CancerSEA: a cancer single-cell state atlas

NTCdb: Single-cell transcriptome database of human inflammatory-associated diseases

With both the advancement of technology and the decline in costs, single-cell transcriptomics sequencing has become widespread in the biomedical area in recent years. It can facilitate the pathogenic characteristics at the single-cell level, which will assist clinical researchers in exploring the mechanism of diseases. As a result, single-cell transcriptome data based on clinical samples grew exponentially. However, there is still a lack of a comprehensive database about immunocytes in inflammatory-associated diseases. To address this deficiency, we propose a human inflammatory-associated disease-based single-cell transcriptome database, NTCdb (www.ntcdb.org.cn). NTCdb integrates the open-source data of 1,023,166 cells derived from 11 tissues of 17 inflammatory-associated diseases in a uniform pipeline. It provides a set of analyzing results, including cell communication analysis, enrichment analysis, and Pseudo-Time analysis, to obtain various characteristics of immune cells in inflammatory-associated disease. Taking COVID-19 as a case study, NTCdb displays important information including potentially significant functions of certain cells, genes, and signaling pathways, as well as the commonalities of specific immunocytes between different inflammatory-associated disease.

The immunological landscape and silico analysis of key paraptosis regulator LPAR1 in gastric cancer patients

This study aims to identify key regulators of paraptosis in gastric cancer (GC) and explore their potential in guiding therapeutic strategies, especially in stomach adenocarcinoma (STAD). Genes associated with paraptosis were identified from the references and subjected to Cox regression analysis in the TCGA-STAD cohort. Using machine learning models, LPAR1 consistently ranked highest in feature importance. Multiple sequencing data showed that LPAR1 was significantly overexpressed in cancer-associated fibroblasts (CAFs). LPAR1 expression was significantly higher in normal tissues, and ROC analysis demonstrated its discriminative ability. Copy number alterations and microsatellite instability were significantly associated with LPAR1 expression. High LPAR1 expression correlated with advanced tumor grades and specific cancer immune subtypes, and multivariate analysis confirmed LPAR1 as an independent predictor of poor prognosis. LPAR1 expression was associated with different immune response metrics, including immune effector activation and upregulated chemokine secretion. High LPAR1 expression also correlated with increased sensitivity to compounds, such as BET bromodomain inhibitors I-BET151 and RITA, suggesting LPAR1 as a biomarker for predicting drug activity. FOXP2 showed a strong positive correlation with LPAR1 transcriptional regulation, while increased methylation of LPAR1 promoter regions was negatively correlated with gene expression. Knockdown of LPAR1 affected cell growth in most tumor cell lines, and in vitro experiments demonstrated that LPAR1 influenced extracellular matrix (ECM) contraction and cell viability in the paraptosis of CAFs. These findings suggest that LPAR1 is a critical regulator of paraptosis in GC and a potential biomarker for drug sensitivity and immunotherapy response. This underscores the role of CAFs in mediating tumorigenic effects and suggests that targeting LPAR1 could be a promising strategy for precision medicine in GC.

Comprehensive analysis of MAPK genes in the prognosis, immune characteristics, and drug treatment of renal clear cell carcinoma using bioinformatic analysis and Mendelian randomization

Mitogen-activated protein kinase (MAPK) signalling is vitally important in tumour development and progression. This study is the first to comprehensively analyse the role of MAPK-family genes in the progression, prognosis, immune-cell infiltration, methylation, and potential therapeutic value drug candidates in ccRCC. We identified a novel prognostic panel of six MAPK-signature genes (MAP3K12, MAP3K1, MAP3K5, MAPK1, MAPK8, MAPK9), and introduced a robust MAPK-signature risk model for predicting ccRCC prognosis. Model construction, evaluation, and external validation using datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database demonstrated its stability, as well as high sensitivity and specificity. Enrichment analysis suggested the participation of immune-mediated mechanism in MAPK dysregulation in ccRCC. Immune-infiltration analysis confirmed the relationship and revealed that the MAPK-signature risk model might stratify immunotherapy response in ccRCC, which was verified in drug sensitivity analysis and validated in external ccRCC immunotherapy dataset (GSE67501). Potential therapeutic drug predictions for key MAPKs using DSigDB, Network Analyst, CTD, and DGIdb were subsequently verified by molecular docking with AutoDock Vina and PyMol. Mendelian randomization further demonstrated the possibilities of the MAPK-signature genes as targets for therapeutic drugs in ccRCC. Methylation analysis using UALCAN and MethSurv revealed the participation of epigenetic modifications in dysregulation and survival difference of MAPK pathway in ccRCC. Among the key MAPKs, MAP3K12 exhibited the highest significance, indicating its independent prognostic value as single gene in ccRCC. Knockout and overexpression validation experiments in vitro and in vivo found that MAP3K12 acted as a promoter of tumour progression in RCC, suggesting a pivotal role for MAP3K12 in the proliferation, migration, and invasion of RCC cells. Our findings proposed the potential of MAPK-signature genes as biomarkers for prognosis and therapy response, as well as targets for therapeutic drugs in ccRCC.

A cancer-associated fibroblasts related risk score (CAFscore) helps to guide prognosis and personal treatment for Glioblastoma

BACKGROUND

Recent studies have identified the presence of cancer-associated fibroblasts (CAFs) within glioblastoma (GBM), yet their biological roles and underlying mechanisms remain poorly understood. This study aimed to construct a CAF-related prognostic model to guide patient prognosis and treatment strategies.

METHOD

We employed various bioinformatics methods, including enrichment analysis, Weighted Gene Co-expression Network Analysis (WGCNA), Lasso regression analysis, and machine learning techniques such as XGBoost and Random Forest, to develop a novel risk index termed CAFscore. Patients were stratified into high and low CAFscore groups for subsequent survival analysis. The area under the curve (AUC) and concordance index (C-index) for CAFscore were calculated and compared against other clinical characteristics and existing prognostic models. Drug sensitivity assessments were conducted using the Oncopredict package. Functional validation of key genes was performed through scratch and invasion assays in GBM cells.

RESULTS

Our analyses revealed four core CAF-related genes, leading to the establishment of CAFscore. Notably, patients in the high CAFscore group exhibited significantly reduced survival and exhibited enrichment in epithelial-mesenchymal transition (EMT) and inflammation response pathways. Furthermore, CAFscore showed a significant negative correlation with the sensitivity to irinotecan and its analogs, while demonstrating a positive correlation with sensitivity to 505,124 (a TGFβRI inhibitor). LRP10 emerged as a central gene within the CAFscore, displaying markedly elevated expression in GBM and a strong association with CAF infiltration. Silencing LRP10 significantly inhibited the invasive capabilities of GBM cells.

CONCLUSION

This study presented the first CAF related prognostic model (CAFscore) in GBM, and demonstrated that the model could effectively guide patient prognosis and potentially inform personalized treatment strategies. The core gene of CAFscore, LRP10, was significantly overexpressed in GBM and might play a pivotal role in regulating CAF infiltration as well as tumor invasion and metastasis, highlighting LRP10 as a promising therapeutic target for GBM management.

