Uniform processing of diverse sequencing data: A cross-population comparison of colon cancer genomic landscapes from The Cancer Genome Atlas and a Chinese cohort.

Background: Xuanwei County in Yunnan Province is one of the regions with the highest lung cancer mortality rates in China, the mortality rate in female lung cancer ranks first in China. Our previous study identified a higher mutation frequency of KRAS (25%) and EGFR uncommon mutations (56.4%) in a Xuanwei cohort compared to a large cohort of Chinese patients(pts) with non-small cell lung cancer (NSCLC) (n=1200). Tumor mutation burden (TMB) is a predictive biomarker for immune checkpoint inhibitors in NSCLC. The aim of this study was to explore gene mutations and the correlation with TMB in Xuanwei NSCLC pts. Materials and Methods: Formalin-fixed, paraffin-embedded (FFPE) tumor samples and matched blood samples of 111 Xuanwei NSCLC pts were collected for 450 cancer gene next-generation sequencing (NGS) targeted panel assay. Genomic alterations (GAs), including single base substitution, short and long insertion/deletions, copy number variations, gene fusions, and rearrangements, and TMB values were assessed with a mean coverage of 1000X. Results: Tumor samples were lung adenocarcinoma (LUAD) (n=99, 89.2%), lung squamous cell carcinoma (LUSC) (n=6, 5.4%), or others (n=6, 5.4%). The cohort included 58 males (52.3%) and 53 females (47.7%) with a median age of 54 years (range 36-78). In total, 73.8% of the pts had one or more actionable GAs. The most common were TP53 (51%), EGFR (49%), KRAS (28%), LRP1B (26%), SPTA1 (23%), NF1 (18%), MED12 (14%), RBM10 (14%), and KMT2C (13%). TMB high (TMB-H) (≥10 muts/Mb) was seen in 58.5% (65/111) of the Xuanwei cohort compared with 29.4% of the Chinese cohort(P <0.001), and the Xuanwei cohort had a higher median TMB than the Chinese cohort (13.1 vs 4.6 muts/Mb, respectively, P <0.001). A higher TMB was associated with higher age, and TMB was higher in males and current/former smokers. Genomic alterations associated with TMB were analysised. Among the common actionable mutations. KRAS mutation cases had a higher median TMB than KRAS wildtype (21.1 vs 9.6 muts/Mb, respectively, P <0.01). TMB-H was seen in 80.6% (25/31) of the Xuanwei KRAS mutation cohort. KRAS G12C (61.3%, 19/31) was the most common mutation and these cases showed lower TMB than non-KRAS G12C cases (P<0.05). EGFR mutations were significantly adversely correlated with TMB (P <0.001). Tumors with the common mutations in EGFR showed significantly lower TMB than those with the uncommon mutations in EGFR (P <0.01). TP53, LRP1B, SPTA1, NF1, and KMT2C mutations frequently occurred in NSCLC pts and were significantly positively correlated with TMB(p<0.001, p<0.001, p<0.001, p<0.001, and p<0.001, respectively). Conclusions: The Xuanwei NSCLC cohort had a higher median TMB than the Chinese NSCLC cohort. KRAS, TP53, LRP1B, SPTA1, NF1, and KMT2C mutations positively correlated with TMB while EGFR mutations were significantly adversely correlated with TMB. NGS revealed potential immunotherapy biomarkers for Xuanwei NSCLC pts. Citation Format: Yinqiang Liu, Jin Liang, Juan Zhao, Shuirong Zhang, Shiyue Zhang, Yunfei Shi, Ruoshan Huang, Xiaojie Wang. The impact of genomic mutational status and correlation with tumor mutation burden in non-small cell lung cancer of Xuanwei, Yunnan Province, China [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5885.

