Cancer Genome Research Articles

Curing Stage IV Melanoma: Where Have We Been and Where Are We?

Little more than 10 years ago, metastatic melanoma was considered to have one of the poorest cancer outcomes, associated with a median overall survival of 6-8 months. Cytotoxic chemotherapy offered modest response rates of 20%-30%, but no clear survival benefit. Patients were routinely enrolled in clinical trials as their first-line therapy in the search for effective novel therapeutics. Remarkable developments in molecular biology, cancer genomics, immunology, and drug discovery have dominated the early part of the 21st century, and nowhere have the benefits been better realized than in the transformation of outcomes for patients with metastatic melanoma: since 2011, 14 new agents have been approved that significantly increase survival, with long-term remissions and, possibly now, potential for cure. Even so, there is still much work to be done, given that most treated patients still die of their disease. Although most survival gains have so far been realized for cutaneous melanoma, improving treatment options for those 10% of patients with rarer, noncutaneous melanomas is a high priority. Key novel therapeutic approaches aimed at improving outcomes with potential for curing patients with melanoma are considered.

Bioinformatics and Experimental Study revealed LINC00982/ miR-183-5p/ABCA8 Axis Suppresses LUAD Progression.

Lung adenocarcinoma (LUAD) is a major health challenge worldwide with an undesirable prognosis. LINC00982 has been implicated as a tumor suppressor in diverse human cancers; however, its role in LUAD has not been fully characterized. Expression level and prognostic value of LINC00982 were investigated in pan-cancer and lung cancer from The Cancer Genome Atlas (TCGA) project. Differential expression analysis based on the LINC00982 expression level was performed in LUAD followed by gene set enrichment analysis (GSEA) and functional enrichment analyses. The association between LINC00982 expression and tumor immune microenvironment characteristics was evaluated. A potential ceRNA regulatory axis was identified and experimentally validated. We found that LINC00982 expression was downregulated and correlated with poor prognosis in LUAD. Enrichment analyses revealed that LINC00982 could inhibit DNA damage repair and cell proliferation, but enhance tumor metabolic reprogramming. We identified a competing endogenous RNA network involving LINC00982, miR-183-5p, and ATP-binding cassette subfamily A member 8 (ABCA8). Luciferase assays confirmed that miR-183-5p can interact with LINC00982 and ABCA8. Forced miR-183-5p expression reduced LINC00982 transcript levels and suppressed ABCA8 expression. Our findings revealed the LINC00982/miR-183-5p/ABCA8 axis as a potential therapeutic target in LUAD.

Action of m6A-related gene signatures on the prognosis and immune microenvironment of colonic adenocarcinoma

N6-methyladenosine (m6A) modification in human tumor cells exerts considerable influence on crucial processes like tumorigenesis, invasion, metastasis, and immune response. This study aims to comprehensively analyze the impact of m6A-related genes on the prognosis and immune microenvironment (IME) of colonic adenocarcinoma (COAD). Public data sources, predictive algorithms identified m6A-related genes and differential gene expression in COAD. Subtype analysis and assessment of immune cell infiltration patterns were performed using consensus clustering and the CIBERSORT algorithm. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis determined gene signatures. Independent prognostic factors were identified using univariate and multivariate Cox proportional hazards models. The findings indicate that 206 prognostic m6A-related DEGs contribute to the m6A regulatory network along with 8 m6A enzymes. Based on the expression levels of these genes, 438 COAD samples from The Cancer Genome Atlas (TCGA) were classified into 3 distinct subtypes, showing marked differences in survival prognosis, clinical characteristics, and immune cell infiltration profiles. Subtype 3 and 2 displayed reduced levels of infiltrating regulatory T cells and M0 macrophages, respectively. A six-gene signature, encompassing KLC3, SLC6A15, AQP7 JMJD7, HOXC6, and CLDN9, was identified and incorporated into a prognostic model. Validation across TCGA and GSE39582 datasets exhibited robust predictive specificity and sensitivity in determining the survival status of COAD patients. Additionally, independent prognostic factors were recognized, and a nomogram model was developed as a prognostic predictor for COAD. In conclusion, the six target genes governed by m6A mechanisms offer substantial potential in predicting COAD outcomes and provide insights into the unique IME profiles associated with various COAD subtypes.

