Visualizing and interpreting cancer genomics data via the Xena platform

Identification of TTLL8, POTEE, and PKMYT1 as immunogenic cancer-associated antigens and potential immunotherapy targets in ovarian cancer

Most high-grade serous ovarian cancers (OC) do not respond to current immunotherapies. To identify potential new actionable tumor antigens in OC, we performed immunopeptidomics on a human OC cell line expressing the HLA-A02:01 haplotype, which is commonly expressed across many racial and ethnic groups. From this dataset, we identified TTLL8, POTEE, and PKMYT1 peptides as candidate tumor antigens with low expression in normal tissues and upregulated expression in OC. Using tissue microarrays, we assessed the protein expression of TTLL8 and POTEE and their association with patient outcomes in a large cohort of OC patients. TTLL8 was found to be expressed in 56.7% of OC and was associated with a worse overall prognosis. POTEE was expressed in 97.2% of OC patients and had no significant association with survival. In patient TILs, increases in cytokine production and tetramer-positive populations identified antigen-specific CD8 T cell responses, which were dependent on antigen presentation by HLA class I. Antigen-specific T cells triggered cancer cell killing of antigen-pulsed OC cells. These findings suggest that TTLL8, POTEE, and PKMYT1 are potential targets for the development of antigen-targeted immunotherapy in OC.

Nano-polymeric platinum activates PAR2 gene editing to suppress tumor metastasis

Metastasis as the hallmark of cancer preferentially contributes to tumor recurrence and therapy resistance, aggrandizing the lethality of patients with cancer. Despite their robust suppressions of tumor progression, chemotherapeutics failed to attenuate cancer cell migration and even triggered pro-metastatic effects. In parallel, protease-activated receptor 2 (PAR2), a member of the G protein-coupled receptor subfamily, actively participates in cancer metastasis via multiple signal transduction pathways. CRISPR/Cas9 that is a dominating genome editing tool can evoke PAR2 knockout to inhibit cancer metastasis. However, the absence of valid delivery systems largely limits its efficacy. Herein, we nanosized polymeric platinum (NanoPt) as therapeutical drug carries to deliver CRISPR/Cas9 to elicit genome editing of PAR2, which drastically augmented anti-metastatic effects and alleviated systematic toxicity of platinum-based treatment in vitro and in vivo. More importantly, the NanoPt@Cas9-PAR2 initiated PAR2 deficiency to mechanistically attenuate EMT process and ferroptosis via RAGE/ERK signalling, consequently preventing cancer cell migration. Our findings indicate that NanoPt@Cas9-PAR2 that mitigated PAR2 signalling and cytotoxic effects of platinum could be a safe and powerful all-in-one combinatorial strategy for cancer treatment.

Efficient discovery of robust prognostic biomarkers and signatures in solid tumors

Recent advancements in multi-omics and big-data technologies have facilitated the discovery of numerous cancer prognostic biomarkers and gene signatures. However, their clinical application remains limited due to poor reproducibility and insufficient independent validation. Despite the availability of high-quality datasets, achieving reliable biomarker identification across multiple cohorts continues to be a significant challenge. To address these issues, we developed a comprehensive platform, SurvivalML, designed to support the discovery and validation of prognostic biomarkers and gene signatures using large-scale and harmonized data from 21 cancer types. Through SurvivalML, we identified DCLRE1B as a novel prognostic biomarker for hepatocellular carcinoma, with experimental confirmation of its role in promoting tumor progression. Additionally, we developed the Chinese glioblastoma prognostic signature (CGPS) and its simplified version, SCGPS, a three-gene model. Both demonstrated superior predictive performance compared to other glioblastoma signatures in our in-house cohort and five independent Chinese datasets. The SCGPS model was further validated in 109 clinical samples using multiplex immunofluorescence, showing strong consistency with the original CGPS model. Overall, SurvivalML provides a robust platform for the identification and validation of prognostic biomarkers and gene signatures, offering a valuable resource for advancing cancer research and clinical application.

iMetAct: An integrated systematic inference of metabolic activity for dissecting tumor metabolic preference and tumor-immune microenvironment

Metabolic enzymes play a central role in cancer metabolic reprogramming, and their dysregulation creates vulnerabilities that can be exploited for therapy. However, accurately measuring metabolic enzyme activity in a high-throughput manner remains challenging due to the complex, multi-layered regulatory mechanisms involved. Here, we present iMetAct, a framework that integrates metabolic-transcription networks with an information propagation strategy to infer enzyme activity from gene expression data. iMetAct outperforms expression-based methods in predicting metabolite conversion rates by accounting for the effects of post-translational modifications. With iMetAct, we identify clinically significant subtypes of hepatocellular carcinoma with distinct metabolic preferences driven by dysregulated enzymes and metabolic regulators acting at both the transcriptional and non-transcriptional levels. Moreover, applying iMetAct to single-cell RNA sequencing data allows for the exploration of cancer cell metabolism and its interplay with immune regulation in the tumor microenvironment. An accompanying online platform further facilitates tumor metabolic analysis, patient stratification, and immune microenvironment characterization.

Interspecies interactions mediated by arginine metabolism enhance the stress tolerance of Fusobacterium nucleatum against Bifidobacterium animalis

Colorectal cancer (CRC) is a common cancer accompanied by microbiome dysbiosis. Exploration of probiotics against oncogenic microorganisms is promising for CRC treatment. Here, differential microorganisms between CRC and healthy control were analyzed. Antibacterial experiments, whole-genome sequencing, and metabolic network reconstruction were combined to reveal the anti-Fusobacterium nucleatum mechanism, which was verified by co-culture assay and mendelian randomization analysis. Sequencing results showed that F. nucleatum was enriched in CRC, yet Bifidobacterium animalis decreased gradually from healthy to CRC. Additionally, F. nucleatum could be inhibited by B. animalis. Whole-genome sequencing of B. animalis showed high phylogenetic similarity with known probiotic strains and highlighted its functions for amino acid and carbohydrate metabolism. Metabolic network reconstruction demonstrated that cross-feeding and specific metabolites (acidic molecules, arginine) had a great influence on the coexistence relationship. Finally, the arginine supplement enhanced the competitive ability of F. nucleatum against B. animalis, and the mendelian randomization and metagenomic sequencing analysis confirmed the positive relationship among F. nucleatum, arginine metabolism, and CRC. Thus, whole-genome sequencing and metabolic network reconstruction are valuable for probiotic mining and patient dietary guidance.IMPORTANCEUsing probiotics to inhibit oncogenic microorganisms (Fusobacterium nucleatum) is promising for colorectal cancer (CRC) treatment. In this study, whole-genome sequencing and metabolic network reconstruction were combined to reveal the anti-F. nucleatum mechanism of Bifidobacterium animalis, which was verified by co-culture assay and mendelian randomization analysis. The result indicated that the arginine supplement enhanced the competitive ability of F. nucleatum, which may be harmful to F. nucleatum-infected CRC patients. B. animalis is a potential probiotic to relieve this dilemma. Thus, using in silico simulation methods based on flux balance analysis, such as genome-scale metabolic reconstruction, provides valuable insights for probiotic mining and dietary guidance for cancer patients.

TCGEx: a powerful visual interface for exploring and analyzing cancer gene expression data

Analyzing gene expression data from the Cancer Genome Atlas (TCGA) and similar repositories often requires advanced coding skills, creating a barrier for many researchers. To address this challenge, we developed The Cancer Genome Explorer (TCGEx), a user-friendly, web-based platform for conducting sophisticated analyses such as survival modeling, gene set enrichment analysis, unsupervised clustering, and linear regression-based machine learning. TCGEx provides access to preprocessed TCGA data and immune checkpoint inhibition studies while allowing integration of user-uploaded data sets. Using TCGEx, we explore molecular subsets of human melanoma and identify microRNAs associated with intratumoral immunity. These findings are validated with independent clinical trial data on immune checkpoint inhibitors for melanoma and other cancers. In addition, we identify cytokine genes that can be used to predict treatment responses to various immune checkpoint inhibitors prior to treatment. Built on the R/Shiny framework, TCGEx offers customizable features to adapt analyses for diverse research contexts and generate publication-ready visualizations. TCGEx is freely available at https://tcgex.iyte.edu.tr , providing an accessible tool to extract insights from cancer transcriptomics data.

Deciphering FOXM1 regulation: implications for stemness and metabolic adaptations in glioblastoma

The Forkhead box M1 (FOXM1) gene-mediated Wnt signaling pathway plays a significant role in the development and growth of glioblastoma multiforme (GBM), an exceptionally aggressive form of brain cancer. Our research explores the crucial involvement of the FOXM1 gene, a key transcription factor within the Wnt signaling pathway using bioinformatics techniques in both GBM and glioma stem cells (GSCs). Elevated FOXM1 gene expression is strongly associated with poor patient survival in GBM. Furthermore, FOXM1 gene expression is correlated with stemness-related factors, such as SOX2 and SOX9, which act as key drivers in the progression of cancer stem cells. Moreover, we specifically look into the direct associations of the FOXM1 gene with angiogenetic-related factors, metabolic genes, metastatic genes, pluripotency-related factors, immune cell infiltration, transcriptional networks, and functional category enrichment analysis, shedding light on the intricate molecular mechanisms involved in GBM initiation and progression. Additionally, our research identifies FOXM1-targeting miRNAs, revealing their potential as therapeutic candidates with implications for patient survival rates and DNA methylation patterns of the FOXM1 gene, uncovering insights into its epigenetic regulation. This knowledge contributes to a comprehensive understanding of the molecular landscape and potential avenues for developing more effective therapeutic approaches against GBM and GSCs.