With the rapid advancement of immune therapy on cancer treatment, there is an increasing demand for accurate and comprehensive profile of tumor immunogenomics landscape in order to broaden our knowledge on predicting patient response as well as to facilitate drug development process. We established a cloud based analytical platform to comprehensively characterize genomic features that are potentially related to patients’ responses to immunotherapy. We implemented a neoantigen prediction pipeline based on whole exome sequencing (WES) and transcriptome sequencing data that integrates accurate HLA typing based on WES, somatic variant detection/phasing, RNA expression, class I MHC binding prediction as well as peptide epitope ranking. Among that, the HLA typing pipeline was validated using 73 Chinese and Japanese subjects covering >60 known class I HLA alleles with an accuracy above 95%. In addition, we also developed and validated methods to compute microsatellite instability (MSI) and tumor mutation burden (TMB) based on either a 600 gene panel or WES. Thirdly, this platform also enables the detection of HLA somatic variants and loss of heterozygosity events based on WES data. Next, we applied this analysis platform to process 127 samples across four cancer types (colon, rectal, endometrial and gastric) from TCGA as well as two Chinese cohorts of 100 non-small cell lung cancers and 30 esophageal squamous cell carcinomas sequenced at WuXi NextCODE. Within the TCGA cohort, the data reveals that patients with MSI High status produces significantly more neoantigens than patients with MS Stable status (7.06±4.60 vs 0.71±0.64, p = 7.65e-16, neo-peptides per Mb). Number of neopeptides predicted from each frameshift event is significantly higher than that from each missense mutation (1.30±1.56 vs 0.58±0.54, p = 2.86e-11, neo-peptides per Mb). We also observed strong correlation between TMB and neoantigen burden across multiple cancer types. In conclusion, we have developed a immunogenomics solution that captures tumors’ TMB, MSI, neoantigen as well as deleterious events associated with their HLAs. This platform will allow more comprehensive molecular features assessed to potentially improve the prediction of patients’ response to immune therapy. Citation Format: Jie Wang, Ao Li, Jiawei Wang, Zhaoze Cheng. A comprehensive immunogenomics profiling platform enables the exploration of the intricate relationship between TMB, MSI, Neoantigen and HLA status among multiple cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 754.

Ovarian cancer is one of the most lethal gynecologic malignancies, primarily due to its late-stage diagnosis and intrinsic tumor heterogeneity. Histologically, epithelial ovarian cancer (EOC) accounts for approximately 70% of cases and exhibits distinct molecular and clinical characteristics. High-grade serous ovarian cancer (HGSOC), the most aggressive form of EOC, stands out for its widespread genomic instability and poor prognosis. Copy number variations (CNVs) play a critical role in tumor heterogeneity, treatment resistance, and disease progression. While CNVs have been extensively studied using bulk sequencing approaches, their spatial heterogeneity within tumors remains underexplored. To investigate this, we integrated spatial transcriptomics (10x Genomics Visium Spatial) with whole-exome sequencing (WES) in 24 fresh-frozen HGSOC samples. This dual approach enabled us to validate CNV patterns inferred from spatial data while leveraging WES for a genome-wide view of CNVs. First, spatial transcriptomics data were processed using the Space Ranger pipeline (10x Genomics) to generate spatially resolved gene expression matrices. Tumor purity scores were estimated using the R package ESTIMATE, and were then used to inform CNV inference with the tool InferCNV. This analysis revealed varied CNVs across spatial domains, indicating intratumoral heterogeneity and the existence of subclones with distinct CNV profiles and spatial niches. We further resolved loss of heterozygosity (LOH) in these samples using the R package tLOH. Clonal LOH of chr 17p, encompassing the TP53 locus, was detected in several samples. Pseudotime and spatial trajectory analysis confirmed that chr17 LOH is an early event in the trajectory of CNV development. To validate the CNV and LOH patterns inferred from spatial transcriptomics, we performed WES on paired tumor and normal tissues from the same cohort. WES data were first aligned to the human reference genome GRCh38 using BWA, followed by CNV profiling with GATK CNV. Recurrent CNV patterns, including gains on chromosomes 1q, 3q, 6p, 8q, and 20q, and losses on chromosomes 4, 5q, 6q, 9p, 13q, 14q, and 17, were observed, consistent with previous reports. A comparison between spatially inferred CNV clusters and GATK CNV results showed strong concordance, further validating the robustness of spatial CNV inference. Interestingly, germline BRCA-mutated samples exhibited a higher frequency of CNVs than BRCA wild-type samples, suggesting a link between BRCA status and genomic instability. By placing CNVs in tissue context, our findings highlight the genetic and spatial heterogeneity of HGSOC, and enhance our understanding of the driving role of CNVs in tumor evolution and growth. This abstract was developed with the assistance of generative AI to revise and clarify the text. Citation Format: Yuxin Jin, Jing Qian, Michelle G. Webb, David W. Craig, Lynda Roman, John D. Carpten, Rania Bassiouni. Multi-omics characterization of copy number variation in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5359.