Identification of PANoptosis-related genes as prognostic indicators of thyroid cancer

BackgroundThyroid cancer (THCA) has become a common malignancy in recent years, with the mortality rate steadily increasing. PANoptosis is a unique kind of programmed cell death (PCD), including pyroptosis, necroptosis, and apoptosis, and is involved in the proliferation and prognosis of numerous cancers. This paper demonstrated the connection between PANoptosis-related genes and THCA based on the analyses of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, which have not been evaluated yet. MethodsWe identified PANoptosis-related expression genes (PRDEGs) by multi-analyzing the TCGA-THCA and GEO datasets. To identify the significant PRDEGs, a prognostic model was constructed using least absolute shrinkage and selection operator regression (LASSO). The predictive values of the significant PRDEGs for THCA outcomes were determined using Cox regression analysis and nomograms. Gene enrichment analyses were performed. Finally, immunohistochemistry was carried out using the human protein atlas. ResultsA LASSO regression model based on nine PRDEGs was constructed, and the prognostic value of key PRDEGs was explored via risk score. Univariate and multivariate Cox regression were implemented to identify further three significant PRDEGs closely related to distant metastasis, lymph node metastasis, and tumor stage. Then, a nomogram was constructed, which presented high predictive accuracy for 5 years survival of THCA patients. Gene enrichment analyses in THCA were strongly associated with PCD pathways. CASP6 presented significantly differential expression during clinical T stage, N stage, and PFI events (P<0.05 for all) and demonstrated the highest degree of diagnostic efficacy in PRDEGs (HR: 2.060, 95% CI: 1.170-3.628, P < 0.05). Immunohistochemistry showed CASP6 was more abundant in THCA tumor tissue. ConclusionA potential prognostic role for PRDEGs in THCA was identified, providing a new direction for treatment. CASP6 may be a potential therapeutic target and a novel prognostic biomarker for THCA.

Enterotoxin-related genes PPFIA4 and SCN3B promote colorectal cancer development and progression.

To identify the role of enterotoxin-related genes in colorectal cancer (CRC) development and progression. Upregulated differentially expressed genes shared by three out of five Gene Expression Omnibus (GEO) data sets were included to screen the key enterotoxin-induced oncogenes (EIOGs) according to criteria oncogene definition, enrichment, and protein-protein interaction (PPI) network analysis, followed by prognosis survival, immune infiltration, and protential drugs analyses was performed via integration of RNA-sequencing data and The Cancer Genome Atlas-derived clinical profiles. We screened nine common key EIOGs from at least three GEO data sets. A Cox proportional hazards regression models verified that more alive cases, decreased overall survival, and highest 4-year survival prediction in CRC patients with high-risk score. Protein tyrosine phosphatase receptor type F polypeptide-interacting protein alpha-4 (PPFIA4), STY11, SCN3B, and SPTBN5 were shared in the same PPI network. Immune infiltration results showed that SCN3B and synaptotagmin 11 expression were obviously associated with B cell, macrophage, myeloid dendritic cell, neutrophils, and T cell CD4+ and CD8+ in both colon adenocarcinoma and rectal adenocarcinoma. CHIR-99021, MLN4924, and YK4-279 were identified as the potential drugs for treatment. Finally, upregulated EIOGs genes PPFIA4 and SCN3B were found in colon adenocarcinoma and PPFIA4 and SCN3B were proved to promote cell proliferation and migration in vitro. We demonstrated here that EIOGs promoting a malignancy phenotype was related with poor survival and prognosis in CRC, which might be served as novel therapeutic targets in CRC management.

