Catalogue Of Somatic Mutations In Cancer Research Articles

Abstract SY36-01: Somatic evolution, cancer, and our inevitable decline with age: Inextricably linked

Abstract Why do we get cancer? Why is cancer highly associated with old age? Aging is associated with the accumulation of more mutations; some of which can contribute to cancer phenotypes. However, we now understand that carcinogenesis is much more complex than originally appreciated. In particular, there are tissue environmental forces that both impede and promote cancer evolution. Just as organismal evolution is known to be driven by environmental changes, cellular (somatic) evolution in our bodies is similarly driven by changes in tissue environments, whether caused by the normal process of aging, by lifestyle choices, or by extrinsic exposures. Environmental change promotes selection for new phenotypes that are adaptive to the new context. In our tissues, aging or insult-driven alterations in tissues drives selection for adaptive mutations, and some of these mutations can confer malignant phenotypes. To better understand the evolutionary forces that control somatic cell evolution, we used mouse models of cancer initiation, mathematical models of cellular evolution, and analyses of human tissue samples. We have shown that aging- and inflammation-dependent changes in stem cells and their tissue environments dramatically dictate whether cancer-causing mutations are advantageous to stem cells in our tissues, starting the cells down the path to cancer and deepening our insight into cancer risk. Recent studies from many labs have shown how as we age our tissues become dominated by clones bearing mutations in known cancer-associated genes. I will present studies from our labs exploring how cigarette smoking and aging can alter mutational landscapes in the non-malignant lung. To observe somatic mutations in lung biopsies from individuals with different smoking histories, we used a rare-mutation detection technique called Duplex Sequencing to analyze somatic variants from over 200 lung samples, including from subjects from the BDRE (Colorado), PEACE, and TRACERx cohorts. Using this method, we have identified large numbers of mutations in each brushing or biopsy, many of which are cataloged in the Catalogue Of Somatic Mutations In Cancer (COSMIC), and most of these are predicted to disrupt protein function. We also observe pervasive positive selection acting on mutations in many but not all of the cancer-associated genes, with different patterns of selection in the lungs of ever-smokers and never-smokers. Ongoing studies are using primary human and mouse lung epithelial cultures and mouse models to study how these mutations interact with smoking and age to alter associated clonal expansions, tissue integrity, and malignant progression. We propose a model whereby aging and microenvironmental changes induced through lifestyle choices like smoking can promote selection for cells with adaptive mutations, which can contribute to not only cancer risk but also tissue aging. Thus, while young tissues impede selection for such adaptive mutations, old age is associated with a feed-forward loop of aging tissue-mediated selection for mutant clones that then increase tissue aging. Thus, understanding the forces controlling clonal selection as we age and due to lifetime exposures could be critical for controlling multiple diseases of old age. [EJE, EL and FM contributed equally.These studies were led by CS and JD.] Citation Format: Edward J. Evans, Emilia Lim, Fabio Marongiu, Shi Biao Chia, William Hill, Clare Weeden, Oriol Pich, Andrew Rowan, Faiz Jabbar, Cristina Naceur-Lombardelli, Raju Veeriah, Moumita Ghosh, Daniel Merrick, York E. Miller, Robert Keith, Mariam Jamal-Hanjani, Charles Swanton, James V. DeGregori. Somatic evolution, cancer, and our inevitable decline with age: Inextricably linked [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY36-01.

Rev1 overexpression accelerates N-methyl-N-nitrosourea (MNU)-induced thymic lymphoma by increasing mutagenesis.

Rev1 has two important functions in the translesion synthesis pathway, including dCMP transferase activity, and acts as a scaffolding protein for other polymerases involved in translesion synthesis. However, the role of Rev1 in mutagenesis and tumorigenesis invivo remains unclear. We previously generated Rev1-overexpressing (Rev1-Tg) mice and reported that they exhibited a significantly increased incidence of intestinal adenoma and thymic lymphoma (TL) after N-methyl-N-nitrosourea (MNU) treatment. In this study, we investigated mutagenesis of MNU-induced TL tumorigenesis in wild-type (WT) and Rev1-Tg mice using diverse approaches, including whole-exome sequencing (WES). In Rev1-Tg TLs, the mutation frequency was higher than that in WT TL in most cases. However, no difference in the number of nonsynonymous mutations in the Catalogue of Somatic Mutations in Cancer (COSMIC) genes was observed, and mutations involved in Notch1 and MAPK signaling were similarly detected in both TLs. Mutational signature analysis of WT and Rev1-Tg TLs revealed cosine similarity with COSMIC mutational SBS5 (aging-related) and SBS11 (alkylation-related). Interestingly, the total number of mutations, but not the genotypes of WT and Rev1-Tg, was positively correlated with the relative contribution of SBS5 in individual TLs, suggesting that genetic instability could be accelerated in Rev1-Tg TLs. Finally, we demonstrated that preleukemic cells could be detected earlier in Rev1-Tg mice than in WT mice, following MNU treatment. In conclusion, Rev1 overexpression accelerates mutagenesis and increases the incidence of MNU-induced TL by shortening the latency period, which may be associated with more frequent DNA damage-induced genetic instability.