Introduction: Currently NGS techniques are being widely used as a tool in routine oncology workflows. Majority of labs use either DNA based small hotspots panels or two separate DNA and RNA panel. Unfortunately, this methodology can lead to an incomplete mutation profile because it lacks comprehensive tumor screening for theranostics. Many heterogeneous tumors carry multiple mutations and gene function can be altered by several types of variations including SNVs, CNV’s, Indels, SV’s and GF’s. Recently, it has been shown by various studies that TMB and MSI can correlate with a cancer patient’s responsiveness to checkpoint inhibitor immunotherapy. These findings have stimulated a widespread interest in the development of cost-effective assays that accurately measure TMB and MSI along with somatic variants. Here we assess whether TMB measured through NGS of a 1.9 MB-523-gene panel correlates with that determined through Foundation one CDx panel. We also assess and compare the accuracy of determining the MSI status of multiple cancers through sequencing a 523-gene targeted DNA panel vs MSI by PCR or MMR by immunohistochemistry. The assay is a targeted next-generation sequencing (NGS) assay designed to detect genetic alterations in 523 genes for SNVs, CNV’s, Indels, and SV’s & 55 genes for fusion and splice variant detection. Assessment of GF’s, SV’s, SNVs, CNV’s, TMB and MSI in one assay using DNA and RNA creates efficiencies in sample usage, time, and cost. Methods: The validation was guided by the joint consensus recommendation for validation of NGS assays by the AMP, CAP & NYSDOH. The validation included evaluations of precision, analytic sensitivity, analytic specificity, accuracy, reportable range, and reference range. RNA and DNA from of 100 samples (mixture of known patient specimens, known CAP proficiency specimens as well as known synthetic reference standards {Accormetrix hotspot DNA panel Seracare CNV DNA panel, & Seracare fusion V2 panel}) was used. These clinical samples were earlier tested on gold standard orthogonal methods like PCR, FISH, CDx NGS, and karyotype ( n=100 clinical and reference materials formalin-fixed, paraffin-embedded (FFPE) tumor samples from lung, GI, skin, CNS, breast, kidney, uterus, ovarian, salivary, thyroid gland tumors, soft tissue & bone cancer etc. Libraries for were prepared using the Illumina TruSight Oncology 500 (TSO500+) kit and sequenced on NextSeq 550. Sequencing analysis, variant, TMB and MSI calling were performed using software provided by illumina. Results: We were able to validate manufacture's analytical claims for all the variants groups including TMB and MSI in our validation. Conclusions: DNA and RNA libraries are prepared in parallel, sequenced, and analyzed simultaneously for efficient assessment of numerous types of somatic variants. We anticipate that this approach of obtaining high-resolution data from an FFPE samples at reduced sequencing cost, will facilitate testing in different malignancies which was not previously possible especially for determination of TMB and MSI. Note: This abstract was not presented at the meeting. Citation Format: Ravindra Kolhe, Pankaj Ahluwalia, Saleh Heneidi, Sudha Ananth, Vamsi Kota, Ashis Mondal. Guideline adherent clinical validation of a comprehensive DNA/RNA panel (523 genes-TruSight Oncology 500) for determination of single nucleotide variants (SNV’s), small insertions or deletions (Indels), copy number variations (CNV’s), splice variations (SV’s), gene fusions (GF’s), tumor mutation burden (TMB) and micro-satellite instability (MSI) on anext-generation sequencing (NGS)platform in a CLIA setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-227.