A novel Senescence-Based prognostic model unveils tumor interactions and drug resistance in colorectal cancer

BackgroundIn China, CRC incidence is escalating. The main hurdles are heterogeneity and drug resistance. This research delves into cellular senescence in CRC, aiming to devise a prognostic model and pinpoint mechanisms impacting drug resistance. MethodsMendelian randomization (MR) analysis confirmed the association between CRC and cellular aging. The Cancer Genome Atlas (TCGA)-CRC data served as the training set, with GSE38832 and GSE39582 as validation sets. Various bioinformatics methods were employed to construct and validate a risk model. CRC cells with NADPH Oxidase 4 (NOX4) knockout were generated using CRISPR-Cas9 technology. Protein blotting and colony formation assays elucidated the role of NOX4 in CRC cell aging and drug resistance. ResultsA prognostic model, derived from dataset analysis, uncovered a link between high-risk groups and cancer progression. Notable differences in the tumor microenvironment were observed between risk groups. Finally, NOX4 was found to be linked with aging and drug resistance in CRC. ConclusionThis research presents a novel senescence-based CRC prognosis model. It identifies NOX4′s role in CRC drug resistance, suggesting it is a potential treatment target.

Artemisia argyi extracts overcome lapatinib resistance via enhancing TMPRSS2 activation in HER2-positive breast cancer.

Breast cancer stands as the predominant malignancy and primary cause of cancer-related mortality among females globally. Approximately 25% of breast cancers exhibit HER2 overexpression, imparting a more aggressive tumor phenotype and correlating with poor prognoses. Patients with metastatic breast cancer receiving HER2 tyrosine kinase inhibitors (HER2 TKIs), such as Lapatinib, develop acquired resistance within a year, posing a critical challenge in managing this disease. Here, we explore the potential of Artemisia argyi, a Chinese herbal medicine known for its anti-cancer properties, in mitigating HER2 TKI resistance in breast cancer. Analysis of the Cancer Genome Atlas (TCGA) revealed diminished expression of transmembrane serine protease 2 (TMPRSS2), a subfamily of membrane proteolytic enzymes, in breast cancer patients, correlating with unfavorable outcomes. Intriguingly, lapatinib-responsive patients exhibited higher TMPRSS2 expression. Our study unveiled that the compounds from Artemisia argyi, eriodictyol, and umbelliferone could inhibit the growth of lapatinib-resistant HER2-positive breast cancer cells. Mechanistically, they suppressed HER2 kinase activation by enhancing TMPRSS2 activity. Our findings propose TMPRSS2 as a critical determinant in lapatinib sensitivity, and Artemisia argyi emerges as a potential agent to overcome lapatinib via activating TMPRSS2 in HER2-positive breast cancer. This study not only unravels the molecular mechanisms driving cell death in HER2-positive breast cancer cells induced by Artemisia argyi but also lays the groundwork for developing novel inhibitors to enhance therapy outcomes.

A computational pipeline for identifying gene targets and signalling pathways in cancer cells to improve lymphocyte infiltration and immune checkpoint therapy efficacy

Tumour-infiltrating lymphocytes (TILs) are crucial for effective immune checkpoint blockade (ICB) therapy in solid tumours. However, ∼70% of these tumours exhibit poor lymphocyte infiltration, rendering ICB therapies less effective. We developed a bioinformatics pipeline integrating multiple previously unconsidered factors or datasets, including tumour cell immune-related pathways, copy number variation (CNV), and single tumour cell sequencing data, as well as tumour mRNA-seq data and patient survival data, to identify targets that can potentially improve T cell infiltration and enhance ICB efficacy. Furthermore, we conducted wet-lab experiments and successfully validated one of the top-identified genes. We applied this pipeline in solid tumours of the Cancer Genome Atlas (TCGA) and identified a set of genes in 18 cancer types that might potentially improve lymphocyte infiltration and ICB efficacy, providing a valuable drug target resource to be further explored. Importantly, we experimentally validated SUN1, which had not been linked to T cell infiltration and ICB therapy previously, but was one of the top-identified gene targets among 3 cancer types based on the pipeline, in a mouse colon cancer syngeneic model. We showed that Sun1 KO could significantly enhance antigen presentation, increase T-cell infiltration, and improve anti-PD1 treatment efficacy. Moreover, with a single-cell multiome analysis, we identified subgene regulatory networks (sub-GRNs) showing Stat proteins play important roles in enhancing the immune-related pathways in Sun1-KO cancer cells. This study not only established a computational pipeline for discovering new gene targets and signalling pathways in cancer cells that block T-cell infiltration, but also provided a gene target pool for further exploration in improving lymphocyte infiltration and ICB efficacy in solid tumours. A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Identification of the CD8+ T-cell Related Signature for Predicting the Prognosis of Gastric Cancer Based on Integrated Analysis of Bulk and Single-cell RNA Sequencing Data.