Unveiling the impact of estrogen exposure on ovarian cancer: A comprehensive risk model and immune landscape analysis

This study examines the impact of estrogenic compounds like bisphenol A (BPA), estradiol (E2), and zearalenone (ZEA) on human ovarian cancer, focusing on constructing a risk model, conducting Gene Set Variation Analysis (GSVA), and evaluating immune infiltration. Differential gene expression analysis identified 980 shared differentially expressed genes (DEGs) in human ovarian cells exposed to BPA, E2, and ZEA, indicating disruptions in ribosome biogenesis and RNA processing. Using the Cancer Genome Atlas Ovarian Cancer (TCGA-OV) dataset, a least absolute shrinkage and selection operator (LASSO)-based risk model was developed incorporating prognostic genes 4-Hydroxyphenylpyruvate Dioxygenase Like (HPDL), Thy-1 Cell Surface Antigen (THY1), and Peptidase Inhibitor 3 (PI3). This model effectively stratified ovarian cancer patients into high-risk and low-risk categories, showing significant differences in overall survival, disease-specific survival, and progression-free survival. GSVA analysis linked HPDL expression to pathways related to the cell cycle, DNA damage, and repair, while THY1 and PI3 were associated with apoptosis, hypoxia, and proliferation pathways. Immune infiltration analysis revealed distinct immune cell profiles for high and low expression groups of HPDL, THY1, and PI3, indicating their influence on the tumor microenvironment. The findings demonstrate that estrogenic compounds significantly alter gene expression and oncogenic pathways in ovarian cancer. The risk model integrating HPDL, THY1, and PI3 offers a strong prognostic tool, with GSVA and immune infiltration analyses providing insights into the interplay between these genes and the tumor microenvironment, suggesting potential targets for personalized therapies.

Bioinformatics tools and resources for cancer and application

ABSTRACT

Tumor bioinformatics plays an important role in cancer research and precision medicine. The primary focus of traditional cancer research has been molecular and clinical studies of a number of fundamental pathways and genes. In recent years, driven by breakthroughs in high-throughput technologies, large-scale cancer omics data have accumulated rapidly. How to effectively utilize and share these data is particularly important. To address this crucial task, many computational tools and databases have been developed over the past few years. To help researchers quickly learn and understand the functions of these tools, in this review, we summarize publicly available bioinformatics tools and resources for pan-cancer multi-omics analysis, regulatory analysis of tumorigenesis, tumor treatment and prognosis, immune infiltration analysis, immune repertoire analysis, cancer driver gene and driver mutation analysis, and cancer single-cell analysis, which may further help researchers find more suitable tools for their research.

Identification of a hypoxia-suppressed lncRNA RAMP2-AS1 in breast cancer

Hypoxia is a critical feature of solid tumors and exerts crucial roles in cancers, including breast cancer. However, the detailed relationship between lncRNA-miRNA-mRNA triple network and hypoxia in breast cancer is still indistinct. In this study, a series of in silico analyses and online databases or tools were employed to establish a hypoxia-related lncRNA-miRNA-mRNA network in breast cancer based on competing endogenous RNA mechanism at single-cell resolution. RAMP2-AS1 was, eventually, identified as the most potential lncRNA, which was significantly negatively associated with hypoxia in breast cancer. Compared with normal controls, RAMP2-AS1 was markedly downregulated in breast cancer. Moreover, survival analysis revealed favorable prognostic values of RAMP2-AS1 in total or in specific clinicopathological breast cancer patients. Next, miR-660-5p, miR-2277-5p and miR-1301-3p, upregulated and possessed poor prognostic values in breast cancer, were identified as three potential downstream miRNAs of RAMP2-AS1. Then, the most potential downstream hypoxia-related genes (ATM and MYH11) of RAMP2-AS1/miRNA axis in breast cancer were screened out. Intriguingly, in vitro experiments confirmed that RAMP2-AS1 was a hypoxia-suppressed lncRNA and miR-660-5p/ATM was a potential downstream axis of RAMP2-AS1 in breast cancer. Collectively, our current data elucidated a key hypoxia-suppressed lncRNA RAMP2-AS1 and its possible miRNA-mRNA regulatory mechanism in breast cancer.

Novel insight into mitochondrial dynamin-related protein-1 as a new chemo-sensitizing target in resistant cancer cells

Mitochondrial dynamics have pillar roles in several diseases including cancer. Cancer cell survival is monitored by mitochondria which impacts several cellular functions such as cell metabolism, calcium signaling, and ROS production. The equilibrium of death and survival rate of mitochondria is important for healthy cellular processes. Whereas inhibition of mitochondrial metabolism and dynamics can have crucial regulatory decisions between cell survival and death. The steady rate of physiological flux of both mitochondrial fission and fusion is strongly related to the preservation of cellular bioenergetics. Dysregulation of mitochondrial dynamics including fission and fusion is a critical machinery in cells accompanied by crosstalk in cancer progression and resistance. Many cancer cells express high levels of Drp-1 to induce cancer cell invasion, metastasis and chemoresistance including breast cancer, liver cancer, pancreatic cancer, and colon cancer. Targeting Drp-1 by inhibitors such as Midivi-1 helps to enhance the responsiveness of cancer cells towards chemotherapy. The review showed Drp-1 linked processes such as mitochondrial dynamics and relationship with cancer, invasion, and chemoresistance along with computational assessing of all publicly available Drp-1 inhibitors. Drp1-IN-1, Dynole 34-2, trimethyloctadecylammonium bromide, and Schaftoside showed potential inhibitory effects on Drp-1 as compared to standard Mdivi- 1. This emerging approach may have extensive strength in the context of cancer development and chemoresistance and further work is needed to aid in more effective cancer management.

Mendelian randomization reveals potential causal relationships between cellular senescence-related genes and multiple cancer risks

Cellular senescence is widely acknowledged as having strong associations with cancer. However, the intricate relationships between cellular senescence-related (CSR) genes and cancer risk remain poorly explored, with insights on causality remaining elusive. In this study, Mendelian Randomization (MR) analyses were used to draw causal inferences from 866 CSR genes as exposures and summary statistics for 18 common cancers as outcomes. We focused on genetic variants affecting gene expression, DNA methylation, and protein expression quantitative trait loci (cis-eQTL, cis-mQTL, and cis-pQTL, respectively), which were strongly linked to CSR genes alterations. Variants were selected as instrumental variables (IVs) and analyzed for causality with cancer using both summary-data-based MR (SMR) and two-sample MR (TSMR) approaches. Bayesian colocalization was used to unravel potential regulatory mechanisms underpinning risk variants in cancer, and further validate the robustness of MR results. We identified five CSR genes (CNOT6, DNMT3B, MAP2K1, TBPL1, and SREBF1), 18 DNA methylation genes, and LAYN protein expression which were all causally associated with different cancer types. Beyond causality, a comprehensive analysis of gene function, pathways, and druggability values was also conducted. These findings provide a robust foundation for unravelling CSR genes molecular mechanisms and promoting clinical drug development for cancer.

Comprehensive pan-cancer analysis reveals EPHB2 is a novel predictive biomarker for prognosis and immunotherapy response

PURPOSE

Recent studies have increasingly linked Ephrin receptor B2 (EPHB2) to cancer progression. However, comprehensive investigations into the immunological roles and prognostic significance of EPHB2 across various cancers remain lacking.

METHODS

We employed various databases and bioinformatics tools to investigate the impact of EPHB2 on prognosis, immune infiltration, genome instability, and response to immunotherapy. Validation of the correlation between EPHB2 expression and M2 macrophages included analyses using bulk and single-cell transcriptomic datasets, spatial transcriptomics, and multi-fluorescence staining. Moreover, we performed cMap web tool to screen for EPHB2-targeted compounds and assessed their potential through molecular docking and dynamics simulations. Additionally, in vitro validation using lung adenocarcinoma (LUAD) cell lines was conducted to confirm the bioinformatics predictions about EPHB2.

RESULTS

EPHB2 dysregulation was observed across multiple cancer types, where it demonstrated significant diagnostic and prognostic value. Gene Set Enrichment Analysis (GSEA) indicated that EPHB2 is involved in enhancing cellular proliferation, invasiveness of cancer cells, and modulation of the anti-cancer immune response. Furthermore, it is emerged as a pan-cancer marker for M2 macrophage infiltration, supported by integrated analyses of transcriptomics and multiple fluorescence staining. In LUAD cells, knockdown of EPHB2 expression led to a decrease in both cell proliferation and migratory activity.

