WES Data Research Articles

Multi-omics integration analysis identifies pathogenic candidate genes of congenital heart defects with vascular malformation

Abstract Background Congenital heart defects (CHD) with vascular malformation harbors numerous genetic and epigenetic aberrations of DNA copy numbers and methylation. Proteomic deregulation by the aberrations plays key driver roles in heterogeneous progression of CHD. However, it still remains largely unknown about integrative analysis of genetic, epigenetic regulation and proteome in CHD. Purpose We employed a multi-omics approach to explore pathogenic candidate genes in CHD with vascular malformation. Methods Previously, we gathered WES data for 216 CHD patients with vascular malformation and 100 healthy controls. Meanwhile, we carried out DNA methylation analysis from 11 patients and 5 controls. Here, we profile proteomics of vascular tissues from 11 patients and 5 controls. Integration analysis of DNA copy-number-correlated (CNVcor) genes, methylation-correlated (METcor) genes and differentially proteins reveal the innovative and crucial pathogenetic genes. We then detected spatiotemporal expression patterns of candidate genes in zebrafish embryos using in situ hybridization and qPCR, and verified the roles in vascular development by morpholino-mediated gene knockdown. Results 90 differentially expressed proteins (DEPs) were obtained using proteomics and were mainly related to cell adhesion and migration, angiogenesis, amino acid metabolism, and HIF-1 signaling pathway through GO and KEGG pathway enrichment analysis. 15 hub proteins were identified by WGCNA analysis (Fig 1). Additionally, we found that the frequencies of the aberrancies of the CNVcor genes were significantly correlated with the METcor genes (Fig 2 C). We obtained 1924 differentially CNVcor genes and 952 differentially METcor genes. Then, we computed the Pearson’s correlation coefficients of all three-omics by pairwise comparison and found that the distribution of correlations was bimodal (Fig 2 D). Meanwhile, 28 overlapped genes were observed among three-omics. We screened out 11 candidate genes (TIMP1, BGN, LTBP1, AKR1C3, LOXL3, MAOA, MAOB, GNA12, IFI30, CNTNAP1, IGF2BP1) according to the node degree of PPI network analysis between 28 genes and known vascular development related genes. We further figured out LOXL3, MAOA, CNTNAP1 and IGF2BP1 are the novel important genes for vascular malformation, of which CNTNAP1 is the joint gene of three-omics. Through expression patterns and gene knockdown in zebrafish embryos, we revealed that LOXL3, MAOA, CNTNAP1 and IGF2BP1 affect vascular development (Fig 2 E-G). Conclusions We identify novel key candidate genes (LOXL3, MAOA, CNTNAP1 and IGF2BP1) potentially related to CHD with vascular malformation and elucidate the possible molecular pathogenesis of CHD. Our multi-omics integrative analysis provides new insights on the multi-layered etiology of CHD, which might be helpful in developing clinical diagnosis and precaution for CHD.Figure 1Figure 2

Abstract A017: Identifying proliferative and immune-modulatory drivers of small cell lung cancer (SCLC)

Abstract Small cell lung cancer (SCLC) is a highly aggressive form of lung cancer that causes an estimated 200,000 patient deaths globally every year. Most (>70%) patients present with extensive stage (ES)-SCLC, and the disease primarily presents with a neuroendocrine (NE), immune-desert phenotype, with low expression of antigen-presenting machinery genes. Despite limited immune infiltration in the tumor, SCLC has reproducibly responded to immune checkpoint blockade. IMpower133 was a pivotal Phase III trial that added atezolizumab (anti-PD-L1) to platinum/etoposide chemotherapy for treatment of first-line ES-SCLC, which led to the first approval of an immune checkpoint blockade strategy in SCLC. While the inclusion of atezolizumab to the treatment regimen has extended the survival of some patients, SCLC remains an unmet medical need with a mOS of 12.3 months. Furthermore, we lack a deep molecular understanding of factors mediating response and resistance to standard of care therapies in SCLC. To understand the genetic drivers of SCLC that could be linked to immunotherapy resistance, we analyzed the matched whole-exome sequencing and RNA-seq data from baseline tumor samples collected from the IMpower133 trial. Previously, we applied the non-negative matrix factorization (NMF) approach to the RNA-seq data, which clustered patients into four subsets of SCLC, with varying degrees of immune infiltration, neuroendocrine program activation, and clinical benefit from immunotherapy. Notably, we identified an inflamed-neuroendocrine (I-NE) subset of patients that exhibit longer overall survival with chemoimmunotherapy compared to chemotherapy alone, and an inflamed-non-neuroendocrine (I-nonNE) subset of patients that did not show a similar benefit from the addition of immunotherapy to chemotherapy. Here, we interrogated the matched WES data for recurrent alterations that may identify subsets of tumors with distinct immunological features. We identified several genes whose alterations significantly affected the enrichment of immune-related gene signatures. In particular, we identified MANF and CSK, genes previously shown to be potential tumor suppressors, as genes whose alteration associates with an “immune desert” transcriptional program. Specifically, genetic deletions or low RNA expression was associated with significantly decreased gene expression of gene signatures associated with lymphocytes, macrophages, and antigen presentation machinery. These data suggest a potential mechanism by which commonly inactivated tumor suppressors may shape the “immune desert” phenotype of SCLC. Further work is needed to determine if and how these genes may directly or indirectly modulate the tumor-immune interaction. Citation Format: Myung Chang Lee, Velimir Gayevskiy, Stefanie Morris, Minu K Srivastava, Namrata S Patil, Stephen V Liu, Martin Reck, Sanjeev Mariathasan, David S Shames, David P MacPherson, Robert J Johnston, Barzin Y Nabet. Identifying proliferative and immune-modulatory drivers of small cell lung cancer (SCLC) [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2024 Oct 18-21; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2024;12(10 Suppl):Abstract nr A017.

The recommendation of re-classification of variants of uncertain significance (VUS) in adult genetic disorders patients.