Abstract 5062: Evaluation of genetic mutations in non-small cell lung cancer patients

Abstract Lung cancers represent the second most common cancer and Non-Small Cell Lung Cancer (NSCLC) constitutes 80-85% of all lung cancers. Genes within several cellular pathways have been previously evaluated for their clinical impact in NSCLC. In this investigation, we evaluate genetic mutations found in 50 cancer-critical genes implicated in the signaling pathways RTK/RAS/MAP, TGFβ, PI3K, Wnt, GPCR, p53, JAK/STAT, Notch, and the cell cycle pathway. Some of these mutations have not yet been described or have not been described in NSCLC. The intent of our study is to evaluate these mutations and allow further research into their impact, specifically highlighting mutations that are involved in clinically important pathways. We evaluated mutations found in 59 NSCLC patients at the Prisma Health Cancer Institute. These mutations are part of 2,800 COSMIC (Catalogue of Somatic Mutations in Cancer) hotspot mutations in 50 cancer-critical genes. Each mutation was investigated further using the ClinVar database to identify whether it had been described in NSCLC or other cancers/conditions, its genetic consequence, pathogenesis, possible variations, and origin. A total of 73 unique mutations in 59 NSCLC patients were evaluated. Of the 73 mutations, 17 had not been described at all, 40 had been described in other cancers/conditions, and 16 had been previously described in NSCLC. The known mutations’ effects in other cancers/conditions were categorized as pathogenic, likely pathogenic, likely benign, benign, or uncertain. Novel mutations were found in genes that provide a druggable target, help predict treatment response, are under investigation for their ability to predict treatment response or confer additional clinical utility. Medical management of cancer has benefitted greatly from studies of genetic mutations. Most mutations identified in our patient population had not been described in NSCLC, and a smaller number of those had not been described at all. Further elucidation of these mutations may lead to additional discoveries relevant to NSCLC prognostication and treatment. Citation Format: Miles Rothstein, Phillip Broughton, Ella Markalunas, Avery Funkhouser, Lorie Allen, Julie Martin, W. Jeffery Edenfield, Anna V. Blenda. Evaluation of genetic mutations in non-small cell lung cancer patients [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 5062.

Abstract 7312: Construction of a gene panel for liquid biopsy-based diagnostics of gynecologic cancer

Abstract Background: Ovarian carcinoma (OC) is the leading cause of death from gynecologic cancers mainly due to late detection, where most patients are diagnosed at advanced stages (51% in stage III; 29% in stage IV). Despite an overall more favorable prognosis, endometrial carcinoma (EC) is the most common gynecologic cancer, with an increasing incidence and where some subtypes are associated with a poor prognosis. Identification of DNA mutations from precancerous lesions or early-stage OC and EC would allow for early intervention. Liquid biopsies through routine sampling such as endocervical sampling, or blood collection for isolation and analysis of ctDNA have previously been assessed for their use in detection of OC and EC. These studies have provided evidence that tumor-derived mutations can be detected in endocervical samples, supporting endocervical liquid biopsies as a potential source of ctDNA. Herein, we aimed to construct a diagnostic gene panel corresponding to common mutation profiles of OC and EC to detect early-stage malignancy through a non-invasive approach. Methods: Using the NGS-method, Simple multiplexed PCR-based barcoding of DNA for sensitive mutation detection using sequencing (SiMSen-Seq), a gene panel was constructed targeting hotspot mutations in known OC- and EC-associated genes. Hotspots were identified using the Catalogue of Somatic Mutations in Cancer (COSMIC) database or retrieved from the literature and assays were designed for amplification of short DNA fragments. Precise assay development was carried out including multiple steps of careful validation to ensure high specificity and efficient amplification. Individual assays were validated in multiple steps using qPCR and fragment analysis. Results: The gene panel was designed as two non-overlapping subunits for comprehensive diagnosis of OC and EC. The two constructed multiplexes, together composed of 125 single assays target genomic regions in 34 EC and OC-associated genes e.g., PTEN, TP53, PIK3CA and CTNNB1. Included assays had a median amplicon size of 92 bp (range 57-111 bp). Both multiplexes displayed good performance with distinguishable libraries at low DNA input (10 ng). Validation of individual assays showed high specificity and efficient amplification where >80% of assays displayed a sequencing coverage >500 UMI counts at a consensus depth of 3. Patient coverage calculations of COSMIC data suggested comparable coverage as similar published approaches. Conclusion: The results suggest that the constructed gene panel has great potential to detect mutations in liquid biopsies collected from the gynecologic tract, despite low tumor DNA levels. Validation of the two multiplexes by fragment analysis and sequencing showed high performance, hence, prospective for the approaching sequencing of liquid biopsies. Citation Format: Sara Schumacher, Therese Carlsson, Jacob Malchau Lauesgaard, Anna Linder, Amanda Olsson Widjaja, Karin Sundfeldt. Construction of a gene panel for liquid biopsy-based diagnostics of gynecologic 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 7312.