CONCLUSION

EPHB2 expression may serve as a pivotal indicator of M2 macrophage infiltration, offering vital insights into tumor dynamics and progression across various cancers, including lung adenocarcinoma, highlighting its significant prognostic and therapeutic potential for further exploration.

Integrated pan-cancer analysis and experimental verification of the roles of meiotic nuclear divisions 1 in breast cancer

INTRODUCTION

The aberrant up-regulation of meiotic nuclear division 1 (MND1) in somatic cells is considered as one of the driving factors of oncogenesis, whereas its expression and role in breast invasive cancer (BRCA) remain unclear. Hence, this study embarked on a comprehensive evaluation of MND1 across various cancers and identified its roles in BRCA.

METHODS

Based on publicly available databases, including but not limited to UCSC Xena, TCGA, GTEx, GEO, STRING, GeneMANIA, and CancerSEA, we evaluated the expression patterns, genomic features, and biological functions of MND1 from a pan-cancer viewpoint and delved into the implications of MND1 in the prognosis and treatment of BRCA. Further molecular biology experiments were undertaken to identify the role of MND1 in proliferation, migration, and apoptosis in BRCA cells.

RESULTS

Elevated levels of MND1 were notably observed in a wide array of tumor types, especially in BRCA, COAD, HNSC, LIHC, LUAD, LUSC, STAD, and UCEC. Elevated MND1 expression was markedly associated with shortened OS in several tumors, including BRCA (HR = 1.52 [95%CI, 1.10-2.09], P = 0.011). The up-regulation of MND1 in BRCA was validated in external cohorts and clinical samples. Survival analyses demonstrated that elevated MND1 expression was associated with decreased survival for patients with BRCA. Co-expressed genes of MND1 were identified, and subsequent pathway analyses based on significantly associated genes indicated that MND1 plays key roles in DNA replication, cell cycle regulation, and DNA damage repair. The observed abnormal elevation and activation of MND1 led to increased proliferation and migration, along with decreased apoptosis in BRCA cells.

CONCLUSIONS

MND1 emerges as a promising biomarker for diagnostic and therapeutic targeting in various cancers, including BRCA. The abnormal up-regulation and activation of MND1 are linked to carcinogenesis and poor prognosis among BRCA patients, which may be attributed to its involvement in HR-dependent ALT, warranting further scrutiny.

Multi-omics pan-cancer analysis reveals the prognostic values and immunological functions of PPA2, with a spotlight on breast cancer

Background

Recently, the role of inorganic pyrophosphatase 2 (PPA2) has been remaining merely superficial in many tumors. Hence, the aim was to analyze the potential functions of PPA2 in pan-cancer, focusing on its role in breast cancer.

Methods

A systematic pan-cancer analysis conducted primarily utilizing various open databases such as TCGA and GTEx. We explored the clinical value of PPA2 as well as various biological functions, including expression levels and subcellular localization, multi-dimensional immune-correlation analysis, co-expression networks, and gene heterogeneity. In addition, we not only verified the function of PPA2 through cell experiments but also analyzed PPA2 at the single-cell level and its drug sensitivity.

Results

PPA2 is abnormally expressed in various tumors, and it is mainly distributed in mitochondria. Furthermore, the indicators (OS, DSS, DFI, and PFI) of analysis hint that PPA2 exhibits significant prognostic value. At the same time, the genomic heterogeneity (including TMB, MSI, MATH, and NEO) of PPA2 in pan-cancer was analyzed. Across multiple tumors, the results showed a close correlation between PPA2 expression levels and different immune signatures (such as immune cell infiltration). All of these indicate that PPA2 could potentially be applied in the guidance of immunotherapy. We also have demonstrated that PPA2 promoted the process of breast cancer. Finally, some potential therapeutic agents (such as Fulvestrant) targeting the abnormal expression of PPA2 are revealed.

Conclusion

In conclusion, the results demonstrated the great value of PPA2 in pan-cancer research, as well as its potential as a therapeutic target for breast tumors.

Pan-cancer analysis and single-cell analysis reveals FAM110B as a potential target for survival and immunotherapy

Background: FAM110B belongs to the family that has a 110 sequence similarity (FAM110) and is located in the centrosome and mitotic spindle. FAM110B has been linked to tumor cell growth in earlier research. Uncertainty exists regarding FAM110B's function within the tumor microenvironment is unclear as well as pan-cancer. Methods: In order to assess the variation in FAM110B expression within normal and pan-cancer tissues, we combined the TCGA and GTEx databases. The cBioPortal database and the GSCALite platform were used to examine the variation in genome and methylation alteration of FAM110B. Cox regression, Kaplan-Meier, and SangerBox were employed to examine the clinical features and prognosis of FAM110B and pan-cancer. The purpose of the correlational research was to investigate the associations within immunerelated genes, tumor mutation burden, microsatellite instability, immune-related genes, and immunological checkpoints and FAM110B expression. ESTIMATE, EPIC, QUANTISEQ, and MCPCOUNTER methods were used to calculate the interaction among FAM110B expression as well as the tumor immune microenvironment. The immunoinfiltration and function of FAM110B were analyzed by single-cell databases (TISCH and CancerSEA). Finally, we evaluated the sensitivity of FAM110B to small-molecule medications through GDSC and CTRP databases. Results: The transcription and protein expression of FAM110B varies significantly throughout cancer types, and this has predictive value for the prognosis of some tumors; including brain lower grade glioma (LGG), stomach adenocarcinoma (STAD), pancreatic adenocarcinoma (PAAD), etc. In the tumor microenvironment, the expression level of FAM110B was associated with immune cell infiltration, immune checkpoint immune regulatory genes, tumor mutational burden, and microsatellite fragility to a certain extent. Conclusion: This work investigates the possibility of utility of FAM110B as a marker to forecast pan-cancer immunotherapy response, providing a theoretical basis for cancer therapy.

Identifying and validating the roles of the cuproptosis-related gene DKC1 in cancer with a focus on esophageal carcinoma

BACKGROUND

Esophageal cancer is a common malignancy of the digestive tract. Despite remarkable advancements in its treatment, the overall prognosis for patients remains poor. Cuproptosis is a form of programmed cell death that affects the malignant progression of tumors. This study aimed to examine the impact of the cuproptosis-associated gene DKC1 on the malignant progression of esophageal cancer.

METHODS

Clinical and RNA sequencing data of patients with esophageal cancer were extracted from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis was used to identify the differentially expressed genes related to cuproptosis that are associated with prognosis. We then validated the difference in the expression of DKC1 between tumor and normal tissues via three-dimensional multiomics difference analysis. Subsequently, we investigated the association between DKC1 expression and the tumor microenvironment by employing the TIMER2.0 algorithm, which was further validated in 96 single-cell datasets obtained from the TISCH database. Additionally, the functional role of DKC1 in pancarcinoma was assessed through GSEA. Furthermore, a comprehensive pancancer survival map was constructed, and the expression of DKC1 was verified in various molecular subtypes. By utilizing the CellMiner, GDSC, and CTRP databases, we successfully established a connection between DKC1 and drug sensitivity. Finally, the involvement of DKC1 in the progression of esophageal cancer was investigated through in vivo and in vitro experiments.