Since variants of uncertain significance (VUS) reported in genetic testing cannot be acted upon clinically, this classification may delay or prohibit precise diagnosis and genetic counseling in adult genetic disorders patients. Large-scale analyses about qualitatively distinct lines of evidence used for VUS can make them re-classification more accurately. We analyzed 458 Chinese adult patients WES data, within 15 pathogenic evidence PS1, PS2, PM1, PM6 and PP4 were not used for VUS pathogenic classification, meanwhile the PP3, BP4, PP2 were used much more frequently. The PM2_Supporting was used most widely for all reported variants. There were also 31 null variants (nonsense, frameshift, canonical ±1 or 2 splice sites) which were probably the disease-causing variants of the patients were classified as VUS. By analyzed the evidence used for all VUS we recommend that appropriate genetic counseling, reliable releasing of in-house data, allele frequency comparison between case and control, expanded verification in patient family, co-segregation analysis and functional assays were urgent need to gather more evidence to reclassify VUS. We also found adult patients with nervous system disease were reported the most phenotype-associated VUS and the lower the phenotypic specificity, the more reported VUS. This result emphasized the importance of pretest genetic counseling which would make less reporting of VUS. Our result revealed the characteristics of the pathogenic classification evidence used for VUS in adult genetic disorders patients for the first time, recommend a rules-based process to evaluate the pathogenicity of VUS which could provide a strong basis for accurately evaluating the pathogenicity and clinical grade information of VUS. Meanwhile, we further expanded the genetic spectrum and improve the diagnostic rate of adult genetic disorders.

ENU-based dominant genetic screen identifies contractile and neuronal gene mutations in congenital heart disease

BackgroundCongenital heart disease (CHD) is the most prevalent congenital anomaly, but its underlying causes are still not fully understood. It is believed that multiple rare genetic mutations may contribute to the development of CHD.MethodsIn this study, we aimed to identify novel genetic risk factors for CHD using an ENU-based dominant genetic screen in mice. We analyzed fetuses with malformed hearts and compared them to control littermates by whole exome or whole genome sequencing (WES/WGS). The differences in mutation rates between observed and expected values were tested using the Poisson and Binomial distribution. Additionally, we compared WES data from human CHD probands obtained from the Pediatric Cardiac Genomics Consortium with control subjects from the 1000 Genomes Project using Fisher’s exact test to evaluate the burden of rare inherited damaging mutations in patients.ResultsBy screening 10,285 fetuses, we identified 1109 cases with various heart defects, with ventricular septal defects and bicuspid aortic valves being the most common types. WES/WGS analysis of 598 cases and 532 control littermates revealed a higher number of ENU-induced damaging mutations in cases compared to controls. GO term and KEGG pathway enrichment analysis showed that pathways related to cardiac contraction and neuronal development and functions were enriched in cases. Further analysis of 1457 human CHD probands and 2675 control subjects also revealed an enrichment of genes associated with muscle and nervous system development in patients. By combining the mice and human data, we identified a list of 101 candidate digenic genesets, from which each geneset was co-mutated in at least one mouse and two human probands with CHD but not in control mouse and control human subjects.ConclusionsOur findings suggest that gene mutations affecting early hemodynamic perturbations in the developing heart may play a significant role as a genetic risk factor for CHD. Further validation of the candidate gene set identified in this study could enhance our understanding of the complex genetics underlying CHD and potentially lead to the development of new diagnostic and therapeutic approaches.

On the Boundary of Exploratory Genomics and Translation in Sequential Glioblastoma.

OMICS methods brought significant advancements to the understanding of tumor cell biology, which transformed the treatment and prognosis of several cancers. Clinical practice and outcomes, however, changed significantly less in the case of glioblastoma (GBM). In this study, we aimed to assess the utility of whole exome (WES) sequencing in the clinical setting. Ten pairs of formalin-fixed, paraffin-embedded (FFPE) GBM specimens were obtained at onset (GBM-P) and at recurrence (GBM-R). Histopathological and molecular features of all samples supported the diagnosis of GBM based on WHO CNS5. WES data were filtered, applying a strict and custom-made pipeline, and occurrence of oncogenic and likely oncogenic variants in GBM-P, GBM-R or both were identified by using the VarSeq program version 2.5.0 (Golden Helix, Inc.). Characteristics and recurrence of the variants were analyzed in our own cohort and were also compared to those available in the COSMIC database. The lists of oncogenic and likely oncogenic variants corresponded to those identified in other studies. The average number of these variants were 4 and 5 out of all detected 24 and 34 variants in GBM-P and GBM-R samples, respectively. On average, one shared oncogenic/likely oncogenic variant was found in the pairs. We assessed the identified variants' therapeutic significance, also taking into consideration the guidelines by the Association for Molecular Pathology (AMP). Our data support that a thorough WES analysis is suitable for identifying oncogenic and likely oncogenic variants in an individual clinical sample or a small cohort of FFPE glioma specimens, which concur with those of comprehensive research studies. Such analyses also allow us to monitor molecular dynamics of sequential GBM. In addition, careful evaluation of data according to the AMP guideline reveal that though therapeutic applicability of the variants is generally limited in the clinic, such information may be valuable in selected cases, and can support innovative preclinical and clinical trials.

Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL

Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis was used to identify a signature associated with high risk of early clinical failure independent of IPI and COO. Further analysis revealed the signature was associated with metabolic reprogramming and identified cases with a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. This novel and integrative approach is the first to identify a signature at diagnosis, in a real-world cohort of DLBCL, that identifies patients at high risk for early clinical failure and may have significant implications for design of therapeutic options.

Molecular findings in patients for whole exome sequencing and mitochondrial genome assessment

ObjectiveWhole exome sequencing (WES) is becoming more widely used as a diagnostic tool in the field of medicine. In this article, we reported the diagnostic yield of WES and mitochondrial genome assessment in 2226 consecutive cases in a single clinical laboratory. Materials and methodsWe retrospectively analyzed consecutive WES reports from 2226 patients with various genetic disorders. WES-process was focused exclusively on the probands and aimed at a higher diagnostic capacity. We determined the diagnostic rate of WES overall and by phenotypic category, mode of inheritance, mitochondrial genome variant, and copy number variants (CNVs). ResultsAmong the 2226 patients who had diagnostic WES proband-only, the overall diagnostic yield of WES was 34.59% (770/2226). The highest diagnostic yield was observed in autosomal dominant disorders, at 45.58% (351/770), followed by autosomal recessive at 31.95%(246/770), X-linked disorder at 9.61%(74/770), and mitochondrial diseases at a notably lower 0.65%(5/770). The 12.21% (94/770) diagnoses were based on a total of 94 copy number variants reported from WES data. CNVs in children accounted for 67.02% of the total CNVs. While majority of the molecular diagnoses were related to nuclear genes, the inclusion of mitochondrial genome sequencing in the WES test contributed to five diagnoses. all mitochondrial diseases were identified in adults. ConclusionsThe proband-only WES provided a definitive molecular diagnosis for 34.59% of a large cohort of patients while analysis of WES simultaneously analyzed the SNVs, exons, mitochondrial genome, and CNVs, thereby improving the diagnostic yield significantly compared to the single-detection WES method; and facilitating the identification of novel candidate genes.

