Cancer Genome Research Articles

The N6-methyladenosine methylation landscape stratifies breast cancer into two subtypes with distinct immunological characteristics.

N6-methyladenosine (m6A) methylation modification affects the tumorigenesis and metastasis of breast cancer (BC). This study investigated the association between m6A regulator-mediated methylation modification patterns and characterization of the tumour microenvironment in BC, as well as their prognostic importance. Public gene expression data and clinical annotations were collected from The Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus website and the METABRIC program. We analysed the genetic expression, gene-gene interactions, gene mutations and copy number variations using R software. The data were screened for risk genes using the Cox risk regression model, and we developed an algorithm for risk score and its predictive value. Compared to adjacent normal tissue, we identified 16 differentially expressed m6A regulators in BC, including six writers and 10 readers. Under unsupervised clustering, two distinguished modification patterns were identified, cluster C1 and C2. Compared to m6A cluster C2, cluster C1 was found to be more involved in immune-related pathways, with a relatively higher immune score and stromal score (P < 0.05). Patients were divided into two groups based on their risk scores for survival analysis. The patients in the high-risk score group had significantly worse overall survival than patients in the low-risk score group, (P < 0.0001). The TCGA database validation revealed the same prognostic tendency. In summary, our study showed distinct m6A regulator modification patterns contribute to the immunological heterogeneity and diversity of BC. The development of m6A gene signatures and the m6A score aid in the prognostic prediction of patients with BC.

Single-Cell RNA Sequencing Identifies Crucial Genes Influencing the Polarization of Tumor-Associated Macrophages in Liver Cancer

Background. In the context of hepatocellular carcinoma (HCC), tumor-associated macrophages (TAMs) are pivotal for the immunosuppressive nature of the tumor microenvironment (TME). This investigation delves into the functional transformations of TAMs within the TME by leveraging single-cell transcriptomics to pinpoint critical genes influencing TAM subset polarization. Methods. We procured single-cell and bulk transcriptomic data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), implementing quality assurance, dimensional reduction, clustering, and annotation on the single-cell sequencing data. To examine cellular interactions, CellChat was utilized, while single-cell regulatory network inference and clustering (SCENIC) was applied to deduce transcription factors (TFs) and their associated targets. Through gene enrichment, survival, and immune infiltration correlation analyses, we sought to pinpoint and validate influential genes. A TAM model under HCC conditions was then established to confirm the expression levels of these key genes. Results. Our analysis encompassed 74,742 cells and 23,110 genes. Through postdimensional reduction and clustering, we identified seven distinct cell types and nine TAM subtypes. Analysis via CellChat highlighted a predominance of M2-phenotype-inclined TAM subsets within the tumor’s core. SCENIC pinpointed the transcription factor PRDM1 and its target genes as pivotal in this region. Further analysis indicated these genes’ involvement in macrophage polarization. Employing trajectory analysis, survival analysis, and immune infiltration correlation, we scrutinized and validated genes likely directing M2 polarization. Experimental validation confirmed PRDM1’s heightened expression in TAMs conditioned by HCC. Conclusions. Our findings suggest the PRDM1 gene is a key regulator of M2 macrophage polarization, contributing to the immunosuppressive TME in HCC.

Based on scRNA-seq and bulk RNA-seq to establish tumor immune microenvironment-associated signature of skin melanoma and predict immunotherapy response.

Skin cutaneous melanoma (SKCM), a form of skin cancer, ranks among the most formidable and lethal malignancies. Exploring tumor microenvironment (TME)-based prognostic indicators would help improve the efficacy of immunotherapy for SKCM patients. This study analyzed SKCM scRNA-seq data to cluster non-malignant cells that could be used to explore the TME into nine immune/stromal cell types, including B cells, CD4 T cells, CD8 T cells, dendritic cells, endothelial cells, Fibroblasts, macrophages, neurons, and natural killer (NK) cells. Using data from The Cancer Genome Atlas (TCGA), we employed SKCM expression profiling to identify differentially expressed immune-associated genes (DEIAGs), which were then incorporated into weighted gene co-expression network analysis (WGCNA) to investigate TME-associated hub genes. Discover candidate small molecule drugs based on pivotal genes. Tumor immune microenvironment-associated genes (TIMAGs) for constructing TIMAS were identified and validated. Finally, the characteristics of TIAMS subgroups and the ability of TIMAS to predict immunotherapy outcomes were analyzed. We identified five TIMAGs (CD86, CD80, SEMA4D, C1QA, and IRF1) and used them to construct TIMAS. In addition, five potential SKCM drugs were identified. The results showed that TIMAS-low patients were associated with immune-related signaling pathways, high MUC16 mutation frequency, high T cell infiltration, and M1 macrophages, and were more favorable for immunotherapy. Collectively, TIMAS constructed by comprehensive analysis of scRNA-seq and bulk RNA-seq data is a promising marker for predicting ICI treatment outcomes and improving individualized therapy for SKCM patients.