NOTCH1 Drives Sexually Dimorphic Immune Responses in Hepatocellular Carcinoma

Hepatocellular carcinoma presents strong sexual dimorphism, being two to three times more frequent in males than in females; however, the role of sex in response to immunotherapies in HCC remains unknown. We demonstrate that NOTCH1, an understudied oncogene in HCC, elicits sexually dimorphic antitumor immunity and response to FDA-approved immunotherapies. Surprisingly, males harboring NOTCH1-driven tumors displayed enhanced antitumor immune responses, which, in mice, were mediated by dendritic and T cells. Conversely, females harboring NOTCH1-driven tumors presented immune evasion and resistance to immunotherapies through a defect in dendritic cell (DC)-mediated priming and activation of CD8+ T cells in mice, which was restored therapeutically with CD40 agonism. Mechanistically, the sexually dimorphic immunity was mediated by genes in the sex chromosomes but not by sex hormones. Together, our study unravels an unexpected association between NOTCH1 and sex in cancer immunity and highlights the potential of restoring the DC-CD8+ T-cell axis with CD40 agonism to improve outcomes. Significance: Although HCC presents strong sexual dimorphism, the role of sex in response to immunotherapies remains elusive. With a novel HCC mouse model and validation in patients with HCC, we demonstrate that NOTCH1 disrupts antitumor immunity specifically in females through a mechanism mediated by sex chromosome genes, which is reversed with CD40 agonism. See related commentary by Zhu and Koltsova, p. 452.

Androgen Receptor Inhibition Increases MHC Class I Expression and Improves Immune Response in Prostate Cancer

SIGNIFICANCE

Immunotherapy options for immune cold tumors, like prostate cancer, are limited. We show that AR downregulates MHCI expression/antigen presentation and that AR inhibition improves T-cell responses and tumor control. This suggests that treatments combining AR inhibitors and checkpoint blockade may improve tumor immune surveillance and antitumor immunity in patients.

Darolutamide or capecitabine in triple-negative, androgen receptor-positive, advanced breast cancer (UCBG 3-06 START): a multicentre, non-comparative, randomised, phase 2 trial

BACKGROUND

We proposed in 2005 that androgens replace oestrogens as the driver steroids in a subgroup of triple-negative breast cancer (TNBC) with androgen receptor (AR) expression called molecular apocrine (MA) or luminal androgen receptor (LAR). Here, we report the analysis of a clinical trial evaluating the antitumour activity of the anti-androgen darolutamide in MA breast cancer. Our aim was to assess the clinical benefit in patients with AR-positive TNBCs defined by immunohistochemistry and by RNA profiling.

METHODS

In this multicentre, non-comparative, randomised, phase 2 trial, women aged 18 years or older with an Eastern Cooperative Oncology Group performance status of 0-1 and with advanced TNBC that was previously treated with a maximum of one line of chemotherapy were recruited from 45 hospitals in France. After central confirmation of TNBC status and AR positivity (≥10%; SP107 antibody), participants were randomly assigned (2:1) to receive darolutamide 600 mg orally twice daily or capecitabine minimum 1000 mg/m2 twice daily for 2 weeks on and 1 week off, until disease progression, unacceptable toxicity, lost to follow-up, or withdrawal of consent. Randomisation was done centrally using the minimisation procedure and was stratified according to the number of previous lines of chemotherapy. Transcriptomic analysis was used to classify tumours into groups with high and low AR activity (MAhigh and MAlow). The primary clinical endpoint was clinical benefit rate at 16 weeks (confirmed complete response, partial response, or stable disease). The primary translational endpoint was clinical benefit rate in the darolutamide group in MAhigh tumours versus all other tumours. Analyses were done per protocol. This trial is registered with ClinicalTrials.gov (NCT03383679), and is closed to recruitment.

FINDINGS

Between April 9, 2018, and July 20, 2021, 254 women were screened and 94 were randomly assigned to darolutamide (n=61) or capecitabine (n=33), of whom 90 were evaluable for efficacy analyses. Median follow-up at the data cutoff on July 20, 2022, was 22·5 months (IQR 16·5-30·5). The clinical benefit rate was 29% (17 of 58; 90% CI 19-39) with darolutamide and 59% (19 of 32; 90% CI 45-74) with capecitabine. In patients treated with darolutamide, the clinical benefit rate was 57% (12 of 21; 95% CI 36-78) in MAhigh tumours, and 16% (five of 31; 95% CI 3-29; p=0·0020) in other tumours. The most common grade 3 adverse events were palmar-plantar erythrodysaesthesia syndrome (none of 60 in the darolutamide group vs two [6%] of 33 in the capecitabine group), and headache (three [5%] vs none). No grade 4 or 5 adverse events were observed. Drug-related serious adverse events occurred in three (5%) patients in the darolutamide group and three (9%) in the capecitabine group, which were toxicoderma (n=1) and headache (n=2) in the darolutamide group, and diarrhoea, general physical deterioration, and hepatic cytolysis in the capecitabine group (n=1 each).

INTERPRETATION

This study did not reach its prespecified endpoint for darolutamide activity in patients with triple-negative breast cancer selected on the basis of immunohistochemistry for AR. Further studies selecting patients based on RNA profiling might allow better identification of tumours sensitive to anti-androgens.

FUNDING

Bayer and Fondation Bergonié.

Sustained cancer-relevant alternative RNA splicing events driven by PRMT5 in high-risk neuroblastoma

Protein arginine methyltransferase 5 (PRMT5) is over-expressed in a wide variety of cancers and is implicated as having a key oncogenic role, achieved in part through its control of the master transcription regulator E2F1. We investigated the relevance of PRMT5 and E2F1 in neuroblastoma (NB) and found that elevated expression of PRMT5 and E2F1 occurs in poor prognosis high-risk disease and correlates with an amplified Myelocytomatosis viral-related oncogene, neuroblastoma-derived (MYCN) gene. Our results show that MYCN drives the expression of splicing factor genes that, together with PRMT5 and E2F1, lead to a deregulated alternative RNA splicing programme that impedes apoptosis. Pharmacological inhibition of PRMT5 or inactivation of E2F1 restores normal splicing and renders NB cells sensitive to apoptosis. Our findings suggest that a sustained cancer-relevant alternative RNA splicing programme desensitises NB cells to apoptosis, and identify PRMT5 as a potential therapeutic target for high-risk disease.

Helicobacter pylori induces GBA1 demethylation to inhibit ferroptosis in gastric cancer

This research investigates potential therapeutic targets for gastric cancer, focusing on ferroptosis-related genes. Gastric cancer is known for its lower survival rates, necessitating new treatment strategies. This study employed Mendelian randomization to identify ferroptosis-related genes and methylation sites in gastric cancer, examining correlations between Helicobacter pylori infection, GBA1 gene expression, and promoter methylation with single-cell datasets and the TCGA-STAD database. We used Helicobacter pylori-infected gastric cancer cell models and used next-generation sequencing to monitor methylation changes pre- and post-infection. GBA1 expression levels were assessed via qRT-PCR and Western blot both before and after infection. The effect of Helicobacter pylori on GC cell proliferation was analyzed using CCK-8 and EdU assays after knocking down the GBA1 gene. The association between Helicobacter pylori infection and ferroptosis, including its reversibility after GBA1 knockdown, was evaluated using FerrOrange, GSH, MDA, and C11-BODIPY assays. Mass spectrometry measured the impact of Helicobacter pylori and GBA1 knockdown on lipid metabolism. An in vivo subcutaneous tumor-bearing model was also established to confirm these findings. Mendelian randomization analysis revealed that high GBA1 expression and reduced methylation levels of its promoter are risk factors for gastric cancer. Single-cell sequencing and TCGA-STAD datasets indicated a positive correlation between Helicobacter pylori infection and GBA1 expression, with a concurrent negative correlation between GBA1 promoter methylation and GBA1 expression. In gastric cancer cell lines, Helicobacter pylori infection was observed to enhance GBA1 expression and decrease methylation levels at its promoter. Additionally, Helicobacter pylori promoted GC cell proliferation, an effect mitigated by knocking down GBA1. Infection also reduced lipid peroxidation, increased glutathione levels, and impeded ferroptosis in GC cells; however, these effects were reversed following GBA1 knockdown. Changes in sphingolipid metabolism induced by I were detected in GC cell lines. In vivo experiments using a subcutaneous tumor-bearing model demonstrated that Helicobacter pylori infection fosters tumorigenesis in GC cells. Our study demonstrates that Helicobacter pylori infection triggers demethylation and upregulation of GBA1, subsequently inhibiting ferroptosis in gastric cancer cells. These findings suggest that targeting the GBA1 pathway may offer a novel therapeutic approach for managing gastric cancer.

Genes of DLK1-DIO3 Locus and miR-379/656 Cluster is a Potential Diagnostic and Prognostic Marker in Patients With Hepatocellular Carcinoma: A Systems Biology Study

Background

Hepatocellular carcinoma is the sixth most common malignancy reported globally. This highlights the need for reliable biomarkers that can be employed for diagnostic and prognostic applications. The present study aimed to classify and characterize the clinical potential of delta like non-canonical Notch ligand 1-type III iodothyronine deiodinase (DLK1-DIO3) and miR-379/656 cluster genes in hepatocellular carcinoma.