Kinome reprogramming as a therapeutic opportunity in ESR1 fusion driven breast cancer but not in gynecologic cancers.

1045 Background: The administration of specific tyrosine-kinase inhibitors in kinase fusion positive cancers has led to significant improvement in clinical outcomes. Gene fusions involving the ESR1 gene, a non-kinase, have been previously reported in breast and gynecologic cancers including ovarian cancer and uterine cancer. However, ERa inhibitors proved to be ineffective in ESR1 fusion positive cases, we have effectively characterized ESR1 fusions and hypothesized a surrogate downstream target as an effective approach to target ESR1 fusion positive breast cancer. Methods: We retrospectively analyzed 216,176 samples submitted for clinical molecular profiling at Caris Life Sciences via Caris MI Tumor Seek (Phoenix, AZ). Gene fusion detection was performed on mRNA isolated from a FFPE tumor sample using the Illumina NovaSeq platform. All ESR1 fusions with ≥ 3 junction reads were identified for manual review and for domain prediction, breakpoints, frame retention and co-occurring alterations by NGS. WES data was also investigated to evaluate co-occurring pathogenic mutations to establish the oncogenicity of gene fusions. Results: ESR1 fusions had the highest frequency in gynecologic and breast cancer. We evaluated ESR1 expression in cases with ESR1 fusions detected and observed higher expression of ESR1 in breast cancer, ovarian cancer (P<0.0001) and uterine cancer (P<0.0001) compared to respective cancer cases as determined by TPM values. The Kaplan-Meier curve also indicated poor prognosis for breast cancer patients with ESR1 fusions (619 days [n=105]) as opposed to patients who did not harbor any ESR1 variants (1396 days [n=755]; P<0.0001). Further, pathway analysis was performed on breast cancer ESR1 fusion positive and negative cases to discern specific downstream markers that might be upregulated. It was observed that RET(p<0.0001), IGF1R(p=0.0001) and FGFR3 (p<0.0001) were upregulated in ESR1 fusion positive breast cancer cases which may be largely determined by the TP53-FOXA1-ER alpha transcriptional axis. However, no significant increase of RET, IGF1R and FGFR3 was observed in gynecologic cancers, owing to high TP53 mutation frequency observed in ovarian cancer (90%) and uterine cancer (82%) compared to breast cancer(19%). Conclusions: We highlight that ESR1 fusions can be reliably detected in patients with breast cancer, ovarian cancer, and endometrial cancers. ESR1 fusions lose the ligand binding domain and cannot be targeted using current estrogen modulators or degraders. We have discovered the upregulation of oncogenic kinase signaling in ESR1 fusion positive breast cancer, but not in gynecologic cancers. Our observations highlight enhanced oncogenic kinase signaling as a surrogate approach with clinically approved kinase inhibitors for targeting ESR1 fusion positive breast cancer cases but not in ovarian and uterine cancers.

Biological subgroups in melanoma: A correlation of tumor genomic and transcriptomic analysis with spatial immunophenotyping.

e14667 Background: A prominent challenge advancing immunotherapy is the heterogeneity of resistance mechanisms leading to drug development failure despite efficacy in subgroup of patients. To address these shortcomings, precision medicine platforms aimed at prospectively stratifying patients into treatment groups based on tumor mutational burden (TMB) and tumor inflammation scores by gene expression profiling (GEP) are now being explored. Whether these gene-based variables reflect the true immunologic state of the tumor remains an open question. Here, we sought to evaluate TMB and GEP as markers of intratumoral inflammatory state by single-cell spatial analysis. Methods: Under an IRB approved protocol through the Huntsman Cancer Institute, 25 melanoma tumors with available clinical, WES, and RNAseq data were stained with a multiplex immunofluorescence-based protocol using Opal dye and Leica Bond Rx (CD8, CD68, PD1, PD-L1, Ki67, SOX10, DAPI) and scanned with Akoya Polaris whole slide scanner. Images were analyzed using HALO. Results: Melanoma tumors were stratified into 4 subgroups based on TMB (<10 vs ≥10 m/Mb) by WES, and inflammatory (Inflm) gene signature expression (GSEA >0 vs ≤0) by RNAseq, denoted as S1 (TMBhi/Inflmhi; n=4), S2 (TMBhi/Inflmlo; n=4), S3 (TMBlo/Inflmhi; n=8), and S4 (TMBlo/Inflmlo; n=9). The rate of disease progression was 0% (S1), 25% (S2), 25% (S3), and 56% (S4). Infiltration analysis of CD8 T cells showed elevated intratumoral CD8 density in S1 (249/mm2) and S3 (157/mm2) vs S2 (65/mm2) and S4 (65/mm2; p=0.0002), consistent with GEP findings. Spatial analysis showed a similar pattern of CD8 distribution across subgroups with peak CD8 density in the tumor periphery. Proximity analyses showed average distance of CD8 T cell to the nearest tumor cell was not different across subgroups. Furthermore, we found Inflmhi tumors had a higher frequency of PD1+ CD8 T cells relative to Inflmlo tumors (12.9 vs 2.8 cells/HPF; p=0.0002), suggesting GEP also reflects CD8 activation and functional status. Increased frequency of PD1+ CD8 T cells was correlated with a much improved overall survival (HR=3.3; p=0.017). A similar analysis performed on CD68+ macrophages showed significantly increased peri-tumoral macrophage recruitment in S4 (445/mm2) vs S1 (209/mm2; p<0.0001), S2 (91/mm2; p<0.0001), and S3 (267/mm2; p=0.0003) subgroups. Interestingly, Inflmhi tumors were associated with an increased proportion of PDL1+ macrophages regardless of TMB status (43% vs 3%; p<0.0001), suggestive of an upregulated adaptive immune response in tumors with active inflammation. Conclusions: Our findings illustrate that biological groupings based on TMB and GEP biomarkers correlate with CD8 spatial location and activation state. Each subgroup has unique tumor immune features that can be related to immune resistance and warrant further investigation.

