CNSistent integration and feature extraction from somatic copy number profiles

BackgroundSomatic copy number alterations (SCNAs) are an important class of genomic alteration in cancer. They are frequently observed in cancer samples, with studies showing that, on average, SCNAs affect 34% of a cancer cell’s genome. Furthermore, SCNAs have been shown to be major drivers of tumour development and have been associated with response to therapy and prognosis. Large-scale cancer genome studies suggest that tumours are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Despite the frequency of SCNAs and their clinical relevance, the use of genomics assays in the clinic is biased towards targeted gene panels, which identify SNVs but provide limited scope to detect SCNAs throughout the genome. There is a need for a comparably low-cost and simple method for high-resolution SCNA profiling.ResultsWe present conliga, a fully probabilistic method that infers SCNA profiles from a low-cost, simple, and clinically-relevant assay (FAST-SeqS). When applied to 11 high-purity oesophageal adenocarcinoma samples, we obtain good agreement (Spearman’s rank correlation coefficient, rs=0.94) between conliga’s inferred SCNA profiles using FAST-SeqS data (approximately £14 per sample) and those inferred by ASCAT using high-coverage WGS (gold-standard). We find that conliga outperforms CNVkit (rs=0.89), also applied to FAST-SeqS data, and is comparable to QDNAseq (rs=0.96) applied to low-coverage WGS, which is approximately four-fold more expensive, more laborious and less clinically-relevant. By performing an in silico dilution series experiment, we find that conliga is particularly suited to detecting SCNAs in low tumour purity samples. At two million reads per sample, conliga is able to detect SCNAs in all nine samples at 3% tumour purity and as low as 0.5% purity in one sample. Crucially, we show that conliga’s hidden state information can be used to decide when a sample is abnormal or normal, whereas CNVkit and QDNAseq cannot provide this critical information.ConclusionsWe show that conliga provides high-resolution SCNA profiles using a convenient, low-cost assay. We believe conliga makes FAST-SeqS a more clinically valuable assay as well as a useful research tool, enabling inexpensive and fast copy number profiling of pre-malignant and cancer samples.

Background: Studies by The Cancer Genome Atlas (TCGA) and others have identified regions of somatic copy number alteration (SCNA) in cervical squamous cell carcinoma (CESC), head and neck squamous cell carcinoma (HNSC), and lung squamous cell carcinoma (LUSC). These three tumor types exhibit frequent SCNAs in chromosome 11, including focal gains in 11q13 and 11q22, as well as broad losses in 11p and 11q22-qter. Because expression levels are affected by underlying genomic events, we hypothesized that an integrated analysis of multiple genomic data types would provide increased ability to identify target genes in SCNA regions when compared to methods based on copy number alone while providing insight into mechanisms regulating expression. Examination of multiple tumor types provides a method to validate findings. Techniques: Gene expression (GE), DNA copy number (CN), DNA methylation (ME), and microRNA expression (miR) data were obtained from the TCGA studies of CESC, HNSC, and LUSC. For each tumor type, univariate and multivariate linear models were constructed on a gene-by-gene basis to investigate the effect of changes in CN, ME, and miR on GE. Analysis of model output provided an approach to identify target genes in SCNA regions and assess the effect of genomic alterations on expression. Results: Genome-wide GE, CN, ME, and miR data were available for n = 191 (CESC), n = 453 (HNSC), and n = 326 (LUSC) tumor samples. Univariate modeling detected a strong overall association between GE and CN, as measured by the coefficient of determination (model R2). Underlying CN events produced high model R2 for widely recognized genes, e.g. FADD in HNSC and LUSC, and less well-known genes. For example, DCUN1D5 (11q22) exhibits high model R2 in all three tumor types. Univariate analyses suggest that ALDH3B1 (11q13), a predicted target of the tumor suppressor miR-205, is epigenetically regulated. Most samples exhibit high expression of miR-205 and moderate expression of ALDH3B1, but increased ALDH3B1 levels are seen when miR-205 levels are low. This is notable in light of the striking negative association between miR-205 expression and methylation levels, particularly in CESC and LUSC. Fanconi anemia family member FANCF lies in a broad region of CN loss in 11p that contains no clear driver gene. Whereas univariate associations between FANCF GE and CN were moderate, multivariate analyses highlighted this gene because of the additional effect of ME on GE, which was pronounced in CESC and LUSC. Conclusion: Linear modeling techniques provide a flexible and powerful basis for performing integrated analysis of genomic data. Our approach produces predicted results when analyzing known cancer genes, highlights lesser known genes for future study, provides insight into gene regulation, and draws attention to genes relevant in multiple tumor types. Citation Format: Vonn Walter, Ying Du, Xiaoying Yin, Wei Sun, Matthew D. Wilkerson, Michele C. Hayward, Ashley H. Salazar, Charles M. Perou, David N. Hayes. Integrated genomic analysis of chromosome 11 in squamous tumors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4801. doi:10.1158/1538-7445.AM2015-4801

