Pan-Cancer Analysis Of Whole Genomes Research Articles

Abstract GS03-09: Characterization and proposed therapeutic exploitation of fusion RNAs in metastatic breast cancers

Abstract BACKGROUND: Large-scale genomic studies such as The Cancer Genome Atlas (TCGA) and Pan-Cancer Analysis of Whole Genomes (PCAWG) show that the breast cancer (BrCa) genome is dominated by structural variation (SV) rather than single base pair mutations, producing a fertile environment for gene fusions. In this study, we implement a rigorous, expression-based approach to create a comprehensive landscape of fusion RNAs in metastatic breast cancer (MBC). We find fusion RNAs—many of which are novel involving known oncogenes—are surprisingly common in the advanced setting and credential their use as base-editing therapeutic targets. METHODS: Two retrospective cohorts of MBC RNA-sequencing data were analyzed— Dana-Farber Cancer Institute CCPM (n = 252 cases, 276 specimens), MichiganCSER (n = 171 cases, 190 specimens)—with a Fusion MetaCaller that integrates 5 unsupervised fusion-finding algorithms. Fusion RNAs identified in at least 2 callers (High-Confidence) and absent in RNA-seq from normal tissue (Cancer-Specific) were classified as HCCS-Fusions. Further removal of common artifactual fusions was performed using public databases. Expression of each HCCS-Fusion was quantified using a supervised method (FusionInspector)—expressed HCCS-Fusions were defined as having a Fusion Fragment Per Million (FFPM) value > 0.1 and at least 10% of read counts mapping to the fusion breakpoint versus the flanking 5’ or 3’ partners’ exons. Normalized gene-level expression abundances were calculated to correlate transcriptomic features (gene expression, PAM50) with fusion RNAs. Recurrent, potentially pathogenic fusion RNAs were annotated using OncoKB and outlier expressed fusions (Q3 FFPM + [1.5 X IQR]) were interrogated. RESULTS: The frequency of HCCS-Fusions differed between subtypes with basal BrCa harboring the most per tumor followed by Her2, LumB and LumA—with a median HCCS-Fusion count of 13, 12, 7, 4 respectively. 64.5% of cases harbored a HCCS-Fusion in an OncoKB cancer-related gene. The most recurrent fusions involving a cancer-related gene were 5’ ESR1 fusions (14 cases)—all with in-frame breakpoints near exon6/7, disrupting ESR1’s ligand binding domain. 13 of 14 ESR1 fusions were called in Luminal B (LumB) metastases (Fisher’s exact enrichment p < 0.005 vs other subtypes)—defining an ESR1 fusion frequency of 6.5% in LumB disease. Beyond ESR1, we identify recurrent, low-frequency (2-4 cases) in-frame kinase fusions involving FGFR2, ADK, TLK2, PRKCA, BRAF, CHKA, CSNK1D, NEK11, TNIK—some potentially targetable with FDA-approved small molecule inhibitors—as well as recurrent, predicted loss-of-function fusion RNAs in NF1, MSI2, USP32, PTEN, and CDH1. Lastly, 33.6% of cases harbored at least one outlier expressed fusion RNA; including highly expressed in-frame fusions involving known BrCa mediators such as ERBB2, BRCA1, ARID1B, RPS6KB1/2, PIK3R3, AXIN1, TGFB1/2, FOXP1, PAK1, and CREBBP. CONCLUSIONS: Taken together, these results demonstrate that fusion RNAs in MBC—some recurrent, many highly expressed and unique to individual tumors—are common. We create the most comprehensive catalog of ESR1 fusions in MBC, better define their frequency, discover their enrichment in LumB-like tumors, and will discuss clinicopathologic and transcriptomic features associated with ESR1 fusion positive disease. We identify druggable fusions that would likely be missed by current testing standards, find recurrent loss-of-function fusion RNAs, and show that over one-third of metastatic cases harbor at least one outlier expressed fusion—many of which involve BrCa-related genes. In summary, we propose that fusion RNAs are a driving and perhaps overlooked mechanism of tumor evolution in therapy-resistant disease and postulate fusion transcripts present a compelling therapeutic opportunity in MBC. Preliminary data targeting fusion RNA breakpoints using a novel RNA base-editing approach will be discussed. Citation Format: Nolan Priedigkeit, Alinés Lebrón-Torres, Janny Liao, Jean-Baptiste Alberge, Stefania Morganti, Jakob Weiss, Jorge Gomez Tejeda Zanudo, Albert Grinshpun, Melissa Hughes, Karla Helvie, Kerry Sendrick, Kyleen Nguyen, Sarah Strauss, Janet Files, Maxwell Lloyd, Nikhil Wagle, Chip Stewart, Eric Winer, Bruce Johnson, Yvonne Li, Rinath Jeselsohn, Sara Tolaney, Daniel Abravanel, Nancy Lin, Heather Parsons, Gad Getz, Steffi Oesterreich, Adrian Lee, Todd Golub. Characterization and proposed therapeutic exploitation of fusion RNAs in metastatic breast cancers [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr GS03-09.

Abstract 5675: An intronic SINE-VNTR-Alu element insertion in CASP8 alters gene expression and confers resistance to induction of cell death in gastrointestinal cancer