Whole exome sequencing in young atrial fibrillation patients

Abstract Background Up to 10% of atrial fibrillation (Afib) patients develop the condition in the young age and in the absence of any related risk factors. Recent publications emphasized the importance of genetic testing in this population. However, the yield of the investigation is highly variable and ranges from 1 to 24% precents. Purpose The purpose of this study is to evaluate the prevalence of causative genetic variants in young Afib patients without risk factors and evaluate any structural changes of the heart. Methods We performed whole exome sequencing in 54 young (age of Afib onset less than 65 years) Afib patients without any Afib related risk factors (original cohort). Using ACMG guidelines we performed analysis of 349 previously described cardiomyopathy and arrhythmia associated genes. If a pathogenic (P) or likely pathogenic (LP) variant was found, a cardiac magnetic resonance imaging (CMR) was performed to exclude any structural abnormalities of the heart. We also extracted 107 young Afib patients without any risk factors from UK Biobank (UK Biobank cohort) and performed analysis of the same genes in the subgroup. Results The prevalence of P and LP variants was 24% (13 cases) in the original cohort and 8% (9 cases) in the UK Biobank cohort (p=0.006). We observed variants in cardiac structural and developmental genes only in both cohorts (Table 1 and 2). In the original cohort there were nine (17%) patients with P and LP variant in TTN gene. Moreover, five patients were positive for the same TTN variant NM_001267550.2:c.13696C>T p.(Gln4566Ter). In six (46%) original cohort patients we observed structural changes of the heart on CMR – in five patients there was dilation of one or both ventricles and in one there was increased T1 mapping intensity of septal wall segments. Conclusions 1. There is a high prevalence of pathogenic and likely pathogenic causative genetic variants in young atrial fibrillation patients without any risk factors. 2. All variants are localized in cardiac structural or developmental genes only. 3. There is a high grade of structural changes of the heart observed on cardiac magnetic resonance imaging in patients with monogenic atrial fibrillation.Table 1.WES data in original cohortTable 2.WES data in UK Biobank cohort

Genome-wide profiling of angiogenic cis-regulatory elements unravels cis-regulatory SNPs for vascular abnormality

Angiogenesis is extensively involved in embryonic development and requires complex regulation networks, whose defects can cause a variety of vascular abnormalities. Cis-regulatory elements control gene expression at all developmental stages, but they have not been studied or profiled in angiogenesis yet. In this study, we exploited public DNase-seq and RNA-seq datasets from a VEGFA-stimulated in vitro angiogenic model, and carried out an integrated analysis of the transcriptome and chromatin accessibility across the entire process. Totally, we generated a bank of 47,125 angiogenic cis-regulatory elements with promoter (marker by H3K4me3) and/or enhancer (marker by H3K27ac) activities. Motif enrichment analysis revealed that these angiogenic cis-regulatory elements interacted preferentially with ETS family TFs. With this tool, we performed an association study using our WES data of TAPVC and identified rs199530718 as a cis-regulatory SNP associated with disease risk. Altogether, this study generated a genome-wide bank of angiogenic cis-regulatory elements and illustrated its utility in identifying novel cis-regulatory SNPs for TAPVC, expanding new horizons of angiogenesis as well as vascular abnormality genetics.

Exploring the role of HLA variants in neuroblastoma susceptibility through whole exome sequencing.

Although a number of susceptibility loci for neuroblastoma (NB) have been identified by genome-wide association studies, it is still unclear whether variants in the HLA region contribute to NB susceptibility. In this study, we conducted a comprehensive genetic analysis of variants in the HLA region among 724 NB patients and 2863 matched controls from different cohorts. We exploited whole-exome sequencing data to accurately type HLA alleles with an ensemble approach on the results from three different typing tools, and carried out rigorous sample quality control to ensure a fine-scale ancestry matching. The frequencies of common HLA alleles were compared between cases and controls by logistic regression under additive and non-additive models. Population stratification was taken into account adjusting for ancestry-informative principal components. We detected significant HLA associations with NB. In particular, HLA-DQB1*05:02 (OR = 1.61; padj = 5.4 × 10-3) and HLA-DRB1*16:01 (OR = 1.60; padj = 2.3 × 10-2) alleles were associated to higher risk of developing NB. Conditional analysis highlighted the HLA-DQB1*05:02 allele and its residue Ser57 as key to this association. DQB1*05:02 allele was not associated to clinical features worse outcomes in the NB cohort. Nevertheless, a risk score derived from the allelic combinations of five HLA variants showed a substantial predictive value for patient survival (HR = 1.53; p = 0.032) that was independent from established NB prognostic factors. Our study leveraged powerful computational methods to explore WES data and HLA variants and to reveal complex genetic associations. Further studies are needed to validate the mechanisms of these interactions that contribute to the multifaceted pattern of factors underlying the disease initiation and progression.