Methods

We extensively studied the clinical potential of DLK1-DIO3 genes through a comprehensive systems biology approach and assessed the diagnostic and prognostic potential of the genes associated with the region. Additionally, we have predicted the gene targets of the miR-379/656 cluster associated with the locus and have identified the gene ontology, pathway, and disease associations.

Results

We report this region as a potential biomarker for hepatocellular carcinoma. About thirty clustered miRNAs, a long-non-coding RNA, and two coding genes of the region were underexpressed in tumors. The receiver operating characteristic analysis identified 11 clustered miRNAs with diagnostic potential. Survival analyses identified maternally expressed gene 3 and the miR-379/656 cluster as prognostically significant. Further, the random forest model predicted that the miRNA cluster classifies patients according to Tumor, Node, Metastasis (TNM) staging. Furthermore, overrepresentation analysis identified several key pathways, molecular functions, and biological processes associated with the cluster gene targets.

Conclusion

Our study suggests that DLK1-DIO3 genes, miR-379/656 cluster, and its target gene network might be potential diagnostic and prognostic markers for hepatocellular carcinoma management and therapy.

Integrative analysis of senescence-related genes identifies robust prognostic clusters with distinct features in hepatocellular carcinoma

INTRODUCTION

Senescence refers to a state of permanent cell growth arrest and is regarded as a tumor suppressive mechanism, whereas accumulative evidence demonstrate that senescent cells play an adverse role during cancer progression. The scarcity of specific and reliable markers reflecting senescence level in cancer impede our understanding of this biological basis.

OBJECTIVES

Senescence-related genes (SRGs) were collected for integrative analysis to reveal the role of senescence in hepatocellular carcinoma (HCC).

METHODS

Consensus clustering was used to subtype HCC based on SRGs. Several computational methods, including single sample gene set enrichment analysis (ssGSEA), fuzzy c-means algorithm, were performed. Data of drug sensitivities were utilized to screen potential therapeutic agents for different senescence patients. Additionally, we developed a method called signature-related gene analysis (SRGA) for identification of markers relevant to phenotype of interest. Experimental strategies consisting quantitative real-time PCR (qRT-PCR), β-galactosidase assay, western blot, and tumor-T cell co-culture system were used to validate the findings in vitro.

RESULTS

We identified three robust prognostic clusters of HCC patients with distinct survival outcome, mutational landscape, and immune features. We further extracted signature genes of senescence clusters to construct the senescence scoring system and profile senescence level in HCC at bulk and single-cell resolution. Senescence-induced stemness reprogramming was confirmed both in silico and in vitro. HCC patients with high senescence were immune suppressed and sensitive to Tozasertib and other drugs. We suggested that MAFG, PLIN3, and 4 other genes were pertinent to HCC senescence, and MAFG potentially mediated immune suppression, senescence, and stemness.

CONCLUSION

Our findings provide insights into the role of SRGs in patients stratification and precision medicine.

Exploring the relationship between MGAT2 and glioblastoma: A Mendelian Randomization and bioinformatics approach

BACKGROUND

Mannosyl-glycoprotein beta-1,2-N-acetylglucosaminyltransferase 2 (MGAT2) and tumors' relevant research was in full swing recently. Therefore, we employed Mendelian Randomization (MR) alongside bioinformatics to thoroughly investigate the possible relationship between MGAT2 and glioblastoma (GBM).

METHODS

We utilized the summary statistics of genome-wide association studies (GWAS) for MGAT2 (N = 35,559 from deCODE) and glioblastoma (N = 379,155 from FinnGen). MR was used to assess the causal relationship between MGAT2 and GBM. Bioinformatics was used for a more in-depth exploration of the relationship between MGAT2 and GBM.

RESULTS

MR analysis demonstrated a causal relationship, showing that elevated levels of MGAT2 are associated with an increased risk of GBM (OR = 2.59, 95 % CI: 1.13-5.91, p = 0.023). Further investigation revealed significant differences in MGAT2 expression across normal tissue, tumor tissue, and gliomas of different types. Additionally, we found that MGAT2 may influence GBM through immune-related pathways, particularly through the role of macrophages. Proteins associated with MGAT2 were also identified in the PPI network.

CONCLUSION

This study first validated the causal relationship between MGAT2 and glioblastoma, and used bioinformatics to explore the relationship from multiple perspectives. Additionally, we proposed hypotheses for further research to investigate the potential mechanisms underlying this connection.

Advancing personalized cancer therapy: Onko_DrugCombScreen-a novel Shiny app for precision drug combination screening

Identifying and validating genotype-guided drug combinations for a specific molecular subtype in cancer therapy represents an unmet medical need and is important in enhancing efficacy and reducing toxicity. However, the exponential increase in combinatorial possibilities constrains the ability to identify and validate effective drug combinations. In this context, we have developed Onko_DrugCombScreen, an innovative tool aiming at advancing precision medicine based on identifying significant drug combination candidates in a target cancer cohort compared to a comparison cohort. Onko_DrugCombScreen, inspired by the molecular tumor board process, synergizes drug knowledgebase analysis with various statistical methodologies and data visualization techniques to pinpoint drug combination candidates. Validated through a TCGA-BRCA case study, Onko_DrugCombScreen has demonstrated its proficiency in discerning established drug combinations in a specific cancer type and in revealing potential novel drug combinations. By enhancing the capability of drug combination discovery through drug knowledgebases, Onko_DrugCombScreen represents a significant advancement in personalized cancer treatment by identifying promising drug combinations, setting the stage for the development of more precise and potent combination treatments in cancer care. The Onko_DrugCombScreen Shiny app is available at https://rshiny.gwdg.de/apps/onko_drugcombscreen/. The Git repository can be accessed at https://gitlab.gwdg.de/MedBioinf/mtb/onko_drugcombscreen.

Cytochrome P450 2E1 inhibitor Q11 is effective on hepatocellular carcinoma by promoting peritumor neutrophil chemotaxis

Current studies found that the peritumoral tissue of hepatocellular carcinoma (HCC) may be different from normal liver tissue based on proteomics, and related to progression, recurrence and metastasis of HCC. Our previous study proposed "peritumor microenvironment (PME)" to summarize the influence of peritumor tissue on occurrence and progression of HCC. Peritumor CYP2E1 activity was significantly elevated in HCC, and related to occurrence and progression of HCC. However, the effectiveness and mechanism of inhibiting CYP2E1 against HCC remain unclear. In this study, by integrating the advantages of proteomics and transcriptomics, we reanalyzed the various influencing factors in PME. Although there were large differences in the occurrence and progression, the immunity and inflammation still played crucial roles. Peritumor neutrophil were "pro-tumor" phenotype in the stage of progression, while it showed cytotoxicity for tumor cell in the occurrence stage. CYP2E1 activity is associated with peritumor neutrophil infiltration and occurrence of HCC. CYP2E1 inhibitor Q11 showed anti-tumor effects in an orthotopic HCC mouse model by promoting secretion of chemokines and infiltration of neutrophils in peritumor tissue. Overall, these findings provided a reasonable mechanism of anti-tumor effects of CYP2E1 inhibitors, which may be a new strategy for the prevention and treatment of HCC.

Association of tumor microbiome with survival in resected early-stage PDAC

The pancreas tumor microbiota may influence tumor microenvironment and influence survival in early-stage pancreatic ductal adenocarcinoma (PDAC); however, current studies are limited and small. We investigated the relationship of tumor microbiota to survival in 201 surgically resected patients with localized PDAC (Stages I-II), from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts. We characterized the tumor microbiome using RNA-sequencing data. We examined the association of the tumor microbiome with overall survival (OS), via meta-analysis with the Cox PH model. A microbial risk score (MRS) was calculated from the OS-associated microbiota. We further explored whether the OS-associated microbiota is related to host tumor immune infiltration. PDAC tumor microbiome α- and β-diversities were not associated with OS; however, 11 bacterial species, including species of Gammaproteobacteria, confirmed by extensive resampling, were significantly associated with OS (all Q < 0.05). The MRS summarizing these bacteria was related to a threefold change in OS (hazard ratio = 2.96 per standard deviation change in the MRS, 95% confidence interval = 2.26-3.86). This result was consistent across the two cohorts and in stratified analyses by adjuvant therapy (chemotherapy/radiation). Identified microbiota and the MRS also exhibited association with memory B cells and naïve CD4+ T cells, which may be related to the immune landscape through BCR and TCR signaling pathways. Our study shows that a unique tumor microbiome structure, potentially affecting the tumor immune microenvironment, is associated with poorer survival in resected early-stage PDAC. These findings suggest that microbial mechanisms may be involved in PDAC survival, potentially informing PDAC prognosis and guiding personalized treatment strategies.IMPORTANCEMuch of the available data on the PDAC tumor microbiome and survival are derived from relatively small and heterogeneous studies, including those involving patients with advanced stages of pancreatic cancer. There is a critical knowledge gap in terms of the tumor microbiome and survival in early-stage patients treated by surgical resection; we expect that advancements in survival may initially be best achieved in these patients who are treated with curative intent.