Genomic landscape of comprehensive genomic profiling in patients with malignant solid tumors in Japan.

Comprehensive genomic profiling (CGP) can aid the discovery of clinically useful, candidate antitumor agents; however, the variant annotations sometimes differ among the various types of CGP tests as well as the public database. The aim of this study is to clarify the genomic landscape of evaluating detected variants in patients with a malignant solid tumor. The present, cross-sectional study used data from 57,084 patients with a malignant solid tumor who underwent CGP at the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) between June 1, 2019 and August 18, 2023. The pathogenicity of the variants was annotated using public databases. As a result of re-annotation of the detected variants, 20.1% were pathogenic and 1.4% were benign. The mean number of pathogenic variants was 4.30 (95% confidence interval: 4.27-4.32) per patient. Of the entire cohort, 5.7% had no pathogenic variant. The co-occurrence of the genes depended on the tumor type. Germline findings were detected in 6.2%, 8.8%, and 15.8% of the patients using a tumor/normal panel, tumor-only panel, and liquid panel, respectively, with the most common gene being BRCA2 followed by TP53 and BRCA1. The detected variants should be re-annotated because several benign variants or variants of unknown significance were included in the CGP, and the genomic landscape derived from these results will help researchers and physicians interpret the results of CGP tests. The method of extracting presumptive, germline, pathogenic variants from patients using a tumor-only panel or circulating tumor DNA panel requires improvement.

Impact of RANGAP1 SUMOylation on Smad4 nuclear export by bioinformatic analysis and cell assays.

Small Ubiquitin-like Modifier (SUMOylation) regulates a variety of cellular activities, and its dysregulation has been associated with glioma etiology. The aim of this research was to clarify the function of SUMOylation-related genes in glioma and determine relevant prognostic markers. The Cancer Genome Atlas (TCGA) Glioma and GSE16011 datasets were analyzed through bioinformatics to identify Ran GTPase activating protein 1 (RANGAP1) as the hub gene for further study. Experimental validation consisted of quantitative real-time polymerase chain reaction (qRT-PCR), western blotting (WB), and immunoprecipitation (IP) to evaluate RANGAP1 expression, function, and interaction with SUMO1. To assess the role of RANGAP1 knockdown and SUMOylation in glioma cells, various assays were conducted, including cell proliferation, migration, invasion, and apoptosis. In addition, cell cycle analysis and immunofluorescence were performed. Through bioinformatics, RANGAP1 was identified as a crucial prognostic gene for glioma. Experimental studies confirmed the downregulation of RANGAP1 in glioma cells and verified that RANGAP1 repair impedes tumor growth. When it comes to RANGAP1 silencing, it enhanced cell proliferation, invasion and migration. Additionally, SUMO1 was identified as a specific SUMO molecule coupled to RANGAP1, affecting the location of Sma and Mad related protein 4 (Smad4) in the nucleocytoplasm and the transforming growth factor (TGF)-β/Smad signaling pathway. The functional impact of RANGAP1 SUMOylation on cell proliferation and migration was further confirmed through experiments using a SUMOylation-impairing mutation (K524R). Our findings suggest that RANGAP1 may be a potential prognostic marker in gliomas and could play a role in regulating cell proliferation, migration, and invasion. SUMOylation of RANGAP1 is responsible for regulating the TGF-β/Smad signaling pathway, which is crucial for the progression of tumors. Further investigations and experiments are necessary to confirm these results.