GDF9His209GlnfsTer6/S428T and GDF9Q321X/S428T bi-allelic variants caused female subfertility with defective follicle enlargement

BackgroundAntral follicles consist of an oocyte cumulus complex surrounding by somatic cells, including mural granulosa cells as the inner layer and theca cells as the outsider layer. The communications between oocytes and granulosa cells have been extensively explored in in vitro studies, however, the role of oocyte-derived factor GDF9 on in vivo antral follicle development remains elusive due to lack of an appropriate animal model. Clinically, the phenotype of GDF9 variants needs to be determined.MethodsWhole-exome sequencing (WES) was performed on two unrelated infertile women characterized by an early rise of estradiol level and defect in follicle enlargement. Besides, WES data on 1,039 women undergoing ART treatment were collected. A Gdf9Q308X/S415T mouse model was generated based on the variant found in one of the patients.ResultsTwo probands with bi-allelic GDF9 variants (GDF9His209GlnfsTer6/S428T, GDF9Q321X/S428T) and eight GDF9S428T heterozygotes with normal ovarian response were identified. In vitro experiments confirmed that these variants caused reduction of GDF9 secretion, and/or alleviation in BMP15 binding. Gdf9Q308X/S415T mouse model was constructed, which recapitulated the phenotypes in probands with abnormal estrogen secretion and defected follicle enlargement. Further experiments in mouse model showed an earlier expression of STAR in small antral follicles and decreased proliferative capacity in large antral follicles. In addition, RNA sequencing of granulosa cells revealed the transcriptomic profiles related to defective follicle enlargement in the Gdf9Q308X/S415T group. One of the downregulated genes, P4HA2 (a collagen related gene), was found to be stimulated by GDF9 protein, which partly explained the phenotype of defective follicle enlargement.ConclusionsGDF9 bi-allelic variants contributed to the defect in antral follicle development. Oocyte itself participated in the regulation of follicle development through GDF9 paracrine effect, highlighting the essential role of oocyte-derived factors on ovarian response.

Abstract 4926: Advancements in somatic variant calling from UG100 whole genome and whole exome sequencing data

Abstract Somatic variant calling involves the identification of genomic alterations that occur in somatic cells, requiring deep coverage to enable high sensitivity for low-frequency variants. Characterizing somatic variants across the entire genome therefore benefits from novel cost-efficient sequencing platforms, such as UG100. Here, we present optimization of variant calling tools for short and structural variants on WGS and WES data from UG100. For calling short variants, we optimized DeepVariant (DV) for somatic calling using data from matched tumor-normal sample pairs, improving both variant calling accuracy and pipeline running time (up to 10-fold). We defined the task of somatic variant calling as deciding if the pileup image containing reads from the tumor and normal samples represents a true somatic variant (vs a germline variant or artifact). The challenge of robust variant calling using deep learning models is exacerbated in somatic calling, where sequencing depth and coverage variability are typically high. Our optimized DV overcomes these challenges by several data sampling strategies. First, allele-frequency preserving down-sampling reduces randomness of read sub-sampling in high coverage regions. Second, alternative allele prioritization samples alt-allele supporting reads first allowing to call variants at very high coverage loci without sacrificing sensitivity and computational efficiency. Finally, a Panel-of-Normals based on targeted WES data provides an additional improvement of precision for this assay type. We used these strategies to train two models, one for tumor characterization using WGS (T/N coverage: 40x-150x/40x-100x), and one for deep WES (T/N coverage: >500x/>120x). We called variants on simulated tumors using the WGS model. For VAF>10% the model showed SNV recall >98% and indel recall >95% with false-positive rate of 0.2/Mb. For VAF range of 5-10%, indel recall was 67% and SNV recall was 86%. To demonstrate the utility of our somatic variant calling, we applied the models to call somatic variants from well characterized cancer cell lines: COLO829, HCC1395 and HCC1143. Results showed F1>90% for variants with VAF>10%. The WES model was used to reliably call variants at VAF>5% on simulated tumors with average SNV recall of 99% with precision >99% and indel recall >86% with precision >94%. To analyze structural and copy-number variations, we optimized the assembly engine of GRIDSS to enable fast calling of structural variations and demonstrate that Control-FREEC can be used to call copy number variants. SV calling on COLO829/COLO829BL achieved sensitivity >95%. In conclusion, our research highlights the utility of UG100 within the field of oncology, demonstrating its capacity for comprehensive and precise somatic variant detection, both on WGS and WES data. Citation Format: Doron Shem-Tov, Maya Levy, Gil Hornung, Ilya Soifer, Hila Benjamin, Ariel Jaimovich, Adam Blattler, William Brandler, Robert Sugar, Isaac Kinde, Omer Barad, Doron Lipson. Advancements in somatic variant calling from UG100 whole genome and whole exome sequencing data [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 4926.

Abstract 6897: Defining critical features for successful preclinical use of glioblastoma patient-derived xenografts (PDX) models for therapeutic assessment and clinical trial development

Abstract Mayo Clinic has developed 111 GBM PDXs from newly diagnosed (72 PDX) and recurrent (39 PDX) patients. This large collection of PDXs provides a broad representation of genetic heterogeneity seen in patients. GBM PDXs that perform well in both in vitro and in vivo settings can be extensively utilized in the preclinical setting for downstream analysis. Based on 20 years of experience, we have defined the attributes that best enable preclinical use of our GBM PDX models. Among them are short-term in vitro culturing performance, large scale genomic evaluation data, benchmarked responses to standards of care, and median time to moribund for untreated orthotopic tumors. PDXs with prolonged survival timelines delay study readouts and, in some situations, confound efficacy results due to age-related animal decline. Setting median survival thresholds as part of the upfront experimental design allows for more timely study readouts that are unaffected by these confounding variables. Our preferred cutoff for the Mayo GBM PDX collection is 70 days median survival (n=64). Using this 64 PDX line panel, regimens expected to double survival would produce results within 4-5 months. This timeframe is well within the range of robust health for athymic nude mice. This 64-line collection features both newly diagnosed (nGBM; n=42) and recurrent (rGBM; n=22) tumors. MGMT promoter methylation status was determined by qMS-PCR (25 methylated, 37 unmethylated, 2 indeterminate). Available WES (n=62) and RNAseq (n=42) data, along with our tissue microarray (n=42), are critical resources for biomarker-based evaluations aimed at defining patient populations that are most likely to benefit from a given therapeutic. From these data, the molecular subtypes available include 26 classical, 14 proneural, and 3 mesenchymal. Twenty-seven of these 64 PDX models have also been successfully cultured from fresh as well as cryopreserved cell stocks to further expand their experimental value. Correlative clinical data including diagnosis and treatments are also available (n=61). Current standards of care for GBM include radiation, temozolomide, and bevacizumab. Defining sensitivity to these therapies is an important first step for evaluating the integration of novel therapeutics with these standards. Since the creation of our GBM PDX collection, efficacy of these therapies has been evaluated as follows: RT 26 PDXs, TMZ 20 PDXs, and Avastin 23 PDXs. The Mayo Clinic GBM PDX collection provides an important platform for preclinical evaluation of novel therapeutics. Through careful selection of PDX lines with favorable growth characteristics and known genetic features, researchers can select the most relevant models for their study. This approach will enable more meaningful preclinical work in the hopes of providing more tangible clinical benefits for GBM patients. Citation Format: Danielle M. Burgenske, Ann C. Mladek, Katrina K. Bakken, Zeng Hu, Brett L. Carlson, Paul A. Decker, Jeanette E. Eckel-Passow, Jann N. Sarkaria. Defining critical features for successful preclinical use of glioblastoma patient-derived xenografts (PDX) models for therapeutic assessment and clinical trial development [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 6897.