Abstract Transposable elements are a major source of variation in the human genome. SINE-VNTR-Alus (SVAs), the hominid-specific and youngest active retrotransposon family, are highly polymorphic within the human germline and can contribute to disease risk and progression. In fact, polymorphic SVAs have previously been linked to several human diseases, including rare cases of hereditary cancer syndromes such as neurofibromatosis type I and Lynch syndrome. These examples illustrate that the mobility of SVAs in the genome can significantly impact gene function. Here, we sought to evaluate the potential of SVAs inserting into known tumor suppressors and oncogenes. To this end, we surveyed genomic data from Pan-Cancer Analysis of Whole Genomes (PCAWG) and identified 1956 unique germline SVA insertions in the introns of 1933 genes. Among these, we discovered a highly prevalent polymorphic SVA_E (subfamily) in an intronic region of CASP8. Given caspase-8’s canonical role in apoptosis, we hypothesized that this SVA may impact both caspase-8 expression as well as cell death in cancer. We first created a panel of colon and gastric cancer cell lines genotyped by PCR for the presence or absence of the CASP8-SVA (SVA+/+: RKO, NCI-N87, HT29, NCI-H747, OCUM-1; SVA-/-: HCT116, LoVo, SNU-407, 23132/87, KM12). RT-qPCR analysis showed significantly higher CASP8 expression in SVA+/+ cell lines, which was concordant with caspase-8 protein expression by immunoblot. Treatment of these cell lines with cytotoxic chemotherapy (FOLFOXIRI) in vitro demonstrated increased resistance to cell death in SVA+/+ cell lines. Direct induction of caspase-8-mediated apoptosis via TRAIL (TNF-related apoptosis-inducing ligand) revealed decreased TRAIL-mediated cell death in SVA+/+ cell lines; interestingly, caspase-8 enzymatic activity was also decreased in SVA+/+ cell lines upon TRAIL stimulation despite increased pro-caspase-8 expression. To further isolate the effects of the CASP8-SVA, we generated an isogenic cell line (RKO CASP8-SVA knockout) model via CRISPR-Cas9. Deletion of the CASP8-SVA redemonstrated decreased CASP8 expression at the mRNA and protein levels. Treatment with FOLFOXIRI in the CASP8-SVA KO cell line exhibited increased sensitivity compared to empty vector control. In summary, our findings indicate that an intronic SVA insertion in CASP8 increases gene and protein expression but decreases canonical caspase-8 activity, which was associated with increased resistance to FOLFIRINOX or TRAIL induced cell death. Additional interrogation of SVA-induced effects on transcriptional regulation (e.g., epigenetic effects) as well as non-canonical functions of caspase-8 (e.g., activation of NF-κB) is ongoing. To our knowledge this is the first report describing the mechanistic effects of a germline SVA insertion in the context of cancer and therapeutic resistance. Citation Format: Eric W. Lin, Joshua R. Kocher, Chong Chu, Peter J. Park, David T. Ting. An intronic SINE-VNTR-Alu element insertion in CASP8 alters gene expression and confers resistance to induction of cell death in gastrointestinal cancer [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 5675.

Abstract 6054: UPPGRADER: a bioinformatics-based novel E3 ligase discovery platform

Abstract In Target Protein Degradation (TPD) field, conventional E3 ligases utilized in the clinic are limited to CRBN and VHL, which opens the need for exploration of novel E3 ligases for the advancement of TPD. To address this, we have developed a proprietary platform, UPPGRADER, for systematic discovery of novel E3 ligases based on -omics data including single cell RNA sequencing (scRNA-seq) and whole genome sequencing (WGS), in conjunction with proteomics data and bioinformatics tools.UPPGRADER enables systematic analyses on alterations occurred in all genomic areas including E3 ligase genes and potential target genes. For example, analyzing Pan-Cancer Analysis of Whole Genomes (PCAWG) data identified amino acid changes into Cysteine or Lysine, which can be targeted by covalent binders with cancer specificity. Through such analysis, we discovered several novel E3 ligases, including but not limited to FBXW7, with the categorization of the findings based on specific cancer types.At the single cell expression level, UPPGRADER provides the capability to assess gene expression levels of E3 ligases and target proteins by proprietary measurements based on gene detection rate. This system also allows assessment of E3 ligase-Target gene co-expression per single cell. In colorectal cancer, UPPGRADER has shown that the co-expression of E3 ligase FBXW7 and well-known colorectal cancer target (KRAS) increases from 1% (4 out of 334) in normal epithelial cells to 17% (2,967 out of 17,458) in cancerous epithelial cells, highlighting a significant change in their simultaneous expression patterns during cancer progression.UPPGRADER also identified E3 ligase X which showed high co-expression level with KRAS gene alongside universal expression properties and high cancer cell dependencies. For E3 ligase X, we developed novel small molecule binders (nM binding affinity) with bioavailability > 20% in animal pharmacokinetics. Bifunctional degraders utilizing these binders displayed BRD4 degradation in more than 20 cell lines with double to triple digit nM DC50 and DC90 values. Other targets (AURKA, CRBN and others) were potently degraded with anticipated mechanism of action (assessed by E3 ligase KO cell line and proteasomal inhibitors).To conclude, UPPGRADER is a comprehensive bioinformatics tool for discovering novel E3 ligases with biological validations. Through recent explosion of scRNA-seq and WGS datasets in different diseases and mechanism-based identification of additional molecular targets, UPPGRADER is poised to advance the field of TPD. Citation Format: Kyungsik Ha, Woojeung Song, Woochang Choi, Gi Bbeum Lee, Soohee Ryu, Jun Kyu Lee, Hwajin Lee. UPPGRADER: a bioinformatics-based novel E3 ligase discovery platform [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 6054.

Abstract 1756: Characterizing the mutational spectrum of metastatic mucinous adenocarcinoma of the appendix

Abstract Background: Appendiceal cancer (AC) is an orphan malignancy with only 1-2 cases per 100,000 people in the US. The genomic composition of metastatic, mucinous AC is yet to be resolved at the whole exome level and few groups have assessed the clinical actionability of target genes. Here we performed whole-exome sequencing (WES) on AC specimens to 1) elucidate the mutational spectrum of AC, 2) identify recurrent mutations at frequencies unique to AC or in common with colorectal cancer (CRC), and 3) uncover recurrent AC mutations that are associated with patient survival outcomes. Methodology: Twenty-four FFPE samples, one from each of 24 AC patients treated at our institution with cytoreductive surgery (CRS) followed by heated intraperitoneal chemotherapy (HIPEC), were collected from our tumor bank with IRB approval. DNA from tumor and corresponding normal tissue (PBMCs) was extracted, assessed for integrity and quantity, then analyzed by WES using the Illumina NextSeq 6000 platform. The resulting data were processed using both GATK and DRAGEN pipelines. The frequencies of recurrent mutations in AC were compared with those of CRC from cBioPortal and statistically compared by Fisher’s Exact Test. Logrank test was performed to estimate survival associations based off mutation status. Mutational signatures derived from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium were cross-compared to our cohort to identify previously unknown mutational processes in AC. Results: The most frequent mutations were found in MUC6 (63%), KRAS (58%), HLA-B (54%), PABPC1 (50%), and MUC5AC (50%). Distinct from a 534-patient CRC cohort, AC had lower rates of alteration in APC (4% vs 73% CRC, p<0.001) and TP53 (21% vs. 62%, p<0.001), with higher rates of alteration in HLA-B (54% vs 3%, p<0.001), GNAS (38% vs 5%, p<0.001), and ABCA1 (29% vs 7%, p=0.001). Notably, ABCA1 mutation frequency was higher in mucinous CRC (n=56) when compared to non-mucinous CRC (n=478, 20% vs 7%; p<0.001), suggesting that ABCA1 may be uniquely altered in bowel cancers of mucinous phenotype. Alterations in Rho-A were a statistically significant predictor of poor survival in both AC (p<0.001) and CRC (p=0.05). PCAWG analysis showed that the predominant mutational signature in AC most resembles SBS5, suggesting that the mutational etiology of AC may be linked to age and/or smoking status. Discussion: Here we present the largest whole-exome sequencing analysis of AC analyzed to date and identify previously undescribed recurrently mutated genes unique to AC as compared to CRC. We demonstrate novel associations between altered genes and patient survival, which opens discussion regarding the clinical utility of molecular markers in AC for assisting treatment decision making. Citation Format: Daniel J. Gironda, Ming Leung, Guangxu Jin, Liang Liu, Konstantinos I. Votanopoulos, Edward A. Levine, Lance D. Miller. Characterizing the mutational spectrum of metastatic mucinous adenocarcinoma of the appendix [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 1756.