SLC7A5 correlated with malignancies and immunotherapy response in bladder cancer

BackgroundMetabolic reprogramming contributes to bladder cancer development. This study aimed to understand the role of SLC7A5 in bladder cancer.MethodsWe systematically analyzed the correlation between SLC7A5 and bladder cancer through various approaches, including bioinformatics, western blotting, cell cycle analysis, cell proliferation assays, and invasion experiments. We also investigated the immunological features within the tumor microenvironment (TME), encompassing cancer immune cycles, immune modulators, immune checkpoints, tumor-infiltrating immune cells (TIIC), T cell inflammation scores, and treatment responses. Additionally, for a comprehensive assessment of the expression patterns and immunological roles of SLC7A5, pan-cancer analysis was performed using cancer genomics datasets.ResultsSLC7A5 was associated with adverse prognosis in bladder cancer patients, activating the Wnt pathway and promoting bladder cancer cell cycle progression, proliferation, migration, and invasion. Based on the evidence that SLC7A5 positively correlated with immunomodulators, TIIC, the cancer immune cycle, immune checkpoint and T cell inflammation scores, we also found that SLC7A5 was associated with the inflammatory tumor immune microenvironment. EGFR-targeted therapy, cancer immunotherapy, and radiation therapy were effective for patients with high SLC7A5 expression in bladder cancer. Low SLC7A5 patients were, however, sensitive to targeted therapies and anti-angiogenic therapy, such as blocking β-catenin network, PPAR-γ and FGFR3 signaling. Anti-SLC7A5 combined with cancer immunotherapy may have greater effectiveness than either therapy alone. Furthermore, we observed specific overexpression of SLC7A5 in TME of various cancers.ConclusionSLC7A5 can predict therapeutic response to immunotherapy, radiotherapy and chemotherapy in bladder cancer patients. Targeting SLC7A5 in combination with immunotherapy may be a potentially appropriate treatment option.

Defining three ferroptosis-based molecular subtypes and developing a prognostic risk model for high-grade serous ovarian cancer.

As a newly defined regulated cell death, ferroptosis is a potential biomarker in ovarian cancer (OV). However, its underlying mechanism in tumor microenvironment (TME) and clinical prediction significance in OV remained to be elucidated. The transcriptome data of high-grade serous OV from The Cancer Genome Atlas (TCGA) database were downloaded. Molecular subtypes were classified based on ferroptosis-correlated genes from the FerrDb database by performing consensus clustering analysis. The associations between the subtypes and clinicopathologic characteristics, mutation, regulatory pathways and immune landscape were assessed. A ferroptosis-related prognostic model was constructed and verified using International Cancer Genome Consortium (ICGC) cohort and GSE70769. Three molecular subtypes of OV were defined. Patients in subtype C3 tended to have the most favorable prognosis, while subtype C1 showing more mesenchymal cells, increased immune infiltration of Macrophages_M2, lower tumor purity, and epithelial-to-mesenchymal transition (EMT) features had the poorest prognosis. A ferroptosis-related risk model was constructed using 8 genes (PDP1, FCGBP, EPHA4, GAS1, SLC7A11, BLOC1S1, SPOCK2, and CXCL9) and manifested a strong prediction performance. High-risk patients had enriched EMT pathways, more Macrophages_M2, less plasma cells and CD8 cell infiltration, greater tendency of immune escape and worse prognosis. The risk score has negatively correlated relation with LAG3, TIGIT, CTLA4, IDO1, CD27, ICOS, and IL2RB but positively correlated with PVR, CD276, and CD28. Moreover, low-risk patients were more sensitive to Cisplatin and Gefitinib, Gemcitabine. Our results could improve the understanding of ferroptosis in OV, providing promising insights for the clinical targeted therapy for the cancer.

Human DNA topoisomerase I poisoning causes R loop-mediated genome instability attenuated by transcription factor IIS.

DNA topoisomerase I can contribute to cancer genome instability. During catalytic activity, topoisomerase I forms a transient intermediate, topoisomerase I-DNA cleavage complex (Top1cc) to allow strand rotation and duplex relaxation, which can lead to elevated levels of DNA-RNA hybrids and micronuclei. To comprehend the underlying mechanisms, we have integrated genomic data of Top1cc-triggered hybrids and DNA double-strand breaks (DSBs) shortly after Top1cc induction, revealing that Top1ccs increase hybrid levels with different mechanisms. DSBs are at highly transcribed genes in early replicating initiation zones and overlap with hybrids downstream of accumulated RNA polymerase II (RNAPII) at gene 5'-ends. A transcription factor IIS mutant impairing transcription elongation further increased RNAPII accumulation likely due to backtracking. Moreover, Top1ccs can trigger micronuclei when occurring during late G1 or early/mid S, but not during late S. As micronuclei and transcription-replication conflicts are attenuated by transcription factor IIS, our results support a role of RNAPII arrest in Top1cc-induced transcription-replication conflicts leading to DSBs and micronuclei.