Abstract 2551: Harness the power of real-world-data for oncology target and biomarker research: A case study by applying clinic-genomics data for 2,659 lung cancer patients and beyond

Abstract Randomized controlled trials (RCTs) are the gold standard for evaluating drug safety and efficacy in controlled settings, but they have limited generalizability due to their focus on selective and homogeneous populations. Real-world-data (RWD), collected from larger and more varied patient populations, can address inherent limitations of RCTs and aid in clinical trial design and drug approval. However, with the challenges of RWD, unlocking its full potential for tumor target and biomarker identification and validation demands innovative analytical approaches. Here we present RWD analyses of ConcertAI® electronic health records (EHR) linked with Caris Lab data for 2,659 lung cancer patients. Comprehensive genomics analyses incorporate WES and RNA-seq data, coupled with rich clinical EHR data. By integrating clinical and genomics data, we showcase the potential of harnessing RWD as follows: (1) we investigated genomic alterations across five histology groups (adenocarcinoma, squamous, large cell, small cell lung cancer [SCLC], neuroendocrine [NE] lung cancer). Notably, TP53 and LRP1B mutations were prevalent across all groups. LRP1B mutations correlated with higher tumor mutation burden, indicative of a favorable response to immunotherapy. Biallelic TP53 and RB1 inactivation was predominant in SCLC and NE lung tumors. The five histological groups exhibit distinct expression profiles, reflecting tumor intrinsic characteristics. Most immune gene signature scores were significantly lower in SCLC and NE tumors, aligned with that they are cold tumors with immune resistance, except CD56-centered NK and neuroendocrine gene signatures; (2) we analyzed patient treatment patterns and persistence by line of therapy. Among the 206 NSCLC patients with clinically actionable EGFR mutations, 143 received targeted therapy during their treatment courses (69.4%). Time to treatment discontinuation (TTD) was used as a surrogate clinical outcome endpoint. TTD was significantly longer when TKI was the first line treatment compared to later lines (p = 0.01), while the trend is opposite for ICI where TTD is significantly shorter in the 1st line setting (p = 0.025); (3) we highlight the unique potential of leveraging H&E imaging modality in such RWD. In summary, we successfully identified unique molecular signatures among various lung cancer histological groups, pinpointed distinct subpopulations within lung adenocarcinoma and squamous tumors linked to their immune phenotypes, and investigated the different patient treatment patterns and outcomes, facilitating personalized medicine. In the broader context of our work, we have developed a framework for harnessing various data modalities (clinical, multi-omics, imaging) within AbbVie's oncology RWD realm, enhancing the discovery and validation of new oncology targets and biomarkers. Citation Format: Si Wu, Weilong Zhao, Christy Choi, Mona Cai, Peter Ansell, Alexander Liede, Rong Chen, Xi Zhao, Josue Samayoa. Harness the power of real-world-data for oncology target and biomarker research: A case study by applying clinic-genomics data for 2,659 lung cancer patients and beyond [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 2551.

Abstract 5168: Analysis of biomarker and outcomes data: 7-year update from COLUMBUS

Abstract Background: In the randomized, 2-part, phase 3 COLUMBUS study (NCT01909453), encorafenib (enco) + binimetinib (bini)—an approved regimen in the US, EU, and other countries—improved 7-year PFS and OS vs vemurafenib (vemu) in patients (pts) with BRAF V600E/K-mutant locally advanced unresectable or metastatic melanoma. We investigated genetic and transcriptional correlates of outcomes in an exploratory biomarker analysis of COLUMBUS Parts 1 and 2. Methods: In Part 1, 577 pts were randomized 1:1:1 to enco 450 mg QD + bini 45 mg BID, enco 300 mg QD, or vemu 960 mg BID; in Part 2, 344 pts were randomized 3:1 to enco 300 mg QD + bini 45 mg BID or enco 300 mg QD. Baseline tumor samples were analyzed using the ACE ImmunoID NeXT whole exome sequencing/whole transcriptome sequencing (WES/WTS) assays (Personalis). PFS and OS were analyzed (cutoff: Jan 13, 2023) by treatment arm and presence of specific genetic or transcriptomic alterations. Results: Among treated pts, 668 had WES or WTS data. K-means clustering identified 3 major transcriptional clusters: (1) microphthalmia-associated transcription factor (MITF)-low (invasive dedifferentiated tumor cell phenotype), (2) MITF-high (proliferative melanocytic phenotype), and (3) immune-high. Cluster assignments were significantly associated with biopsy site (P<0.001), with cluster 1 enriched in skin biopsies and cluster 3 in lymph node metastases; biopsy site-independent characteristics were also captured. Improved PFS with enco + bini vs vemu was most pronounced in cluster 3 (Table 1). ERBB2 expression and PI3KCA pathway mutation, previously found to be associated with reduced survival benefit with enco + bini vs vemu, were enriched in clusters 1 and 2 vs cluster 3. Conclusions: Enco + bini showed benefit across molecular subtypes in BRAF V600E/K-mutant melanoma. The contribution of bini was most pronounced in the immune-high cluster. Improved outcomes in this cluster support ongoing trials of combinations with immune checkpoint inhibitors, such as STARBOARD and PORTSIDE. Table 1. Hazard ratios of PFS and OS for enco + bini or enco vs vemu by cluster HR (95% CI) vs vemu PFS OS Enco + bini Enco Enco + bini Enco Overall n=255 vs 100 n=159 vs 100 n=255 vs 100 n=159 vs 100 0.47 (0.35, 0.63) 0.78 (0.57, 1.07) 0.66 (0.50, 0.86) 0.85 (0.63, 1.13) Clusters Cluster 1: MITF-low n=72 vs 34 n=44 vs 34 n=72 vs 34 n=44 vs 34 0.74 (0.44, 1.26) 0.92 (0.51, 1.66) 0.63 (0.40, 1.00) 0.57 (0.34, 0.96) Cluster 2: MITF-high n=120 vs 46 n=76 vs 46 n=120 vs 46 n=76 vs 46 0.48 (0.32, 0.74) 0.75 (0.48, 1.17) 0.66 (0.45, 0.97) 0.86 (0.56, 1.32) Cluster 3: Immune-high n=63 vs 20 n=39 vs 20 n=63 vs 20 n=39 vs 20 0.23 (0.12, 0.44) 0.64 (0.33, 1.21) 0.80 (0.40, 1.59) 1.55 (0.76, 3.15) Numbers are given as the number of pts included in the treatment arm vs the number of pts in the comparator arm (vemu-treated). Statistical significance (P<0.05) is shown by bold font. Bini, binimetinib; enco, encorafenib; MITF, microphthalmia-associated transcription factor; pts, patients; vemu, vemurafenib. Citation Format: Reinhard Dummer, Keith Flaherty, Shibing Deng, Tao Xie, Phineas Hamilton, Nuzhat Pathan, Caroline Robert, Ana Arance, Jan Willem de Groot, Claus Garbe, Helen J. Gogas, Ralf Gutzmer, Ivana Krajsová, Gabriella Liszkay, Carmen Loquai, Mario Mandala, Dirk Schadendorf, Naoya Yamazaki, Paolo A. Ascierto, Alessandra di Pietro, Craig B. Davis. Analysis of biomarker and outcomes data: 7-year update from COLUMBUS [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 5168.