Abstract 988: Genome-wide repeat landscapes in cancer and cell-free DNA

Abstract Introduction: Repeat sequences comprise >50% of the human genome and structural and epigenetic changes in these regions are implicated in cancer. However, no systematic analysis of the compendium of repeat sequences has ever been performed in human cancer or cell-free DNA (cfDNA), largely due to the inability to identify and quantify repeat sequences genome-wide. We describe here the first comprehensive analysis of genome-wide repeat landscapes in cancer and demonstrate their utility in cfDNA liquid biopsies. Methods: We developed ARTEMIS (Analysis of RepeaT EleMents in dISease) an alignment-free, genome-wide approach for analyzing repeat landscapes in short read sequencing. This approach uses a de novo search of short sequences (kmers) in the telomere to telomere (chm13) reference genome to identify 1.2 billion 24-mers uniquely defining 1280 individual repeat types occurring genome-wide across 57 subfamilies and 6 families. We analyzed ARTEMIS kmers in whole genome sequences of 525 matched tumor/normal pairs from breast, colorectal, liver, lung, ovarian, cervical, prostate, thyroid, head and neck, gastric, and bladder cancers in the Pan Cancer Analysis of Whole Genomes (PCAWG), and in low coverage (1-2x) whole genome sequences of 1450 cfDNA samples from individuals with and without 8 types of cancer. Results: Analysis of ARTEMIS kmer repeat landscapes in 525 PCAWG tumors identified changes in all 1280 repeat element types, including 820 novel elements not previously known to be altered in cancer. A median of 807 repeat elements (range 246-1280) were altered in each tumor compared to its matched normal. The majority of changes were in repeat elements not previously described as altered in tumorigenesis and were most frequently found within Satellites, LINEs and SINEs, though changes were also observed in LTRs, Transposable Elements, and RNA Elements. A cross-validated cfDNA model using repeat landscapes (ARTEMIS) and fragmentation features (DELFI) detected individuals in a diagnostic cohort (n=287) across all stages of lung cancer with high performance (AUC 0.91, 95% CI 0.88-0.95) and was externally validated in a separate population (n=513). The locked model generated scores that correlated with circulating tumor mutant allele fractions for patients (n=19) undergoing targeted lung cancer therapy (r=0.80, p<2.2e-16), and stratified progression-free survival (p<0.001). ARTEMIS repeat landscape analyses of cfDNA also detected liver cancer in a high-risk cohort (n=208) of individuals with cirrhosis or viral hepatitis (AUC 0.91, 95% CI 0.87-0.95), and identified tissue of origin among seven tumor types (n=423). Conclusions: ARTEMIS reveals genome-wide repeat landscapes in human cancer, including in 820 novel elements not previously known to be altered in tumorigenesis. These repeat landscapes that can now be described are evaluable in the circulation and provide an avenue for noninvasive detection and characterization of cancer. Citation Format: Akshaya Annapragada, Noushin Niknafs, James R. White, Daniel C. Bruhm, Christopher Cherry, Jamie E. Medina, Vilmos Adleff, Carolyn Hruban, Dimitrios Mathios, Zachariah H. Foda, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu. Genome-wide repeat landscapes in cancer and cell-free DNA [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 988.

Incorporating mutational heterogeneity to identify genes that are enriched for synonymous mutations in cancer

BackgroundSynonymous mutations, which change the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations might be enriched in cancer has been explored in several recent studies. However, none of these studies control for all three types of mutational heterogeneity (patient, histology, and gene) that are known to affect the accurate identification of non-synonymous cancer-associated genes. Our goal is to adopt the current standard for non-synonymous mutations in an investigation of synonymous mutations.ResultsHere, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify cancer-associated genes that are enriched for synonymous mutations based on a non-coding background model that takes into account the mutational heterogeneity across these levels. Using MutSigCVsyn, we first analyzed 2572 cancer whole-genome samples from the Pan-cancer Analysis of Whole Genomes (PCAWG) to identify non-synonymous cancer drivers as a quality control. Indicative of the algorithm accuracy we find that 58.6% of these candidate genes were also found in Cancer Census Gene (CGC) list, and 66.2% were found within the PCAWG cancer driver list. We then applied it to identify 30 putative cancer-associated genes that are enriched for synonymous mutations within the same samples. One of the promising gene candidates is the B cell lymphoma 2 (BCL-2) gene. BCL-2 regulates apoptosis by antagonizing the action of proapoptotic BCL-2 family member proteins. The synonymous mutations in BCL2 are enriched in its anti-apoptotic domain and likely play a role in cancer cell proliferation.ConclusionOur study introduces MutSigCVsyn, an algorithm that accounts for mutational heterogeneity at patient, histology, and gene levels, to identify cancer-associated genes that are enriched for synonymous mutations using whole genome sequencing data. We identified 30 putative candidate genes that will benefit from future experimental studies on the role of synonymous mutations in cancer biology.