RESULTS

In this study, we identified a copper death-related gene, DKC1, in esophageal cancer. Furthermore, we observed varying levels of DKC1 expression across different tumor types. Additionally, we conducted an analysis to determine the correlation between DKC1 expression and clinical features, revealing its association with common cell cycle pathways and multiple metabolic pathways. Notably, high DKC1 expression was found to indicate poor prognosis in patients with various tumors and to influence drug sensitivity. Moreover, our investigation revealed significant associations between DKC1 expression and the expression of molecules involved in immune regulation and infiltration of lymphocyte subtypes. Ultimately, the increased expression of DKC1 in esophageal cancer tissues was verified using clinical tissue samples. Furthermore, DKC1-mediated promotion of esophageal cancer cell proliferation and migration was confirmed through both in vitro and in vivo experiments. Additionally, it is plausible that DKC1 may play a role in the regulation of cuproptosis.

CONCLUSION

In this study, we conducted a systematic analysis of DKC1 and its regulatory factors and experimentally validated its excellent diagnostic and prognostic abilities in various cancers. Further research indicated that DKC1 may reshape the tumor microenvironment (TME), highlighting the potential of DKC1-based cancer treatment and its usefulness in predicting the response to chemotherapy.

scPriorGraph: constructing biosemantic cell-cell graphs with prior gene set selection for cell type identification from scRNA-seq data

Cell type identification is an indispensable analytical step in single-cell data analyses. To address the high noise stemming from gene expression data, existing computational methods often overlook the biologically meaningful relationships between genes, opting to reduce all genes to a unified data space. We assume that such relationships can aid in characterizing cell type features and improving cell type recognition accuracy. To this end, we introduce scPriorGraph, a dual-channel graph neural network that integrates multi-level gene biosemantics. Experimental results demonstrate that scPriorGraph effectively aggregates feature values of similar cells using high-quality graphs, achieving state-of-the-art performance in cell type identification.

Targeting axonal guidance dependencies in glioblastoma with ROBO1 CAR T cells

Resistance to genotoxic therapies and tumor recurrence are hallmarks of glioblastoma (GBM), an aggressive brain tumor. In this study, we investigated functional drivers of post-treatment recurrent GBM through integrative genomic analyses, genome-wide genetic perturbation screens in patient-derived GBM models and independent lines of validation. Specific genetic dependencies were found consistent across recurrent tumor models, accompanied by increased mutational burden and differential transcript and protein expression compared to its primary GBM predecessor. Our observations suggest a multi-layered genetic response to drive tumor recurrence and implicate PTP4A2 (protein tyrosine phosphatase 4A2) as a modulator of self-renewal, proliferation and tumorigenicity in recurrent GBM. Genetic perturbation or small-molecule inhibition of PTP4A2 acts through a dephosphorylation axis with roundabout guidance receptor 1 (ROBO1) and its downstream molecular players, exploiting a functional dependency on ROBO signaling. Because a pan-PTP4A inhibitor was limited by poor penetrance across the blood-brain barrier in vivo, we engineered a second-generation chimeric antigen receptor (CAR) T cell therapy against ROBO1, a cell surface receptor enriched across recurrent GBM specimens. A single dose of ROBO1-targeted CAR T cells doubled median survival in cell-line-derived xenograft (CDX) models of recurrent GBM. Moreover, in CDX models of adult lung-to-brain metastases and pediatric relapsed medulloblastoma, ROBO1 CAR T cells eradicated tumors in 50-100% of mice. Our study identifies a promising multi-targetable PTP4A-ROBO1 signaling axis that drives tumorigenicity in recurrent GBM, with potential in other malignant brain tumors.

Integrative analysis reveals the potential prognostic roles and immunological values of unc-5 netrin receptor A (UNC5A) in glioma

BACKGROUND

UNC5A had been reported to play crucial roles in multiple cancers. However, little was known about the associations among UNC5A and glioma. Therefore, we first combined scRNA-seq, proteomics, as well as bulk RNA-seq in order to investigate UNC5A's functions in gliomas.

METHODS

Online databases provided scRNA-seq, proteomics, as well as bulk RNA-seq data on UNC5A in gliomas. The following procedures were conducted in order: QRT-PCR, Norman chart, gene set enrichment analysis (GSEA), and univariate/multifactor Cox regression analyses. We further explored the associations among UNC5A and tumor immunity.

RESULTS

By comparing gliomas with normal tissues, the TCGA dataset showed a significantly reduced expression of UNC5A, which was also confirmed by GSE50161, GSE4290, and QRT-PCR findings (p < 0.05). In both the TCGA and CGGA datasets, gliomas patients with low-UNC5A expression would have poorer overall survival (OS) prognoses (p < 0.05). ScRNA-seq analysis by the CancerSEA online website presented that UNC5A had a low expression in various glioma clusters and significantly associated with six functional states. Moreover, UNC5A might be a reliable independent biomarker of OS in gliomas patients (p < 0.05). Based on the results of GSEA, UNC5A might be connected to three significant pathways in gliomas. We also successfully created a Norman chart to assess the OS prognoses of these patients. Additionally, in aspects of tumor immunity, the infiltration levels of immune cells in LGG, the immune cell pathways, tumor immune microenvironment, as well as immune checkpoints in both LGG and GBM were revealed to be significantly influenced by UNC5A (p < 0.05).

CONCLUSIONS

UNC5A was found to have prognostic and immunological significance in gliomas, offering patients with gliomas new treatment options.

The Integrated Bioinformatic Approach Reveals the Prognostic Significance of LRP1 Expression in Ovarian Cancer

A hyperactive tumour microenvironment (TME) drives unrestricted cancer cell survival, drug resistance, and metastasis in ovarian carcinoma (OC). However, therapeutic targets within the TME for OC remain elusive, and efficient methods to quantify TME activity are still limited. Herein, we employed an integrated bioinformatics approach to determine which immune-related genes (IRGs) modulate the TME and further assess their potential theragnostic (therapeutic + diagnostic) significance in OC progression. Using a robust approach, we developed a predictive risk model to retrospectively examine the clinicopathological parameters of OC patients from The Cancer Genome Atlas (TCGA) database. The validity of the prognostic model was confirmed with data from the International Cancer Genome Consortium (ICGC) cohort. Our approach identified nine IRGs, AKT2, FGF7, FOS, IL27RA, LRP1, OBP2A, PAEP, PDGFRA, and PI3, that form a prognostic model in OC progression, distinguishing patients with significantly better clinical outcomes in the low-risk group. We validated this model as an independent prognostic indicator and demonstrated enhanced prognostic significance when used alongside clinical nomograms for accurate prediction. Elevated LRP1 expression, which indicates poor prognosis in bladder cancer (BLCA), OC, low-grade gliomas (LGG), and glioblastoma (GBM), was also associated with immune infiltration in several other cancers. Significant correlations with immune checkpoint genes (ICGs) highlight the potential importance of LRP1 as a biomarker and therapeutic target. Furthermore, gene set enrichment analysis highlighted LRP1's involvement in metabolism-related pathways, supporting its prognostic and therapeutic relevance also in BLCA, OC, low-grade gliomas (LGG), GBM, kidney cancer, OC, BLCA, kidney renal clear cell carcinoma (KIRC), stomach adenocarcinoma (STAD), and stomach and oesophageal carcinoma (STES). Our study has generated a novel signature of nine IRGs within the TME across cancers, that could serve as potential prognostic predictors and provide a valuable resource to improve the prognosis of OC.