Abstract 1201: Pervasive HLA disruption fuels cancer evolution

Abstract Disruption of the human leukocyte antigen (HLA) molecules has important implications for immune evasion and tumor evolution. However, although genomic loss of HLA is frequent in non-small cell lung cancer (NSCLC) and in some types of breast cancer, the extent and importance of transcriptomic disruption to HLA presentation, including transcript repression and alternative splicing (AS), remains unclear. To address this, we developed MHC Hammer, a tool to call HLA allele-specific mutations, loss of heterozygosity (LOH), transcriptional repression, and alternative splicing. We first assessed HLA allelic expression and the prevalence of AS in normal tissue. Applying MHC Hammer to 510 normal lung samples and 407 normal breast samples from the Genotype-Tissue Expression cohort, we identified extensive heterogeneity in HLA allelic expression depending on both the allele and tissue type. In addition, HLA allelic AS, occurring in at least 20% of the allele transcripts, was observed in 19% of normal lung and 13% of normal breast samples. Next, we applied MHC Hammer to 413 TRACERx NSCLCs and 743 TCGA breast tumours. While mutations were uncommon, HLA LOH was a frequent event, occurring in 32% of lung adenocarcinomas (LUAD) and 57% of lung squamous cell carcinomas (LUSC). We observed a similar rate of HLA LOH in estrogen receptor positive (ER+) and negative (ER-) tumors (ER+: 14%, ER-: 15%), while in triple negative breast tumours we observed a higher rate of LOH (31%). Due to the heterogeneity in HLA expression observed in the normal samples, to measure tumor specific HLA repression and alternative splicing, we restricted our analysis to tumours with WES, tumor and tumor-adjacent normal RNAseq data. This resulted in a cohort of 88 NSCLCs from the TRACERx study as well as 44 ER+ breast tumours from the TCGA cohort. 61% of LUAD, 75% of LUSC and 35% of ER+ tumours harbored class I HLA transcriptional repression that could not be explained by underlying genomic loss. 27% of LUAD, 7% of LUSC and 55% of ER+ breast tumor patients exhibited no HLA disruption. Tumor specific AS affecting HLA exons 2, 3 or 4, potentially disrupting HLA antigen presentation, was identified in 8% of LUADs, 11% of LUSC and 7% of ER+ breast tumours. Tumor specific AS of exon 5, yielding soluble HLA molecules without a transmembrane domain was identified in 20% of LUAD, 14% of LUSCs and 18% of ER+ breast tumours. LUAD and LUSC tumor regions without HLA LOH or repression were enriched for somatic HLA AS events and alleles with somatic HLA AS had a higher neoantigen burden than those without. We found no relationship between survival and HLA expression or AS in the normal tissue. However, consistent with the importance of HLA dysfunction in tumor evolution, LUADs with low HLA expression in at least one tumor region were associated with shorter disease-free survival, HLA LOH was more common in LUAD’s that metastasized and HLA repression was enriched in LUSC primary regions seeding metastases. Citation Format: Clare Puttick, Thomas P. Jones, Michelle Leung, Oriol Pich, Felipe Galvez Cancino, Jiali Liu, Manuel Varas-Godoy, Andrew Rowan, Carlos Martinez-Ruiz, Robert Bentham, Krijn K. Dijkstra, Rachel Rosenthal, Nnennaya Kanu, Kevin Litchfield, Roberto Salgado, David A. Moore, Peter Van Loo, Mariam Jamal-Hanjani, Sergio A. Quezada, Nicholas McGranahan, Charles Swanton. Pervasive HLA disruption fuels cancer evolution [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 1201.

