Catalogue Of Somatic Mutations 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.

Comparative Analyses of Targeted Myeloid Cancer Next-Generation Sequencing Panel in Fresh Blood, Bone Marrow and FFPE Material.

Next-generation sequencing is a vital tool for personalized diagnostics and therapies in cancer. Despite numerous advantages, the method depends on multiple parameters regarding the sample material, e.g., sample fixation. A panel's ability to ensure balanced pre-amplification of the regions of interest is challenging, especially in targeted sequencing approaches, but of significant importance to its applicability across hematological malignancies and solid tumors. This study comparatively evaluated the technical performance of the commercially available OncomineTM Myeloid Panel in fresh and Formalin-fixed paraffin-embedded (FFPE) material by using an Ion Torrent™ Personal Genome Machine™ System and Ion GeneStudio S5 System platform. In total, 114 samples were analyzed, including 55 fresh materials and 59 FFPE samples. Samples were sequenced with a minimum of one million reads. Amplicons with coverage below 400 reads were classified as underperforming. In fresh material, 49/526 amplicons were identified as performing insufficiently, corresponding with 18 genes. Using FFPE material, 103/526 amplicons underperformed. Independent of input material, regions in 27 genes, including ASXL1, BCOR and BRAF, did not match quality parameters. Subsequently, exemplary mutations were extracted from the Catalogue of Somatic Mutations in Cancer database. This technical evaluation of the OncomineTM Myeloid Panel identified amplicons that do not achieve adequate coverage levels and which need to be considered when interpreting sequencing.

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.

Conserved allosteric perturbation of the GTPase domains by region 1 of Ras hypervariable regions

Ras proteins are important intracellular signaling hubs that can interact with numerous downstream effectors and upstream regulators through their GTPase domains (G-domains) anchored to plasma membranes by the C-terminal hypervariable regions (HVRs). The biological functions of Ras were proposed to be regulated at multiple levels including the intramolecular G-domain-HVR interactions, of which the exact mechanism and specificity are still controversial. Here, we demonstrate that the HVRs, instead of having direct contacts, can weakly perturb the G-domains via an allosteric interaction that is restricted to a ∼20 Å range and highly conserved in the tested Ras isoforms (HRas and KRas4B) and nucleotide-bound states. The origin of this allosteric perturbation has been localized to a short segment (residues 167–171) coinciding with region 1 of HVRs, which exhibits moderate to weak α-helical propensities. A charge-reversal mutation (E168K) of KRas4B in region 1, previously described in the Catalog of Somatic Mutations in Cancer database, was found to induce similar chemical shift perturbations as truncation of the HVR does. Further membrane paramagnetic relaxation enhancement (mPRE) data show that this region 1 mutation alters the membrane orientations of KRas4B and moderately increases the relative population of the signaling-compatible state.

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.

Detection of driver mutations and genomic signatures in endometrial cancers using artificial intelligence algorithms.

Analyzed endometrial cancer (EC) genomes have allowed for the identification of molecular signatures, which enable the classification, and sometimes prognostication, of these cancers. Artificial intelligence algorithms have facilitated the partitioning of mutations into driver and passenger based on a variety of parameters, including gene function and frequency of mutation. Here, we undertook an evaluation of EC cancer genomes deposited on the Catalogue of Somatic Mutations in Cancers (COSMIC), with the goal to classify all mutations as either driver or passenger. Our analysis showed that approximately 2.5% of all mutations are driver and cause cellular transformation and immortalization. We also characterized nucleotide level mutation signatures, gross chromosomal re-arrangements, and gene expression profiles. We observed that endometrial cancers show distinct nucleotide substitution and chromosomal re-arrangement signatures compared to other cancers. We also identified high expression levels of the CLDN18 claudin gene, which is involved in growth, survival, metastasis and proliferation. We then used in silico protein structure analysis to examine the effect of certain previously uncharacterized driver mutations on protein structure. We found that certain mutations in CTNNB1 and TP53 increase protein stability, which may contribute to cellular transformation. While our analysis retrieved previously classified mutations and genomic alterations, which is to be expected, this study also identified new signatures. Additionally, we show that artificial intelligence algorithms can be effectively leveraged to accurately predict key drivers of cancer. This analysis will expand our understanding of ECs and improve the molecular toolbox for classification, diagnosis, or potential treatment of these cancers.