Introduction: Recently, it has been shown by various studies that tumor mutation burden (TMB) can correlate with a cancer patient's responsiveness to checkpoint inhibitor immunotherapy. These findings have stimulated a widespread interest in the development of cost-effective assays that accurately measure TMB. Here we assess whether TMB measured through next-generation sequencing (NGS) of a 2-megabase 500-gene panel correlates with that determined through whole exome sequencing (WES). We further investigate whether sequencing tumor samples alone combined with a germline filtering and background noise removal algorithm can measure TMB accurately compared with sequencing of tumor-normal pairs. Experimental Method: WES data of tumor and subject-matched normal DNA were either downloaded from The Cancer Genome Atlas (TCGA) or generated in-house. A 500-gene targeted DNA sequencing panel, which includes various cancer-relevant genes and covers two megabases, was also developed in-house. TMB was calculated as mutations (single nucleotide variants, insertions, and deletions) per megabase. Data Summary: Using downloaded TCGA data from 2,385 subjects across colon, lung and melanoma cancer types, TMB was measured using tumor-normal WES or the in-silico-filtered tumor-only 500-gene panel and the two approaches correlated linearly (R2 = 0.96). Furthermore, we demonstrated that the targeted panel achieved >90% sensitivity and >85% specificity when classifying TMB-high and low tumor samples at the cutoff of 15 compared to the same TCGA data. TMB as determined from tumor-only WES was also analyzed using computational germline-filtering and background noise-removal to demonstrate excellent concordance with WES of tumor-normal pairs. To further validate these findings, by analyzing WES data and 500-gene panel targeted NGS data of >45 subjects generated in house. Through interrogating the 500-gene NGS data, we found that TMB determined using tumor-only sequencing was also similar from that ascertained through tumor-normal pairs. Of interest, further analysis showed that TMB determined from the 500-gene panel data using tumor-only sequencing along with germline filtering and background noise removing was comparable to that calculated from WES of tumor-normal pairs. Conclusion: Collectively, our data demonstrates that TMB determined from NGS of a two megabase DNA region utilizing a 500 gene panel correlates strongly with TMB measured through WES, with a sensitivity of >90% and a specificity of >85%. In addition, sequencing tumor samples alone combined with bioinformatic germline-filtering and background noise-removal was similar to sequencing subject-matched normal DNA. These findings support the use of a 500 gene panel for accurate measurement of TMB while the addition of bioinformatics enables tumor-only sequencing. Citation Format: Alex Steven So, Shannon Kaplan, Chen Zhao, Shile Zhang, Li Liu, Phillip Le, Raakhee Vijayaraghavan, Tingting Jiang, Sven Bilke, Traci Pawlowski, Karen Gutekunst. Accurate measurement of tumor mutation burden through tumor-only sequencing using a 500-gene panel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 435.

Genetic variants such as copy number variation (CNV), microsatellite instability (MSI), and tumor mutation burden (TMB) have been reported to associate with the immune microenvironment and prognosis of patients with breast cancer. In this study, we performed an integrated analysis of CNV, MSI, and TMB data obtained from The Cancer Genome Atlas, thereby generating two genetic variants-related subgroups. We characterized the differences between the two subgroups in terms of prognosis, MSI burden, TMB, CNV, mutation landscape, and immune landscape. We found that cluster 2 was marked by a worse prognosis and lower TMB. According to these groupings, we identified 130 differentially expressed genes, which were subjected to univariate and least absolute shrinkage and selection operator-penalized multivariate modeling. Consequently, we constructed an 11-gene signature risk model called the genomic variation-related prognostic risk model (GVRM). Using ROC analysis and a calibration plot, we estimated the prognostic prediction of this GVRM. We confirmed the predictive efficiency of this GVRM by validating it in another independent International Cancer Genome Consortium cohort. Our results conclude that an 11-gene signature developed by integrated analysis of CNV, MSI, and TMB has a high potential to predict breast cancer prognosis, which provided a strong rationale for further investigating molecular mechanisms and guiding clinical decision-making in breast cancer.