Abstract 5845: Cytarabine resistance leads to a unique mutational signature

Abstract The prognosis of recurrent T-cell acute lymphoblastic leukemia (T-ALL) is poor, mainly due to chemotherapy resistance. The mechanism(s) leading to chemoresistance at relapse are incompletely understood. We previously characterized a mouse strain that is hypomorphic for the DNA replication factor Mcm2. Mcm2hypo mice develop T-ALL due to acquired DNA copy number variations (CNV) involving tumor suppressor or oncogenes. We hypothesize that treatment of Mcm2hypo cells with specific chemotherapy agents may reveal CNV that lead to chemoresistance. We treated two Mcm2hypo T-ALL cell lines (designated 2883 and 2869) and an Mcm2 WT T-ALL cell line (designated 7298) with cytarabine (ARAC), an active agent often incorporated in T-ALL treatment regimens. After one year of treatment with gradually increasing ARAC concentrations, we obtained ARAC resistant cell lines (designated with the suffix CR) that tolerate drug concentrations up to 10,000X that of parental cell lines. These samples were characterized by sparse WGS (for CNV assessment), RNA-Seq and WES. Both the 2883CR and 2869CR cell lines had bi-allelic mutations involving Dck, which is the rate-limiting enzyme in the cytidine salvage pathway, and is thought to be required for metabolism of ARAC. In both cases, one allele was deleted while the second allele had a splice site/region mutation leading to partial intron retention and resultant frameshift. The 7298CR cell line had homozygous deletion of Dck. Western blotting showed absence of WT Dck protein in all three cell lines. Further analysis of WES data revealed thousands of acquired single nucleotide variants (SNV) in both Dck mutant Mcm2hypo cell lines. These mutations occurred in a specific trinucleotide context (C>T in a GCG context, T>C in a GTC context, T>G mutations in GTC and GTT context, and C>G in a GCC context) generating a mutational signature that is not present in the COSMIC database. In addition, the parental 2883 and 2869 cell lines showed fewer mutations (ie, hundreds vs thousands) in a similar context (C>T in a GCG context, T>C in a GTC context, T>G mutations in GTC and GTT context, but not the C>G in GCC context). A GEMINI (Genotoxic Mutational Signature Identified After Clonal Expansion In Vitro) assay of untreated 2883CR and 2869CR cells demonstrated that ongoing ARAC exposure was not required for the mutational signature. We hypothesize that the basic signature (C>T in a GCG context, T>C in a GTC context, T>G mutations in GTC and GTT context) can be produced by Mcm2 deficiency, and this signature is amplified and modified (to include a C>G in GCC context) by Dck inactivation. In summary, we identified three mechanisms responsible for Dck inactivation associated with ARAC resistance: copy number loss, splice site mutations, and splice region mutations. Moreover, Dck inactivation leads to a specific mutation signature. These findings add to emerging data that exposure to specific chemotherapy agents can lead to specific mutational signatures. Citation Format: Dengchao Cao, Mianmian Yin, Zhenhua Zhang, Taimour Baslan, Jack Zhu, Ryan Bertoli, Paul Meltzer, Peter Aplan. Cytarabine resistance leads to a unique mutational signature [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 5845.

Abstract 1757: Pan-cancer analysis identifies signatures of HRD-positivity in germline BRCA1/2 mutated non-BRCA associated cancers

Abstract Introduction: BRCA-associated cancers (breast, ovarian, pancreas, and prostate) with germline pathogenic mutations in BRCA1/2 (gBRCA1/2) are associated with homologous recombination deficiency (HRD) and benefit from platinum/PARPi. However, the role of gBRCA1/2 in non-BRCA assoc. cancers is poorly understood. HRD tumors present with ‘genomic scars’ that can be quantified in tumor profiling (“HRD-sum” score). We reasoned that the HRD-sum score together with germline mutation status (including loss of wild-type) is a strong correlate of HRD-positivity. Leveraging 42,448 prospectively sequenced patients across 63 cancer types, we sought to characterize the prevalence of the HRD-positivity in non-BRCA-assoc. cancers. Methods: Allele-specific copy number data was inferred using FACETS. HRD-sum was calculated as a sum of the numbers of telomeric imbalances, large-scale transitions and genome-wide losses of heterozygosity. Calculating each score was iteratively optimized to improve detection of the scars using MSK-IMPACT targeted sequencing data using patient-matched WES data from 1841 tumors as reference. Germline mutations were identified by a clinically validated pipeline and annotated for pathogenicity using ClinVar. After excluding low quality tumors, 27,375 patients were retained for analysis. “HRD-positive” tumors are those with gBRCA1/2 mutations, loss of wild type, and an HRD-sum score >=42. Results: Expectedly, gBRCA1/2 mutations were more frequent in BRCA-assoc. cancers (7.2%, 558 of 7,737 patients) compared to non-BRCA-assoc. cancers (2.6%, 500 of 19,638) (p=5e-60). Among non-BRCA-assoc. cancers, gBRCA1/2 were most common in esophagogastric (3.9%), lung (3%), hepatobiliary (2.9%), and bladder (2.8%) cancers. Although biallelic loss in gBRCA1/2 patients was sig. higher in BRCA-assoc. cancers (80% vs. 37% in non-BRCA-assoc.), several cancer types showed high rates of loss of wild-type including gBRCA1 tumors in hepatobiliary (5/5) and endometrial (10/11) cancers. HRD-sum scores in all gBRCA1/2 biallelic tumors were sig. higher (median 58) compared to monoallelic (26) or wild-type (25) tumors. Notably, the non-BRCA assoc. cancers with biallelic gBRCA1/2 harbored higher HRD-sum scores compared to monoallelic (median 51 vs. 22, p<0.0001). These include cancer types such as endometrial (64 vs. 37, p= 0.0014) and esophagogastric (62 vs. 45, p=0.0017). In all, 68% of gBRCA1/2 patients in BRCA-assoc. cancers showed HRD-positivity. Interestingly, 18% (91/500) of gBRCA1/2 patients in non-BRCA-assoc. cancers also showed HRD-positivity. These included 52% of esophagogastric, 28% of lung, and 22% of bladder cancer patients with gBRCA1/2. Conclusion: Using a robust measure to detect HRD scars from MSK-IMPACT panel data, we demonstrate evidence for BRCA-mediated tumorigenesis in an expanded spectrum of cancers with potential therapeutic relevance. Citation Format: Daniel M. Muldoon, Miika Mehine, Samuel Tischfield, A. Rose Brannon, Marc Ladanyi, Zsofia K. Stadler, David B. Solit, Alexander Drilon, Michael F. Berger, Yonina Murciano-Goroff, Chaitanya Bandlamudi. Pan-cancer analysis identifies signatures of HRD-positivity in germline BRCA1/2 mutated non-BRCA associated cancers [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 1757.