Variability in radiotherapy outcomes across cancer types: a comparative study of glioblastoma multiforme and low-grade gliomas

Radiotherapy is a crucial treatment option for various cancers. However, the results of radiotherapy can vary widely across different cancer types and even among patients with the same type of cancer. This variability presents a major challenge in optimizing treatment strategies and improving patient survival. Here, we collected radiotherapy phenotype and expression data from 32 TCGA cancer datasets and performed overall survival analysis for 32 cancer types. Additionally, we conducted a signaling pathway enrichment analysis to identify key pathways involved in radiotherapy resistance and sensitivity. Our findings show that radiotherapy improves survival outcomes in certain cancer types, such as glioblasoma multiforme (GBM), while worsening outcomes in others, such as low-grade glioma (LGG). Next, we focused on exploring the differences in radiotherapy outcomes between GBM and LGG, focusing on the molecular mechanisms contributing to these variations. We identify differential regulation of pathways related to programmed cell death, DNA repair, telomere maintenance, chromosome condensation, antiviral responses, and interferon signaling between GBM and LGG patients perhaps explaining radiotherapy efficacy. A genetic analysis confirmed the importance of immune response and radiotherapy outcome for LGG patients. These insights underscore the importance of personalized treatment approaches and the need for further research to improve radiotherapy outcomes in cancer patients.

Thymidine kinase 1 indicates resistance to immune checkpoint plus tyrosine kinase inhibition in renal cell carcinoma

PURPOSE

Immune checkpoint plus tyrosine kinase inhibition (IO + TKI) has emerged as the first-line therapy in metastatic renal cell carcinoma (RCC), but no biomarker can predict its efficacy. Thymidine kinase 1 (TK1) is closely associated with immune evasion in tumors.

METHODS

Metastatic RCC patients treated by IO + TKI were enrolled from two cohorts (ZS-MRCC, n = 45; Javelin-101, n = 726). High-risk localized RCC were also enrolled (ZS-HRRCC, n = 40). TK1 was assessed by RNA-sequencing in all cohorts, and the immune contexture was assessed by flow cytometry and immunohistochemistry.

RESULTS

Higher TK1 expression was found in patients resistant to IO + TKI therapy (p = 0.025). High-TK1 group showed poor progression-free survival (PFS) in both the ZS-MRCC cohort (P = 0.008) and the Javelin-101 cohort (P = 0.036). By multivariate Cox regression, high-TK1 was determined as an independent factor for poor PFS (hazard ratio (HR) = 3.855, P = 0.002). High-TK1 expression was associated with decreased granzyme B+ CD8+ T cells (ρ=-0.22, P = 0.18), increased PD1+ CD4+ T cells (ρ = 0.33, P = 0.04), increased PDL1+ macrophages (ρ = 0.45, P < 0.001), and increased regulatory T cells (ρ = 0.35, P = 0.03). A novel random forest (RF) risk score was built by machine learning based on TK1 and immunologic parameters. Combined IO + TKI therapy surpassed sunitinib monotherapy in the low RF risk score group (HR = 0.158, P < 0.001), but was inferior to sunitinib in the high RF risk score group (HR, 2.195, P < 0.001).

CONCLUSION

High-TK1 expression could be a potential indicator for therapeutic resistance, poor PFS and immune evasion in metastatic RCC under IO + TKI therapy. The novel RF risk score may help stratify patients for IO + TKI therapy.

8q24 derived ZNF252P promotes tumorigenesis by driving phase separation to activate c-Myc mediated feedback loop

As a well-known cancer risk region, the 8q24 locus is frequently amplified in a variety of solid tumors. Here we identify a pseudogene-derived oncogenic lncRNA, ZNF252P, which is upregulated in a variety of cancer types by copy number gain as well as c-Myc-mediated transcriptional activation. Mechanistically, ZNF252P binds and drives "phase separation" of HNRNPK and ILF3 protein in the nucleus and cytoplasm, respectively, to transcriptionally and posttranscriptionally activate c-Myc, thus forming a c-Myc/ZNF252P/c-Myc positive feedback loop. These findings expand the understanding of the relationship between genomic instability in the 8q24 region and tumorigenesis and clarify a regulatory mechanism involved in transcription and posttranscription from the perspective of RNA-mediated nuclear and cytoplasmic protein phase separation, which sheds light on the dialogue with the driver oncogene c-Myc. The pivotal regulatory axis of ZNF252P/c-Myc has potential as a promising biomarker and therapeutic target in cancer development.

Annexin A's Life in Pan-Cancer: Especially in Glioma Immune Cells

The Annexin A (ANXA) family plays a critical role in cancer, with particular emphasis on their prognostic significance in pan-cancer analyses and gliomas. By integrating multi-omics data from The Cancer Genome Atlas (TCGA) and single-cell sequencing analysis, we conducted a comprehensive evaluation of ANXA2 and ANXA4 to investigate their expression patterns and functional impacts across various cancers, with a focus on glioblastoma (GBM). Our analysis encompassed several key components, including literature review, identification of differentially expressed genes (DEGs) in cancer, survival analysis, co-expression studies, competing endogenous RNA networks, cellular functional analysis, tumor microenvironment response to chemotherapy, and tumor stemness. Special attention was given to glioblastoma and low-grade glioma. Notably, our findings highlighted discrepancies among the analytical tools used, underscoring the necessity of employing multiple methods for accurate identification of DEGs. Additionally, we determined that ANXA2 and ANXA4 are predominantly expressed by M2 macrophages in GBM, based on our characterization of human glioma macrophages. These results suggest a strong correlation between ANXA2 and ANXA4 expression levels and the presence of macrophages and CD4 + resting memory T cells in gliomas, offering valuable insights into the complex interplay between the ANXA family and cancer progression.

Biophysical investigation of the molecular interaction between minichromosome maintenance protein 6 and Bloom syndrome helicase

The minichromosome maintenance protein (MCM) complex and Bloom syndrome helicase (BLM) are crucial components in DNA replication and cell division. MCM, a hexameric helicase that unwinds double-stranded DNA, serves as an important diagnostic and prognostic biomarker for cancer cells and a target for anticancer drug development. BLM, associated with G-quadruplex structures, is another key helicase in maintaining genomic stability. In this study, we investigate the interaction between MCM6 and BLM at the atomic level, as their expression levels are highly correlated in various cancer types, with elevated levels indicating poor prognosis. To elucidate the molecular basis of MCM6/BLM interaction, we employed fluorescence polarization anisotropy analysis, NMR chemical shifts perturbation analysis (CSP), and paramagnetic relaxation enhancement (PRE) experiments. MCM6 binding domain (MBD) C and D exhibit similar binding affinities to MCM6 winged-helix domain (WHD). However, significant CSPs with MBD-D and PRE experiments suggested that MBD-D is closer to MCM6 WHD than MBD-C. Despite both proteins containing numerous negatively charged residues, hydrophobic interactions govern the association between MCM6 WHD and BLM MBD-D. This biophysical characterization of the MCM6/BLM interaction provides new insights into their functional relationship and challenges existing models. Our findings reveal that MCM6 binds BLM at a different site than its other known partner chromatin licensing and DNA replication factor. Understanding these protein-protein interactions at the molecular level may contribute to the development of novel anticancer therapies targeting the MCM6/BLM interaction.

Pan-cancer analysis reveals SMARCAL1 expression is associated with immune cell infiltration and poor prognosis in various cancers

Although immune checkpoint inhibition in particular has shown promise in cancer immunotherapy, it is not always efficient. Recent studies suggest that SMARCAL1 may play a role in tumor immune evasion, yet its pan-cancer role is unclear. We conducted a comprehensive analysis of SMARCAL1 using TCGA, GTEx, and CCLE databases, evaluating its expression, genetic alterations, epigenetic modifications, and their clinical correlations across 33 cancer types. Our findings indicate that SMARCAL1 is overexpressed in several cancers, such as Glioma, LUAD, KIRC, and LIHC, impacting prognosis. Elevated SMARCAL1 is linked to poor outcomes in Glioma, LUAD, and LIHC but correlates with better survival in KIRC. We also found significant associations between SMARCAL1 expression and DNA methylation in 13 cancers. Furthermore, SMARCAL1 expression correlates with immune infiltration, suggesting it as a potential therapeutic target in cancer immunotherapy. This study underscores the need for further research on SMARCAL1 to enhance immunotherapeutic strategies.

Integrated bioinformatics investigation and experimental validation reveals the clinical and biological significance of chromobox family in breast cancer

Chromobox (CBX) proteins are essential components of the Polycomb group and play pivotal roles in tumor onset, progression, and metastasis. However, the prognostic significance and functions of CBXs in the advancement of breast cancer (BC) have not been sufficiently investigated. A comprehensive analysis of the expression and prognostic relevance of CBX1-8 in BC was conducted comprehensively using The Cancer Genome Atlas (TCGA) and multiple databases. High mRNA expression of CBX2, CBX3, and CBX5 in BC patients was significantly associated with reduced overall survival (OS). Results from univariate and multivariate Cox regression analysis revealed that the mRNA expression level of CBX2 in BC patients served as an independent prognostic factor. In Luminal A and Luminal B BC subtypes, high expression of CBX2 correlated with unfavorable prognosis. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated a strong association between CBX2 and the cell cycle as well as DNA replication processes. CCK-8 and EdU assays demonstrated that silencing CBX2 inhibited the proliferation of T47D and MCF7 cell lines. Moreover, the cell cycle assay indicated that CBX2 silencing led to cell cycle arrest, accompanied by a significant decrease in the levels of CDK4 and CyclinD1. Elevated CBX2 expression significantly correlated with the infiltration of T cells, B cells, macrophages, and dendritic cells in BC. Our findings could provide new perspectives for identifying potential prognostic markers within the CBX family in BC. Targeting CBX2 may present a promising approach to address endocrine resistance in BC therapy.