Abstract PO-026: Intra-tumor heterogeneity of HPV integration and its association with focal genomic instability in oropharyngeal cancer

Abstract Human papillomavirus (HPV) integration has been considered as one of the driver factors for cancer progression, but its pattern and role in carcinogenesis is still unclear. Whole genome sequencing data of 14 Japanese HPV16+ OPSCC and 13 HPV+ OPSCC from Pan-Cancer Analysis of Whole Genomes were used to identify integrations and somatic mutations. The phylogenetic analysis of HPV16 revealed that in tumors of 14 Japanese subjects, the A4 variant was the most common (8/14, 57.1%), followed by the A5 variant (2/14, 14.3%), which is considered unique to HPV16 in East and Southeast Asian, and the A2/A3/D2/D3 variants (1/14, 7.1%), showing a significant difference from the distribution of the HPV16 sublineages in Europe and the United States, where the A1 variant accounts for half. A total of 250 integration breakpoints (BPs) in 20 of the 27 tumors (74.1%) were detected. We estimated the cancer cell fraction of integration BPs and found that HPV integration also shows intra-tumor heterogeneity, indicating that nearly half of the integration events occurred after carcinogenesis. Clonal BPs were more likely to occur in the E1 (P = 0.036), confirming that the disruption of the E1 gene may result in abnormal negative regulation of the E6/E7 oncogenes and promote OPSCC carcinogenesis. Subclonal BPs were less likely to occur in the E6 (P = 0.045), suggesting that the E6 may also play an important role in the process of cancer evolution after carcinogenesis. Four states of the HPV genome were identified: (1) episomal-only (7/27, 25.9%), (2) integrated-only (4/27, 14.8%), (3) clonally-mixed (episomal + clonally integrated) (11/27, 40.7%), and (4) subclonally-mixed (episomal + subclonally integrated) (5/27, 18.5%). Since nearly half of these cancers have developed with just episomal copies of HPV, integration itself is not essential for carcinogenesis and can occur during and after carcinogenesis. Interestingly, the E6/E7 were conserved in all four cancers with integrated-only HPV, while the E2 and E1 were disrupted or deleted. This confirms that the constitutive expression of E6/E7 is essential for the carcinogenesis of HPV+ OPSCC. These results suggest that some integrations may be drivers of carcinogenesis with disruption of E1/E2, as in these four cancers, and others may arise randomly due to genomic instability, as in the cancers with the E6/E7 deleted integrants. The number of BPs of structural variations (SVs) occurred in the overlapping 100 kb regions flanking integration BPs (ITG regions) was positively correlated with the number of integration BPs (Spearman’s rank correlation ρ = 0.78; Permutation test P = 9.9 × 10−5). The genomic instability that causes clonal integrations during carcinogenesis is considered to cause clonal SVs, mainly large duplications, and subclonal integrations and SVs such as large deletions. Clonal SVs, mainly large duplications, were also observed in the regions where only subclonal integrations occurred, suggesting that large duplications occur before integrations. Citation Format: Noah Sasa, Hirotaka Eguchi, Hidenori Tanaka, Takahito Fukusumi, Motoyuki Suzuki, Yukinori Takenaka, Yukinori Okada, Hidenori Inohara. Intra-tumor heterogeneity of HPV integration and its association with focal genomic instability in oropharyngeal cancer [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-026.

Single-molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

Pan-cancer analysis of whole-genome doubling and its association with patient prognosis

BackgroundWhole-genome doubling (WGD) is a common mutation in cancer. Various studies have suggested that WGD is associated with a poor prognosis in cancer. However, the detailed association between WGD occurrence and prognosis remains unclear. In this study, we aimed to elucidate the mechanism by which WGD affects prognosis using sequencing data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) and The Cancer Genome Atlas.MethodsWhole-genome sequencing data of 23 cancer types were downloaded from PCAWG project. We defined the WGD event in each sample using the WGD status annotated using PCAWG. We used MutationTimeR to predict the relative timings of mutations and loss of heterozygosity (LOH) in WGD, thus evaluating their association with WGD. We also analyzed the association between WGD-associated factors and patient prognosis.ResultsWGD was associated with several factors, e.g., length of LOH regions. Survival analysis using WGD-associated factors revealed that longer LOH regions and LOH in chr17 were associated with poor prognosis in samples with WGD (WGD samples) and samples without WGD (nWGD samples). In addition to these two factors, nWGD samples showed that the number of mutations in tumor suppressor genes was associated with prognosis. Moreover, we explored the genes associated with prognosis in both samples separately.ConclusionThe prognosis-related factors in WGD samples differed significantly compared with those in nWGD samples. This study emphasizes the need for different treatment strategies for WGD and nWGD samples.

Abstract 6560: Identification of distinct patterns in diffuse large B-cell lymphoma through alternative splicing analysis

Abstract Background Aberrant splicing in cancer cells contributes to cellular proliferation, escape from cell death, growth inhibition, invasion and metastasis, and immune escape. Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, but the effect of AS on its pathogenesis has not been fully elucidated, so it is essential to find out DLBCL-specific splicing patterns and their potential as treatment targets. Material and Method RNA-Seq dataset from DLBCL patients was retrieved from The Cancer Genome Atlas (TCGA) DLBCL (N=48) and Pan-cancer Analysis of Whole Genomes (PCAWG) DLBC (N=7) were used as the cancer group. In order to identify spliced genes that are significantly different from normal tissue, RNA-Seq data of normal lymphoid tissue produced in two studies of E-MTAB-513 (N=1) and E-MTAB-1733 (N=13) from the BioStudies were downloaded. Sequence reads were aligned to the GRCh38 reference genome using STAR aligner. Results 5,470 genes identified as differentially spliced compared to normal in both rMATS and MAJIQ tools were studied. After sorting the AS events of these genes in order of highest average PSI value, events with an average PSI value of 0.7 or more in the top 2/3 samples and events with an average PSI value of 0.3 or less in the bottom 2/3 samples are selected. 8 exons of 7 genes were involved in Exon skipping (ES) events, 6 exons of 5 genes were involved in mutually exclusive exon (MXE) events, and an exon of a gene was involved in alternative 5' splice site (A5SS) Among these genes, exons 6 and 7 in CD53 showed high PSI values between exons 4 and 9. The average PSI values for exons 6 and 7 of CD53 in DLBCL were 0.923855 and 0.89096, respectively, which were significantly higher than the Normal group (p<0.05). CD53 mediates IL-7R signaling and plays a role in the regulation of normal B-cell development. As a gene coding for cell surface protein, it is involved in various immune systems in T-cell and B-cell surfaces. In healthy tissue, transcripts that skip exon 5 and have a junction between exon 4 and exon 6 or 7 are not yet known and should be further studied. In addition, SLAMF8, which has an exon with a PSI value specific to DLBCL, is also involved lymphocyte activation and regulates B-cell receptor signaling. Conclusion These DLBCL-specific patterns of selective exon usage are expected to be potential targets for cancer immunotherapy. Citation Format: Sanyeowool An, Youngil Koh, Sung-Soo Yoon. Identification of distinct patterns in diffuse large B-cell lymphoma through alternative splicing analysis [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 6560.