The prognostic value of Dickkopf-3 (Dkk3), TGFB1 and ECM-1 in prostate cancer

Prostate cancer (PCa) is considered one of the most common cancers worldwide. Despite advances in patient diagnosis, management, and risk stratification, 10%–20% of patients progress to castration-resistant disease. Our previous report highlighted a protective role of Dickkopf-3 (DKK3) in PCa stroma. This role was proposed to be mediated through opposing extracellular matrix protein 1 (ECM-1) and TGF-β signalling activity. However, a detailed analysis of the prognostic value of DKK3, ECM-1 and members of the TGF-β signalling pathway in PCa was not thoroughly investigated. In this study, we explored the prognostic value of DKK3, ECM-1 and TGFB1 using a bioinformatical approach through analysis of large publicly available datasets from The Cancer Genome Atlas Program (TGCA) and Pan-Cancer Atlas databases. Our results showed a significant gradual loss of DKK3 expression with PCa progression (p &amp;lt; 0.0001) associated with increased DNA methylation in its promoter region (p &amp;lt; 1.63E-12). In contrast, patients with metastatic lesions showed significantly higher levels of TGFB1 expression compared to primary tumours (p &amp;lt; 0.00001). Our results also showed a marginal association between more advanced tumour stage presented as positive lymph node involvement and low DKK3 mRNA expression (p = 0.082). However, while ECM1 showed no association with tumour stage (p = 0.773), high TGFB1 expression showed a significant association with more advanced stage presented as advanced T3 stage compared to patients with low TGFB1 mRNA expression (p &amp;lt; 0.001). Interestingly, while ECM1 showed no significant association with patient outcome, patients with high DKK3 mRNA expression showed a significant association with favourable outcomes presented as prolonged disease-specific (p = 0.0266), progression-free survival (p = 0.047) and disease-free (p = 0.05). In contrast, high TGFB1 mRNA expression showed a significant association with poor patient outcomes presented as shortened progression-free (p = 0.00032) and disease-free survival (p = 0.0433). Moreover, DKK3, TGFB1 and ECM1 have acted as immune-associated genes in the PCa tumour microenvironment. In conclusion, our findings showed a distinct prognostic value for this three-gene signature in PCa. While both DKK3 and TGFB1 showed a potential role as a clinical marker for PCa stratification, ECM1 showed no significant association with the majority of clinicopathological parameters, which reduce its clinical significance as a reliable prognostic marker.

Involvement of N4BP2L1, PLEKHA4, and BEGAIN genes in breast cancer and muscle cell development

Patients with breast cancer show altered expression of genes within the pectoralis major skeletal muscle cells of the breast. Through analyses of The Cancer Genome Atlas (TCGA)-breast cancer (BRCA), we identified three previously uncharacterized putative novel tumor suppressor genes expressed in normal muscle cells, whose expression was downregulated in breast tumors. We found that NEDD4 binding protein 2-like 1 (N4BP2L1), pleckstrin homology domain-containing family A member 4 (PLEKHA4), and brain-enriched guanylate kinase-associated protein (BEGAIN) that are normally highly expressed in breast myoepithelial cells and smooth muscle cells were significantly downregulated in breast tumor tissues of a cohort of 50 patients with this cancer. Our data revealed that the low expression of PLEKHA4 in patients with menopause below 50 years correlated with a higher risk of breast cancer. Moreover, we identified N4BP2L1 and BEGAIN as potential biomarkers of HER2-positive breast cancer. Furthermore, low BEGAIN expression in breast cancer patients with blood fat, heart problems, and diabetes correlated with a higher risk of this cancer. In addition, protein and RNA expression analysis of TCGA-BRCA revealed N4BP2L1 as a promising diagnostic protein biomarker in breast cancer. In addition, the in silico data of scRNA-seq showed high expression of these genes in several cell types of normal breast tissue, including breast myoepithelial cells and smooth muscle cells. Thus, our results suggest their possible tumor-suppressive function in breast cancer and muscle development.

FAP Serves as a Prognostic Biomarker in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) poses significant challenges with poor survival rates and limited therapeutic strategies. Our study, using The Cancer Genome Atlas (TCGA) data, assesses cancer-associated fibroblast (CAF) gene signatures’ clinical relevance. In our analysis across TCGA tumor types, differential gene expression analysis revealed that fibroblast activation protein (FAP) is upregulated in tumor tissues and associated with poorer survival rates in HNSCC. Furthermore, mechanistic studies employing gene-silencing techniques substantiated that FAP knockout led to a significant decrease in cellular proliferation, invasion, and migration in HNSCC cell lines. Through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we established that high FAP expression correlates with vital biological processes such as extracellular matrix organization, angiogenesis, and cellular motility. Importantly, FAP was found to regulate these processes by promoting the expression of key proteins involved in epithelial–mesenchymal transition-related pathways. Additionally, our analysis revealed a significant correlation between FAP expression and the expression profiles of immune checkpoint molecules, underscoring its potential role in immune modulation. Collectively, our findings illuminate FAP’s pivotal role in HNSCC pathogenesis and its potential as a prognostic biomarker and therapeutic target. This research lays the groundwork for understanding the multifaceted roles and regulatory mechanisms of CAFs in HNSCC, thereby offering valuable perspectives for the development of targeted therapeutic strategies aimed at improving patient outcomes.