Identification of germline population variants misclassified as cancer-associated somatic variants.

Databases used for clinical interpretation in oncology rely on genetic data derived primarily from patients of European ancestry, leading to biases in cancer genetics research and clinical practice. One practical issue that arises in this context is the potential misclassification of multi-ancestral population variants as tumor-associated because they are not represented in reference genomes against which tumor sequencing data is aligned. To systematically find misclassified variants, we compared somatic variants in census genes from the Catalogue of Somatic Mutations in Cancer (COSMIC) V99 with multi-ancestral population variants from the Genome Aggregation Databases' Linkage Disequilibrium (GnomAD). By comparing genomic coordinates, reference, and alternate alleles, we could identify misclassified variants in genes associated with cancer. We found 192 of 208 genes in COSMIC's cancer-associated census genes (92.31%) to be associated with variant misclassifications. Among the 1,906,732 variants in COSMIC, 6,957 variants (0.36%) aligned with normal population variants in GnomAD, concerning for misclassification. The African / African American ancestral population included the greatest number of misclassified variants and also had the greatest number of unique misclassified variants. The direct, systematic comparison of variants from COSMIC for co-occurrence in GnomAD supports a more accurate interpretation of tumor sequencing data and reduces bias related to genomic ancestry.

Dynamic Survival Risk Prognostic Model and Genomic Landscape for Atypical Teratoid/Rhabdoid Tumors: A Population-Based, Real-World Study.

An atypical teratoid/rhabdoid tumor (AT/RT) is an uncommon and aggressive pediatric central nervous system neoplasm. However, a universal clinical consensus or reliable prognostic evaluation system for this malignancy is lacking. Our study aimed to develop a risk model based on comprehensive clinical data to assist in clinical decision-making. We conducted a retrospective study by examining data from the Surveillance, Epidemiology, and End Results (SEER) repository, spanning 2000 to 2019. The external validation cohort was sourced from the Children's Hospital Affiliated to Chongqing Medical University, China. To discern independent factors affecting overall survival (OS) and cancer-specific survival (CSS), we applied Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF) regression analyses. Based on these factors, we structured nomogram survival predictions and initiated a dynamic online risk-evaluation system. To contrast survival outcomes among diverse treatments, we used propensity score matching (PSM) methodology. Molecular data with the most common mutations in AT/RT were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. The annual incidence of AT/RT showed an increasing trend (APC, 2.86%; 95% CI:0.75-5.01). Our prognostic study included 316 SEER database participants and 27 external validation patients. The entire group had a median OS of 18 months (range 11.5 to 24 months) and median CSS of 21 months (range 11.7 to 29.2). Evaluations involving C-statistics, DCA, and ROC analysis underscored the distinctive capabilities of our prediction model. An analysis via PSM highlighted that individuals undergoing triple therapy (integrating surgery, radiotherapy, and chemotherapy) had discernibly enhanced OS and CSS. The most common mutations of AT/RT identified in the COSMIC database were SMARCB1, BRAF, SMARCA4, NF2, and NRAS. In this study, we devised a predictive model that effectively gauges the prognosis of AT/RT and briefly analyzed its genomic features, which might offer a valuable tool to address existing clinical challenges.

Cancer-Related Mutations in the Sam Domains of EphA2 Receptor and Ship2 Lipid Phosphatase: A Computational Study.

The lipid phosphatase Ship2 interacts with the EphA2 receptor by forming a heterotypic Sam (sterile alpha motif)-Sam complex. Ship2 works as a negative regulator of receptor endocytosis and consequent degradation, and anti-oncogenic effects in cancer cells should be induced by hindering its association with EphA2. Herein, a computational approach is presented to investigate the relationship between Ship2-Sam/EphA2-Sam interaction and cancer onset and further progression. A search was first conducted through the COSMIC (Catalogue of Somatic Mutations in Cancer) database to identify cancer-related missense mutations positioned inside or close to the EphA2-Sam and Ship2-Sam reciprocal binding interfaces. Next, potential differences in the chemical-physical properties of mutant and wild-type Sam domains were evaluated by bioinformatics tools based on analyses of primary sequences. Three-dimensional (3D) structural models of mutated EphA2-Sam and Ship2-Sam domains were built as well and deeply analysed with diverse computational instruments, including molecular dynamics, to classify potentially stabilizing and destabilizing mutations. In the end, the influence of mutations on the EphA2-Sam/Ship2-Sam interaction was studied through docking techniques. This in silico approach contributes to understanding, at the molecular level, the mutation/cancer relationship by predicting if amino acid substitutions could modulate EphA2 receptor endocytosis.

Genetic profiling of rat gliomas and cardiac schwannomas from life-time radiofrequency radiation exposure study using a targeted next-generation sequencing gene panel.