Neuromedin U receptor 1 deletion leads to impaired immunotherapy response and high malignancy in colorectal cancer

Colorectal cancer (CRC) exhibits significant heterogeneity, impacting immunotherapy efficacy, particularly in immune desert subtypes. Neuromedin U receptor 1 (NMUR1) has been reported to perform a vital function in immunity and inflammation. Through comprehensive multi-omics analyses, we have systematically characterized NMUR1 across various tumors, assessing expression patterns, genetic alterations, prognostic significance, immune infiltration, and pathway associations at both the bulk sequencing and single-cell scales. Our findings demonstrate a positive correlation between NMUR1 and CD8+ T cell infiltration, with elevated NMUR1 levels in CD8+ T cells linked to improved immunotherapy outcomes in patients with CRC. Further, we have validated the NMUR1 expression signature in CRC cell lines and patient-derived tissues, revealing its interaction with key immune checkpoints, including lymphocyte activation gene 3 and cytotoxic T-lymphocyte-associated protein 4. Additionally, NMUR1 suppression enhances CRC cell proliferation and invasiveness. Our integrated analyses and experiments open new avenues for personalized immunotherapy strategies in CRC treatment.

Comprehensive analysis of PHF5A as a potential prognostic biomarker and therapeutic target across cancers and in hepatocellular carcinoma

OBJECTIVE

Cancer is a predominant cause of death globally. PHD-finger domain protein 5 A (PHF5A) has been reported to participate in various cancers; however, there has been no pan-cancer analysis of PHF5A. This study aims to present a novel prognostic biomarker and therapeutic target for cancer treatment.

METHODS

This study explored PHF5A expression and its impact on prognosis, tumor mutation burden (TMB), microsatellite instability (MSI), functional status and tumor immunity across cancers using various public databases, and validated PHF5A expression and its correlation with survival, immune evasion, angiogenesis, and treatment response in hepatocellular carcinoma (HCC) using bioinformatics tools, qRT-PCR and immunohistochemistry (IHC).

RESULTS

PHF5A was differentially expressed between tumor and corresponding normal tissues and was correlated with prognosis in diverse cancers. Its expression was also associated with TMB, MSI, functional status, tumor microenvironment, immune infiltration, immune checkpoint genes and tumor immune dysfunction and exclusion (TIDE) score in diverse malignancies. In HCC, PHF5A was confirmed to be upregulated by qRT-PCR and IHC, and elevated PHF5A expression may promote immune evasion and angiogenesis in HCC. Additionally, multiple canonical pathways were revealed to be involved in the biological activity of PHF5A in HCC. Moreover, immunotherapy and transcatheter arterial chemoembolization (TACE) worked better in the low PHF5A expression group, while sorafenib, chemotherapy and AKT inhibitor were more effective in the high expression group.

CONCLUSIONS

This study provides a comprehensive understanding of the biological function of PHF5A in the carcinogenesis and progression of various cancers. PHF5A could serve as a tumor biomarker related to prognosis across cancers, especially HCC, and shed new light on the development of novel therapeutic targets.

Integrative Pan-Cancer Analysis Reveals the Oncogenic Role of MND1 and Validation of MND1's Role in Breast Cancer

Purpose

Meiotic nuclear division 1 (MND1) is a meiosis-specific protein that promotes lung adenocarcinoma progression. However, its expression and biological function across cancers remain largely unexplored.

Patients and Methods

The expression, prognostic significance, mutation status, and methylation profile of MND1 in various cancers were comprehensively analyzed using the TIMER, GTEX, Kaplan-Meier plotter, cBioPortal, and GSCA databases. Additionally, we constructed a PPI network, enrichment analysis and single-cell transcriptomic sequencing to elucidate the underlying mechanism of MND1. Furthermore, we investigated the association between MND1 expression and drug sensitivity using CellMiner. Moreover, we also explored the correlation between MND1 expression and immune infiltration. Finally, we validated the functional role of MND1 in breast cancer through IHC staining, CCK8, EdU, colony formation, and flow cytometry assays.

Results

MND1 has been reported to be highly expressed in Pan-cancer, High MND1 expression was significantly associated with poor prognosis in cancers. Additionally, MND1 mutation frequency is high in most cancers, and its expression correlates with methylation. Furthermore, MND1 expression significantly correlates with immune checkpoint blockade (ICB) markers, including PD-L1, PD-1, and CTLA-4. The PPI network reveals interactions between MND1 and PSMC3IP, BRCA1, and BRCA2. Enrichment analysis and single-cell sequencing indicate that MND1 positively correlates with cell cycle. ROC curve reveals favorable diagnostic efficacy of MND1 in breast cancer. In vitro, MND1 overexpression promotes breast cancer cell proliferation and increases the expression of key cell cycle regulators (CDK4, CDK6, and cyclin D3), accelerating the G1/S phase transition and leading to abnormal breast cancer cell proliferation. The immunohistochemical analysis revealed a robust expression of MND1 in breast cancer tissues, exhibiting a significant positive correlation with PD-L1 and FOXP3.

Conclusion

MND1 is an oncogene and may serve as a biomarker for cancer prognosis and immunotherapy. Targeting MND1 may be a potential tumor treatment strategy.

Construction and assessment of an angiogenesis-related gene signature for prognosis of head and neck squamous cell carcinoma

OBJECTIVE

Angiogenesis-associated genes (AAGs) play a critical role in cancer patient survival. However, there are insufficient reports on the prognostic value of AAGs in head and neck squamous cell carcinoma (HNSC). Therefore, this study aimed to investigate the correlation between AAG expression levels and survival in HNSC patients, explore the predictive value of signature genes and lay the groundwork for future in-depth research.

METHODS

Relevant data for HNSC were obtained from the databases. AAGs-associated signature genes linked to prognosis were screened to construct a predictive model. Further analysis was conducted to determine the functional correlation of the signature genes.

RESULTS

The signature genes (STC1, SERPINA5, APP, OLR1, and PDGFA) were used to construct prognostic models. Patients were divided into high-risk and low-risk groups based on the calculated risk scores. Survival analysis showed that patients in the high-risk group had a significantly lower overall survival than those in the low-risk group (P < 0.05). Therefore, this prognostic model was an independent prognostic factor for predicting HNSC. In addition, patients in the low-risk group were more sensitive to multiple anti-cancer drugs. Functional correlation analysis showed a good correlation between the characteristic genes and HNSC metastasis, invasion, and angiogenesis.

CONCLUSION

This study established a new prognostic model for AAGs and may guide the selection of therapeutic agents for HNSC. These genes have important functions in the tumor microenvironment; it also provides a valuable resource for the future clinical trials investigating the relationship between HNSC and AAGs.

DNA methylation profiling deciphers three EMT subtypes with distinct prognoses and therapeutic vulnerabilities in breast cancer

Background: Epithelial-mesenchymal transition (EMT), deemed a pivotal hallmark of tumours, is intricately regulated by DNA methylation and encompasses multiple states along tumour progression. The potential mechanisms that drive the intrinsic heterogeneity of breast cancer (BC) via EMT transformation have not been identified, presenting a significant obstacle in clinical diagnosis and treatment. Methods: A total of 7,602 patients have been included in this study. We leveraged integrated multiomics data (epigenomic, genomic, and transcriptomic data) to delineate the comprehensive landscape of EMT in BC. Subsequently, a subtyping classifier was developed through a machine learning framework proposed by us. Results: We classified the BC samples into three methylation-driven EMT subtypes with distinct features, namely, C1 (the mammary duct development subtype with TP53 activation), C2 (the immune infiltration subtype with high TP53 mutation), and C3 (the ERBB2 amplification subtype with an unfavorable prognosis). Specifically, patients with the C1 subtype might respond to endocrine therapy or the p53-MDM2 antagonist nutlin-3. Patients with the C2 subtype might benefit from combined therapeutic regimens involving radiotherapy, PARP inhibitors, and immune checkpoint blockade therapy. Patients with the C3 subtype might benefit from anti-HER2 agents such as lapatinib. Notably, to increase the clinical applicability of the EMT subtypes, we devised a 96-gene panel-based classifier via a machine learning framework. Conclusions: Our study identified three methylation-driven EMT subtypes with distinct prognoses and biological traits to capture heterogeneity in BC and provided a rationale for the use of this classification as a powerful tool for developing new strategies for clinical trials.

OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing

Single-cell sequencing is frequently affected by "omission" due to limitations in sequencing throughput, yet bulk RNA-seq may contain these ostensibly "omitted" cells. Here, we introduce the single cell trajectory blending from Bulk RNA-seq (BulkTrajBlend) algorithm, a component of the OmicVerse suite that leverages a Beta-Variational AutoEncoder for data deconvolution and graph neural networks for the discovery of overlapping communities. This approach effectively interpolates and restores the continuity of "omitted" cells within single-cell RNA sequencing datasets. Furthermore, OmicVerse provides an extensive toolkit for both bulk and single cell RNA-seq analysis, offering seamless access to diverse methodologies, streamlining computational processes, fostering exquisite data visualization, and facilitating the extraction of significant biological insights to advance scientific research.

A systematic overview of single-cell transcriptomics databases, their use cases, and limitations

Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of transcriptomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Such platforms can help bridge the gap between computational and wet lab scientists through user-friendly web-based interfaces needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the field.

Deep pan-cancer analysis and multi-omics evidence reveal that ALG3 inhibits CD8+ T cell infiltration by suppressing chemokine secretion and is associated with 5-fluorouracil sensitivity

BACKGROUND

α-1,3-mannosyltransferase (ALG3) holds significance as a key member within the mannosyltransferase family. Nevertheless, the exact function of ALG3 in cancer remains ambiguous. Consequently, the current research aimed to examine the function and potential mechanisms of ALG3 in various types of cancer.

METHODS

Deep pan-cancer analyses were conducted to investigate the expression patterns, prognostic value, genetic variations, single-cell omics, immunology, and drug responses associated with ALG3. Subsequently, in vitro experiments were executed to ascertain the biological role of ALG3 in breast cancer. Moreover, the link between ALG3 and CD8+ T cells was verified using immunofluorescence. Lastly, the association between ALG3 and chemokines was assessed using qRT-PCR and ELISA.

RESULTS

Deep pan-cancer analysis demonstrated a heightened expression of ALG3 in the majority of tumors based on multi-omics evidence. ALG3 emerges as a diagnostic and prognostic biomarker across diverse cancer types. In addition, ALG3 participates in regulating the tumor immune microenvironment. Elevated levels of ALG3 were closely linked to the infiltration of bone marrow-derived suppressor cells (MDSC) and CD8+ T cells. According to in vitro experiments, ALG3 promotes proliferation and migration of breast cancer cells. Moreover, ALG3 inhibited CD8+ T cell infiltration by suppressing chemokine secretion. Finally, the inhibition of ALG3 enhanced the responsiveness of breast cancer cells to 5-fluorouracil treatment.

CONCLUSION

ALG3 shows potential as both a prognostic indicator and immune infiltration biomarker across various types of cancer. Inhibition of ALG3 may represent a promising therapeutic strategy for tumor treatment.

Altered tumor microenvironment heterogeneity of penile cancer during progression from non-lymphatic to lymphatic metastasis

BACKGROUND

Lymphatic metastasis is the major challenge in the treatment of penile cancer. The prognosis of individuals with lymphatic metastasis is extremely poor. Therefore, early identification of disease progression and lymphatic metastasis is an urgent task for researchers in penile cancer worldwide.

METHODS

In this study, using single-cell RNA sequencing, an immune landscape was established for the cancer ecosystem based on 46,861 cells from six patients with penile cancer (four with lymphatic metastasis [stage IV] and two without lymphatic metastasis [stage I]). Using bulk RNA sequencing, the discrepancy between the cancers and their respective metastatic lymph nodes was depicted based on seven patients with penile cancer.

RESULTS

The interaction between epithelial cells, fibroblasts, and endothelial cells, and the functional cooperation among invasion, epithelial-mesenchymal transition, and angiogenesis were found to be important landscapes in the penile cancer ecosystem, playing important roles in progression of cancer and lymph node metastasis.

CONCLUSIONS

This study is the first to investigate the altered tumor microenvironment heterogeneity of penile cancer as it evolves from non-lymphatic to lymphatic metastasis and provides insights into the mechanisms underlying malignant progression, the premetastatic niche, and lymphatic metastasis in penile cancer.

Identification of a Novel hsa_circ_0058058/miR-324-5p Axis and Prognostic/Predictive Molecules for Acute Myeloid Leukemia Outcome by Bioinformatics-Based Analysis

Acute myeloid leukemia (LAML) is one of the most prevalent hematological malignancies. In recent years, while targeted approaches have shown promise in the fight against cancer, the treatability and prognosis of patients remain inadequate due to the shortage of drugs. Noncoding RNAs, especially circular RNA (circRNA) and microRNA (miRNA), have been shown to play a unique role in tumor development. This study aims to identify the disease-associated circRNA-miRNA-mRNA network by bioinformatic analysis and investigate the mechanisms in the development and progression of LAML. Additionally, it reveals the promising roles of these molecules as a diagnostic biomarker and therapeutic target for LAML treatment. Using various bioinformatics approaches, we identified the hsa_circ_0058058/miR-324-5p axis in LAML and its possible functions in LAML development. According to our results, hsa circ-0058058 can regulate the expression of AP1G1 and SP1 through miR-324-5p to support angiogenesis, the cell cycle, and DNA replication processes. Downregulation of hsa circ-0058058 may contribute to the anticancer functions of miR-324-5p on LAML tumorigenesis, and upregulation of miR-324-5p can abolish the oncogenic effects of AP1G1 and SP1 on LAML tumorigenesis. Additionally, highly enriched pathways indicated possible interactions between molecules underlying LAML pathology. Targeted molecules within this network may be able to function as therapeutic and diagnostic biomarkers for disease, while more research and clinical confirmation are needed.

Comprehensive analysis and experimental verification reveal the molecular characteristics of EGLN3 in pan-cancer and its relationship with the proliferation and apoptosis of lung cancer

Background

Egl-9 family hypoxia-inducible factor 3 (EGLN3) is involved in the regulation of tumor microenvironment and tumor progression. However, its biological function and clinical significance in various cancers remain unclear.

Methods

RNA-seq, immunofluorescence, and single-cell sequencing were used to investigate the expression landscape of EGLN3 in pan-cancer. The TISCH2 and CancerSEA databases were used for single-cell function analysis of EGLN3 in tumors. TIMER2.0 database was used to explain the relationship between EGLN3 expression and immune cell infiltration. In addition, the LinkedOmics database was used to perform KEGG enrichment analysis of EGLN3 in pan-cancer. siRNA was used to silence gene expression. CCK8, transwell migration assay, flow cytometry analysis, RT-PCR, and western blotting were used to explore biological function of EGLN3.

Results

The results showed that EGLN3 was highly expressed in a variety of tumors, and was mainly localized to the cytosol. EGLN3 expression is associated with immunoinfiltration of a variety of immune cells, including macrophages in the tumor immune microenvironment and tumor-associated fibroblasts. Functional experiments revealed that EGLN3 knockdown could inhibit cell proliferation, migration, and promote cell apoptosis. In addition, we found that Bax expression was up-regulated and Bcl-2 expression was down-regulated in the si-EGLN3 group. Taken together, as a potential oncogene, EGLN3 is involved in the regulation of tumor malignant process, especially tumor cell apoptosis.

Conclusion

We comprehensively investigated the expression pattern, single-cell function, immune infiltration level and regulated signaling pathway of EGLN3 in pan-cancer. We found that EGLN3 is an important hypoxia and immune-related gene that may serve as a potential target for tumor immunotherapy.