Enrichment of colibactin-associated mutational signatures in unexplained colorectal polyposis patients

BackgroundColibactin, a genotoxin produced by polyketide synthase harboring (pks+) bacteria, induces double-strand breaks and chromosome aberrations. Consequently, enrichment of pks+Escherichia coli in colorectal cancer and polyposis suggests a possible carcinogenic effect in the large intestine. Additionally, specific colibactin-associated mutational signatures; SBS88 and ID18 in the Catalogue of Somatic Mutations in Cancer database, are detected in colorectal carcinomas. Previous research showed that a recurrent APC splice variant perfectly fits SBS88.MethodsIn this study, we explore the presence of colibactin-associated signatures and fecal pks in an unexplained polyposis cohort. Somatic targeted Next-Generation Sequencing (NGS) was performed for 379 patients. Additionally, for a subset of 29 patients, metagenomics was performed on feces and mutational signature analyses using Whole-Genome Sequencing (WGS) on Formalin-Fixed Paraffin Embedded (FFPE) colorectal tissue blocks.ResultsNGS showed somatic APC variants fitting SBS88 or ID18 in at least one colorectal adenoma or carcinoma in 29% of patients. Fecal metagenomic analyses revealed enriched presence of pks genes in patients with somatic variants fitting colibactin-associated signatures compared to patients without variants fitting colibactin-associated signatures. Also, mutational signature analyses showed enrichment of SBS88 and ID18 in patients with variants fitting these signatures in NGS compared to patients without.ConclusionsThese findings further support colibactins ability to mutagenize colorectal mucosa and contribute to the development of colorectal adenomas and carcinomas explaining a relevant part of patients with unexplained polyposis.

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.

Abstract B014: KDM4B mutations in human cancers

Abstract Homology-dependent-repair (HDR) is an essential process for the error-free correction of double-strand-breaks (DSBs). The histone demethylase KDM4B plays a role in the HDR repair process, wherein its H3K9 demethylase activity aids recruitment of repair factors such as the ATM checkpoint activator and KAT5 histone acetyltransferase and remodeler to the break site. Inhibition of KDM4B has been shown to disrupt the recruitment of ATM, and KAT5, affecting other downstream HDR factors and leading to widespread unrepaired DNA damage. Both over- and under-expression of KDM4B have implications for cancer severity, and changes in KDM4B expression have been shown to affect the expression of other oncogenes outside of the HDR pathway. We performed a pan-cancer analysis of the effects of KDM4B alterations in human cancers using data from the Catalogue of Somatic Mutations in Cancers (COSMIC). We find that KDM4B mutations occur in nearly every cancer. Further, there is a tendency of co-occurring mutations between KDM4B and several HDR genes the most significant being BRCA2. Machine learning tools did not predict any of the observed KDM4B mutations to be drivers. Our data suggests that although KDM4B does not display a driver phenotype it contributes to the destabilization of DNA damage repair machinery that causes cellular transformation and immortalization. Citation Format: Wesley A. Bush, Ruben C. Petreaca. KDM4B mutations in human cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr B014.

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.

In silico analysis of several frequent SLX4 mutations appearing in human cancers.

SLX4 is an interactor and activator of structure-specific exonuclease that helps resolve tangled recombination intermediates arising at stalled replication forks. It is one of the many factors that assist with homologous recombination, the major mechanism for restarting replication. SLX4 mutations have been reported in many cancers but a pan cancer map of all the mutations has not been undertaken. Here, using data from the Catalogue of Somatic Mutations in Cancers (COSMIC), we show that mutations occur in almost every cancer and many of them truncate the protein which should severely alter the function of the enzyme. We identified a frequent R1779W point mutation that occurs in the SLX4 domain required for heterodimerization with its partner, SLX1. In silico protein structure analysis of this mutation shows that it significantly alters the protein structure and is likely to destabilize the interaction with SLX1. Although this brief communication is limited to only in silico analysis, it identifies certain high frequency SLX4 mutations in human cancers that would warrant further in vivo studies. Additionally, these mutations may be potentially actionable for drug therapies.

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.