The mutational landscape and functional effects of noncoding ultraconserved elements in human cancers

The mutational landscape of phylogenetically ultraconserved elements (UCEs), especially those in noncoding DNAs (ncUCEs), and their functional relevance in cancers remain poorly characterized. Here, we perform a systematic analysis of whole-genome and in-house targeted UCE sequencing datasets from more than 3000 patients with cancer of 13,736 UCEs and demonstrate that ncUCE somatic alterations are common. Using a multiplexed CRISPR knockout screen in colorectal cancer cells, we show that the loss of several altered ncUCEs significantly affects cell proliferation. In-depth functional studies in vitro and in vivo further reveal that specific ncUCEs can be enhancers of tumor suppressors (such as ARID1B) and silencers of oncogenic proteins (such as RPS13). Moreover, several miRNAs located in ncUCEs are recurrently mutated. Mutations in miR-142 locus can affect the Drosha-mediated processing of precursor miRNAs, resulting in the down-regulation of the mature transcript. These results provide systematic evidence that specific ncUCEs play diverse regulatory roles in cancer.

The Breast Cancer Classifier refines molecular breast cancer classification to delineate the HER2-low subtype

Current breast cancer classification methods, particularly immunohistochemistry and PAM50, face challenges in accurately characterizing the HER2-low subtype, a therapeutically relevant entity with distinct biological features. This notable gap can lead to misclassification, resulting in inappropriate treatment decisions and suboptimal patient outcomes. Leveraging RNA-seq and machine-learning algorithms, we developed the Breast Cancer Classifier (BCC), a unique transcriptomic classifier for more precise breast cancer subtyping, specifically by delineating and incorporating HER2-low as a distinct subtype. BCC also redefined the PAM50 Normal subtype into other subtypes, disputing its classification as a unique molecular group. Our statistical analysis not only confirmed the reproducibility and accuracy of BCC, but also revealed similarities in prognostic characteristics between the HER2-low and Basal subtypes. Addressing this gap in breast cancer classification is clinically significant because it not only improves treatment stratification, but also uncovers novel molecular and immunohistochemical features associated with the HER2-low and HER2-high subtypes, thereby advancing our understanding of breast cancer heterogeneity and providing guidance in precision oncology.

Potential value of immunogenic cell death related-genes in refining European leukemiaNet guidelines classification and predicting the immune infiltration landscape in acute myeloid leukemia

Immunogenic cell death (ICD) is the kind of cell death that triggers the immune system. It affects several tumors, whereas its significance for prognosis in acute myeloid leukemia (AML) remains uncertain. AML categorization by cytogenetic variables is inaccurate. In addition, risk stratification of AML based on cytogenetics is imprecise. The data of AML patients were extracted from 4 databases, a total of 1,537 patients. Univariate and LASSO Cox regression analyses were conducted to construct an ICD risk signature (ICDRS). The ICDRS showed strong prognostic value for AML through Kaplan-Meier, Cox, ROC analyses and nomogram. Combining the ICDRS with the European LeukemiaNet (ELN) classification to redefine the risk stratification can better predict the prognosis of AML. Moreover, the ICDRS was examined to identify gene functional enrichment, immunological characteristics, drug susceptibility, and somatic mutation, which revealed considerable variations among different risk categories. We further validated the expression of ICDRS in the AML bone marrow microenvironment by single-cell RNA (scRNA) analysis. Ultimately, the functional role of CASP1 was proven in AML by a series of in-vitro experiments. Our study highlights the significant impact of ICDRS on AML, which may improve ELN risk classification, predict immune landscapes, and guide personalized therapy.

Genetic regulation of TERT splicing affects cancer risk by altering cellular longevity and replicative potential

The chromosome 5p15.33 region, which encodes telomerase reverse transcriptase (TERT), harbors multiple germline variants identified by genome-wide association studies (GWAS) as risk for some cancers but protective for others. Here, we characterize a variable number tandem repeat within TERT intron 6, VNTR6-1 (38-bp repeat unit), and detect a strong link between VNTR6-1 alleles (Short: 24-27 repeats, Long: 40.5-66.5 repeats) and GWAS signals rs2242652 and rs10069690 within TERT intron 4. Bioinformatics analyses reveal that rs10069690-T allele increases intron 4 retention while VNTR6-1-Long allele expands a polymorphic G-quadruplex (G4, 35-113 copies) within intron 6, with both variants contributing to variable TERT expression through alternative splicing and nonsense-mediated decay. In two cell lines, CRISPR/Cas9 deletion of VNTR6-1 increases the ratio of TERT-full-length (FL) to the alternative TERT-β isoform, promoting apoptosis and reducing cell proliferation. In contrast, treatment with G4-stabilizing ligands shifts splicing from TERT-FL to TERT-β isoform, implicating VNTR6-1 as a splicing switch. We associate the functional variants VNTR6-1, rs10069690, and their haplotypes with multi-cancer risk and age-related telomere shortening. By regulating TERT splicing, these variants may contribute to fine-tuning cellular longevity and replicative potential in the context of stress due to tissue-specific endogenous and exogenous exposures, thereby influencing the cancer risk conferred by this locus.

Comprehensive pan-cancer analysis of ENOPH1 in human tumors

BACKGROUND

ENOPH1 (Enolase-phosphatase 1), a member of the HAD-like hydrolase superfamily, has been linked to a range of physiological conditions, including neurological disorders. However, its involvement in tumorigenesis remains underexplored. This study is the first to conduct a pan-cancer analysis of ENOPH1, aiming to elucidate its role in multiple cancers through various bioinformatics platforms.

METHODS

We conducted a thorough analysis using data from UCSC databases. ENOPH1 expression in tumor and normal tissues was evaluated using R language software. Survival analyses, genetic alterations, and RNA modifications were assessed through the GEPIA2 and cBioPortal platforms. The relationships between ENOPH1 and immune infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), and homologous recombination deficiency (HRD) were examined using TIMER2 and R software. ENOPH1-related gene enrichment analysis was performed using the STRING and GEPIA2 databases, followed by Gene Ontology (GO) and KEGG pathway enrichment analyses.

RESULTS

ENOPH1 expression was significantly upregulated in various cancers, including ACC, BLCA, BRCA, and COAD. High ENOPH1 expression was associated with poor overall survival (OS) in cancers such as KICH, LIHC, BRCA and LUAD. High ENOPH1 expression was associated with poor disease specific survival (DSS) in cancers such as KICH, LIHC, BRCA and MESO. Genetic alterations of ENOPH1, primarily mutations and deep deletions, were identified in UCEC, BLCA, and OV. ENOPH1 showed significant correlations with RNA modifications (m1A, m5C, m6A), immune checkpoints, and immune modulators across multiple cancer types. ENOPH1 was positively correlated with TMB, MSI, and HRD in cancers like BLCA, BRCA, and STAD. Furthermore, enrichment analysis revealed that ENOPH1 interacts with proteins involved in critical pathways such as AMPK, Hippo, and PI3K-AKT, suggesting its role in cancer progression.

CONCLUSION

This pan-cancer analysis reveals ENOPH1's potential as a prognostic biomarker and its involvement in key signaling pathways across multiple cancers. Our findings provide new insights into the role of ENOPH1 in tumorigenesis and highlight its potential as a therapeutic target in cancer treatment.

Unveiling expression patterns, mechanisms, and therapeutic opportunities of transmembrane protein 106C: From pan-cancers to hepatocellular carcinoma

BACKGROUND

Although transmembrane protein 106C (TMEM106C) has been elucidated to be overexpressed in cancers, its underlying mechanisms have not yet been fully understood.

AIM

To investigate the expression levels and molecular mechanisms of TMEM106C across 34 different cancer types, including liver hepatocellular carcinoma (LIHC).

METHODS

We analyzed TMEM106C expression patterns in pan-cancers using microenvironment cell populations counter to evaluate its association with the tumor microenvironment. Gene set enrichment analysis was conducted to identify molecular pathways related to TMEM106C. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) analysis was conducted to identify upstream transcriptional regulators of TMEM106C. In LIHC, we examined mRNA profiles, performed in-house quantitative polymerase chain reaction, immunohistochemistry, and constructed a co-expression gene network. Functional assays, including cell counting kit-8, cell cycle, apoptosis, migration, and invasion, were conducted. The effect of nitidine chloride (NC) on LIHC xenograft was evaluated through RNA sequencing and molecular docking. Finally, potential therapeutic agents targeting TMEM106C were predicted.

RESULTS

TMEM106C was significantly overexpressed in 27 different cancer types and presaged poor prognosis in four of these types, including LIHC. Across pan-cancers, TMEM106C was inversely correlated to the abundances of immune and stromal cells. Furthermore, TMEM106C was significantly linked to cell cycle and DNA replication pathways in pan-cancers. ChIP-seq analysis predicted CCCTC-binding factor as a pivotal transcriptional factor targeting the TMEM106C gene in pan-cancers. Integrated analysis showed that TMEM106C was upregulated in 4657 LIHC compared with 3652 normal liver tissue [combined standardized mean difference = 1.31 (1.09, 1.52)]. In-house LIHC samples verified the expression status of TMEM106C. Higher TMEM106C expression signified worse survival conditions in LIHC patients treated with sorafenib, a tyrosine kinase inhibitor (TKI). Co-expressed analysis revealed that TMEM106C were significantly enriched in the cell cycle pathway. Knockout experiments demonstrated that TMEM106C plays a crucial role in LIHC cell proliferation, migration, and invasion, with cell cycle arrest occurring at the DNA synthesis phase, and increased apoptosis. Notably, TMEM106C upregulation was attenuated by NC treatment. Finally, TMEM106C expression levels were significantly correlated with the drug sensitivity of anti-hepatocellular carcinoma agents, including JNJ-42756493, a TKI agent.