The cancer hazard associated with lifetime exposure to radiofrequency radiation (RFR) was examined in Sprague Dawley (SD) rats at the Ramazzini Institute (RI), Italy. There were increased incidences of gliomas and cardiac schwannomas. The translational relevance of these rare rat tumors for human disease is poorly understood. We examined the genetic alterations in RFR-derived rat tumors through molecular characterization of important cancer genes relevant for human gliomagenesis. A targeted next-generation sequencing (NGS) panel was designed for rats based on the top 23 orthologous human glioma-related genes. Single-nucleotide variants (SNVs) and small insertion and deletions (indels) were characterized in the rat gliomas and cardiac schwannomas. Translational relevance of these genetic alterations in rat tumors to human disease was determined through comparison with the Catalogue of Somatic Mutations in Cancer (COSMIC) database. These data suggest that rat gliomas resulting from life-time exposure to RFR histologically resemble low grade human gliomas but surprisingly no mutations were detected in rat gliomas that had homology to the human IDH1 p.R132 or IDH2 p.R172 suggesting that rat gliomas are primarily wild-type for IDH hotspot mutations implicated in human gliomas. The rat gliomas appear to share some genetic alterations with IDH1 wildtype human gliomas and rat cardiac schwannomas also harbor mutations in some of the queried cancer genes. These data demonstrate that targeted NGS panels based on tumor specific orthologous human cancer driver genes are an important tool to examine the translational relevance of rodent tumors resulting from chronic/life-time rodent bioassays.

Whole-exome sequencing of Nigerian benign prostatic hyperplasia reveals increased alterations in apoptotic pathways.

Through whole-exome sequencing of 60 formalin-fixed paraffin-embedded Nigerian (NGRn) benign prostatic hyperplasia (BPH) samples, we identified germline and somatic alterations in apoptotic pathways impacting BPH development and progression. Prostate enlargement is a common occurrence in male aging; however, this enlargement can lead to lower urinary tract symptoms that negatively impact quality of life. This impact is disproportionately present in men of African ancestry. BPH pathophysiology is poorly understood and studies examining non-European populations are lacking. In this study, NGRn BPH, normal prostate, and prostate cancer (PCa) tumor samples were sequenced and compared to characterize genetic alterations in NGRn BPH. Two hundred and two nonbenign, ClinVar-annotated germline variants were present in NGRn BPH samples. Six genes [BRCA1 (92%), HSD3B1 (85%), TP53 (37%), PMS2 (23%), BARD1 (20%), and BRCA2 (17%)] were altered in at least 10% of samples; however, compared to NGRn normal and tumor, the frequency of alterations in BPH samples showed no significant differences at the gene or variant level. BRCA2_rs11571831 and TP53_rs1042522 germline alterations had a statistically significant co-occurrence interaction in BPH samples. In at least two BPH samples, 173 genes harbored somatic variants known to be clinically actionable. Three genes (COL18A1, KIF16B, and LRP1) showed a statistically significant (p < 0.05) higher frequency in BPH. NGRn BPH also had five gene pairs (PKD1/KIAA0100, PKHD1/PKD1, DNAH9/LRP1B, NWD1/DCHS2, and TCERG1/LMTK2) with statistically significant co-occurring interactions. Two hundred and seventy-nine genes contained novel somatic variants in NGRn BPH. Three genes (CABP1, FKBP1C, and RP11-595B24.2) had a statistically significant (p < 0.05) higher alteration frequency in NGRn BPH and three were significantly higher in NGRn tumor (CACNA1A, DMKN, and CACNA2D2). Pairwise Fisher's exact tests showed 14 gene pairs with statistically significant (p < 0.05) interactions and four interactions approaching significance (p < 0.10). Mutational patterns in NGRn BPH were similar to COSMIC (Catalog of Somatic Mutations in Cancer) signatures associated with aging and dysfunctional DNA damage repair. NGRn BPH contained significant germline alteration interactions (BRCA2_rs11571831 and TP53_rs1042522) and increased somatic alteration frequencies (LMTK2, LRP1, COL18A1, CABP1, and FKBP1C) that impact apoptosis. Normal prostate development is maintained by balancing apoptotic and proliferative activity. Dysfunction in either mechanism can lead to abnormal prostate growth. This work is the first to examine genomic sequencing in NGRn BPH and provides data that fill known gaps in the understanding BPH and how it impacts men of African ancestry.

