al. 2012 Br J Cancer; TAI, Birkbak et al. 2012 Cancer Discov; LST, Popava et al. 2012 Cancer Res) have been developed, shown to be highly associated with BRCA1/2 mutation status, and found to predict sensitivity to platinum based chemotherapy in TNBC. The HRD Score was defined as the sum of LOH, TAI, and LST measurements, and a threshold separating tumors with high and low HRD Scores was established. This study assesses the association of HRD Score with response to cisplatin neoadjuvant chemotherapy in patients with TNBC. A clinical test that identifies tumors with defects in HR may distinguish those patients more likely to benefit from the addition of platinum. Methods: Archival tumor samples were obtained from 74 patients with TNBC from 2 separate clinical trials conducted at DFHCC under IRB approved protocols. One trial enrolled 28 patients who received neoadjuvant cisplatin monotherapy (Silver et al., 2010 J Clin Oncol). The second trial enrolled 51 patients who received cisplatin and bevacizumab chemotherapy (Ryan, et al.,2009 J Clin Oncol). HRD Score and tumor BRCA1/2 mutation status were determined. BRCA1/2 deficiency was defined as the presence of BRCA1/2 mutation with loss of the second allele in the tumor. Response was categorized by the residual cancer burden (RCB) score with responders defined as RCB0 or 1, and non-responders as RBC2 or 3. A second measure of response, pathologic complete response (pCR), was defined as RCB0 and non-responders as RCB1,2 or 3. Logistic regression was used to evaluate HRD Score in combination with BRCA1/2 deficiency as a predictor of response to neoadjuvant therapy. All analysis was conducted according to a pre-specified Statistical Analysis Plan. Results: As of May 29, 2014 41 samples have been processed. Seven carried deleterious mutations in BRCA1/2 (17%). Thirty-three of the tumors produced SNP data of sufficient quality for HRD score calculation. HRD scores in the passing samples ranged from 7 – 74, with an average score of 45. The HRD scores observed in BRCA1/2 mutation carriers (n=6) ranged from 43 – 57 with an average HRD score of 55. We anticipate that all molecular data will be generated by July 1, 2014. Correlation with pCR and RCB0/1 will be assessed. Conclusions: The LOH, TAI, and LST metrics have been shown in previous studies to predict response to platinum-based neoadjuvant chemotherapy in patients with TNBC. This study will be a validation of LOH, TAI and LST in the form of a combined score, and will demonstrate that HRD Score can be used as a tool to identify patients with breast tumors with underlying HR deficiency who may benefit from platinum therapy. Citation Format: Andrea L Richardson, Daniel P Silver, Zoltan Szallasi, Nicolai J Birkbak, Zhigang C Wang, J Dirk Iglehart, Erica L Mayer, Eric P Winer, Nadine M Tung, Paula D Ryan, Steven J Isakoff, William T Barry, April Greene-Collozi, Alexander Gutin, Julia Reid, Chris Neff, Joshua Jones, Kirsten Timms, Anne-Renee Hartman, Judy E Garber. Homologous recombination deficiency (HRD) assay predicts response to cisplatin neoadjuvant chemotherapy in patients with triple negative breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-11.

Summary Chromosomal instability (CIN) contributes to cancer evolution, intratumor heterogeneity, and drug resistance. CIN is driven by chromosome segregation errors and a tolerance phenotype that permits the propagation of aneuploid genomes. Through genomic analysis of colorectal cancers and cell lines, we find frequent loss of heterozygosity and mutations in BCL9L in aneuploid tumors. BCL9L deficiency promoted tolerance of chromosome missegregation events, propagation of aneuploidy, and genetic heterogeneity in xenograft models likely through modulation of Wnt signaling. We find that BCL9L dysfunction contributes to aneuploidy tolerance in both TP53-WT and mutant cells by reducing basal caspase-2 levels and preventing cleavage of MDM2 and BID. Efforts to exploit aneuploidy tolerance mechanisms and the BCL9L/caspase-2/BID axis may limit cancer diversity and evolution., Graphical Abstract, Highlights • Loss-of-function alterations in BCL9L are frequent in aneuploid CRC • BCL9L dysfunction drives aneuploidy tolerance by reducing levels of caspase-2 • Caspase-2 activation following aneuploidy results in MDM2 and BID cleavage • p53 stabilization after chromosome missegregation is regulated by caspase-2, López-García et al. find that BCL9L is often genetically inactivated in human colorectal cancers with chromosomal instability. BCL9L dysfunction promotes aneuploidy tolerance by reducing basal caspase-2 levels and preventing cleavage of MDM2 and BID independent of TP53 mutation status.