Molecular characterization, clinical value, and cancer–immune interactions of genes related to disulfidptosis and ferroptosis in colorectal cancer

BackgroundThis research strived to construct a new signature utilizing disulfidptosis-related ferroptosis (SRF) genes to anticipate response to immunotherapy, prognosis, and drug sensitivity in individuals with colorectal cancer (CRC).MethodsThe data for RNA sequencing as well as corresponding clinical information of individuals with CRC, were extracted from The Cancer Genome Atlas (TCGA) dataset. SRF were constructed with the help of the random forest (RF), least absolute shrinkage and selection operator (LASSO), and stepwise regression algorithms. To validate the SRF model, we applied it to an external cohort, GSE38832. Prognosis, immunotherapy response, drug sensitivity, molecular functions of genes, and somatic mutations of genes were compared across the high- and low-risk groups (categories). Following this, all statistical analyses were conducted with the aid of the R (version 4.23) software and various packages of the Cytoscape (version 3.8.0) tool.ResultsSRF was developed based on five genes (ATG7, USP7, MMD, PLIN4, and THDC2). Both univariate and multivariate Cox regression analyses established SRF as an independent, prognosis-related risk factor. Individuals from the high-risk category had a more unfavorable prognosis, elevated tumor mutational burden (TMB), and significant immunosuppressive status. Hence, they might have better outcomes post-immunotherapy and might benefit from the administration of pazopanib, lapatinib, and sunitinib.ConclusionIn conclusion, SRF can act as a new biomarker for prognosis assessment. Moreover, it is also a good predictor of drug sensitivity and immunotherapy response in CRC but should undergo optimization before implementation in clinical settings.

Constitutive type-1 interferons signaling activity in malignant gliomas.

Recent studies revealed a pro-tumor effect of constitutive Type-1 interferons (IFN-I) production and the downstream signaling activity in several malignancies. In contrast, heterogeneity and clinical significance of the signaling activity in gliomas remain unknown. Thus, we aimed to depict the heterogeneity and clinical significance of constitutive Type-1 interferon (IFN-I) production and the downstream signaling activity in gliomas. We utilized multiplex immunofluorescence (mIF) on a 364 gliomas tissue microarray from our cohort. Moreover, we conducted bioinformatic analyses on the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases to investigate the heterogeneity and clinical significance of constitutive IFN-I signaling activity in gliomas. We observed high heterogeneity of the constitutive IFN-I signaling activity among glioma subtypes. Signaling increased with the WHO malignancy grade while decreasing in the gliomas with IDH mutations. Additionally, high IFN-I activity served as an independent predictor of unfavorable outcomes, and global DNA hypermethylation in IDH-mutant gliomas was associated with decreased IFN-I signaling activity. Positive correlations were observed between the IFN-I activity and glioma-associated inflammation, encompassing both anti-tumor and pro-tumor immune responses. Furthermore, the IFN-I activity varied significantly among tumor and immune cells in the glioma microenvironment (GME). Notably, a distinct pattern of IFN-I signaling activity distribution in GME cells was observed among glioma subtypes, and the pattern was independently associated with patient overall survival. Constitutive IFN-I signaling activity varies significantly among glioma subtypes and represents a potential indicator for increased glioma inflammation and unfavorable clinical outcomes.

Pan-cancer discovery of somatic mutations from RNA sequencing data

Identification of somatic mutations (SMs) is essential for characterizing cancer genomes. While DNA-seq is the prevalent method for identifying SMs, RNA-seq provides an alternative strategy to discover tumor mutations in the transcribed genome. Here, we have developed a machine learning based pipeline to discover SMs based on RNA-seq data (designated as RNA-SMs). Subsequently, we have conducted a pan-cancer analysis to systematically identify RNA-SMs from over 8,000 tumors in The Cancer Genome Atlas (TCGA). In this way, we have identified over 105,000 novel SMs that had not been reported in previous TCGA studies. These novel SMs have significant clinical implications in designing targeted therapy for improved patient outcomes. Further, we have combined the SMs identified by both RNA-seq and DNA-seq analyses to depict an updated mutational landscape across 32 cancer types. This new online SM atlas, OncoDB (https://oncodb.org), offers a more complete view of gene mutations that underline the development and progression of various cancers.