The infiltration of CD8+ T cells in the tumor microenvironment is associated with better survival and immunotherapy response. However, their roles in gastric cancer have not been explored so far. In here, the profiles of GC gene expression were collected from The Cancer Genome Atlas database. Single-cell transcriptomic data originated from GSE134520. Cell clustering, annotation, and CD8+ T-cell differential genes were from the TISCH database. We determined 896 CD8+ T-cell differential genes by scRNA-seq analysis. After integrating immune-related genes, 174 overlapping genes were obtained and a novel risk model was subsequently built. The performance of CD8+ T-cell-associated gene signature was assessed in the training and external validation sets. The gene signature showed independent risk factors of overall survival for GC. A quantitative nomogram was built to enhance the clinical efficacy of this signature. Furthermore, low-risk individuals showed higher mutation status, higher immune checkpoint expression, low Tumour Immune Dysfunction and Exclusion (TIDE) scores, and higher IPS-PD-1 combined IPS-CTLA4 scores, indicating a greater response to immunotherapy. In addition, analysis of IMvigor210 immunotherapy cohort demonstrated that low-risk individuals had a favorable response to prognosis and immunotherapy. In conclusion, we generated a CD8+ T-cell-related signature that can serve as a promising tool for personalized prognosis prediction and guiding decisions regarding immunotherapy in GC patients.

A study on construction of a prognosis model for liver cancer based on analgesic targets and screening therapeutic drugs.

Liver cancer is one of the most malignant liver diseases in the world, and the 5-year survival rate of such patients is low. Analgesics are often used to cure pain prevalent in liver cancer. The expression changes and clinical significance of the analgesic targets (ATs) in liver cancer have not been deeply understood. The purpose of this study is to clarify the expression pattern of ATs gene in liver cancer and its clinical significance. Through the comprehensive analysis of transcriptome data and clinical parameters, the prognosis model related to ATs gene is established, and the drug information sensitive to ATs is mined. The study primarily utilized transcriptomic data and clinical information from liver cancer patients sourced from The Cancer Genome Atlas (TCGA) database. These data were employed to analyze the expression of ATs, conduct survival analysis, gene set variation analysis (GSVA), immune cell infiltration analysis, establish a prognostic model, and perform other bioinformatic analyses. Additionally, data from liver cancer patients in the International Cancer Genome Consortium (ICGC) were utilized to validate the accuracy of the model. Furthermore, the impact of analgesics on key genes in the prognostic model was assessed using data from the Comparative Toxicogenomics Database (CTD). The study investigated the differential expression of 58 ATs genes in liver cancer compared to normal tissues. Patients were stratified based on ATs expression, revealing varied survival outcomes. Functional enrichment analysis highlighted distinctions in spindle organization, centrosome, and spindle microtubule functions. Prognostic modeling identified low TP53 expression as protective, while elevated CCNA2, NEU1, and HTR2C levels posed risks. Commonly used analgesics, including acetaminophen and others, were found to influence the expression of these genes. These findings provide insights into potential therapeutic strategies for liver cancer and shed light on the molecular mechanisms underlying its progression. The collective analysis of gene signatures associated with ATs suggests their potential as prognostic predictors in hepatocellular carcinoma patients. These findings not only offer insights into cancer therapy but also provide novel avenues for the development of indications for analgesics.