Introduction: Retinoblastoma (Rb) is the most common childhood intraocular cancer. Tissue biopsy of Rb can cause tumor spread, so it is contraindicated. We demonstrated that aqueous humor (AH), an ocular fluid, is a high-yield liquid biopsy enabling in vivo detection of tumor-derived cell-free DNA (cfDNA) thus overcoming the contraindication of biopsy. Somatic genomic alterations, including both somatic copy number alterations (SCNAs) and single nucleotide variations (SNVs) on RB1 gene, have been able to be identified in the same clinical samples but with two separate sequencing runs. In this study, we first developed a single targeted sequencing method to identify both SCNAs and RB1 SNVs. With this method, we further investigated the degree of genomic concordance between paired tumor and AH samples from the same Rb eye. Materials and Methods: 11 paired AH and Rb tumor samples were included in the study. cfDNA of AH and tumor DNA of enucleated Rb eyes were isolated with QIAgen commercial kits. DNAs were constructed into whole genome libraries followed by hybridization target enrichment (Agilent SureSelect). The enrichment assay covers the whole length of RB1 and MycN genes, the all-exon regions of BCOR and CREBBP genes, and a whole genome CNV backbone. Libraries were submitted to Illumina HiSeq 4000 platform for fastq data generation with 2 × 150bp mode. The bioinformatics pipeline was optimized to generate SCNA profiles from targeted sequencing reads, along with SNV calling. Results: For SCNA profiles, 11/11 AH samples (100%) and 8/11 tumor samples (72.72%) have positive RB-SCNA signatures. Strong concordances were observed between AH and tumor SCNA profiles (median = 90.1%) with targeted sequencing reads. In total, 9 disease-driving RB1 SNVs were identified in 6 patients (54.5%). 7/9 (77.8%) of the variants were shared between AH and tumor samples, while the AH and tumor each contained one unique SNV. In all SNVs, the AH displayed a higher allele frequency. Notably, 4/11 samples have focal RB1 gene deletion detected with SCNA profiling, which may explain the difficulties of RB1 SNV detection in some samples. Further, one case was driven by a MYCN gene amplification with no RB1 alterations. Conclusions: This study presented highlights the utility of a single method to call both SVNs and SCNAs in a single clinical sample, with enriched tumor information detected in AH compared with tumor. This study further strengthens the utility of AH as a liquid biopsy platform for Rb eyes. Citation Format: Liya Xu, Mike J. Schmidt, Rishvanth K. Prakabar, Peter Kuhn, James Hicks, Jesse Berry. Simultaneous somatic copy number alterations and single nucleotide variants detection in paired aqueous humor and tumors from retinoblastoma eyes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3553.