Abstract 2041: Research strategies for rare germline variants and cancer study

Abstract Exploration of rare germline variants in cancer is the fields of ongoing research. So, we would like to suggest several considerations for the rare pathogenic germline variants studies. We confirmed the pathogenicity of each variant using ClinVar (https://www.ncbi.nlm.nih.gov/clinvar). In addition, we utilized in silico prediction tools such as Polyphen and SIFT. Even for the same variant, the report of the variant may vary depending on the database used. We conducted rare germline variants screening using ICGC (International Cancer Genome Consortium) PCAWG (Pan-Cancer Analysis of Whole Genomes) data. we filtered allele frequencies using the gnomAD (v2.1.1) exome database. We utilized several ClinVar versions to check the clinical significance of germline variants. Next, we have investigated some in silico tools that predict ClinVar pathogenic and benign variants well. We observed inconsistent variant reports across versions of ClinVar. Although the information on variants may change over time, there have been inconsistent changes in the clinical significance of variants reported as P (Pathogenic) or LP (Likely pathogenic). The clinical significance of the variants reported in the previous version was P or LP, but those in the updated version were changed to “Conflicting interpretations of pathogenicity”. It was confirmed that the variant report changes when at least one “Uncertain Significance” review is added. Among various prediction tools, we found that the predictive power of a tool called “MetaRNN” was useful. Compared with several tools, we confirmed that MetaRNN’s AUC (Area Under the ROC Curve) value was 0.985, which is the best performance. But, it is not enough to judge the pathogenicity of a variant only by the prediction result of the tool. And, prediction tools are also known to be more efficient in predicting missense variants than others. Therefore, it is necessary to examine the pathogenicity of germline variants using both the prediction tool and the clinical significance of ClinVar. In summary, for rare germline variants in cancer studies, it is necessary to observe variants compared to the previous versions of ClinVar. Moreover, if prediction tools are appropriately used, researchers will increase the possibility of finding a variant or gene with more crucial clinical significance to reveal the association between the rare germline variants and cancer development. Citation Format: Seokhyeon Kim, Youngil Koh, Sung-Soo Yoon. Research strategies for rare germline variants and cancer study [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 2041.

Abstract 2149: A whole genome sequencing classifier of homologous recombination deficiency

Abstract Homologous recombination deficiency (HRd) is a DNA repair defect prevalent in but not exclusive to breast and ovarian cancer most commonly associated with BRCA1 or BRCA2 alterations. HRd results in accumulation of small and large scale genetic alterations across the genome, including allele specific copy number alterations (aCNAs), small nucleotide variants (SNVs), deletions, and structural variants (SVs). Detection of HRd in tumors predicts response to genotoxic drugs such as PARP inhibitors and platinum. Genome wide aCNAs such as large state transitions (LST), loss of heterozygosity (LOH), and telomeric allelic imbalances (TAI) in conjunction with BRCA1/2 mutation detection have been implemented in routine diagnostic testing to identify HRd in tumors. However, these features represent a subset of the genetic signatures predictive of HRd, and we hypothesize that a significant portion of tumors with HRd are missed using these existing assays. Whole genome sequencing (WGS) enables the detection of the full spectrum of genetic lesions that arise in an HRd tumor in a single assay. To demonstrate the added value of WGS to identify HRd, we trained and validated a pan-cancer classifier of HRd. A tumor/normal matched cohort of 321 cancer patients sequenced by WGS was assembled and analyzed as part of a retrospective study, representing 62 tumor types. An unbiased analysis of HRd associated SV signatures revealed the top quartile of samples harboring tandem duplications (Dups) and deletions (Dels) in the size range of 1-10kbp were enriched with BRCA1, BRCA2, and RAD51C/D alterations. Through curating Dels, Dups, HRd SNV/InDel signatures, and alteration of HRd associated genes, 37 unique patients were found to have high confidence HRd, out of which 13% had no alterations in BRCA1, BRCA2, or other HRd genes. We then trained a random forest classifier to identify HRd tumors. The most important predictive features were WGS-specific, namely small deletions with microhomology, SV Dels, and SV Dups. The HRd classifier was validated using an independent cohort of 556 samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG) study. Of 46 samples with biallelic BRCA1/2 alterations, the classifier achieved high areas under receiver-operator characteristic (AUROC, 0.99) and precision recall curves (AUPRC, 0.96). The aCNA score, the number of segments harboring LST, LOH, and TAI, had similar AUROC (0.96) but lower AUPRC (0.87). There were 11 BRCA1/2 non-altered cases predicted to be HRd with the classifier which were not identified by CNA scores, in which 10 had at least 1 alteration in an HRd gene, including RAD51C, CHEK2 biallelic alterations and SVs in PALB2, Fanconi pathway genes, and ATM/ATR. We conclude that a classifier incorporating the additional mutational features which can only be detected using WGS can achieve superior precision in identifying HRd tumors and, in the future, uncover additional patients for therapeutic options. Citation Format: Kevin Hadi, Gunes Gundem, Max F. Levine, Aditya Deshpande, Minal Patel, Stan Skzrypczak, Majd Al Assaad, Juan Miguel Mosquera, Olivier Elemento, Andrew L. Kung, Juan S. Medina-Martínez, Elli Papaemmanuil. A whole genome sequencing classifier of homologous recombination deficiency [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 2149.