Introduction: Breast cancers (BCs) with microsatellite instability (MSI)/DNA mismatch repair (MMR) deficiency are rare. Their identification is key, given that these tumors might be sensitive to immune checkpoint blockade. Here we sought to define the characteristics of primary and metastatic MSI-high (MSI-H) BCs using massively parallel sequencing. Materials and methods: To define MSI, MSISensor was applied to MSK-IMPACT targeted sequencing data of 918 primary BCs (pBCs) and 1,000 metastatic BCs (mBCs), and MSISensor and MANTIS to whole-exome sequencing (WES) data of 1,084 pBCs from The Cancer Genome Atlas (TCGA) BC project. BCs were classified as MSI-H if they displayed an MSISensor score ≥3.5 for WES or ≥10 for targeted sequencing data, or a MANTIS score ≥0.4 for WES data. The dominant mutational signature was inferred using SigMA in cases harboring at least 5 single nucleotide variants (SNVs). Mann-Whitney U and Fisher’s exact t-tests were employed for statistical analyses. Results: MSISensor classified 0.3% (3/903) of pBCs and 0.3% (3/965) of the mBCs subjected to MSK-IMPACT sequencing as MSI-H. The MSI-H pBCs were invasive ductal carcinomas (IDC), preferentially ER-positive/HER2-negative (66.6%). Compared to MSS pBCs, MSI-H pBCs displayed a higher tumor mutational burden (TMB; 11.2 vs 2.6 somatic mutations) and were enriched for dominant MMR mutational signatures 20 or 26 (33% vs 1.1%). MSI-H mBCs were all ER-positive/HER2-negative IDCs, displayed similar TMBs, percentage of small insertions and deletions (indels) and fraction of the genome altered (FGA) as compared to MSS mBCs. Only one of the three MSI-H mBCs had enough SNVs for inference of a dominant mutational signature, which was aging. MSISensor and MANTIS classified 1.5% (11/735) and 1.8% (15/836) of pBCs from TCGA as MSI-H. We observed a moderate agreement between MSISensor and MANTIS (Cohen’s Kappa = 0.552) with 1% (7/735) of pBCs being classified as MSI-H by both algorithms. pBCs from TCGA classified as MSI by either MSISensor or MANTIS were IDCs (90.9% and 85.7%, respectively) and invasive lobular carcinoma (ILC; 9.1% and 14.3%, respectively), and were either ER-positive/HER2-negative (45.5% and 42.9%, respectively) or ER-negative/HER2-negative (45.5% and 42.9%, respectively). These MSI-H pBCs (TCGA) displayed a higher TMB (MSISensor: 12.7 vs 0.8; MANTIS: 3.6 vs 0.8; both P<0.01), percentage of indels (MSISensor: 8.2% vs 4.7%; MANTIS: 8.1% vs 4.8%, both P<0.01) and were enriched for dominant MMR mutational signatures 15, 20 or 26 (MSISensor: 63.6% vs 1.4%, MANTIS: 46.7% vs 1.2%, both P<0.01) than MSS pBCs. pBCs from TCGA classified as MSI by both MSISensor and MANTIS were IDCs (85.7%) and ILCs (14.3%), and were preferentially ER-positive/HER2-negative or ER-negative/HER2-negative (42.9%, each). Compared to MSS pBCs, MSI-H pBCs from TCGA displayed a higher TMB (17.4 MSI-H vs 0.8 MSS; P<0.01), percentage of indels (12.1% MSI-H vs 4.7% MSS; P<0.01) and an enrichment for dominant MMR mutational signatures 15, 20 or 26 (87.5% MSI-H vs 1.4% MSS; P<0.01). Conclusions: We observed a moderate agreement between different MSI detection algorithms in the classification of pBCs as MSI-H based on WES analysis. pBCs classified as MSI-H were of common histologic types, either ER-positive/HER2-negative or ER-negative/HER2-negative, and displayed features characteristic of MSI, including a high TMB, high percentage of indels and an enrichment for MMR deficiency mutational signatures. mBCs classified as MSI-H by targeted capture sequencing were found to be of ER-positive/HER2-negative phenotype. Citation Format: Pier Selenica, Fresia Pareja, Lorenzo Ferrando, David N Brown, Nadeem Riaz, Britta Weigelt, Joshua Z Drago, Mark E Robson, Pedram Razavi, Sarat Chandarlapaty, Jorge S Reis-Filho. Massively parallel sequencing analysis of microsatellite instability in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-01.