Background: Characterization of focal somatic copy number alterations (SCNAs) has led to the identification of many cancer genes, yet similar investigations of arm-level SCNAs remain challenging. The identity of driver genes within these broad SCNAs remains a critical unanswered question in cancer genetics. One of the most frequent arm-level SCNAs is 9p loss, which contains the tumor suppressor gene (TSG) CDKN2A. It is also believed that other TSGs exist on 9p, though their identity has yet to be revealed. Methods: We analyzed every arm-level SCNA in 28 cancer types from The Cancer Genome Atlas (TCGA) to clarify the relative impact of 9p loss across cancer. We also performed a multi-tiered genomic dissection of chromosome 9p in 540 patients from 3 independent lower grade glioma (LGG) datasets (TCGA, REMBRANDT, MSKCC) to pinpoint genetic loci that are tied to tumor aggressiveness and poor survival. Focal and arm-level SCNAs were determined by GISTIC2.0. As per recently proposed criteria, 3 LGG subtypes were clustered by IDH mutation and 1p/19q deletion status. Survival analyses were performed using log-rank tests or Cox regression. Results: We found that chromosome 9p loss is one of the most frequent and prognostic arm-level events across 28 TCGA cancer types. Of these, the strongest 9p survival association was found in LGG. We performed a large-scale associations test of 376 important clinical and molecular variables and revealed that 9p loss was only associated with 6q or 9q loss, and 9p loss alone was sufficient to predict poor prognosis. On subtype-specific analysis, 9p loss predicted worse overall survival (OS) in both IDH mutant LGG subtypes but not IDH wild-type (IDHwt). To identify underlying drivers on 9p, we identified 87 genes most frequently targeted by 9p loss. Additional genetic events were rare except for homozygous deletion (HD) at 9p21.3, which contains CDKN2A. In contrast, mRNA/miRNA expression at all gene loci was much more variable and poorly correlated to copy number status. Therefore, pan-LGG and subtype-specific gene expression analyses were used to identify several drivers of tumor aggressiveness, notably KLHL9, MTAP, PLAA, and PTPRD. Although CDKN2A HD was linked to worse OS in a pan-LGG analysis, this event significantly co-occurred with the LGG IDHwt subtype, a group with GBM-like survival outcomes. Further, CDKN2A copy number status and expression did not predict worse OS in any subtype. Discussion: We characterize the nature of 9p loss in LGG, pinpoint genes involved in worse survival, and redefine the role of the tumor suppressor CDKN2A. These results provide new critical insight into long-standing questions about the nature of chromosome 9p loss and establish a framework for examining other arm-level SCNAs in cancer. Citation Format: David M. Roy, Logan A. Walsh, Alexis Desrichard, Jianjiong Gao, Promita Bose, Jason T. Huse, William Lee, Timothy A. Chan. Multidimensional genomic dissection of chromosome 9p in glioma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-169. doi:10.1158/1538-7445.AM2015-LB-169

Putative Drivers of Aggressiveness in TCEB1-mutant Renal Cell Carcinoma: An Emerging Entity with Variable Clinical Course

7507 Background: Somatic copy number alterations (SCNAs) are common and clinically important genomic events in lymphomas. For example, MYC and BCL2 amplifications are associated with adverse outcomes (Quesada, ASH 2016), while PD-L1 ( CD274) amplifications are associated with improved response to checkpoint inhibitors (Ansell, NEJM 2015). However, noninvasive detection of these events from circulating tumor DNA (ctDNA) remains difficult. Using CAPP-Seq, a targeted high-throughput sequencing platform, we developed a method to profile both focal and broad SCNAs from plasma. Methods: We profiled plasmas from a cohort of 75 pretreatment diffuse large B-cell lymphoma patients and 48 healthy controls. Focal SCNAs were evaluated at ultra-high depths (~10,000x), allowing for detection of lesions at ~1% ctDNA fraction. Thresholds were tuned to allow a false positive rate of 1%, which was empirically validated in an independent healthy cohort (n = 15), yielding a panel-wide false discovery rate of ~2.3% (0% in our genes of interest). Sequencing reads outside the targeted regions were separately pooled and analyzed to evaluate arm and chromosome level SCNAs. Results: We detected SCNAs in clinically relevant genes at the frequencies reported in literature, including amplifications in MYC (8.0%), BCL2 (24.0%), and BCL6 (14.7%) and deletions in TP53 (13.3%) and CDKN2A (9.3%). Remarkably, 26.7% of the cohort demonstrated amplification of both PD-L1 and PD-L2 ( PDCD1LG2). Furthermore, we discovered amplifications in PD-L2, but not PD-L1, in 13.3% of our patients. Interestingly, PD-L1 amplifications were more common in patients with relapsed lymphoma than in those with treatment-naïve disease (43.5% vs 19.2%, p = 0.02). Most PD-L1 amplifications were focal (65%) while the remainder typically involved > 80% of Chr9p. Corresponding tissue profiling data is in progress and will also be presented. Conclusions: Noninvasive sampling of lymphoma ctDNA enables detection of both focal and broad SCNAs, including amplifications of MYC, BCL2, and PD-L1. The ability to noninvasively profile copy number altered regions allows for biopsy-free discovery of clinically significant structural alterations in lymphoma patients.

Cancer develops through a process of somatic evolution1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes3. Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)4, we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.