CONCLUSION

Overexpressed TMEM106C was predicted as an oncogene in pan-cancers, which may serve as a promising therapeutic target for various cancers, including LIHC. Targeting TMEM106C could potentially offer a novel direction in overcoming TKI resistance specifically in LIHC. Future research directions include in-depth experimental validation and exploration of TMEM106C's role in other cancer types.

Using major histocompatibility complex (MHC) II expression to predict antitumor response to CD4 + lymphocyte depletion

Immunotherapy targeting CD4 + FoxP3 + regulatory T cells (Tregs) through CD4 + lymphocyte depletion is being investigated as cancer treatment. This study examines the efficacy and limitations of CD4 depletion across various cancer models. We examined CD4 depletion in syngeneic mouse tumor models including B16 melanoma, Renca kidney cancer, and Hepa1-6 hepatocellular carcinoma. The study explored the relationship between MHC II expression and tumor growth, immune response, and survival. In mouse models, CD4 depletion suppressed B16 and Renca tumor growth but accelerated Hepa1-6 tumors. Hepa1-6 had high MHC II expression while the other two lines had low MHC II expression. Manipulation of MHC II expression in Hepa1-6 and Renca cell lines confirmed the mechanistic importance of MHC II in generating a CD4-based antitumor immune response. Analysis of the TCGA dataset supports the relevance of this mechanism in patients. In tumors with high MHC II and low MHC I expression, increased CD4 levels correlated with improved survival. CD4 depletion can suppress tumor growth or promote tumor growth, depending on tumor MHC expression status. MHC status may identify tumors where intratumor CD4 may be a better early-response marker than CD8.

Creation of an innovative diagnostic framework for hepatocellular carcinoma employing bioinformatics techniques focused on senescence-related and pyroptosis-related genes

Background

Liver hepatocellular carcinoma (LIHC) continues to pose a major global health concern and is characterized by elevated mortality rates and a lack of effective therapies. This study aimed to explore differential gene expression linked to cellular senescence and pyroptosis in LIHC and to develop a prognostic risk model for use in clinical settings.

Methods

We acquired datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). DESeq2 was used to identify differentially expressed genes associated with cell senescence and pyrodeath. The least absolute shrinkage and selection operator (LASSO) regression model was developed using cellular senescence- and pyroptosis-related differentially expressed genes (CSR&PRDEGs), and its predictive performance was evaluated with Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) curves. We also performed various functional analyses of the genes. These findings were validated by real-time fluorescence quantitative polymerase chain reaction (PCR).

Results

Using bioinformatics analysis, we developed a prognostic risk framework incorporating six critical genes: ANXA2, APOA1, EZH2, IGF2BP3, SQSTM1, and TNFRSF11B.The model demonstrated a statistically significant difference in overall survival between the high-risk and low-risk groups (p < 0.05). Additionally, real-time fluorescence quantitative PCR confirmed that genes ANXA2, APOA1, EZH2, IGF2BP3, SQSTM1, and TNFRSF11B were significantly overexpressed in the peripheral blood of patients with LIHC in comparison to normal volunteers, thereby validating the prognostic risk model's accuracy.

Conclusions

This study systematically elucidated the functions of genes associated with senescence and pyroptosis in LIHC cells. The constructed prognostic risk model serves to guide the development of personalized treatment plans, enhance patient management via risk stratification, facilitate the identification of high-risk patients, intensify monitoring or implement proactive interventions, thereby providing a novel perspective for the diagnosis and treatment of LIHC.

ITGA4 as a potential prognostic and immunotherapeutic biomarker in human cancer and its clinical significance in gastric cancer: an integrated analysis and validation

Background

Integrin Subunit Alpha 4 (ITGA4), a member of the integrin protein family, is involved in the progression of malignant tumors. However, its role across different cancer types is not well understood.

Methods

Utilizing multi-omics data, we comprehensively evaluated ITGA4's expression, clinical relevance, diagnostic and prognostic value, functions, mutations, and methylation status, along with its impact on immunity, mismatch repair (MMR), heterogeneity, stemness, immunotherapy responsiveness, and drug resistance in pan-cancer, with partial validation in gastric cancer (GC) using transcriptomic analysis, single-cell data, western blot (WB), wound-healing assay, flow cytometry and immunohistochemistry (IHC). We further investigated its correlation with clinicopathology and serological markers on tissues from 80 GC patients.

Results

ITGA4 expression was generally low in normal tissues but varied significantly across tumor types, with higher levels in advanced stages and grades. It demonstrated diagnostic value in 20 cancer types and effectively predicted 1-, 3-, and 5-year survival rates as part of a prognostic model. ITGA4 played roles in cell adhesion, migration, immune regulation, and pathways like PI3K-Akt and TSC-mTOR. It showed alterations in 22 cancer types, with methylation at 9 sites inhibiting its expression. ITGA4 positively correlated with immune cell infiltration, immune regulatory genes, chemokines, and might reduce microsatellite instability (MSI) and tumor mutation burden (TMB) by promoting MMR gene expression. It could also predict immunotherapy efficacy and chemotherapy sensitivity. In GC, high ITGA4 expression was related to poor prognosis, promoted tumor proliferation and migration, and enhanced immune cell infiltration. ITGA4 expression was higher in GC cells and tissues than normal ones. Its downregulation inhibited GC cell migration and promoted apoptosis. Moreover, ITGA4 was correlated with N stage, pathological stage, neural and vascular invasion, serum levels of Ki-67, immune cells, CRP and CA125.

Conclusion

ITGA4 is a potential biomarker and therapeutic target to enhance cancer treatment and improve patient outcomes.

A machine learning-based investigation of integrin expression patterns in cancer and metastasis

Integrins, a family of transmembrane receptor proteins, are well known to play important roles in cancer development and metastasis. However, a comprehensive understanding of these roles has not been achieved due to the complex relationships between specific integrins, cancer types, and the stages of cancer progression. Publicly accessible repositories from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) projects provide rich datasets for exploring these relationships using machine learning (ML). In this study, integrin RNA-Seq expression data of ~ 8 healthy tissues in GTEx and corresponding tumors in TCGA were selected. Integrin expression was used to train ML models to distinguish between different healthy tissues, solid tumors, as well as normal and tumor samples from the same tissue type. These ML models can classify samples by tissue origin or disease status with high accuracy, and the integrins essential to these classifiers were identified. In some cases, the expression of only one or two integrins was needed to classify tissue type, tumor type or disease status with accuracy > 0.9. For example, expression of ITGA7 alone can distinguish healthy and cancerous breast tissue. Additionally, integrin co-expression networks in healthy and cancerous breast tissues were compared and were found to change significantly from healthy to cancer, indicating changes in functional involvement of integrins due to cancer. Integrin expression in metastatic tumors were further examined using data from the AURORA project for Metastatic Breast Cancer (MBC), and several integrins such as ITGAD, ITGA4, ITGAL, and ITGA11 were found to have significantly lower expression in metastases than in primary tumors.

Induction of the p21/CDK6 pathway and alteration of the immune microenvironment by the stem cell marker CBX3 in melanoma

BACKGROUND

As one of the stem cell markers, chromobox protein homolog 3 (CBX3) participates in multiple signaling pathways that affect the progression of various tumors. However, the role of CBX3 in melanoma remains unclear, and the mechanisms by which CBX3 may regulate immunotherapy outcome remain largely unknown.

METHODS

We used the Cancer Genome Atlas, Genotype-Tissue Expression portal, and Gene Expression Omnibus database to estimate CBX3 expression and its prognostic effect in melanoma. The role of CBX3 in proliferation and migration of melanoma cells were examined using the CCK8, cloning, wound healing, and transwell assays. The effect of CBX3 on melanoma tumorigenesis was assessed using an in vivo animal model. The role of CBX3 in cell cycle was examined using flow cytometry, and expression levels of cell cycle-related genes and proteins in cells with altered CBX3 levels were analyzed using qPCR and western blotting. The function of CBX3 in the immune microenvironment of melanoma was studied using single-cell RNA sequencing and public databases.

RESULTS

We found that CBX3 was highly expressed in melanoma with poor prognosis. CBX3 promoted the proliferation and migration of melanoma cells in vivo and in vitro. Functional analysis revealed that CBX3 regulates cell cycle, as it accelerated the G1 to S transition, decreased p21 expression, and increased CDK6 expression. Finally, single-cell sequencing and immune-related assays showed that CBX3 is immunogenic and can change the immune microenvironment of melanoma.

CONCLUSIONS

We conclude that the stem cell marker, CBX3 activates the p21/CDK6 pathway and alters the immune microenvironment in melanoma.

Fast-Relaxing Hydrogels Promote Pancreatic Adenocarcinoma Cell Aggressiveness through Integrin β1 Signaling

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense extracellular matrix (ECM) exhibiting high stiffness and fast stress relaxation. In this work, gelatin-based viscoelastic hydrogels were developed to mimic the compositions, stiffness, and fast stress relaxation of PDAC tissues. The hydrogels were cross-linked by gelatin-norbornene-boronic acid (GelNB-BA), thiolated macromers, and a 1,2-diol-containing linear synthetic polymer PHD. Controlling the thiol-norbornene cross-linking afforded tunable stiffness, whereas increasing PHD content led to hydrogels with PDAC-mimicking fast stress relaxation. In vitro studies, including proliferation, morphology, and mRNA-sequencing, showed that fast-relaxing hydrogels supported PDAC cell proliferation, epithelial-mesenchymal transition (EMT), and integrin β1 activation. Blocking integrin β1 in vitro led to upregulating EMT markers in both slow and fast-relaxing hydrogels. However, this strategy profoundly impacted tumor growth rate and reduced tumor size but did not alter metastasis patterns in an orthotopic mouse model. This suggests a need to further evaluate the antitumor effect of integrin β1 blockade.