#1193 Tracking kidney cancer initiation via somatic mutation analysis of pre-cancer cells from Von Hippel Lindau cancer predisposition syndrome

Abstract Background and Aims Somatic mutations promote the transition from a normal cell to a cancer clone. Little is known about the factors that promote mutation in normal tissues, but whole genome sequencing of pre-cancer cells, followed by mutational pattern analyses, is a revolutionary tool to understand somatic mutation mechanisms active during an individual's lifetime. In the kidney, we have shown that normal kidney tubule epithelial cells (TEC) derived from damaged PT display an excess of somatic mutations and a peculiar enrichment of mutations in exons and highly transcribed DNA compared to other cell types [1]. However, the direct contribution of this PT-specific mutational process to carcinogenesis needs further demonstration. Here, we have analyzed normal TEC that are genetically predisposed to evolve into clear cell renal cell carcinoma (ccRCC), as they harbor a germline heterozygous mutation in the tumor suppressor Von Hippel Lindau, VHL. Using this genetic model of tumor predisposition, we have tracked the PT-specific mutational process from normal cells to overt ccRCC. This study sheds light on the etiology of this mutational process, as well as its causative role in ccRCC. Method We detected somatic mutations in single genomes from normal kidney TEC from 8 control individuals and 7 VHL-disease patients in the age range 24-70. Different from our previous study [1], we isolated kidney tubule cells from the urine. Multiple TECs per individual were subjected to in vitro clonal expansion, followed by whole genome sequencing (WGS), a golden-standard method to obtain high confidence somatic mutation data. We analyzed concomitant somatic mutation- and gene expression-data from 58 clones, and expression data from 154 TEC clones. Results First, we compared our newly generated dataset (TECs obtained from urines) with our previous dataset (TECs obtained from kidney biopsies). QPCR measurements of marker gene expression and somatic mutational pattern analyses showed that the same two populations could be clonally expanded from both urines and kidney biopsies. One population expressed markers of proximal tubule (AQP1, SLC17A3) and tubule damage (VCAM1, KIM1), and showed an excess of somatic single base substitutions (SBSs). This TEC population was defined: VCAM1-PT cells. We characterized the types of SBSs that are more frequently found in VCAM1-PT genomes. The mutation spectrum was different from that induced by exposure to common mutagens, e.g. aristolochic acid, reactive oxygen species and tobacco. Normal cells, including TEC, fat and blood progenitors, showed mutation depletion in highly transcribed genes, in agreement with more efficient repair. Instead, VCAM1-PT cells showed an enrichment of specific SBS types, distinct from those induced by another transcription-coupled mutational process described in the liver. In vitro exposure of TECs to the alkylating agent ENU recapitulates some features of the spectrum of mutations observed in vivo, suggesting that VCAM1-PT cells might fail to repair damage induced by endogenous alkylating agents. The VCAM1-PT-specific mutational signature was observed in ccRCC, but not found in a variety of non-kidney cell-types and cancers. Importantly, the impact of the mutational signature was more evident in VCAM1-PT genomes from VHL-disease patients compared to similar samples from control individuals. Moreover, VCAM1-PT cells were more common (8-fold increase, chi squared test P = .026) in the urines of VHL-disease patients than in the urines of controls. Conclusion Our data show that TECs derived from damaged PTs are subjected to a specific somatic mutation process during adult life. The process is a distinctive feature of kidney cancer (ccRCC) genomes, and is more evident in patients affected by VHL-cancer predisposition syndrome. These data suggest that heterozygous loss of VHL facilitates a PT-specific, somatic mutation process involved in cancer initiation.

A Combination of Microarray-Based Profiling and Biocomputational Analysis Identified miR331-3p and hsa-let-7d-5p as Potential Biomarkers of Ulcerative Colitis Progression to Colorectal Cancer