Mutational Signatures Analysis of Micropapillary Components and Exploration of ZNF469 Gene in Early-stage Lung Adenocarcinoma with Ground-glass Opacities

In China, lung cancer remains the cancer with the highest incidence and mortality rate. Among early-stage lung adenocarcinomas (LUAD), the micropapillary (MPP) component is prevalent and typically exhibits high aggressiveness, significantly correlating with early metastasis, lymphatic infiltration, and reduced five-year survival rates. Therefore, the study is to explore the similarities and differences between MPP and non-micropapillary (non-MPP) components in malignant pulmonary nodules characterized by GGOs in early-stage LUAD, identify unique mutational features of the MPP component and analyze the relationship between the ZNF469 gene, a member of the zinc-finger protein family, and the prognosis of early-stage LUAD, as well as its correlation with immune infiltration. A total of 31 malignant pulmonary nodules of LUAD were collected and dissected into paired MPP and non-MPP components using microdissection. Whole-exome sequencing (WES) was performed on the components of early-stage malignant pulmonary nodules. Mutational signatures analysis was conducted using R packages such as maftools, Nonnegative Matrix Factorization (NMF), and Sigminer to unveil the genomic mutational characteristics unique to MPP components in invasive LUAD compared to other tumor tissues. Furthermore, we explored the expression of the ZNF469 gene in LUAD using The Cancer Genome Atlas (TCGA) database to investigate its potential association with the prognosis. We also investigated gene interaction networks and signaling pathways related to ZNF469 in LUAD using the GeneMANIA database and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Lastly, we analyzed the correlation between ZNF469 gene expression and levels of immune cell infiltration in LUAD using the TIMER and TISIDB databases. MPP components exhibited a higher number of genomic variations, particularly the 13th COSMIC (Catalogue of Somatic Mutations in Cancer) mutational signature characterized by the activity of the cytidine deaminase APOBEC family, which was unique to MPP components compared to non-MPP components in tumor tissues. This suggests the potential involvement of APOBEC in the progression of MPP components in early-stage LUAD. Additionally, MPP samples with high similarity to APOBEC signature displayed a higher tumor mutational burden (TMB), indicating that these patients may be more likely to benefit from immunotherapy. The expression of ZNF469 was significantly upregulated in LUAD compared to normal tissue, and was associated with poor prognosis in LUAD patients (P<0.05). Gene interaction network analysis and GO/KEGG enrichment analysis revealed that COL6A1, COL1A1, COL1A2, TGFB2, MMP2, COL8A2 and C2CD4C interacted with ZNF469 and were mainly involved in encoding collagen proteins and participating in the constitution of extracellular matrix. ZNF469 expression was positively correlated with immune cell infiltration in LUAD (P<0.05). The study has unveiled distinctive mutational signatures in the MPP components of early-stage invasive LUAD in the Asian population. Furthermore, we have identified that the elevated expression of mutated ZNF469 impacts the prognosis and immune infiltration in LUAD, suggesting its potential as a diagnostic and prognostic biomarker in LUAD.

Papillary Renal Cell Carcinoma: Demographics, Survival Analysis, Racial Disparities, and Genomic Landscape.

Papillary renal cell carcinoma (PRCC) is the second most common histological subtype of renal cell cancer. This research aims to present a large database study highlighting the demographic, clinical, and pathological factors, racial disparities, prognosis, and survival of PRCC. The clinical and demographic data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database, and molecular data was cured from the Catalogue Of Somatic Mutations in Cancer (COSMIC) database. PRCC had a median age of diagnosis at 64 years, with a higher incidence in men (77%), and Whites (68%). 70.3% of cases were Grades I-IV (13, 53, 31, and 3%, respectively). In patients with known data, 85% were localized to the kidney, and 84% of cases were 7 cm in size. No metastasis occurred in 97% of the known data. The most common treatment offered was surgical resection (9%). The 5-year overall survival was 79%, with patients undergoing surgery having a 90.6% 5-year survival. Multivariable analysis revealed age > 60 years, Black race, poor histologic differentiation, distant metastases, and tumor size > 10 cm as independent risk factors for mortality. The most common mutations identified from the COSMIC database were MET, KMT2D, KMT2C, ARID1A, and SPEN. PRCC affects male individuals in the sixth decade of life. Increased age, Black race, distant metastases, and tumors > 10 cm are associated with a worse prognosis. Surgical resection offers a favorable survival outcome. Next-generation sequencing (NGS) could identify potentially targetable alterations and future personalized therapeutic approaches.

Co-occurring BRCA2/SPOP Mutations Predict Exceptional Poly (ADP-ribose) Polymerase Inhibitor Sensitivity in Metastatic Castration-Resistant Prostate Cancer