FTO elicits tumor neovascularization in cancer-associated fibroblasts through eliminating m6A modifications of multiple pro-angiogenic factors

Cancer-associated fibroblasts (CAFs) exhibit notable versatility, plasticity, and robustness, actively participating in cancer progression through intricate interactions within the tumor microenvironment (TME). N6-methyladenosine (m6A) modification is the most prevalent modification in eukaryotic mRNA, playing essential roles in mRNA metabolism and various biological processes. Howbeit, the precise involvement of m6A in CAF activation remains enigmatic. In this study, we revealed that the m6A demethylase FTO supports CAF-mediated angiogenesis through activation of EGR1 and VEGFA in conjunctival melanoma (CoM). First, single-cell transcriptome analysis revealed that FTO was specifically upregulated in the CAF population, thereby contributing to the hypo-m6A status in the TME of CoM. Moreover, CAFs of CoM displayed extensive proangiogenic potential, which was largely compromised by FTO inhibition, both in vitro and in vivo. By employing multi-omics analysis, we showed that FTO effectively eliminates the m6A modifications of VEGFA and EGR1. This process subsequently disrupts the YTHDF2-dependent mRNA decay pathway, resulting in increased mRNA stability and upregulated expression of these molecules. Collectively, our findings initially indicate that the upregulation of FTO plays a pivotal role in tumor development by promoting CAF-mediated angiogenesis. Therapeutically, targeting FTO may show promise as a potential antiangiogenic strategy to optimize cancer treatment.

Identification of metastasis-related genes for predicting prostate cancer diagnosis, metastasis and immunotherapy drug candidates using machine learning approaches

BACKGROUND

Prostate cancer (PCa) is the second leading cause of tumor-related mortality in men. Metastasis from advanced tumors is the primary cause of death among patients. Identifying novel and effective biomarkers is essential for understanding the mechanisms of metastasis in PCa patients and developing successful interventions.

METHODS

Using the GSE8511 and GSE27616 data sets, 21 metastasis-related genes were identified through the weighted gene co-expression network analysis (WGCNA) method. Subsequent functional analysis of these genes was conducted on the gene set cancer analysis (GSCA) website. Cluster analysis was utilized to explore the relationship between these genes, immune infiltration in PCa, and the efficacy of targeted drug IC50 scores. Machine learning algorithms were then employed to construct diagnostic and prognostic models, assessing their predictive accuracy. Additionally, multivariate COX regression analysis highlighted the significant role of POLD1 and examined its association with DNA methylation. Finally, molecular docking and immunohistochemistry experiments were carried out to assess the binding affinity of POLD1 to PCa drugs and its impact on PCa prognosis.

RESULTS

The study identified 21 metastasis-related genes using the WGCNA method, which were found to be associated with DNA damage, hormone AR activation, and inhibition of the RTK pathway. Cluster analysis confirmed a significant correlation between these genes and PCa metastasis, particularly in the context of immunotherapy and targeted therapy drugs. A diagnostic model combining multiple machine learning algorithms showed strong predictive capabilities for PCa diagnosis, while a transfer model using the LASSO algorithm also yielded promising results. POLD1 emerged as a key prognostic gene among the metastatic genes, showing associations with DNA methylation. Molecular docking experiments supported its high affinity with PCa-targeted drugs. Immunohistochemistry experiments further validated that increased POLD1 expression is linked to poor prognosis in PCa patients.

CONCLUSIONS

The developed diagnostic and metastasis models provide substantial value for patients with prostate cancer. The discovery of POLD1 as a novel biomarker related to prostate cancer metastasis offers a promising avenue for enhancing treatment of prostate cancer metastasis.

Systematic analysis of fatty acid desaturases in breast invasive carcinoma: The prognosis, gene mutation, and tumor immune microenvironment

Breast invasive carcinoma (BRCA) is one of the most common cancers in women, with its malignant progression significantly influenced by intracellular fatty acid (FA) desaturation. Stearoyl-coenzyme A desaturase (SCD) and fatty acid desaturase 2 (FADS2) are two key rate-limiting enzymes that catalyze the FA desaturation process and cooperate to accelerate lipid metabolic activities. In this study, we investigated the potential functions of SCD and FADS2 in BRCA using bioinformatic analysis and experimental validation. The gene expression profiling interactive analysis database showed that the expression of SCD or FADS2 genes was positively linked to worse overall survival and disease-free survival in the Cancer Genome Atlas database-BRCA. The University of Alabama at Birmingham cancer data analysis portal database indicates that the expression and methylation levels of SCD or FADS2 are associated with various clinicopathological factors in patients with BRCA. Moreover, the tumor immune estimation resource and TISCH databases showed a significant positive correlation between the expression of SCD and the abundance of CD8+ T cells and macrophage cell infiltration, while the expression of FADS2 was positively correlated with the abundance of B cells. Meanwhile, SCD or FADS2 had a higher expression in monocytes/macrophages analyzed the BRCA_GSE143423 and BRCA_GSE114727_inDrop datasets. Mechanistically, the Search Tool for the Retrieval of Distant Genes and CancerSEA databases showed that SCD and FADS2 were upregulated in several cell biology signaling pathways, particularly in inflammation, apoptosis, and DNA repair. Finally, SCD or FADS2 knockdown inhibited the proliferation of MCF-7 and MDA-MB-231 cells. In summary, SCD and FADS2 play significant roles in BRCA development, suggesting that they may serve as potential therapeutic targets for BRCA treatment.

A microdeletion event at 19q13.43 in IDH-mutant astrocytomas is strongly correlated with MYC overexpression

MYC dysregulation is pivotal in the onset and progression of IDH-mutant gliomas, mostly driven by copy-number alterations, regulatory element alterations, or epigenetic changes. Our pilot analysis uncovered instances of relative MYC overexpression without alterations in the proximal MYC network (PMN), prompting a deeper investigation into potential novel oncogenic mechanisms. Analysing comprehensive genomics profiles of 236 "IDH-mutant 1p/19q non-co-deleted" lower-grade gliomas from The Cancer Genome Atlas, we identified somatic genomic alterations within the PMN. In tumours without PMN-alterations but with MYC-overexpression, genes correlated with MYC-overexpression were identified. Our analyses yielded that 86/236 of astrocytomas exhibited no PMN-alterations, a subset of 21/86 displaying relative MYC overexpression. Within this subset, we discovered 42 genes inversely correlated with relative MYC expression, all on 19q. Further analysis pinpointed a minimal common region at 19q13.43, encompassing 15 genes. The inverse correlations of these 15 genes with relative MYC overexpression were re-confirmed using independent scRNAseq data. Further, the micro-deleted astrocytoma subset displayed significantly higher genomic instability compared to WT cases, but lower instability compared to PMN-hit cases. This newly identified 19q micro-deletion represents a potential novel mechanism underlying MYC dysregulation in astrocytomas. Given the prominence of 19q loss in IDH-mutant gliomas, our findings bear significant implications for understanding gliomagenesis.

Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy

Background

Monocytes play a critical role in tumor initiation and progression, with their impact on prostate adenocarcinoma (PRAD) not yet fully understood. This study aimed to identify key monocyte-related genes and elucidate their mechanisms in PRAD.