Acquired copy number alterations of miRNA genes in acute myeloid leukemia are uncommon

IntroductionBrain metastases (BM) severely affect the prognosis and quality of life of patients with NSCLC. Recently, molecularly targeted agents were found to have promising activity against BM in patients with NSCLC whose primary tumors carry “druggable” mutations. Nevertheless, it remains critical to identify specific pathogenic alterations that drive NSCLC-BM and that can provide novel and more effective therapeutic targets. MethodsTo identify potentially targetable pathogenic alterations in NSCLC-BM, we profiled somatic copy number alterations (SCNAs) in 51 matched pairs of primary NSCLC and BM samples from 33 patients with lung adenocarcinoma and 18 patients with lung squamous cell carcinoma. In addition, we performed multiregion copy number profiling on 15 BM samples and whole-exome sequencing on 40 of 51 NSCLC-BM pairs. ResultsBM consistently had a higher burden of SCNAs compared with the matched primary tumors, and SCNAs were typically homogeneously distributed within BM, suggesting BM do not undergo extensive evolution once formed. By comparing focal SCNAs in matched NSCLC-BM pairs, we identified putative BM-driving alterations affecting multiple cancer genes, including several potentially targetable alterations in genes such as CDK12, DDR2, ERBB2, and NTRK1, which we validated in an independent cohort of 84 BM samples. Finally, we identified putative pathogenic alterations in multiple cancer genes, including genes involved in epigenome editing and 3D genome organization, such as EP300, CTCF, and STAG2, which we validated by targeted sequencing of an independent cohort of 115 BM samples. ConclusionsOur study represents the most comprehensive genomic characterization of NSCLC-BM available to date, paving the way to functional studies aimed at assessing the potential of the identified pathogenic alterations as clinical biomarkers and targets.

INTRODUCTION Meningiomas are the most prevalent primary intracranial tumors in adults, with clinical management traditionally guided by the World Health Organization (WHO) grading system. However, discrepancies between histological grade and clinical behavior highlight the limitations of this system. Somatic copy number alterations (SCNAs) have been implicated in meningioma pathogenesis, correlating with tumor aggressiveness and recurrence risk. Their integration into prognostic models may enhance outcomes. This study investigates the influence of SCNAs on meningioma recurrence, focusing on their patterns of mutual exclusivity and co-occurrence. METHODS We analyzed 334 primary meningiomas, noting 23 recurrences (6.9%). Clinical data, including age, sex, WHO grade, and tumor characteristics, were collected. SCNAs and mutations were derived from whole-exome sequencing of tumor and matched blood samples. We employed univariate and multivariate Cox proportional hazards regression analyses to identify SCNAs associated with recurrence, fitting the regression model with the cumulative number of SCNAs as a factor covariate. The Kaplan-Meier estimator was utilized for visualizing survival curves. RESULTS Five SCNAs were significantly associated with recurrence risk (adjusted P < 0.05): 10qLOSS, 11pLOSS, 2pLOSS, 14qLOSS, and 18qLOSS. Each SCNA independently increased recurrence risk; a single SCNA tripled this risk, while two co-occurring SCNAs increased it more than ninefold (P = 0.00003). Notably, meningiomas with four co-occurring SCNAs exhibited a greater than 22-fold increase in recurrence risk. Importantly, all identified SCNAs contributed to chromosomal instability, suggesting a synergistic effect that enhances tumor recurrence potential. CONCLUSION The accumulation and specific combinations of these five SCNAs significantly enhance the likelihood of meningioma recurrence. Although chr1pLOSS did not independently predict recurrence, it promotes chromosomal instability that facilitates the accumulation of these risk SCNAs. Our findings underscore the potential of SCNAs in predicting meningioma recurrence across all grades, contributing to improved patient management strategies.

Copy Number Alterations (CNAs) such as deletions and duplications; compose a larger percentage of genetic variations than single nucleotide polymorphisms or other structural variations in cancer genomes that undergo major chromosomal re-arrangements. It is, therefore, imperative to identify cancer-specific somatic copy number alterations (SCNAs), with respect to matched normal tissue, in order to understand their association with the disease. We have devised an accurate, sensitive, and easy-to-use tool, COPS, COpy number using Paired Samples, for detecting SCNAs. We rigorously tested the performance of COPS using short sequence simulated reads at various sizes and coverage of SCNAs, read depths, read lengths and also with real tumor:normal paired samples. We found COPS to perform better in comparison to other known SCNA detection tools for all evaluated parameters, namely, sensitivity (detection of true positives), specificity (detection of false positives) and size accuracy. COPS performed well for sequencing reads of all lengths when used with most upstream read alignment tools. Additionally, by incorporating a downstream boundary segmentation detection tool, the accuracy of SCNA boundaries was further improved. Here, we report an accurate, sensitive and easy to use tool in detecting cancer-specific SCNAs using short-read sequence data. In addition to cancer, COPS can be used for any disease as long as sequence reads from both disease and normal samples from the same individual are available. An added boundary segmentation detection module makes COPS detected SCNA boundaries more specific for the samples studied. COPS is available at ftp://115.119.160.213 with username “cops” and password “cops”.