Background and objectiveBRCA2 mutations in metastatic castration-resistant prostate cancer (mCRPC) confer sensitivity to poly (ADP-ribose) polymerase (PARP) inhibitors. However, additional factors predicting PARP inhibitor efficacy in mCRPC are needed. Preclinical studies support a relationship between speckle-type POZ protein (SPOP) inactivation and PARP inhibitor sensitivity. We hypothesized that SPOP mutations may predict enhanced PARP inhibitor response in BRCA2-altered mCRPC. MethodsWe conducted a multicenter retrospective study involving 13 sites. We identified 131 patients with BRCA2-altered mCRPC treated with PARP inhibitors, 14 of which also carried concurrent SPOP mutations. The primary efficacy endpoint was prostate-specific antigen (PSA) response rate (≥50% PSA decline). The secondary endpoints were biochemical progression-free survival (PSA-PFS), clinical/radiographic progression-free survival (PFS), and overall survival (OS). These were compared by multivariable Cox proportional hazard models adjusting for age, tumor stage, baseline PSA level, Gleason sum, prior therapies, BRCA2 alteration types, and co-occurring mutations. Key findings and limitationsBaseline characteristics were similar between groups. PSA responses were observed in 60% (70/117) of patients with BRCA2mut/SPOPwt disease and in 86% (12/14) of patients with BRCA2mut/SPOPmut disease (p = 0.06). The median time on PARP inhibitor treatment was 24.0 mo (95% confidence interval [CI] 19.2 mo to not reached) in this group versus 8.0 mo (95% CI 6.1–10.9 mo) in patients with BRCA2 mutation alone (p = 0.05). In an unadjusted analysis, patients with BRCA2mut/SPOPmut disease experienced longer PSA-PFS (hazard ratio [HR] 0.33 [95% CI 0.15–0.72], p = 0.005) and clinical/radiographic PFS (HR 0.4 [95% CI 0.18–0.86], p = 0.02), and numerically longer OS (HR 0.4 [95% CI 0.15–1.12], p = 0.08). In a multivariable analysis including histology, Gleason sum, prior taxane, prior androgen receptor pathway inhibitor, stage, PSA, BRCA2 alteration characteristics, and other co-mutations, patients with BRCA2mut/SPOPmut disease experienced longer PSA-PFS (HR 0.16 [95% CI 0.05–0.47], adjusted p = 0.001), clinical/radiographic PFS (HR 0.28 [95% CI 0.1–0.81], adjusted p = 0.019), and OS (HR 0.19 [95% CI 0.05–0.69], adjusted p = 0.012). In a separate cohort of patients not treated with a PARP inhibitor, there was no difference in OS between patients with BRCA2mut/SPOPmut versus BRCA2mut/SPOPwt disease (HR 0.97 [95% CI 0.40–2.4], p = 0.94). In a genomic signature analysis, Catalog of Somatic Mutations in Cancer (COSMIC) SBS3 scores predictive of homologous recombination repair (HRR) defects were higher for BRCA2mut/SPOPmut than for BRCA2mut/SPOPwt disease (p = 0.04). This was a retrospective study, and additional prospective validation cohorts are needed. Conclusions and clinical implicationsIn this retrospective analysis, PARP inhibitors appeared more effective in patients with BRCA2mut/SPOPmut than in patients with BRCA2mut/SPOPwt mCRPC. This may be related to an increase in HRR defects in coaltered disease. Patient summaryIn this study, we demonstrate that co-alteration of both BRCA2 and SPOP predicts superior clinical outcomes to treatment with poly (ADP-ribose) polymerase (PARP) inhibitors than BRCA2 alteration without SPOP mutation.

COSMIC:a curated database of somatic variants and clinical data for cancer.

The Catalogue Of Somatic Mutations In Cancer (COSMIC), https://cancer.sanger.ac.uk/cosmic, is an expert-curated knowledgebase providing data on somatic variants in cancer, supported by a comprehensive suite of tools for interpreting genomic data, discerning the impact of somatic alterations on disease, and facilitating translational research. The catalogue is accessed and used by thousands of cancer researchers and clinicians daily, allowing them to quickly access information from an immense pool of data curated from over 29 thousand scientific publications and large studies. Within the last 4 years, COSMIC has substantially expanded its utility by adding new resources: the Mutational Signatures catalogue, the Cancer Mutation Census, and Actionability. To improve data accessibility and interoperability, somatic variants have received stable genomic identifiers that are associated with their genomic coordinates in GRCh37 and GRCh38, and new export files with reduced data redundancy have been made available for download.

Homology Modeling and Structure Based Drug Design for Human Gastric Cancer

Abstract: This research article delves into the multifaceted world of structural biology and bioinformatics, exploring a diverse array of tools and resources employed to decipher the intricacies of proteins and their implications in health and disease. The paper navigates through various computational tools and databases used for sequence analysis, structural analysis, mutation site detection, and molecular docking, shedding light on their individual contributions in unraveling the secrets of proteins. COBALT serves as the initial compass, guiding researchers in the alignment of protein sequences, identifying conserved domains, and elucidating structural features in proteins. The exploration continues, with a focus on tools such as RasMol, PyMol, and Pharmit. This research article explores a range of bioinformatics tools and databases crucial for elucidating the complex world of proteins and their involvement in diseases like gastric cancer. It begins by highlighting the pivotal role of the Catalogue of Somatic Mutations in Cancer (COSMIC) in mutation site detection, providing a comprehensive repository of somatic mutations in cancer. The Kyoto Encyclopedia of Genes and Genomes (KEGG) complements this with a wealth of biological data and pathways. Shifting the focus to protein stability and dynamics, the article introduces DynaMUT, a computational tool employing molecular dynamics simulations to predict mutation impacts on protein behavior. Lastly, SwissDock takes the stage for drug discovery, facilitating the prediction and analysis of interactions between small molecules and target proteins. Collectively, these tools and databases offer an interdisciplinary lens through which researchers unravel protein intricacies and their relevance in diseases, exemplifying the indispensable role of structural biology and bioinformatics in advancing biological understanding.