Ulcerative colitis (UC), an inflammatory bowel disease (IBD), may increase the risk of colorectal cancer (CRC) by activating chronic proinflammatory pathways. The goal of this study was to find serum prediction biomarkers in UC to CRC development by combining low-density miRNA microarray and biocomputational approaches. The UC and CRC miRNA expression profiles were compared by low-density miRNA microarray, finding five upregulated miRNAs specific to UC progression to CRC (hsa-let-7d-5p, hsa-miR-16-5p, hsa-miR-145-5p, hsa-miR-223-5p, and hsa-miR-331-3p). The circRNA/miRNA/mRNA competitive endogenous RNA (ceRNA) network analysis showed that the candidate miRNAs were connected to well-known colitis-associated CRC ACVR2A, SOCS1, IGF2BP1, FAM126A, and CCDC85C mRNAs, and circ-SHPRH circRNA. SST and SCARA5 genes regulated by hsa-let-7d-5p, hsa-miR-145-5p, and hsa-miR-331-3p were linked to a poor survival prognosis in a CRC patient dataset from The Cancer Genome Atlas (TCGA). Lastly, our mRNA and miRNA candidates were validated by comparing their expression to differentially expressed mRNAs and miRNAs from colitis-associated CRC tissue databases. A high level of hsa-miR-331-3p and a parallel reduction in SOCS1 mRNA were found in tissue and serum. We propose hsa-miR-331-3p and possibly hsa-let-7d-5p as novel serum biomarkers for predicting UC progression to CRC. More clinical sample analysis is required for further validation.

Exploiting tertiary lymphoid structures gene signature to evaluate tumor microenvironment infiltration and immunotherapy response in colorectal cancer

BackgroundTertiary lymphoid structures (TLS) is a particular component of tumor microenvironment (TME). However, its biological mechanisms in colorectal cancer (CRC) have not yet been understood. We desired to reveal the TLS gene signature in CRC and evaluate its role in prognosis and immunotherapy response.MethodsThe data was sourced from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Based on TLS-related genes (TRGs), the TLS related subclusters were identified through unsupervised clustering. The TME between subclusters were evaluated by CIBERSORT and xCell. Subsequently, developing a risk model and conducting external validation. Integrating risk score and clinical characteristics to create a comprehensive nomogram. Further analyses were conducted to screen TLS-related hub genes and explore the relationship between hub genes, TME, and biological processes, using random forest analysis, enrichment and variation analysis, and competing endogenous RNA (ceRNA) network analysis. Multiple immunofluorescence (mIF) and immunohistochemistry (IHC) were employed to characterize the existence of TLS and the expression of hub gene.ResultsTwo subclusters that enriched or depleted in TLS were identified. The two subclusters had distinct prognoses, clinical characteristics, and tumor immune infiltration. We established a TLS-related prognostic risk model including 14 genes and validated its predictive power in two external datasets. The model’s AUC values for 1-, 3-, and 5-year overall survival (OS) were 0.704, 0.737, and 0.746. The low-risk group had a superior survival rate, more abundant infiltration of immune cells, lower tumor immune dysfunction and exclusion (TIDE) score, and exhibited better immunotherapy efficacy. In addition, we selected the top important features within the model: VSIG4, SELL and PRRX1. Enrichment analysis showed that the hub genes significantly affected signaling pathways related to TLS and tumor progression. The ceRNA network: PRRX1-miRNA (hsa-miR-20a-5p, hsa-miR-485–5p) -lncRNA has been discovered. Finally, IHC and mIF results confirmed that the expression level of PRRX1 was markedly elevated in the TLS- CRC group.ConclusionWe conducted a study to thoroughly describe TLS gene signature in CRC. The TLS-related risk model was applicable for prognostic prediction and assessment of immunotherapy efficacy. The TLS-hub gene PRRX1, which had the potential to function as an immunomodulatory factor of TLS, could be a therapeutic target for CRC.

Pathomic model based on histopathological features and machine learning to predict IDO1 status and its association with breast cancer prognosis.

To establish a pathomic model using histopathological image features for predicting indoleamine 2,3-dioxygenase 1 (IDO1) status and its relationship with overall survival (OS) in breast cancer. A pathomic model was constructed using machine learning and histopathological images obtained from The Cancer Genome Atlas database to predict IDO1 expression. The model performance was evaluated based on the area under the curve, calibration curve, and decision curve analysis (DCA). Prediction scores (PSes) were generated from the model and applied to divide the patients into two groups. Survival outcomes, gene set enrichment, immune microenvironment, and tumor mutations were assessed between the two groups. Survival analysis followed by multivariate correction revealed that high IDO1 is a protective factor for OS. Further, the model was calibrated, and it exhibited good discrimination. Additionally, the DCA showed that the proposed model provided a good clinical net benefit. The Kaplan-Meier analysis revealed a positive correlation between high PS and improved OS. Univariate and multivariate Cox regression analyses demonstrated that PS is an independent protective factor for OS. Moreover, differentially expressed genes were enriched in various essential biological processes, including extracellular matrix receptor interaction, angiogenesis, transforming growth factor β signaling, epithelial mesenchymal transition, cell junction, tryptophan metabolism, and heme metabolic processes. PS was positively correlated with M1 macrophages, CD8 + T cells, T follicular helper cells, and tumor mutational burden. These results indicate the potential ability of the proposed pathomic model to predict IDO1 status and the OS of breast cancer patients.