MAP1LC3C repression reduces CIITA- and HLA class II expression in non-small cell lung cancer

In the last decade, advancements in understanding the genetic landscape of lung squamous cell carcinoma (LUSC) have significantly impacted therapy development. Immune checkpoint inhibitors (ICI) have shown great promise, improving overall and progression-free survival in approximately 25% of the patients. However, challenges remain, such as the lack of predictive biomarkers, difficulties in patient stratification, and identifying mechanisms that cancers use to become immune-resistant ("immune-cold"). Analysis of TCGA datasets reveals reduced MAP1LC3C expression in cancer. Further analysis indicates that low MAP1LC3C is associated with reduced CIITA and HLA expression and with decreased immune cell infiltration. In tumor cells, silencing MAP1LC3C inhibits CIITA expression and suppresses HLA class II production. These findings suggest that cancer cells are selected for low MAP1LC3C expression to evade efficient immune responses.

Molecular Insights into HR-HPV and HCMV Co-Presence in Cervical Cancer Development

BACKGROUND

Cervical cancer remains a significant health concern worldwide and the primary cause of cancerous cervical lesions is the infection with high-risk human papillomavirus (HR-HPV). However, emerging evidence suggests that HR-HPV infection alone is insufficient for cancer development, and other co-factors may contribute to cervical carcinogenesis. Human cytomegalovirus (HCMV), a common herpesvirus frequently detected in cervical cancer samples, has demonstrated oncogenic potential.

OBJECTIVES

This review aims to explore the molecular interactions between HR-HPV and HCMV in promoting cervical cancer progression.

METHODS

A comprehensive search was conducted in PubMed and Google Scholar, focusing on articles examining the role of HCMV in cervical tissues and/or cells, selected based on relevance and significance.

RESULTS

The reviewed literature indicates that HCMV and HR-HPV share several oncogenic mechanisms that could drive cervical cell transformation.

CONCLUSIONS

Both viruses may synergistically promote cervical epithelial transformation and tumor progression in multiple ways. HR-HPV may facilitate HCMV entry by increasing host cell receptors essential for viral attachment. Additionally, HR-HPV and HCMV may cooperatively disrupt cellular processes, enhancing carcinogenesis. Both viruses may also modulate the local immune environment, enabling immune evasion and lesion persistence. However, further in vitro and in vivo studies are required to validate these hypotheses.

LncRNA PVT1 links estrogen receptor alpha and the polycomb repressive complex 2 in suppression of pro-apoptotic genes in hormone-responsive breast cancer

RNA-based therapeutics highlighted novel approaches to target either coding or noncoding molecules for multiple diseases treatment. In breast cancer (BC), a multitude of deregulated long noncoding RNAs (lncRNAs) have been identified as potential therapeutic targets also in the context of antiestrogen resistance, and the RNA binding activity of the estrogen receptor α (ERα) points additional potential candidates to interfere with estrogenic signaling. A set of lncRNAs was selected among ERα-associated RNAs in BC cell nuclei due to their roles in processes such as transcriptional regulation and epigenetic chromatin modifications. Native immunoprecipitation of nuclear ERα-interacting RNAs coupled to NGS (RIP-Seq) was performed in MCF-7 cells, leading to the identification of essential lncRNAs interacting with the receptor in multi-molecular regulatory complexes. Among these, PVT1, FGD5-AS1 and EPB41L4A-AS1 were selected for further investigation. Functional assays and transcriptome analysis following lncRNA knock-down indicated PVT1 as the master modulator of some of the most relevant BC hallmarks, such as cell proliferation, apoptosis, migration and response to hypoxia. In addition, targeted experiments identified PVT1 as a key factor in the composition of PRC2-ERα network involved in downregulation of tumor suppressor genes, including BTG2.

Integrative analysis of SEPN1 in glioma: Prognostic roles, functional implications, and potential therapeutic interventions

BACKGROUND

SEPN1, a selenoprotein involved in redox regulation and endoplasmic reticulum stress response, has an unclear role in cancer. This study aims to investigate the expression, prognostic significance, and tumor microenvironment (TME) relevance of SEPN1 across pan-cancer, with a particular focus on glioma.

METHODS

We analyzed SEPN1 expression and prognosis using the TCGA pan-cancer cohort. SEPN1 in glioma was further examined using data from TCGA, CGGA, GEO, and ZN-GC cohorts, along with survival analysis, single-cell RNA sequencing analysis, and enrichment analysis. We developed an SEPN1-related risk score (SRS) based on SEPN1-related long non-coding RNAs and validated its prognostic value. Drug sensitivity data and connectivity map analysis identified potential anti-glioma drugs based on the SRS.

RESULTS

We found that SEPN1 was significantly upregulated in glioma, associated with poor prognosis, functioned as an independent risk factor, and predominantly expressed in malignant glioma cells. Enrichment analysis indicated the involvement of SEPN1 in immune-related processes and signaling pathways. Suppressing SEPN1 in glioblastoma cells inhibited proliferation and induced G2/M arrest and apoptosis. The SRS demonstrated strong prognostic value and correlated with enhanced immune infiltration in the glioma TME. Potential anti-glioma drugs were identified based on the SRS.

CONCLUSIONS

SEPN1 emerges as a novel biomarker and therapeutic target in glioma, providing a basis for future development of targeted therapies.

Comprehensive Analysis of Granzymes and Perforin Family Genes in Multiple Cancers

Background/Objectives: Cancer remains a significant global health concern, with immunotherapies emerging as promising treatments. This study explored the role of perforin-1 (PRF1) and granzymes A, B and K (GZMA, GZMB and GZMK) in cancer biology, focusing on their impact on tumor cell death and immune response modulation. Methods: Through a comprehensive genomic analysis across various cancer types, we explored the differential expression, mutation profiles and methylation patterns of these genes, providing insights into their potential as therapeutic targets. Furthermore, we investigated their association with immune cell infiltration and pathway activation within the tumor microenvironment in each tumor type. Results: Our findings revealed distinct expression patterns and prognostic implications for PRF1, GZMA, GZMB and GZMK across different cancers, highlighting their multifaceted roles in tumor immunity. We found increased immune infiltration across all tumor types and significant correlations between the genes of interest and cytotoxic T cells, as well as the most significant survival outcomes in breast cancer. We also show that granzymes and perforin-1 are significantly associated with indicators of immunosuppression and T cell dysfunction within patient cohorts. In skin melanoma, glioblastoma, kidney and bladder cancers, we found significant correlations between the genes of interest and patient survival after receiving immune-checkpoint inhibition therapy. Additionally, we identified potential associations between the mRNA expression levels of these genes and drug sensitivity. Conclusions: Overall, this study enhances our understanding of the molecular mechanisms underlying tumor immunity and provides valuable insights into the potential therapeutic implications of PRF1, GZMA, GZMB and GZMK in cancer treatment.

Recombinant CD80 fusion protein combined with discoidin domain receptor 1 inhibitor for cancer treatment

Immune checkpoint inhibitors (ICIs) have significantly advanced the field of cancer immunotherapy. However, clinical data has shown that many patients have a low response rate or even resistance to immune checkpoint inhibitor alone. The underlying reasons for its poor efficacy include the deficiency of immune infiltration and effective CD28/CD80 costimulatory signal in tumor. Discoidin domain receptor 1 (DDR1) has been reported to be negatively related to immune cell infiltration in tumors. Herein, we constructed a soluble fusion protein using CD80, the natural ligand of CD28, in combination with DDR1 inhibitor. Our results demonstrated that CD80-Fc effectively activated T cells and inhibited tumor growth in vivo, even in tumors with poor efficacy of ICIs. Importantly, CD80-Fc fusion protein had a milder affinity against the targets which suggested a potential higher safety than CD28 agonists. Further, in order to promote tumor immune infiltration, we attempted to combine CD80-Fc fusion protein with DDR1 inhibitor for treatment. Our results indicated that using CD80-Fc fusion protein along with DDR1 inhibitor significantly promoted T cell infiltration in tumor microenvironment and more strongly inhibited tumor growth. Therefore, the combination use of CD80 fusion protein and DDR1 inhibitor could become an effective tumor immunotherapy strategy, potentially benefiting a larger number of patients. KEY POINTS: • We successfully constructed, expressed, and purified the recombinant CD80-Fc fusion protein • We demonstrated that CD80-Fc fusion protein has good safety and anti-tumor activity • We demonstrated that using CD80-Fc fusion protein along with DDR1 inhibitor can significantly promote immune infiltration of T cells in tumor microenvironment and more strongly inhibit tumor growth.

DDX39A resolves replication fork-associated RNA-DNA hybrids to balance fork protection and cleavage for genomic stability maintenance

Safeguarding replication fork stability in transcriptionally active regions is crucial for precise DNA replication and mutation prevention. Here, we discover the pervasive existence of replication fork-associated RNA-DNA hybrids (RF-RDs) in transcriptionally active regions of human cells. These hybrids function as protective barriers, preventing DNA2-mediated nascent DNA degradation and replication fork collapse under replication stress. We also identify DDX39A as a RAD51-associated protein that binds to stalled forks and resolves RF-RDs, facilitating proper DNA2-mediated DNA resection and replication fork restart. Excessive dissolution of RF-RDs causes replication fork collapse and genomic instability, while insufficient dissolution of RF-RDs under replication stress increases fork stability, resulting in chemoresistance that can be reversed by eliminating RF-RDs. In summary, we elucidated the prevalence of RF-RDs at replication forks within transcriptionally active regions, revealed their pivotal role in safeguarding replication fork stability, and proposed that targeting RF-RDs holds promise for augmenting chemotherapeutic efficacy.