Identification and validation of a prognostic signature based on six immune-related genes for colorectal cancer

BackgroundColorectal cancer (CRC) is a prevalent malignancy with high mortality and morbidity rates. Although the significant efficacy of immunotherapy is well established, it is only beneficial for a limited number of individuals with CRC.MethodsDifferentially expressed immune-related genes (DE-IRGs) were retrieved from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and ImmPort databases. A prognostic signature comprising DE-IRGs was developed using univariate, LASSO, and multivariate Cox regression analyses. A nomogram integrating the independent prognostic factors was also developed. CIBERSORT was used to assess immune cell infiltration (ICI). Furthermore, wound-healing, colony formation, migration, and invasion assays were performed to study the involvement of ACTG1 in CRC.ResultsA signature including six DE-IRGs was developed. The overall survival (OS) rate was accurately estimated for TCGA and GSE38832 cohorts. The risk score (RS) of the signature was an independent factor for OS. Moreover, a nomogram encompassing age, RS, and pathological T stage accurately predicted the long-term OS probability of individuals with CRC. The high-risk group had an elevated proportion of patients treated with ICIs, including native B cells, relative to the low-risk group. Additionally, ACTG1 expression was upregulated, which supported the proliferation, migration, and invasion abilities of CRC cells.ConclusionsAn immune-related prognostic signature was developed for predicting OS and for determining the immune status of individuals with CRC. The present study provides new insights into accurate immunotherapy for individuals with CRC. Moreover, ACTG1 may serve as a new immune biomarker.

GPR168 functions as a tumor suppressor in mouse melanoma by restraining Akt signaling pathway.

Malignant melanoma (MM) is a malignant tumor associated with high mortality rates and propensity for metastasis. Despite advancement in treatment, the incidence of MM continue to rise globally. GPR168, also known as MrgprF, is a MAS related GPR family member. The low expression of GPR168 has also been reported in many malignant tumors including MM. In the study, the statistical analysis from The Cancer Genome Atlas (TCGA) revealed a significant down regulation of GPR168 in melanoma compared to normal melanocytes, underscoring its importance in MM. The aim of the present study is to investigate the affect of GPR168 overexpression and elucidate its molecular mechanisms in MM cells. In addition, we used mouse melanoma B16-F10 cell line and xenograph tumor model to explore the function of GPR168 in melanoma. Our findings demonstrate that GPR168 overexpression could inhibit B16-F10 cell proliferation, migration, and xenografts tumor growth. Further, mechanistic studies revealed that GPR168 affected B16-F10 progress through Akt signal pathway with the decreased expression of p-Akt, p-GSK-3β, β-catenin, Myc, CyclinD1 and CDK4. In order to validate these findings, a rescue experiment was formulated employing GPR168 polyclonal antibody (Anti-GPR168 pAbs) to block GPR168 functionality. The addition of Anti-GPR168 pAbs into the culture medium restored both cell proliferation and migration. In conclusion, the overexpression of GPR168 in mouse melanoma B16-F10 cells suppressed proliferation and migration through the Akt signaling pathway. These findings collectively propose GPR168 as a promising novel tumor suppressor in MM, suggesting its potential as a therapeutic target in future interventions.