Abstract 4272: Pan-cancer analysis of intra-tumor heterogeneity in 9,116 cancers using a novel regularized likelihood model

Abstract Subpopulations of tumor cells characterized by mutation profiles may confer differential fitness and consequently influence the prognosis of cancers. Understanding subclonal architecture has the potential to provide biological insight in tumor evolution and advance cancer precision treatment. Recent subclonal reconstruction methods require heavy computational resources, prior knowledge of the number of subclones, and extensive postprocessing. These drawbacks can be addressed by using a regularized likelihood modeling approach, which is novel to the field. Therefore, we propose a model-based method, Clonal structure identification through pair-wise Penalization, or CliP, to address these drawbacks. To evaluate the performance of CliP against other methods, we generated a benchmark dataset of 4,050 simulated samples with varied tumor purity, read depth, copy number alteration rate, and true numbers of clusters. Our results suggest that CliP outperforms popular methods such as PhyloWGS in accuracy and shows similar robustness in most scenarios. We further compared CliP performance against 10 other subclonal reconstruction methods to the consensus subclonal reconstruction results on whole-genome sequencing (WGS) data from the Pan-Cancer Analysis of Whole Genomes (PCAWG, n = 1,993). Our result shows that of all 11 methods, CliP achieves the highest correlation with the consensus calls. In terms of speed, CliP can finish running a sample with 5,000 SNVs within one minute, which is ~1,000 times faster than MCMC-based algorithms. Next, we profiled the subclonal structures of 7,711 patient samples with well-annotated clinical outcomes from The Cancer Genome Atlas (TCGA) across 32 cancer types applying CliP to the whole-exome sequencing (WES) data. This is the largest and most complete pan-cancer characterization of intratumor heterogeneity (ITH) through the lens of subclonal reconstruction. We further used CliP outputs to address a commonly asked question on which sequencing platform to use for cancer evolution studies: the cost-effect WES data at higher read depth versus the more comprehensive WGS data at lower read depth. There were a total of 588 tumor samples from 21 cancer types, for which both PCAWG and TCGA have profiled using the WGS and WES platform, respectively. Using both datasets to compare results from these samples as benchmark, we observed that for most cancer types, subclonal reconstruction from WES is as informative as that from the matched WGS data. In summary, our study represents a significant methodological advancement in subclonal reconstruction and highlights the importance of measuring tumor subclone structure. Citation Format: Yujie Jiang, Kaixian Yu, Matthew D. Montierth, Shuangxi Ji, Seung Jun Shin, Shuai Guo, Shaolong Cao, Yuxin Tang, Scott Kopetz, Pavlos Msaouel, Jennifer R. Wang, Marek Kimmel, Peter Van Loo, Hongtu Zhu, Wenyi Wang. Pan-cancer analysis of intra-tumor heterogeneity in 9,116 cancers using a novel regularized likelihood model. [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 4272.

Abstract PR008: Timing complex copy number gains in whole genome duplicated tumors

Abstract The accumulation of genetic copy number aberrations is a process common to the development of many cancers. Tumors that have undergone a whole genome duplication (WGD) are known to have high degrees of genomic instability and often contain genomic regions that have undergone a series of copy number gains resulting in multiple copies of both alleles. Metastases are known to have an even greater rate of WGDs and general genomic instability. WGDs provide a powerful handle to time genetic events, such as single nucleotide variants or copy-number aberrations, in tumor evolution. However, the relative timing of copy number gains in whole genome duplicated tumors is complicated by the fact that there are multiple plausible route histories that could give rise to them. Typically, the most parsimonious event history is assumed to take place but this has never been validated. Here we describe a method, GRITIC, that overcomes this problem by evaluating all possible histories that could result in a given copy number state and determining the timing of the most likely series of gains. GRITIC allows the gains leading to any copy number state to be inferred. On a representative simulated cohort, it accurately measures the timing of complex copy number gains. By applying GRITIC to 6,010 primary and metastatic tumor samples from the Pan-Cancer Analysis of Whole Genomes and Hartwig Medical Foundation datasets, we find that the principle of maximum parsimony is violated in at least 25% of all copy number gains in whole genome duplicated tumors, with gains occurring both much earlier and later than thought under this assumption. We also find evidence for punctuated bursts of gains in WGD tumors, independent of the duplication itself. Finally, GRITIC allows us to look at the influence of WGD on copy-number events by comparing pre- and post-WGD copy number aberration landscapes. We find that the frequency with which different chromosome arms are gained before a WGD is highly correlated with the frequency that they are gained post-WGD. In contrast, the correlation between pre- and post-WGD losses is much smaller. We suggest that this indicates that a genome duplication changes the evolutionary trajectories of copy number losses but not gains. As an exception to this trend, chromosome 8 was disproportionately likely to be gained pre-WGD in metastatic prostate cancer as well as 1q in both breast and liver cancers. Altogether, GRITIC allows for a more accurate inference of evolutionary histories in different cancer types and better insights into the early genomic events that occur in tumors that underwent a WGD. Citation Format: Toby M. Baker, Siqi Lai, Stefan Dentro, Maxime Tarabichi, Peter Van Loo. Timing complex copy number gains in whole genome duplicated tumors [abstract]. In: Proceedings of the AACR Special Conference: Cancer Metastasis; 2022 Nov 14-17; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_2):Abstract nr PR008.

Abstract PR005: Features and susceptibility to dietary-induced alkylating damage in colorectal cancer