e18533 Background: While the immune checkpoint blockades had demonstrated promising benefits in head and neck cancer (HNSC), its clinical efficacy is limited to a selected subset of less than 20% HNSC patients. Tumor mutation burden (TMB) has been reported as a predictor for ICBs in multiple tumors, including HNSC. However, the association of driver genes with TMB and outcomes in patients with HNSC has not yet been established. Methods: Somatic mutation landscape was characterized by interactively analyzed the sequencing data of 495 HNSC samples obtained from The Cancer Genome Atlas (TCGA) database and 185 samples from a Chinese cohort (Geneplus-database). Hybrid capture of a 1021 gene panel with potential clinical relevance was performed on tumor and paired Peripheral blood lymphocytes (PBLs) from 185 HNSC samples in a Chinese cohort. Results: In the Chinese cohort, patients harboring ≥5 muts/Mb (the top quartile of tTMB distribution) were classified as the TMB-H group; while ≥4.7 muts/Mb were classified as the TMB-M group. TMB -H was associated with better OS in the TCGA cohort. The rest were classified as TMB-L patients. Thirteen aberrant genes were significant correlation with TMB-H, including TSC2, POLE, CDK4, TSC1, MLH1, PTCH1, NF1, MSH3, RAD50, MSH2, CDH1, TNFRSF14, TERC. Among them,10 were further verified in the TCGA Head and Neck Cancer cohort, including TNFRSF14, MSH3, NF1, TSC2, RAD50, MSH2, PTCH1, POLE, MLH1, TSC1. Moreover, aberrant genes such as CDH1, MSH2 and RAD50 implicated better DFS (DFS:HR = .296, p = .034; HR = 0.128, p = .016; HR = .0422, p = .043) in HNSC of the TCGA cohort. Transcriptomic analysis in the TCGA Head and Neck Cancer cohort showed various degrees of immune upregulation in the tumor microenvironment (TME) in CDH1, MSH2, and RAD50 mutated population. Conclusions: These findings indicated that CDH1, MSH2, and RAD50 mutations may be associated with TMB-H, immuno-upregulation in TME and better survival outcomes. Combined with TMB, genes mentioned above may give us some insights into how ICB therapeutic strategies assist natural host immune responses against HNSC in Chinese population.

Objective There are no well-defined genetic indicators for distant metastatic illness in patients with colon cancer (CC). The discovery of genetic changes linked to metastatic CC might aid in the development of systemic and local therapeutic approaches. Using The Cancer Genome Atlas (TCGA), we examined the relationship between copy number variation (CNV) of SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily C member 1 (SMARCC1) and distant metastatic illness in patients with CC. Methods Genetic sequencing data of all relevant CC patients and clinical features were collected from TCGA using R. There were 506 CC patients with CNV and clinical outcome data. The CNV of SMARCC1 was examined for its correlation with distant metastatic disease using the TCGA CC dataset (M1 vs. M0). After adjusting for age, sex, T stage, N stage, adjuvant chemotherapy, microsatellite instability (MSI), and surgical margin status, univariate and multivariate logistic regression analyses were performed. Results SMARCC1 CNV was linked to distant metastatic disease (P = 0.012 and 0.008 in univariate and multivariate analysis, respectively); positive lymph nodes and margin status were also associated with distal metastases (all P < 0.01). MSI, T stage, N stage, adjuvant treatment, sex, race, and MSI were not associated with metastases (all P > 0.05). Conclusion SMARCC1 CNV is associated with distant metastatic disease in patients with CC. In individuals with CC, such genetic profiles might be utilized therapeutically to support optimal systemic treatment options against local treatments for CC, such as radiation therapy, pending additional confirmation.