Knowledge of 1p/19q-codeletion and IDH1/2 mutational status is necessary to interpret any investigational study of diffuse gliomas in the modern era. While DNA sequencing is the gold standard for determining IDH mutational status, genome-wide methylation arrays and gene expression profiling have been used for surrogate mutational determination. Previous studies by our group suggest that 1p/19q-codeletion and IDH mutational status can be predicted by genome-wide somatic copy number alteration (SCNA) data alone, however a rigorous model to accomplish this task has yet to be established. In this study, we used SCNA data from 786 adult diffuse gliomas in The Cancer Genome Atlas (TCGA) to develop a two-stage classification system that identifies 1p/19q-codeleted oligodendrogliomas and predicts the IDH mutational status of astrocytic tumors using a machine-learning model. Cross-validated results on TCGA SCNA data showed near perfect classification results. Furthermore, our astrocytic IDH mutation model validated well on four additional datasets (AUC = 0.97, AUC = 0.99, AUC = 0.95, AUC = 0.96) as did our 1p/19q-codeleted oligodendroglioma screen on the two datasets that contained oligodendrogliomas (MCC = 0.97, MCC = 0.97). We then retrained our system using data from these validation sets and applied our system to a cohort of REMBRANDT study subjects for whom SCNA data, but not IDH mutational status, is available. Overall, using genome-wide SCNAs, we successfully developed a system to robustly predict 1p/19q-codeletion and IDH mutational status in diffuse gliomas. This system can assign molecular subtype labels to tumor samples of retrospective diffuse glioma cohorts that lack 1p/19q-codeletion and IDH mutational status, such as the REMBRANDT study, recasting these datasets as validation cohorts for diffuse glioma research.

BackgroundImmune checkpoint inhibitors (ICIs) targeting the programmed cell death 1/programmed death-ligand 1 axis have transformed the management of advanced non-small cell lung cancer (NSCLC). However, many patients do not benefit...

Retinoblastoma is a pediatric retinal cancer that initiates in response to biallelic RB1 loss or MYCN amplification in a cone precursor cell of origin. After initial emergence, RB1-/- retinoblastomas progress to more aggressive forms by accumulation of single nucleotide variants (SNVs) and highly recurrent somatic copy number alterations including 1q+, 2p+, 6p+ and 16q- (RB SCNAs), resulting in heterogeneous mixtures of subclonal cell populations. SCNAs are enriched in highly evolved and aggressive tumor subtypes and show prognostic value in retinoblastoma liquid biopsies. However, the transcriptomic effects of retinoblastoma SCNAs are poorly understood. Single cell methods may enable comparison of tumor subclones within emerging retinoblastoma tumors and thereby provide insight into tumor progression. We retrieved single cell RNA sequencing data for 25 retinoblastoma tumors and inferred SCNAs and subclone phylogenies from scRNAseq information using a recently published tool, Numbat. We identified tumors with clonal variation in RB SCNAs and excluded samples with poor transcriptome quality or excessive additional SCNAs. We proceeded with analysis of 11 tumors with subclonal heterogeneity for an SCNA of interest, including 10 with 1q+, eight with 2p+, four with 6p+, and six with 16q-. After removal of nontumor cells, we defined cell clusters, cluster marker genes, and cell cycle phase gene signatures, and we compared cell state distributions for subclones with an acquired SCNA relative to their immediate antecedents. These analyses revealed recurrently discriminated transcriptomic clusters corresponding to six discrete cell cycle states (post-mitotic G1, G1, G1/S, S, S/G2, G2/M) and variable cell stress states, including a cluster with hypoxia and heat shock related marker gene expression in all samples. In each tumor, SCNA-defined tumor subclones had a distinct cell state distribution. Tumor subclones with acquired 1q+ were enriched in G2 states and depleted in G1 states. Subclones with 2p+ were enriched in G2 states. Subclones with 6p+ were enriched in S phase states. Subclones with 16q- were diminished in post-mitotic cell states. Tumor clones with 1q+ and 16q- were most strongly enriched for G2 phase cells. Such 1q+/16q- tumor cells were significantly differentially distributed in three tumor replicates. Tumor clones with other RB SCNAs were enriched over diploid clones in proliferating G2 cells without SCNA specific effects. To identify candidate drivers of SCNA-specific transcriptomic effects we measured RB SCNA clonal variation in gene expression within and across transcriptomic states. We identified recurrently differentially expressed in-segment genes in 1q+, 2p+, 6p+, and 16q-, as well as out-of-segment genes. Finally, we propose molecular mechanisms underlying SCNA recurrence that may enable tumor evolution in retinoblastoma. Citation Format: Kevin Stachelek, David E. Cobrinik. Transcriptomic effects of retinoblastoma progression-related somatic copy number alteration (SCNA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6941.