Multi-omics analysis of macrophage-associated receptor and ligand reveals a strong prognostic signature and subtypes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a significant contributor to morbidity and mortality worldwide. The interaction between receptors and ligands is the primary mode of intercellular signaling and plays a vital role in the progression of HCC. This study aimed to identify the macrophage-related receptor ligand marker genes associated with HCC and further explored the molecular immune mechanisms attributed to altered biomarkers. Single-cell RNA sequencing data containing primary and recurrent samples were downloaded from the China National GeneBank. Cell types were first identified to explore differences between immune cells from different sample sources. CellChat analysis was used to infer and analyze intercellular communication networks quantitatively. Three molecular subtypes were constructed based on the screened twenty macrophage-associated receptor ligand genes. Bulk RNA-Seq data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. After the screening, the minor absolute shrinkage and selection operator (LASSO) regression model was employed to identify key markers. After collecting peripheral blood and clinical information from patients, an enzyme-linked immunosorbent assay (ELISA) was used to detect the correlation between key markers and IL-10, one of the macrophage markers. After developing a new HCC risk adjustment model and conducting analysis, it was found that there were significant differences in immune status and gene mutations between the high-risk and low-risk groups of patients based on macrophage-associated receptor and ligand genes. This study identified SPP1, ANGPT2, and NCL as key biological targets for HCC. The drug-gene interaction network analysis identified wortmannin, ribavirin, and tarnafloxin as potential therapeutic drugs for the three key markers. In a clinical cohort study, patients with immune checkpoint inhibitor (ICI) resistance had significantly higher expression levels of OPN, ANGPT2, NCL, and IL-10 than patients with ICI-responsiveness. These three key markers were positively correlated with the expression level of IL-10. The signature based on macrophage-associated receptor and ligand genes can accurately predict the prognosis of patients with HCC and the sensitivity to immunotherapy. These results may help guide the development of targeted prevention and personalized treatment of HCC.

Distinct cuproptosis patterns in hepatocellular carcinoma patients correlate with unique immune microenvironment characteristics and cell-cell communication, contributing to varied overall survival outcomes

BackgroundHepatocellular carcinoma (HCC), a prevalent cancer, is linked to cuproptosis in tumor progression. However, cuproptosis's impact on HCC prognosis and its role in the tumor microenvironment remain unclear. We aimed to explore the correlation between cellular cuproptosis and the immune microenvironment in HCC, providing potential immunotherapeutic insights. MethodsExamining cuproptosis-related genes and the immune microenvironment through consensus clustering and WGCNA. Risk models were constructed using LASSO Cox analysis and validated in an independent cohort. Gene expression data from The Cancer Genome Atlas (TCGA) database and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were utilized. We scored cuproptosis expression and explored immunoinfiltration and cell-cell communication. Differential signals in T_memory cells were compared across different cuproptosis levels. ResultsCuproptosis genes associated with fibroblast recruitment (GLS) and macrophage infiltration (FDX1). Liver cancer patients categorized into two subtypes based on cuproptosis gene expression. High expression of DLAT, GLS, and CDKN2A linked to immunosuppression (TGF-β), while high FDX1, MTF1, LIAS, and LIPT1 expression enhanced communication with non-immune cells. Developed reliable prognostic signature score and nomogram using cuproptosis-related genes. Single-cell analysis revealed differences in T_memory and TAM infiltration based on cuproptosis scores, with SPP1 and MIF as dominant signaling molecules. Finally, the results of in vitro experiments showed that when DLAT or CDKN2A was knocked down, the proliferation, migration, and invasion of HCC cells were significantly decreased. ConclusionOur study demonstrates that cuproptosis affects the immune microenvironment and cell-cell communication. Identified 9 genetic markers predicting survival outcomes and immunotherapy responses. Evaluating cuproptosis signaling can optimize immunotherapeutic strategies for hepatocellular carcinoma.

Extracellular vesicles containing MFGE8 from colorectal cancer facilitate macrophage efferocytosis