BackgroundHistorically, the molecular classification of colorectal cancer (CRC) was based on the global genomic status, which identified microsatellite instability in mismatch repair (MMR) deficient CRC, and chromosomal instability in MMR proficient CRC. With the introduction of immune checkpoint inhibitors, the microsatellite and chromosomal instability classification regained momentum as the microsatellite instability condition predicted sensitivity to immune checkpoint inhibitors, possibly due to both high tumor mutation burden (TMB) and high levels of infiltrating lymphocytes. Conversely, proficient MMR CRC are mostly resistant to immunotherapy. To better understand the relationship between the microsatellite and chromosomal instability classification, and eventually discover additional CRC subgroups relevant for therapeutic decisions, we developed a computational pipeline that include molecular integrative analysis of genomic, epigenomic and transcriptomic data.ResultsThe first step of the pipeline was based on unsupervised hierarchical clustering analysis of copy number variations (CNVs) versus hypermutation status that identified a first CRC cluster with few CNVs enriched in Hypermutated and microsatellite instability samples, a second CRC cluster with a high number of CNVs mostly including non-HM and microsatellite stable samples, and a third cluster (7.8% of the entire dataset) with low CNVs and low TMB, which shared clinical-pathological features with Hypermutated CRCs and thus defined Hypermutated-like CRCs. The mutational features, DNA methylation profile and base substitution fingerprints of these tumors revealed that Hypermutated-like patients are molecularly distinct from Hypermutated and non-Hypermutated tumors and are likely to develop and progress through different genetic events. Transcriptomic analysis highlighted further differences amongst the three groups and revealed an inflamed tumor microenvironment and modulation Immune Checkpoint Genes in Hypermutated-like CRCs.ConclusionTherefore, our work highlights Hypermutated-like tumors as a distinct and previously unidentified CRC subgroup possibly responsive to immune checkpoint inhibitors. If further validated, these findings can lead to expanding the fraction of patients eligible to immunotherapy.

Bevacizumab (BV) plus chemotherapy is broadly used in advanced ovarian cancer (OC). However, the efficacy of BV-based regimens for advanced OC patients is not satisfactory. Therefore, it is urgent to explore the predictive genetic biomarkers for BV.Tumor tissues from advanced OC patients receiving BV-based regimens were analyzed with a 150-gene targeted panel for next generation sequencing. The associations between gene alterations or clinicopathology features and progression-free survival (PFS) were analyzed by Kaplan–Meier curves or Cox regression. The association of the genetic alteration in potential predictive genes and expressions of 11 vascular endothelial growth factor-related genes were analyzed in The Cancer Genome Atlas cohort using 292 OC cases.Sixty two Chinese advanced OC patients treated with BV-based therapy were included. The median PFS of was 6.9 months, and objective response rate was 14.5%. In multivariate Cox regression analysis, the status of endothelial growth factor receptor (EGFR) (hazard ratio = 6.39, 95% confidence interval [CI] 2.25–18.13, P < .001) and human epidermal growth factor receptor 2 (HER2) (hazard ratio = 3.58, 95% CI 1.27–10.08, P = .016) were significantly correlated with PFS. MYC Proto-Oncogene amplification seemed to have a positive trend (hazard ratio = 0.21, 95% CI 0.05–1.02, P = .052). Moreover, EGFR and HER2 alterations were not prognostic factors of overall survival for OC in The Cancer Genome Atlas OC cohort. The vascular endothelial growth factor-related signature analysis indicated vascular endothelial factor A expression was upregulated with EGFR alterations (P = .034) which may be involved in BV resistance, and HER2 alterations were associated with hypoxia inducible factor 1 subunit alpha overexpression significantly (P = .029).EGFR or HER2 alterations are negative predictors of PFS for OC patient treated with BV plus chemotherapy. Therefore, the clinicians may consider to use alternative regimens such as anti-EGFR or anti-HER2 targeted therapy instead of BV-based regimens on these patients when standard care fail.