Higher 13-Gene-Estimated TMB Detected from Plasma ctDNA is Associated with Worse Outcome for T-Cell Lymphoma Patients.

Exome sequencing of in situ tumor samples reveals that mutated genes can predict the prognosis of patients with T-cell lymphoma (TCL). However, how tumor mutation burden (TMB) derived from circulating tumor DNA (ctDNA) may stratify TCL patients remains unclear.The plasma ctDNA of 79 newly diagnosed TCL patients from the clinical center is used for targeted exome sequencing, and the exome data of 4035 TCL patients from the Catalogue of Somatic Mutations in Cancer (COSMIC) database is obtained for comparison analysis.TCL patients with higher TMB, as evaluated with a panel of 120 genes (panel-TMB120), are associated with poor prognosis. More importantly, COX regression analysis identifies a subset of 13 genes in panel-TMB120, including AP3B1 (Adaptor related protein complex 3 subunit beta 1), ATM (Ataxia-telangiectasia mutated), BCL6 (B cell lymphoma 6), BRAF (B-Raf proto-oncogene, serine/threonine kinase), CDKN2B (Cyclin dependent kinase inhibitor 2B), EPCAM (Epithelial cell adhesion molecule), FBXO11 (F-box protein 11), JAK1 (Janus kinase 1), MDM2 (Murine double minute 2), NF1 (Neurofibromin 1), STAT5B (Signal transducer and activator of transcription 5B), STAT6 (Signal transducer and activator of transcription 6), and TET2 (Tet methylcytosine dioxygenase 2), which are significantly associated with prognosis. Specifically, higher TMB values calculated with these 13 genes (panel-TMB13) are able to significantly predict unfavorable prognosis for these patients. Together, panel-TMB13 and the International Prognostic Index (IPI) are used for risk stratification.Panel-TMB13 is identified, which can predict poor prognosis for TCL patients carrying higher panel-TMB13 scores and suggest that panel-TMB13 may be a potential biomarker for supplement risk stratification of TCL patients.

Machine learning models-based on integration of next-generation sequencing testing and tumor cell sizes improve subtype classification of mature B-cell neoplasms.

Next-generation sequencing (NGS) panels for mature B-cell neoplasms (MBNs) are widely applied clinically but have yet to be routinely used in a manner that is suitable for subtype differential diagnosis. This study retrospectively investigated newly diagnosed cases of MBNs from our laboratory to investigate mutation landscapes in Chinese patients with MBNs and to combine mutational information and machine learning (ML) into clinical applications for MBNs, especially for subtype classification. Samples from the Catalogue Of Somatic Mutations In Cancer (COSMIC) database were collected for ML model construction and cases from our laboratory were used for ML model validation. Five repeats of 10-fold cross-validation Random Forest algorithm was used for ML model construction. Mutation detection was performed by NGS and tumor cell size was confirmed by cell morphology and/or flow cytometry in our laboratory. Totally 849 newly diagnosed MBN cases from our laboratory were retrospectively identified and included in mutational landscape analyses. Patterns of gene mutations in a variety of MBN subtypes were found, important to investigate tumorigenesis in MBNs. A long list of novel mutations was revealed, valuable to both functional studies and clinical applications. By combining gene mutation information revealed by NGS and ML, we established ML models that provide valuable information for MBN subtype classification. In total, 8895 cases of 8 subtypes of MBNs in the COSMIC database were collected and utilized for ML model construction, and the models were validated on the 849 MBN cases from our laboratory. A series of ML models was constructed in this study, and the most efficient model, with an accuracy of 0.87, was based on integration of NGS testing and tumor cell sizes. The ML models were of great significance in the differential diagnosis of all cases and different MBN subtypes. Additionally, using NGS results to assist in subtype classification of MBNs by method of ML has positive clinical potential.

Efforts to Grow Genomic Research in Ancestrally Diverse and Admixed Populations.

Recent initiatives by the research community to characterize the genomic and molecular landscapes of tumors in ancestrally diverse and admixed populations, including the publication by Ding and colleagues in this issue of Cancer Research, represent important efforts to improve our understanding of the entire spectrum of cancer genomic variation with potential clinical consequences. Ding and colleagues confirmed a similar prevalence of mutations in established breast cancer driver genes including PIK3CA, TP53, GATA3, MAP3K1, CDH1, CBFB, PTEN, and RUNX1 and recurrent amplifications in breast cancer drivers including MYC, FGFR1, CCND1, and ERBB2 in tumors from Hispanic/Latina women as compared with non-Hispanic White women. Importantly, they also identified Catalogue of Somatic Mutations in Cancer (COSMIC) signature 16 in a significant fraction of tumors from Hispanic/Latina women and a novel recurrent amplification on 17q11.2. This study highlights the potential for inclusion of participants from diverse populations to accelerate discoveries and advance equity in genomic medicine, as well as the need for even larger collaborative initiatives. See related article by Ding et al., p. 2600.