Abstract Introduction: Colorectal cancer (CRC) has several established risk factors, including diet. However, their mutagenic effect has not been observed directly in patients’ tumors and the individuals or ethnic groups who are most susceptible to diet-induced carcinogenesis are yet to be identified. We hypothesized that mutational signature analyses in CRC, coupled with epidemiologic, tumor molecular and patient germline data, can be linked to pre-diagnosis diet and specific germline alterations which can further inform cancer prevention efforts. Methods: We analyzed 900 CRCs with whole-exome sequencing (WES) and prospectively collected pre-diagnosis dietary data from the Nurses’ Health Studies I and II (NHS) and the Health Professionals Follow-up Study (HPFS), as well as 540 The Cancer Genome Atlas (TCGA) tumors and 295 non-Western CRCs from the Pan-Cancer Analysis of Whole Genomes. We additionally examined a sequencing dataset of normal colonic crypts. Following variant calling, mutational signature analyses were performed on cancer specimens using Non-negative Matrix Factorization. We leveraged the WES results to identify all patients that harbored the O-6-Methylguanine-DNA Methyltransferase (MGMT) germline rs16906252 single-nucleotide polymorphism (SNP), which is associated with tumor MGMT promoter hypermethylation and impaired alkylating damage repair. Results: We identified a novel alkylating mutational signature in CRC, which was associated with pre-diagnosis intake of red meats (overall red meat P = 0.017, unprocessed red meat P = 7.8×10-3, processed red meat P = 7.1×10-3, Mann-Whitney test), distal tumor location (P = 1.4×10-4, Mann-Whitney test) and worse CRC-specific survival (P trend = 0.036, multivariable Cox regression). We found a similar mutational signature in normal colonic crypts, suggesting an early oncogenic process. We showed that the alkylating signature’s oncogenicity is mainly mediated by KRAS p.G12D and KRAS p.G13D hotspot mutations. In addition, individuals harboring the MGMT rs16906252 germline SNP had a significant enrichment in tumors with alkylating damage (P = 0.015, Mann-Whitney test) and the effect of the SNP was synergistic with pre-diagnosis red-meat intake (P = 0.0099, Wald Test). Notably, we did not observe the alkylating mutational signature in CRCs from African and East-Asian patients, populations in which the MGMT rs16906252 SNP is largely absent. Conclusions: Through the integration of molecular and epidemiologic data, we identified evidence of red meat-associated alkylating damage in CRCs. This alkylating mutational signature was associated with distal colon location, KRAS oncogenic drivers, and poor CRC-specific survival. In addition, tumor alkylating damage was enriched among individuals harboring the MGMT germline rs16906252 polymorphism, absent in East Asian and African CRC patients and was synergistic with pre-diagnosis red-meat intake. Together, these results have significant implications for dietary-induced carcinogenesis and precision prevention in CRC. Citation Format: Carino Gurjao, Rong Zhong, Koichiro Haruki, Chichun Tan, Yvonne Li, Henry Lee-Six, Brendan Reardon, Tomotaka Ugai, Mingyang Song, Eliezer M. Van Allen, Charles S. Fuchs, Jonathan A. Nowak, Kana Wu, Jeffrey A. Meyerhardt, Edward L. Giovannucci, Jeffrey P. Townsend, Shuji Ogino, Marios Giannakis. Features and susceptibility to dietary-induced alkylating damage in colorectal cancer. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr PR005.

Abstract P003: Computational identification of ovarian cancer candidate genes with mutated protein structures caused by missense variants

Abstract Ovarian cancer is one of the leading killers in the US for women. The American Cancer Society (ACR) ranks ovarian cancer as the fifth leading cause of cancer deaths among women. This cancer is hereditary, with higher risks if the patient has more relatives who have had ovarian cancer before. The Cancer Genome Atlas (TCGA) is a joint-effort project by NCI and NHGRI that generates genomic data for the cancer patients and matches normal data samples with these patients. Missense mutations are single nucleotide polymorphisms (SNPs) in which the amino acids are changed. A missense variant could disrupt protein structures; thus the function of the disrupted protein is altered. In this study, we investigated genes with high expression levels in the TCGA RNA-seq dataset by characterizing protein structure change patterns of candidate genes due to missense mutations in association with ovarian cancer. We also analyzed the association of these genes with ovarian cancer prognosis. We aim to select genes that have pathogenic consequences. We selected 44 genes with the highest expression values based on TCGA ovarian cancer RNA-seq data. We then retrieved protein sequences from the Ensembl BioMart database and missense mutation annotation information from cBioPortal for 44 input genes. Specifically, the missense mutation dataset, which is projected by the Pan-Cancer Analysis of Whole Genomes, was retrieved from cBioPortal. We then used the Phyre2 database to predict the 3-D structures of the wild and mutated type genes to identify structural changes. However, some genes were not suitable for Phyre2 analysis. For example, RPL41 was not long enough for analysis with Phyre2 as it only had 25 amino acids whereas Phyre2 required 30. TMSL3 (TMSB4XP8) is a pseudogene not found in both NCBI and AlphaFold. We then searched DrugBank for 42 genes with the predicted protein structure changes by Phyre2 to identify drug targets. We also performed Kaplan-Meier survival analysis to further evaluate the clinical consequences of the candidate genes. Our preliminary results show 26 genes that have drug targets and several of them have been identified to either decrease or increase the survival rate when the expression is high in ovarian cancer patients. This indicates that the highly expressed genes with protein structure changes due to missense mutations could be potential biomarkers for treating ovarian cancer. The functional annotation study could further validate ovarian cancer association for our prioritized gene list. In the future, we also plan to compare prediction results between genders and race groups. Our results could guide medical researchers in prioritizing drug targets and developing better treatment strategies for ovarian cancer. Our approach in prioritizing candidate genes is applicable to other cancers as well, and we plan to develop bioinformatic pipelines for automatically predicting candidate genes with significant effect on patient survival for any cancer type. Citation Format: Ian W. Hou, Yongsheng Bai. Computational identification of ovarian cancer candidate genes with mutated protein structures caused by missense variants. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P003.

Regional mutational signature activities in cancer genomes.

Cancer genomes harbor a catalog of somatic mutations. The type and genomic context of these mutations depend on their causes and allow their attribution to particular mutational signatures. Previous work has shown that mutational signature activities change over the course of tumor development, but investigations of genomic region variability in mutational signatures have been limited. Here, we expand upon this work by constructing regional profiles of mutational signature activities over 2,203 whole genomes across 25 tumor types, using data aggregated by the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium. We present GenomeTrackSig as an extension to the TrackSig R package to construct regional signature profiles using optimal segmentation and the expectation-maximization (EM) algorithm. We find that 426 genomes from 20 tumor types display at least one change in mutational signature activities (changepoint), and 306 genomes contain at least one of 54 recurrent changepoints shared by seven or more genomes of the same tumor type. Five recurrent changepoint locations are shared by multiple tumor types. Within these regions, the particular signature changes are often consistent across samples of the same type and some, but not all, are characterized by signatures associated with subclonal expansion. The changepoints we found cannot strictly be explained by gene density, mutation density, or cell-of-origin chromatin state. We hypothesize that they reflect a confluence of factors including evolutionary timing of mutational processes, regional differences in somatic mutation rate, large-scale changes in chromatin state that may be tissue type-specific, and changes in chromatin accessibility during subclonal expansion. These results provide insight into the regional effects of DNA damage and repair processes, and may help us localize genomic and epigenomic changes that occur during cancer development.