NT5E (CD73) as a prognostic biomarker and therapeutic target associated with immune infiltration in lung adenocarcinoma

Lung adenocarcinoma (LUAD), the most common type of lung cancer, is a leading cause of cancer-related mortality. NT5E, an ecto-5'-nucleotidase enzyme, has been implicated in cancer progression, particularly in efferocytosis. Despite its potential involvement, the prognostic significance of NT5E and relationship with immune cell infiltration in LUAD have not been extensively explored. In this study, we performed a comprehensive analysis to elucidate the expression patterns of NT5E and its prognostic implications in LUAD using data from diverse public databases. Multiple computational algorithms, including CIBERSORT, ESTIMATE, and xCell, were employed to assess the correlation between NT5E expression and immune cell infiltration. We found that NT5E was significantly overexpressed at both the mRNA and protein levels in LUAD tissues. Elevated NT5E expression was significantly linked to multiple clinicopathological factors, including metastasis and pathological stage, and served as a strong predictor of poor prognosis in LUAD patients. Gene Set Enrichment Analysis (GSEA) indicated that NT5E plays a crucial role in regulating immune responses, as evidenced by differential gene expression associated with NT5E levels. A strong positive correlation was observed between NT5E expression and the presence of immune cells, including dendritic cells, macrophages, and CD4+ T cells, as well as the expression of various immune cell markers, suggesting that NT5E may influence the prognosis of LUAD patients by regulating immune cell infiltration. Additionally, drug sensitivity analysis highlights the potential of selumetinib and PD318088, both MEK1/2 inhibitors, to target NT5E in LUAD treatment, suggesting their use as single agents or in combination with other therapies. Collectively, these findings establish NT5E as a promising prognostic biomarker and therapeutic target in LUAD, particularly in the context of immune cell infiltration.

Functional screen identifies RBM42 as a mediator of oncogenic mRNA translation specificity

Oncogenic protein dosage is tightly regulated to enable cancer formation but how this is regulated by translational control remains unknown. The Myc oncogene is a paradigm of an exquisitely regulated oncogene and a driver of pancreatic ductal adenocarcinoma (PDAC). Here we use a CRISPR interference screen in PDAC cells to identify activators of selective MYC translation. The top hit, the RNA-binding protein RBM42, is highly expressed in PDAC and predicts poor survival. We show that RBM42 binds and selectively regulates the translation of MYC and a precise suite of pro-oncogenic transcripts, including JUN and EGFR. Mechanistically, we find that RBM42 binds and remodels the MYC 5' untranslated region structure, facilitating the formation of the translation pre-initiation complex. Importantly, RBM42 is necessary for PDAC tumorigenesis in a Myc-dependent manner in vivo. This work transforms the understanding of the translational code in cancer and illuminates therapeutic openings to target the expression of oncogenes.

A comprehensive analysis of molecular characteristics of hot and cold tumor of gastric cancer

BACKGROUND

The advent of immunotherapy has revolutionized the treatment paradigm for gastric cancer (GC), offering unprecedented clinical benefits. However, a detailed molecular characterization of the tumor immune microenvironment in GC is essential to further optimize these therapies and enhance their efficacy.

METHODS

Consensus clustering was utilized to classify GC patients into distinct immune states, followed by an in-depth analysis of differences in mutation profiles, copy number variations, and DNA methylation patterns. Weighted gene co-expression network analysis (WGCNA) and correlation analysis were applied to identify gene modules underlying the classification of immune "hot" and "cold" tumors. Subsequently, 101 machine learning algorithm combinations were employed to construct a prognostic model based on the identified gene modules. Single-cell analysis was conducted to investigate cellular interactions associated with the immune-determinant gene module. Finally, immunofluorescence staining for CD8, CD45, and CXCR4 was performed on human GC tissue samples.

RESULTS

A total of 1,298 GC patients were included in this comprehensive analysis. For the first time, we identified and characterized immune "hot" and "cold" tumors in GC patients, revealing distinct molecular features associated with these tumor types. Immune "hot" tumor-related genes were identified, and their functional roles were validated through biological behavior analysis. A prognostic signature, termed the hot tumor top regulators (HTTR), was developed using 101 machine learning algorithm combinations. The HTTR signature emerged as an independent prognostic factor, effectively stratifying patients into low- and high-risk groups with significant differences in overall survival. High-risk groups demonstrated strong associations with immune checkpoint regulation, antigen presentation, and inhibitory pathways. Notably, single-cell analysis revealed that HTTR genes were highly active in CD8 + T cells, with the CXCL12-CXCR4 axis playing a critical role in mediating interactions between CD8 + T cells and endothelial cells.

CONCLUSION

In conclusion, the HTTR signature served as a robust prognostic biomarker for GC patients and effectively identified those with immune "hot" tumors. This finding provided valuable insights into the molecular mechanisms of tumor immunity in GC, offering potential avenues for targeted therapeutic interventions.

Nuclear GTPSCS functions as a lactyl-CoA synthetase to promote histone lactylation and gliomagenesis

Histone lysine lactylation is a physiologically and pathologically relevant epigenetic pathway that can be stimulated by the Warburg effect-associated L-lactate. Nevertheless, the mechanism by which cells use L-lactate to generate lactyl-coenzyme A (CoA) and how this process is regulated remains unknown. Here, we report the identification of guanosine triphosphate (GTP)-specific SCS (GTPSCS) as a lactyl-CoA synthetase in the nucleus. The mechanism was elucidated through the crystallographic structure of GTPSCS in complex with L-lactate, followed by mutagenesis experiments. GTPSCS translocates into the nucleus and interacts with p300 to elevate histone lactylation but not succinylation. This process depends on a nuclear localization signal in the GTPSCS G1 subunit and acetylation at G2 subunit residue K73, which mediates the interaction with p300. GTPSCS/p300 collaboration synergistically regulates histone H3K18la and GDF15 expression, promoting glioma proliferation and radioresistance. GTPSCS represents the inaugural enzyme to catalyze lactyl-CoA synthesis for epigenetic histone lactylation and regulate oncogenic gene expression in glioma.

Dynamine 3 as a diagnostic and prognostic biomarker in pancreatic cancer: Implications for early detection and targeted therapy

BACKGROUND

Dynamins are defined as a group of molecules with GTPase activity. Among them, DNM3 has gained recognition in oncology for its tumor suppressor role. Based on this, the aim of this study is to investigate the effects of the DNM3 gene in patients diagnosed with pancreatic cancer using bioinformatics databases.

MATERIALS AND METHODS

For differential gene expression analysis, TCGA TARGET GTEx study on the UCSC Xena and GEO datasets were utilized; for the analysis of changes in gene expression according to clinical and pathological characteristics, UALCAN was employed; for Overall Survival (OS) analysis, Kaplan-Meier Plotter was used; for gene alteration analysis, cBioPortal was utilized; for immune cell infiltration analysis, Tumor Immune Estimation Resource (TIMER) and TIMER2.0 were employed; for enrichment analyses Enrichr was used; for Gene Set Correlation Enrichment Analysis Gscore was used on GSE15471; for essentiality of DNM3 gene in pancratic cancer cell lines DepMap was used; and for the detection of miRNAs, miRDB was utilized; ENCORI was used for gene-miRNA correlation and miRNA prognosis analyses.

RESULTS

In the pancreatic adenocarcinoma (PAAD) cohort, DNM3 gene expression was higher in tumor samples, and there was no significant difference in expression among cancer stages. High levels of DNM3 gene expression were associated with longer OS in PAAD. A weak positive correlation was observed between DNM3 gene expression and B-Cell and CD4+ T Cell infiltrations, while a moderate positive correlation was found with CD8+ T Cell, Macrophage, Neutrophil, and Dendritic Cell infiltrations in TIMER. NK cell by QUANTISEQ, CD 4+ T Cell by TIMER, T cell regulatory (Tregs) by CIBERSORT-ABS infiltrations were positively associated with DNM3 gene expression and decreased risk in prognosis. Common lymphoid progenitor by XCELL and MDSC by TIDE infiltrations were negatively associated with DNM3 gene expression and increased risk of prognosis. Macrophage M1 by QUANTISEQ was positively associated with DNM3 gene expression and increased risk in prognosis. DNM3 gene appears to be associated with various pathways related to inflammation and the immune system. Amplification of the DNM3 gene was detected in 5 out of 175 patients. Enrichment was observed in pathways such as bacterial invasion of epithelial cells, endocytosis, endocrine and other factor-regulated calcium reabsorption, synaptic vesicle cycle, and phospholipase D signaling pathway. According to Gscore, DNM3 gene was associated with Fc epsilon RI signaling pathway, HALLMARK MTORC1 SIGNALING, HALLMARK EPITHELIAL MESENCHYMAL TRANSITION gene sets. According to ENCORI, DNM3 gene was negatively correlated with hsa-miR-203a-3p and increased expression of this miRNA was associated with adverse prognosis in PAAD.

CONCLUSIONS

The DNM3 gene may play a tumor suppressor role in pancreatic cancer, similar to its role in other malignancies. The contribution of immune cells may also be significant in this effect. However, in vitro studies are needed to elucidate the mechanisms triggered in pancreatic cancer.