BackgroundColorectal cancer (CRC) commonly exhibits tolerance to cisplatin treatment, but the underlying mechanisms remain unclear. Within the tumor microenvironment, macrophages play a role in resisting the cytotoxic effects of chemotherapy by engaging in efferocytosis to clear apoptotic cells induced by chemotherapeutic agents. The involvement of extracellular vesicles (EVs), an intercellular communicator within the tumor microenvironment, in regulating the efferocytosis for the promotion of drug resistance has not been thoroughly investigated.MethodsWe constructed GFP fluorescent-expressing CRC cell lines (including GFP-CT26 and GFP-MC38) to detect macrophage efferocytosis through flow cytometric analysis. We isolated and purified CRC-secreted EVs using a multi-step ultracentrifugation method and identified them through electron microscopy and nanoflow cytometry. Proteomic analysis was conducted to identify the protein molecules carried by CRC-EVs. MFGE8 knockout CRC cell lines were constructed using CRISPR-Cas9, and their effects were validated through in vitro and in vivo experiments using Western blotting, immunofluorescence, and flow cytometric analysis, confirming that these EVs activate the macrophage αvβ3-Src-FAK-STAT3 signaling pathway, thereby promoting efferocytosis.ResultsIn this study, we found that CRC-derived EVs (CRC-EVs) enhanced macrophage efferocytosis of cisplatin-induced apoptotic CRC cells. Analysis of The Cancer Genome Atlas (TCGA) database revealed a high expression of the efferocytosis-associated gene MFGE8 in CRC patients, suggesting a poorer prognosis. Additionally, mass spectrometry-based proteomic analysis identified a high abundance of MFGE8 protein in CRC-EVs. Utilizing CRISPR-Cas9 gene edition system, we generated MFGE8-knockout CRC cells, demonstrating that their EVs fail to upregulate macrophage efferocytosis in vitro and in vivo. Furthermore, we demonstrated that MFGE8 in CRC-EVs stimulated macrophage efferocytosis by increasing the expression of αvβ3 on the cell surface, thereby activating the intracellular Src-FAK-STAT3 signaling pathway.ConclusionsTherefore, this study highlighted a mechanism in CRC-EVs carrying MFGE8 activated the macrophage efferocytosis. This activation promoted the clearance of cisplatin-induced apoptotic CRC cells, contributing to CRC resistance against cisplatin. These findings provide novel insights into the potential synergistic application of chemotherapy drugs, EVs inhibitors, and efferocytosis antagonists for CRC treatment.

RAD51 Expression as a Biomarker to Predict Efficacy of Platinum-Based Chemotherapy and PD-L1 Blockade for Muscle-Invasive Bladder Cancer.

RAD51, a key recombinase that catalyzes homologous recombination (HR), is commonly overexpressed in multiple cancers. It is curial for DNA damage repair (DDR) to maintain genomic integrity which could further determine the therapeutic response. Herein, we attempt to explore the clinical value of RAD51 in therapeutic guidance in muscle-invasive bladder cancer (MIBC). In this retrospective study, a total of 823 patients with MIBC were included. Zhongshan hospital (ZSHS) cohort (n=134) and The Cancer Genome Atlas-Bladder Cancer (TCGA-BLCA) cohort (n=391) were included for the investigation of chemotherapeutic response. The IMvigor210 cohort (n=298) was utilized to interrogate the predictive efficacy of RAD51 status to programmed cell death ligand-1 (PD-L1) blockade. In addition, the association of RAD51 with genomic instability and tumor immune contexture was investigated. Patients with RAD51 overexpression were more likely to benefit from both platinum-based chemotherapy and immunotherapy rather than RAD51-low patients. The TMBhighPD-L1highRAD51high subgroup possessed the best clinical benefits from PD-L1 blockade. RAD51-high tumors featured by genomic instability were correlated to highly inflamed and immunogenic contexture with activated immunotherapeutic pathway in MIBC. RAD51 could serve as a prognosticator for treatment response to platinum-based chemotherapy and PD-L1 inhibitor in MIBC patients. Besides, it could also improve the predictive efficacy of TMB and PD-L1.

RGC32 promotes the progression of ccRCC by activating the NF-κB/SHP2/EGFR signaling pathway.

The role and clinical significance of the response gene to complement 32 (RGC32) in various cancers have been documented, yet its implications in clear cell Renal Cell Carcinoma (ccRCC) remain underexplored. This study investigated RGC32's diagnostic and prognostic relevance in ccRCC using bioinformatics methods with data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The impact of RGC32 on ccRCC progression was assessed through nude mouse tumor assays. Immunohistochemistry evaluated RGC32 levels in ccRCC and adjacent normal tissues, while cell proliferation, migration, and invasion capabilities were analyzed using CCK-8, monoclonal proliferation assays, Transwell, and wound healing assays, respectively. Western blotting measured relevant protein expressions. Bioinformatics analysis highlighted RGC32's significant role in ccRCC pathogenesis. Elevated RGC32 expression in ccRCC tissues was linked to disease progression. Functionally, RGC32 was found to enhance the expression of proteins such as p-PI3K, CyclinA1, CyclinD1, p-STAT3, MMP2, MMP3, MMP9, p-SMAD2/3, Snail, Slug, and N-Cadherin via the NF-κB/SHP2/EGFR pathway, while decreasing E-cadherin levels. Moreover, RGC32 facilitated ccRCC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT). RGC32 is a pivotal factor in ccRCC development, primarily through the activation of the NF-κB/SHP2/EGFR signaling pathway.