Background: The current standard of genomic profiling of cancer tissues relies upon multiple separate technologies to aid in tumor characterization. Here we describe an NGS panel and analysis workflow for cancer samples that can detect single nucleotide polymorphisms (SNPs), insertions and deletions (INDEL), somatic copy number alterations (SCNAs), and translocations (TLs), Tumor Mutation Burden (TMB) and Microsatellite Instability (MSI) in a single assay. Methods: We have developed a SureSelect target enrichment sequencing panels for comprehensive profiling of single nucleotide variations (SNP/INDEL), gene copy number variations (CNV), and DNA translocations (TL) and relevant microsatellite regions in a single assay. The TMB panel gene list was curated based on genes found in cancer gene databases such as Clinical Interpretations of Variants in Cancer (CIViC), Cancer Genome Interpreter (CGIdb), Catalog of Somatic Mutations in Cancer Census (COSMIC), Precision Oncology Knowledge Base (OncoKB). An accompanying data analysis pipeline will provide highly sensitive and accurate detection of variants and allows for the determination TMB and MSI status. Probes have been selected for over 500 genes to detect SCNAs and translocation in several cancer subtypes. The probes are optimized with the SureSelect XTHS protocol, which enables sensitive and accurate detection of rare mutation events within a heterogeneous sample with molecular barcode-mediated error correction. The SCNAs probes target regions in the genome that help in decreasing the noise for SCNAs calling. The data analysis utilizes either a matched normal or standard control DNA to compute read depth log ratios. Aberrant regions of constant ploidy are first identified followed by the application of a variational streaming algorithm on log ratio and SNP allele frequencies to determine the major clones present in the tumor. Translocation detection was verified on lung cancer samples by analyzing split reads across the fusion breakpoints. Results: By diluting samples with known copy-number aberrations into normal DNA, a limit of detection of ⇐2.3 copies/cell was demonstrated, equivalent to the detection of 3 copies at 30% tumor fraction. A similar approach demonstrated an ability to detect EML4-ALK and SLC24A2-ROS1 translocations at 3% allele frequency. Performance of the assay was further evaluated using 100+ FFPE samples harboring rearrangements, gene amplifications, and SNP/Indels. Concordance to the reference methods (FISH, WES, WGS) was &amp;gt;90%. TMB and MSI algorithms were benchmarked using in silico analysis of TCGA data and performance of the assay was evaluated on FFPE samples with orthogonally-determined MSI/TMB status. Conclusions: This work represents an important advancement in the development of a single assay to detect copy number variation, DNA rearrangement and mutations, TMB and MSI status of a FFPE sample. Citation Format: Arjun Vadapalli, Akanksha Khare, Hanjun Shin, Ashutosh Ashutosh, Linus Forsmark, Anne Lucas, Scott Happe, Gilbert Amparo, Carlos Pabon, Jayati Ghosh, Tracy Liu, Jimmy Jin, Mike Ruvolo, Douglas Roberts. SureSelect sequencing panels and algorithms to detect copy number variations (CNVs), DNA rearrangements, microsatellite Instability and tumor mutational burden (TMB) in FFPE specimens [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 184.

11605 Background: With the broadening landscape of immunotherapy use, it is important to identify patients who are likely to benefit from the therapy. We reported the comprehensive analyses of potential predictive biomarkers for PD1/PD-L1 inhibitors based on Chinese patients’ exome profiling data. Methods: Over 1,000 cancer patients from 70 hospitals across 20 provinces in China were recruited and the whole exome of tumor/normal samples of each patient were sequenced. Four potential genomic biomarkers: tumor mutation burden (TMB), mismatch repair deficiency (MMR), microsatellite instability (MSI), and PD-L1 (CD274) amplification (PD-L1 AMP) were analyzed in this Chinese cohort and compared with the mainly Caucasian cohort in TCGA database. Results: At least one of the four preselected genomic biomarkers was identified in 40.8% of this Chinese cancer patient cohort by clinical whole exome sequencing (CWES) analysis. Similar to TCGA cohort, the top 3 high TMB tumor types are lung, esophagus and colorectal cancer. Chinese hepatocellular carcinoma (HCC) patients showed higher TMB than the TCGA cohort (Median: 106 vs. 65 non-synonymous mutations per tumor NMT), which might be due to different etiologies. Five late stage cancer patients (3 lung, 1 melanoma and 1 gallbladder) using PD1/PD-L1 blockade with high TMB showed durable clinical benefit (SD≥6months/PR/CR). Comparing with TCGA data, Chinese colorectal cancer cohort (252 patients) had relative lower MSI-high or MMR related mutations (8.33% vs. 12.5%, and 3.97% vs. 10.0% respectively). PD-L1 AMP most frequently occurred in lung squamous (14.3% VS 9.8% TCGA), HER2-positive breast cancer (8.8% VS 6.8% TCGA with unknown HER2 status) and sarcoma (6.0% VS 9.4%TCGA). One Chinese renal cell carcinoma patient with PD-L1 AMP received anti-PD-1 treatment and on-going PFS is 7 months by far. Conclusions: Our CWES analysis and limited clinical follow-up observations suggested that about 40% Chinese cancer patients had at least one of the 4 potential immunotherapy predictive biomarker mutations. Long-term follow-up is needed to verify the validity of those markers.

When should we order a next generation sequencing test in a patient with cancer?

Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.