Topography of mutational signatures in human cancer

The somatic mutations found in a cancer genome are imprinted by different mutational processes. Each process exhibits a characteristic mutational signature, which can be affected by the genome architecture. However, the interplay between mutational signatures and topographical genomic features has not been extensively explored. Here, we integrate mutations from 5,120 whole-genome-sequenced tumors from 40 cancer types with 516 topographical features from ENCODE to evaluate the effect of nucleosome occupancy, histone modifications, CTCF binding, replication timing, and transcription/replication strand asymmetries on the cancer-specific accumulation of mutations from distinct mutagenic processes. Most mutational signatures are affected by topographical features, with signatures of related etiologies being similarly affected. Certain signatures exhibit periodic behaviors or cancer-type-specific enrichments/depletions near topographical features, revealing further information about the processes that imprinted them. Our findings, disseminated via the COSMIC (Catalog of Somatic Mutations in Cancer) signatures database, provide a comprehensive online resource for exploring the interactions between mutational signatures and topographical features across human cancer.

Clock-like Mutation Signature May Be Prognostic for Worse Survival Than Signatures of UV Damage in Cutaneous Melanoma.

Novel treatment modalities comprising immune checkpoint inhibitors and targeted therapies have revolutionized treatment of metastatic melanoma. Still, some patients suffer from rapid progression and decease within months after a diagnosis of stage IV melanoma. We aimed to assess whether genomic alterations may predict survival after the development of stage IV disease, irrespective of received therapy. We analyzed tumor samples of 79 patients with stage IV melanoma using a custom next-generation gene-sequencing panel, MelArray, designed to detect alterations in 190 melanoma-relevant genes. We classified the patients: first, as short survivors (survival ≤6 months after stage IV disease, n = 22) and long survivors (survival >6 months, n = 57); second, by using a cut-off of one year; and third, by comparing the longest surviving 20 patients to the shortest surviving 20. Among analyzed genes, no individual gene alterations, or combinations of alterations, could be dichotomously associated with survival. However, the cohort's mutational profiles closely matched three known mutational signatures curated by the Catalog of Somatic Mutations in Cancer (COSMIC): UV signature COSMIC_7 (cosine-similarity 0.932), clock-like signature COSMIC_5 (cosine-similarity 0.829), and COSMIC_30 (cosine-similarity 0.726). Patients with UV signature had longer survival compared to patients with clock-like and COSMIC 30 (p < 0.0001). Subgroup dichotomization at 6 months showed that 75% of patients with UV signature survived longer than 6 months, and about 75% of patients with clock-like signature survived less than 6 months after development of stage IV disease. In our cohort, clock-like COSMIC_5 mutational signature predicted poor survival while a UV signature COSMIC_7 predicted longer survival. The prognostic value of mutational signatures should be evaluated in prospective studies.

Effect of PTGES3 on the Prognosis and Immune Regulation in Lung Adenocarcinoma.

PTGES3 is upregulated in multiple cancer types and promotes tumorigenesis and progression. However, the clinical outcome and immune regulation of PTGES3 in lung adenocarcinoma (LUAD) are not fully understood. This study aimed to explore the expression level and prognostic value of PTGES3 and its correlation with potential immunotherapy in LUAD. All data were obtained from several databases, including the Cancer Genome Atlas database. Firstly, gene and protein expression of PTGES3 were analyzed using Tumor Immune Estimation Resource (TIMER), R software, Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA). Thereafter, survival analysis was conducted using the R software, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Kaplan-Meier Plotter. In addition, gene alteration and mutation analyses were conducted using the cBio Cancer Genomics Portal (cBioPortal) and Catalog of Somatic Mutations in Cancer (COSMIC) databases. The molecular mechanisms associated with PTGES3 were assessed via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), GeneMANIA, GEPIA2, and R software. Lastly, the role of PTGES3 in immune regulation in LUAD was investigated using TIMER, Tumor-Immune System Interaction Database (TISIDB), and SangerBox. The gene and protein expression of PTGES3 were elevated in LUAD tissues and compared to the normal tissues, and the high expression of PTGES3 was correlated with cancer stage and tumor grade. Survival analysis revealed that overexpression of PTGES3 was associated with poor prognosis of LUAD patients. Moreover, gene alteration and mutation analysis revealed the occurrence of several types of PTGES3 gene alterations in LUAD. Moreover, co-expression analysis and cross-analysis revealed that three genes, including CACYBP, HNRNPC, and TCP1, were correlated and interacted with PTGES3. Functional analysis of these genes revealed that PTGES3 was primarily enriched in oocyte meiosis, progesterone-mediated oocyte maturation, and arachidonic acid metabolism pathways. Furthermore, we found that PTGES3 participated in a complex immune regulation network in LUAD. The current study indicated the crucial role of PTGES3 in LUAD prognosis and immune regulation. Altogether, our results suggested that PTGES3 could serve as a promising therapeutic and prognosis biomarker for the LUAD.