Discovery of novel RNA transcripts for endometrial cancer with copy-number high alterations using pan-cancer analysis of whole genomes (PCAWG) endometrial cancer dataset (275)

<b>Objectives:</b> Uterine serous carcinoma is an aggressive type of endometrial cancer that has a propensity for metastatic spread and disproportionately affects Black women. Several new drugs are being evaluated in clinical trials for uterine serous carcinoma, including trastuzumab, pembrolizumab - lenvatinib combination, and adavosertib. However, additional treatment options are greatly needed. The Cancer Genome Atlas (TCGA) endometrial cancer project has shown that endometrial cancer can be broadly divided into four molecular classifications. Within the four molecular subtypes, the copy-number high group consists of high-grade endometrioid carcinoma and uterine serous carcinoma, which are characterized by frequent <i>TP53</i> mutation and somatic copy number alterations. To better understand the biology of this aggressive subset of endometrial cancer, we have performed bioinformatic analysis using the dataset from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and TCGA. <b>Methods:</b> To better understand the biology of uterine serous carcinoma, we sought to identify novel or poorly characterized genes using the PCAWG dataset. We analyzed the RNA sequencing data from the TCGA endometrial cancer dataset, focusing on the copy-number high group. Genes that are highly expressed in the copy-number high endometrial cancer were identified by comparing the gene expression profiles between the copy-number high endometrial cancer dataset to genes expressed in normal endometrium obtained from the PCAWG project. Survival outcomes for genes of interest were evaluated using Kaplan-Meier Plotter, containing survival data extracted from the TCGA endometrial cancer dataset. <b>Results:</b> RNA transcripts that were significantly upregulated in copy-number high endometrial cancer were identified. Three of the most significantly upregulated transcripts were claudin-6 (<i>CLDN6</i>), cancer-testis antigen <i>MAGEA9B</i>, and long non-coding RNA <i>LINC01833</i>. Kaplan-Meier analysis of overall survival showed that high <i>CLDN6</i> expression was associated with worse overall survival when compared to low <i>CLDN6</i> expression (HR: 2.04 in White patients, p=0.0037; HR: 7.35 in Black patients, p=0.0002). High expression of <i>MAGEA9B</i> was also associated with worse overall survival than low <i>MAGEA9B</i> expression (HR: 1.78 in White patients, p=0.022; HR: 5.69 in Black patients, p=0.000033). In contrast, high expression of long non-coding RNA <i>LINC02159</i> was not associated with significant alteration in overall survival (HR: 1.28 in White patients, p=0.34, HR: 0.52 in Black patients, p=0.17). <b>Conclusions:</b> Integrated genomic analysis of the TCGA endometrial cancer dataset led to the identification of several novels, previously uncharacterized RNA transcripts that are associated with poor prognosis in copy-number high endometrial cancer. Further characterization of these transcripts in uterine serous carcinoma will improve our understanding of the biology of this disease and lead to novel therapeutic options.

Association of tumors having Epstein-Barr virus in surrounding lymphocytes with poor prognosis.

Infection with certain viruses is an important cause of cancer. The Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium recently analyzed the whole-genome sequencing (WGS) data from 2656 cases across 21 cancer types, and indicated that Epstein-Barr virus (EBV) is detected in many different cancer cases at a higher frequency than previously reported. However, whether EBV-positive cancer cases detected by WGS-based screening correspond to those detected by conventional histopathological techniques is still unclear. In this study, to elucidate the involvement of EBV in various cancers, we reanalyzed the WGS data of the PCAWG cohort combined with the analysis of clinical samples of gastric and pancreatic cancer in our cohort. Based on EBV copy number in each case, we classified tumors into three subgroups: EBV-High, EBV-Low, and EBV-Negative. The EBV-High subgroup was found to be EBV-positive in the cancer cells themselves, whereas the EBV-Low subgroup was EBV-positive in the surrounding lymphocytes. Further, the EBV-Low subgroup showed a significantly worse prognosis for both gastric cancer and across cancer types. In summary, we classified tumors based on EBV copy number and found a unique cancer subgroup, EBV-positive in the surrounding lymphocytes, which was associated with a poor prognosis.

Abstract 2733: A computational model of cellular metabolism with mutation data predicts metabolites associated with somatic mutations in cancers

Abstract Metabolic reprogramming is considered a hallmark of cancers, which plays an important role in cancer progression and development, partly as a consequence of somatic mutations. A representative product of metabolic reprogramming in cancers is oncometabolites that show abnormal accumulation in a cancer cell, induce malignancy, and are generated upon mutations in a metabolic gene, often IDH1, SDH or FH. Identification of novel mutation-associated metabolites will facilitate developing biomarkers and treatment strategies for cancers, as in the case of ivosidenib, an FDA approved drug for treating acute myeloid leukemia (AML) having the IDH1 mutant. To this end, we develop a computational workflow that predicts so-called metabolite-gene-pathway sets (MGPs) that present metabolites and metabolic pathways significantly associated with gene mutations in cancers. The computational workflow uses cancer patients’ mutation data and a computational model of cellular metabolism called a genome-scale metabolic models (GEM). In this study, the computational workflow was demonstrated using 943 cancer patient-specific GEMs representing 24 different cancer types based on the Pan-Cancer Analysis of Whole Genomes (PCAWG) data [1], which, as a result, predicted 4,135 MGPs for these multiple cancer types. The computational workflow was shown to generate biologically meaningful MGPs on the basis of multi-omics data from 17 AML samples collected in this study as well as previous published studies. For the AML samples, metabolites of the MGPs predicted using the computational workflow showed significantly different intracellular concentrations, depending on mutation of genes involved in the MGP. Moreover, for the 115 MGPs predicted for CNS-GBM/Oligo that are associated with mutation of CIC, EGFR, IDH1 or TP53, 69% of the MGPs were supported by previous studies. This two-level validation indeed showed that it is possible to characterize metabolic pathways and their metabolites that are affected in response to somatic mutations in a cancer cell. Our computational workflow and its prediction outcomes will help better understand the mutation-associated metabolic reprogramming in cancers, and serve as a valuable resource for further extended studies on cancer metabolism. [1] The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature 578, 82-93 Citation Format: Sang Mi Lee, GaRyoung Lee, Sungyoung Lee, Hyojin Song, Sung Soo Yoon, Hongseok Yun, Youngil Koh, Hyun Uk Kim. A computational model of cellular metabolism with mutation data predicts metabolites associated with somatic mutations in cancers [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 2733.