Machine Learning for Identification of High-Risk Clonal Haematopoiesis Using Blood Count Data

Introduction: Clonal haematopoiesis (CH) is a common, age-related phenomenon associated with an increased risk of myeloid malignancies (MM), raising the prospect of screening to identify individuals at high risk of progression from CH to MM. The nature of the driver mutation(s) is the major determinant of the risk of progression to MM. Presently, the identification of these mutations relies on next generation sequencing (NGS) of blood DNA, making it impractical to identify those at risk at scale. We previously reported that the presence of CH is associated with changes in complete blood count (CBC) parameters such as the red cell distribution width (RDW), mean corpuscular volume (MCV) and others. However, individual parameters have limited discriminative power to distinguish those with CH versus those without. Here, we present a machine learning (ML) pipeline applied to a combined CBC dataset, which can be harnessed to improve our ability to identify individuals with high likelihood of carrying CH, who can subsequently be prioritised for genetic testing. Methods: Whole exome sequencing (WES) data from 454,052 UK Biobank (UKB) participants were analysed using Mutect2 to detect CH-driver mutations across the exons of 43 CH-associated genes. Germline variants were filtered using a panel of ormal and a one-sided exact binomial test. A final set of driver mutations was derived by filtering variants based on a pre-defined list of recurrent CH mutations or recurrence of &amp;gt;= 7 times in haematological cancers in the catalogue of somatic mutations in cancer. Fields pertaining to blood count variables were extracted and filtered to remove individuals with missing data, extreme outliers, highly correlated parameters and variables with near zero-variance resulting in 434,057 participants with complete datasets. Individuals were annotated as “CH” or “no-CH”; a Random Forest (RF) binary classifier was optimised on age, sex and 13 blood count variables as features. To quantify the robustness and stability of the model, the RF optimisation was iterated ten times, on a customised cross validation approach by using a different random sample from the majority (control) class each time. All ML models were constructed using the Caret package (R version 3.6.3). Results: We first found that RF classifiers to identify the presence of CH overall performed poorly (median AUC: 0.640/0.671 for any/large clone VAF &amp;gt;=10% CH respectively). However, gene-specific models showed that the presence of CH associated with mutations in certain high risk genes ( SF3B1, SRSF2, JAK2, CALR) could be predicted from blood counts more confidently (median AUC 0.776, 0.834, 0.933, 0.849 respectively). By contrast, mutations in the more common CH driver genes ( DNMT3A and TET2) could not be accurately predicted from blood count data (median AUC 0.618 and 0.666 respectively) (Figure 1). In light of these findings, we proceeded to build a single RF model to predict the presence of high-risk CH associated with mutations in any of SF3B1, SRSF2, JAK2 or CALR. This performed well, with median AUC of 0.816/0.888 for any/large clone high-risk CH respectively (Figure 2). Our RF models were also able to give insights into novel blood count association with specific types of CH; in particular we found that the basophil count was an important predictor of the presence of CH driven by mutation in codon K57 of the GNB1 gene. To investigate this further, we analysed basophil counts in the UKB and confirmed that basophilia (basophils &amp;gt;0.2 x 10 9/L) was more common amongst carriers of GNB1-K57 mutations (14/234 = 5.9%) than controls (2597/433,863 = 0.5%). Conclusions: Data-driven ML models applied to blood count data can identify individuals with high-risk CH driven by genes associated with progression to myelodysplastic syndrome and myeloproliferative neoplasms, who should be prioritised for genetic testing for somatic mutations. The future integration of raw blood analyser and longitudinal blood count data into predictive models would be an important next step towards improving our ability to identify individuals that may harbour CH and help facilitate the introduction of large-scale screening for the phenomenon.

Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons.

Veterans are at an increased risk for prostate cancer, a disease with extraordinary clinical and molecular heterogeneity, compared with the general population. However, little is known about the underlying molecular heterogeneity within the veteran population and its impact on patient management and treatment. Using clinical and targeted tumor sequencing data from the National Veterans Affairs health system, we conducted a retrospective cohort study on 45 patients with advanced prostate cancer in the Veterans Precision Oncology Data Commons (VPODC), most of whom were metastatic castration-resistant. We characterized the mutational burden in this cohort and conducted unsupervised clustering analysis to stratify patients by molecular alterations. Veterans with prostate cancer exhibited a mutational landscape broadly similar to prior studies, including KMT2A and NOTCH1 mutations associated with neuroendocrine prostate cancer phenotype, previously reported to be enriched in veterans. We also identified several potential novel mutations in PTEN, MSH6, VHL, SMO, and ABL1 Hierarchical clustering analysis revealed two subgroups containing therapeutically targetable molecular features with novel mutational signatures distinct from those reported in the Catalogue of Somatic Mutations in Cancer database. The clustering approach presented in this study can potentially be used to clinically stratify patients based on their distinct mutational profiles and identify actionable somatic mutations for precision oncology.