Bioinformatics screening of prognostic immune-related genes in renal clear cell carcinoma.

This study aims to harness bioinformatics to identify prognostic immune-related genes in clear cell renal cell carcinoma (ccRCC), focusing particularly on LILRB3. It evaluates LILRB3's expression in ccRCC, its association with patient prognosis, and its potential as a biomarker for predicting survival, thereby providing a preliminary basis for the diagnosis of ccRCC. Utilizing The Cancer Genome Atlas (TCGA) datasets and an immune gene set, we sought immune-related genes with elevated expression in ccRCC. Seventy-two normal tissue samples and 531 ccRCC samples were analyzed, and differential genes were identified with a screening criterion of fold change (FC) > 2 and P value < 0.01. Survival analysis and receiver operating characteristic (ROC) curve analysis were employed to discover genes of prognostic and diagnostic relevance to ccRCC. Pearson correlation analysis with a cutoff of |r|≥ 0.5, facilitated by cBioPortal, assessed genes co-expressed with LILRB3. The DAVID online tool conducted functional and pathway enrichment analyses for LILRB3-coexpressed genes. The TIMER and TCIA databases were utilized to explore LILRB3's influence on immune infiltration in the tumor microenvironment and its relation to key immunological checkpoints. Screening the TCGA database revealed 3719 up-regulated differential genes in ccRCC, with 355 overlapping immune-related genes. Survival analysis of these 355 genes revealed 100 with significant survival impact. ROC curve analysis pinpointed the top 10 genes, including LILRB3, with the highest diagnostic efficiency. LILRB3 emerged as an independent risk factor from the Cox risk regression model. GO and KEGG analyses linked LILRB3 to various biological processes, including chemokine signaling pathways, immunological response, antigen processing and presentation, inflammatory response, T cell co-stimulation, and signal transduction. LILRB3 significantly affected ccRCC immune infiltration and correlated positively with several immunological checkpoints, such as PD-1, LAG3, IDO1, PD-L1, CTLA4, TIM3, TIGIT, and VISTA. LILRB3 shows higher expression levels in ccRCC than in normal tissues and correlates with poor patient prognosis. Its impactful role in the immune infiltration of the RCC microenvironment suggests that LILRB3 could serve as a novel target for ccRCC treatment and prognosis, underlining its diagnostic and prognostic significance.

The Downregulation of MMP23B Facilitates the Suppression of Vitality and Induction of Apoptosis in Endometrial Cancer Cells.

Endometrial cancer is a malignant tumor that commonly occurs in the female reproductive system and its incidence is still increasing. The mechanism of the development of endometrial cancer has not yet been fully clarified, so we need to continuously study the relevant mechanisms of endometrial cancer and continue to explore its biomarkers in order to discover more precise and effective treatment methods for endometrial cancer. RT-qPCR (Real-Time quantitative Polymerase Chain Reaction) experiments were used to detect the expression level of MMP23B (Matrix Metalloproteinase 23B) in endometrial cancer cells; the clinical data of the TCGA (The Cancer Genome Atlas) database were downloaded, and gene expression profiles were analyzed to investigate the correlation between MMP23B (Matrix Metalloproteinase 23B) and the survival prognosis of endometrial cancer, and functional enrichment analysis was performed on MMP23B (Matrix Metalloproteinase 23B) related genes. After silencing MMP23B (Matrix Metalloproteinase 23B), CCK8 (Cell Counting Kit-8), RT-qPCR (Real-Time quantitative Polymerase Chain Reaction), scratch assay, and transwell assay were used to detect cell viability, levels of apoptotic factors, migration rate, and invasion number of endometrial cancer, respectively. MMP23B (Matrix Metalloproteinase 23B) was highly expressed in endometrial cancer, which is closely related to a poor survival prognosis for endometrial cancer, and may act on endometrial cancer through apoptosis-related functions. The downregulation of MMP23B (Matrix Metalloproteinase 23B) reduced the cell viability of endometrial cancer cells, upregulated the expression levels of CASP3 (Caspase-3), CASP8 (Caspase-8) and CASP9 (Caspase-9) in cells, and inhibited cell migration and invasion.