Interferon-induced transmembrane protein 2 is a prognostic marker in colorectal cancer and promotes its progression by activating the PI3K/AKT pathway

BackgroundInterferon-induced transmembrane protein 2 (IFITM2) is involved in repressing viral infection. This study aim to investigate the expression of IFITM2 in colorectal cancer (CRC) and explore its effect on cell proliferation, migration, and invasion.MethodsWe analyzed The Cancer Genome Atlas (TCGA) database for IFITM2 expression in colorectal cancer and used western blots to detect IFITM2 protein in specimens and cell lines of colorectal cancers. To assess the association between IFITM2 and clinical features, both univariate and multivariate cox regression analysis were conducted. Kaplan–Meier plots were used in the TCGA database to assess IFITM2 gene expression's prognostic significance. Silencing IFITM2 in SW480 and HCT116 cells was achieved by transient transfection with siRNA. Proliferation of CRCs was examined using Cell Counting Kit-8. The effect of IFITM2 on the migration and invasion of CRC cells was studied using wound healing and transwell assays. Gene set enrichment analysis (GSEA) was used to examine IFITM2-associated pathways and Western blotting was used to confirm it.ResultsIFITM2 was over-expressed in the CRC tissues and cells, with high IFITM2 expression related to the tumor N, M, and pathologic stages. The presence of IFITM2 significantly impacted patient survival in CRC. The proliferation of SW480 and HCT116 cells was suppressed when IFITM2 was silenced, resulting in weakened migration and invasion of CRC cells. GSEA analysis showed that IFITM2 was positively related to the phosphoinositide 3-kinase (PI3K)/AKT pathway, and western blot results confirmed that IFITM2 activated it.ConclusionsIFITM2 was over-expressed in CRC and modulated the PI3K/AKT pathway to promote CRC cells proliferation and metastasis.

Bioinformatics analysis and experimental validation of m6A and cuproptosis-related lncRNA NFE4 in clear cell renal cell carcinoma

PurposeThis study aimed to construct an m6A and cuproptosis-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using the information acquired from The Cancer Genome Atlas (TCGA) database.MethodsFirst, the co-expression analysis was performed to identify lncRNAs linked with N6-methyladenosine (m6A) and cuproptosis in ccRCC. Then, a model encompassing four candidate lncRNAs was constructed via univariate, least absolute shrinkage together with selection operator (LASSO), and multivariate regression analyses. Furthermore, Kaplan–Meier, principal component, functional enrichment annotation, and nomogram analyses were performed to develop a risk model that could effectively assess medical outcomes for ccRCC cases. Moreover, the cellular function of NFE4 in Caki-1/OS-RC-2 cultures was elucidated through CCK-8/EdU assessments and Transwell experiments. Dataset outcomes indicated that NFE4 can have possible implications in m6A and cuproptosis, and may promote ccRCC progression.ResultsWe constructed a panel of m6A and cuproptosis-related lncRNAs to construct a prognostic prediction model. The Kaplan–Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. Furthermore, the m6A and cuproptosis-related lncRNA model indicated higher diagnostic efficiency than other clinical features. Moreover, the NFE4 function analysis indicated a gene associated with m6A and cuproptosis-related lncRNAs in ccRCC. It was also revealed that the proliferation and migration of Caki-1 /OS-RC-2 cells were inhibited in the NFE4 knockdown group.ConclusionOverall, this study indicated that NFE4 and our constructed risk signature could predict outcomes and have potential clinical value.

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.