Summary Background The focus of tumour-specific antigen analyses has been on single nucleotide variants (SNVs), with the contribution of small insertions and deletions (indels) less well characterised. We investigated whether the frameshift nature of indel mutations, which create novel open reading frames and a large quantity of mutagenic peptides highly distinct from self, might contribute to the immunogenic phenotype. Methods We analysed whole-exome sequencing data from 5777 solid tumours, spanning 19 cancer types from The Cancer Genome Atlas. We compared the proportion and number of indels across the cohort, with a subset of results replicated in two independent datasets. We assessed in-silico tumour-specific neoantigen predictions by mutation type with pan-cancer analysis, together with RNAseq profiling in renal clear cell carcinoma cases (n=392), to compare immune gene expression across patient subgroups. Associations between indel burden and treatment response were assessed across four checkpoint inhibitor datasets. Findings We observed renal cell carcinomas to have the highest proportion (0·12) and number of indel mutations across the pan-cancer cohort (p −16 ), more than double the median proportion of indel mutations in all other cancer types examined. Analysis of tumour-specific neoantigens showed that enrichment of indel mutations for high-affinity binders was three times that of non-synonymous SNV mutations. Furthermore, neoantigens derived from indel mutations were nine times enriched for mutant specific binding, as compared with non-synonymous SNV derived neoantigens. Immune gene expression analysis in the renal clear cell carcinoma cohort showed that the presence of mutant-specific neoantigens was associated with upregulation of antigen presentation genes, which correlated ( r =0·78) with T-cell activation as measured by CD8-positive expression. Finally, analysis of checkpoint inhibitor response data revealed frameshift indel count to be significantly associated with checkpoint inhibitor response across three separate melanoma cohorts (p=4·7 × 10 −4 ). Interpretation Renal cell carcinomas have the highest pan-cancer proportion and number of indel mutations. Evidence suggests indels are a highly immunogenic mutational class, which can trigger an increased abundance of neoantigens and greater mutant-binding specificity. Funding Cancer Research UK, UK National Institute for Health Research (NIHR) at the Royal Marsden Hospital National Health Service Foundation Trust, Institute of Cancer Research and University College London Hospitals Biomedical Research Centres, the UK Medical Research Council, the Rosetrees Trust, Novo Nordisk Foundation, the Prostate Cancer Foundation, the Breast Cancer Research Foundation, the European Research Council.

The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide8,9, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFRT790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

Background Intratumoural heterogeneity (ITH) is well recognised in prostate cancer (PC), but its role in high-risk disease is uncertain. A prospective, single-arm, translational study using targeted multiregion prostate biopsies was carried out to study genomic and T-cell ITH in clinically high-risk PC aiming to identify drivers and potential therapeutic strategies. Patients and methods Forty-nine men with elevated prostate-specific antigen and multiparametric-magnetic resonance imaging detected PC underwent image-guided multiregion transperineal biopsy. Seventy-nine tumour regions from 25 patients with PC underwent sequencing, analysis of mutations, copy number and neoepitopes combined with tumour infiltrating T-cell subset quantification. Results We demonstrated extensive somatic nucleotide variation and somatic copy number alteration heterogeneity in high-risk PC. Overall, the mutational burden was low (0.93/Megabase), but two patients had hypermutation, with loss of mismatch repair (MMR) proteins, MSH2 and MSH6. Somatic copy number alteration burden was higher in patients with metastatic hormone-naive PC (mHNPC) than in those with high-risk localised PC (hrlPC), independent of Gleason grade. Mutations were rarely ubiquitous and mutational frequencies were similar for mHNPC and hrlPC patients. Enrichment of focal 3q26.2 and 3q21.3, regions containing putative metastasis drivers, was seen in mHNPC patients. We found evidence of parallel evolution with three separate clones containing activating mutations of β-catenin in a single patient. We demonstrated extensive intratumoural and intertumoural T-cell heterogeneity and high inflammatory infiltrate in the MMR-deficient (MMRD) patients and the patient with parallel evolution of β-catenin. Analysis of all patients with activating Wnt/β-catenin mutations demonstrated a low CD8+/FOXP3+ ratio, a potential surrogate marker of immune evasion. Conclusions The PROGENY (PROstate cancer GENomic heterogeneitY) study provides a diagnostic platform suitable for studying tumour ITH. Genetic aberrations in clinically high-risk PC are associated with altered patterns of immune infiltrate in tumours. Activating mutations of Wnt/β-catenin signalling pathway or MMRD could be considered as potential biomarkers for immunomodulation therapies. Clinical Trials.gov Identifier NCT02022371

Regulators of transition through mitosis such as SURVIVIN and Aurora kinase A (AURKA) have been previously implicated in the initiation of chromosomal instability (CIN), a driver of intratumour heterogeneity. We investigate the relationship between protein expression of these genes and directly quantified CIN, and their prognostic utility in breast cancer. The expression of SURVIVIN and AURKA was determined by immunohistochemistry in a cohort of 426 patients with primary breast cancer. The association between protein expression and histopathological characteristics, clinical outcome and CIN status, as determined by centromeric FISH and defined by modal centromere deviation, was analysed. Significantly poorer clinical outcome was observed in patients with high AURKA expression levels. Expression of SURVIVIN was elevated in ER-negative relative to ER-positive breast cancer. Both AURKA and SURVIVIN increased expression were significantly associated with breast cancer grade. There was a significant association between increased CIN and both increased AURKA and SURVIVIN expression. AURKA gene amplification was also associated with increased CIN. To our knowledge this is the largest study assessing CIN status in parallel with the expression of the mitotic regulators AURKA and SURVIVIN. These data suggest that elevated expression of AURKA and SURVIVIN, together with AURKA gene amplification, are associated with increased CIN in breast cancer, and may be used as a proxy for CIN in breast cancer samples in the absence of more advanced molecular measurements.