Introduction: There is evidence to suggest that the biology of breast cancer (BC) might vary according to age, as BCs in elderly patients might be associated with accumulation of DNA damage and BCs in younger individuals might be enriched for genetic alterations affecting cancer predisposition genes. Whether the genetic landscape of BC in elderly individuals differs is yet to be determined. Here, we sought to describe the spectrum of somatic genetic alterations and mutational signatures in BC according to age. Materials and Methods: We conducted a re-analysis of two cohorts of BC: i) MSK-IMPACT targeted sequencing cohort (primary, n=918; metastatic, n=1,000) and ii) whole-exome sequencing data of primary BCs from The Cancer Genome Atlas (TCGA) BC study (n=1087). BCs of younger (<65 years old) and elderly individuals (≥ 65 years old) were compared, matched by estrogen receptor (ER)/HER2 status at a 2:1 ratio (MSK-IMPACT) or a 1:1 ratio (TCGA). Somatic single nucleotide variants and copy number alterations (CNAs) were determined using a validated bioinformatics pipeline, and mutational signatures were defined using DeconstructSigs and SigMA. Two-tailed Fisher’s exact test was performed. Results: Primary BCs in elderly and younger patients, matched by ER/HER2 status, from the MSK-IMPACT (n=220 and n=440) and TCGA (n=290, each) cohorts, and metastatic BCs from elderly (n=98) and younger (n=196) patients from the MSK-IMPACT cohort, matched by ER/HER2 status, were compared. In both cohorts of primary BCs, PIK3CA, TP53 and CDH1 were the most frequently mutated genes. Compared to younger patients, primary BCs in elderly patients from the MSK-IMPACT cohort displayed a lower frequency of mutations in TP53 (23% vs 34%, P<0.01), AKT1 (2% vs 6%, P<0.05) and MAP2K4 (0.4% vs 4%, P<0.01). In the TCGA cohort, somatic mutations in AKT1 were found to be less frequent in elderly than in younger patients (1% vs 5%, P<0.05), whereas NF1 (2% vs 6%, P<0.05) mutations were more frequent in elderly than in younger patients with primary BCs. Our analyses of BC metastases subjected to MSK-IMPACT revealed that elderly patients harbored a higher frequency of mutations in NCOR1 (11% vs 4%, P<0.05) and RUNX1 (9% vs 2%, P<0.05) than younger patients. The frequency of bi-allelic inactivation of homologous recombination DNA repair deficiency (HRD) genes (i.e. BRCA1, BRCA2, PALB2, RAD51C and RAD51D) in primary BCs of elderly and younger individuals in the TCGA cohort was 2% and 5%, respectively. No differences in the frequency of CNAs were observed between the two groups. The most frequent mutational signatures found in primary BCs of elderly and younger patients were aging, APOBEC and HRD in the MSK-IMPACT cohort, and aging, APOBEC and HRD in primary BCs of the TCGA cohort, with APOBEC being enriched in younger patients compared to elderly patients. The most frequent mutational signatures in metastatic BCs in elderly and younger individuals of the MSK-IMPACT cohort were APOBEC followed by aging and HRD. Conclusion: Our findings show that BCs in elderly patients harbor a lower frequency of somatic mutations in TP53, AKT1 and MAP2K4 than younger individuals. In contrast, BCs in elderly patients more frequently harbor somatic mutations in the transcription factors RUNX1 and NCOR1. Bi-allelic alterations affecting HRD-related genes was numerically more frequent in younger than in older patients. As expected, BCs in elderly patients show a numerically higher incidence of the aging signature, whereas primary BCs affecting younger patients displayed a higher frequency of the APOBEC signature than primary BCs from elderly individuals. Citation Format: Pier Selenica, Fresia Pareja, Audree Tadros, Lorenzo Ferrando, David N Brown, Hong Zhang, Pedram Razavi, Diana Mandelker, Mark E Robson, Sarat Chandarlapaty, Britta Weigelt, Jorge S Reis-Filho. Genomic landscape of breast cancer occurring in elderly individuals [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-08.