Method

Utilizing the TCGA-PRAD dataset, immune cell infiltration levels were assessed using CIBERSORT, and their correlation with patient prognosis was analyzed. The WGCNA method pinpointed 14 crucial monocyte-related genes. A diagnostic model focused on monocytes was developed using a combination of machine learning algorithms, while a prognostic model was created using the LASSO algorithm, both of which were validated. Random forest and gradient boosting machine singled out CCNA2 as the most significant gene related to prognosis in monocytes, with its function further investigated through gene enrichment analysis. Mendelian randomization analysis of the association of HLA-DR high-expressing monocytes with PRAD. Molecular docking was employed to assess the binding affinity of CCNA2 with targeted drugs for PRAD, and experimental validation confirmed the expression and prognostic value of CCNA2 in PRAD.

Result

Based on the identification of 14 monocyte-related genes by WGCNA, we developed a diagnostic model for PRAD using a combination of multiple machine learning algorithms. Additionally, we constructed a prognostic model using the LASSO algorithm, both of which demonstrated excellent predictive capabilities. Analysis with random forest and gradient boosting machine algorithms further supported the potential prognostic value of CCNA2 in PRAD. Gene enrichment analysis revealed the association of CCNA2 with the regulation of cell cycle and cellular senescence in PRAD. Mendelian randomization analysis confirmed that monocytes expressing high levels of HLA-DR may promote PRAD. Molecular docking results suggested a strong affinity of CCNA2 for drugs targeting PRAD. Furthermore, immunohistochemistry experiments validated the upregulation of CCNA2 expression in PRAD and its correlation with patient prognosis.

Conclusion

Our findings offer new insights into monocyte heterogeneity and its role in PRAD. Furthermore, CCNA2 holds potential as a novel targeted drug for PRAD.

DUSP5 regulated by YTHDF1-mediated m6A modification promotes epithelial-mesenchymal transition and EGFR-TKI resistance via the TGF-β/Smad signaling pathway in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) patients have a dismal survival rate because of cancer metastasis and drug resistance. The study aims to identify the genes that concurrently modulate EMT, metastasis and EGFR-TKI resistance, and to investigate the underlying regulatory mechanisms.

METHODS

Cox regression and Kaplan-Meier analyses were applied to identify prognostic oncogenes in LUAD. Gene set enrichment analysis (GSEA) was used to indicate the biological functions of the gene. Wound-healing and Transwell assays were used to detect migratory and invasive ability. EGFR-TKI sensitivity was evaluated by assessing the proliferation, clonogenic survival and metastatic capability of cancer cells with treatment with gefitinib. Methylated RNA immunoprecipitation (MeRIP) and RNA immunoprecipitation (RIP) analyses established the level of m6A modification present on the target gene and the protein's capability to interact with RNA, respectively. Single-sample gene set enrichment (ssGSEA) algorithm used to investigate levels of immune cell infiltration.

RESULTS

Our study identified dual-specificity phosphatase 5 (DUSP5) as a novel and powerful predictor of adverse outcomes for LUAD by using public datasets. Functional enrichment analysis found that DUSP5 was positively enriched in EMT and transforming growth factor-beta (TGF-β) signaling pathway, a prevailing pathway involved in the induction of EMT. As expected, DUSP5 knockdown suppressed EMT via inhibiting the canonical TGF-β/Smad signaling pathway in in vitro experiments. Consistently, knockdown of DUSP5 was first found to inhibit migratory ability and invasiveness of LUAD cells in in vitro and prevent lung metastasis in in vivo. DUSP5 knockdown re-sensitized gefitinib-resistant LUAD cells to gefitinib, accompanying reversion of EMT progress. In LUAD tissue samples, we found 14 cytosine-phosphate-guanine (CpG) sites of DUSP5 that were negatively associated with DUSP5 gene expression. Importantly, 5'Azacytidine (AZA), an FDA-approved DNA methyltransferase inhibitor, restored DUSP5 expression. Moreover, RIP experiments confirmed that YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), a m6A reader protein, could bind DUSP5 mRNA. YTHDF1 promoted DUSP5 expression and the malignant phenotype of LUAD cells. In addition, the DUSP5-derived genomic model revealed the two clusters with distinguishable immune features and tumor mutational burden (TMB).

CONCLUSIONS

Briefly, our study discovered DUSP5 which was regulated by epigenetic modification, might be a potential therapeutic target, especially in LUAD patients with acquired EGFR-TKI resistance.

ZEB family is a prognostic biomarker and correlates with anoikis and immune infiltration in kidney renal clear cell carcinoma

BACKGROUND

Zinc finger E-box binding homEeobox 1 (ZEB1) and ZEB2 are two anoikis-related transcription factors. The mRNA expressions of these two genes are significantly increased in kidney renal clear cell carcinoma (KIRC), which are associated with poor survival. Meanwhile, the mechanisms and clinical significance of ZEB1 and ZEB2 upregulation in KIRC remain unknown.

METHODS

Through the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database, expression profiles, prognostic value and receiver operating characteristic curves (ROCs) of ZEB1 and ZEB2 were evaluated. The correlations of ZEB1 and ZEB2 with anoikis were further assessed in TCGA-KIRC database. Next, miRTarBase, miRDB, and TargetScan were used to predict microRNAs targeting ZEB1 and ZEB2, and TCGA-KIRC database was utilized to discern differences in microRNAs and establish the association between microRNAs and ZEBs. TCGA, TIMER, TISIDB, and TISCH were used to analyze tumor immune infiltration.

RESULTS

It was found that ZEB1 and ZEB2 expression were related with histologic grade in KIRC patient. Kaplan-Meier survival analyses showed that KIRC patients with low ZEB1 or ZEB2 levels had a significantly lower survival rate. Meanwhile, ZEB1 and ZEB2 are closely related to anoikis and are regulated by microRNAs. We constructed a risk model using univariate Cox and LASSO regression analyses to identify two microRNAs (hsa-miR-130b-3p and hsa-miR-138-5p). Furthermore, ZEB1 and ZEB2 regulate immune cell invasion in KIRC tumor microenvironments.

CONCLUSIONS

Anoikis, cytotoxic immune cell infiltration, and patient survival outcomes were correlated with ZEB1 and ZEB2 mRNA upregulation in KIRC. ZEB1 and ZEB2 are regulated by microRNAs.

Elevated RACGAP1 Expression Enhances Malignant Potential in Lung Adenocarcinoma and Serves as a Prognostic Factor

Background: While RACGAP1 is identified as a potential oncogene, its specific role in lung adenocarcinoma (LUAD) remains unclear. Methods: First, we conducted a comprehensive analysis of the role of RACGAP1 across 33 types of cancer. Subsequently, we investigated the expression levels of RACGAP1 and its impact on prognosis using data from The Cancer Genome Atlas (TCGA) database. We utilized single-cell sequencing data to explore the tumor-related processes of RACGAP1 in LUAD and validated our findings through experimental verification. Employing a consensus clustering (CC) approach, we subdivided LUAD patients into two subtypes based on RACGAP1 cell cycle-related genes (RrCCGs). These subtypes exhibited significant differences in tumor characteristics, lymph node metastasis, and recurrence. Furthermore, we evaluated the prognostic influence of RrCCGs using univariate Cox regression and least absolute shrinkage and selection operator regression models (LASSO), successfully establishing a prognostic model. Results: RACGAP1 is frequently overexpressed in various tumors and can impact the prognosis of patients with LUAD. Additionally, experimental evidence has demonstrated that low expression of RACGAP1 favors tumor cell apoptosis and restoration of the cell cycle, while high expression promotes invasion and metastasis. Through CC analysis of RrCCGs, patients were classified into two groups, with survival analysis revealing distinct prognoses and stages between the two groups. Furthermore, Cox and LASSO regression successfully constructed a prognostic model with robust predictive capability.

SERPINC1, a new prognostic predictor of colon cancer, promote colon cancer progression through EMT

BACKGROUND

Liver metastasis of CRC is still the main cause of poor prognosis in patients with CRC. Previous studies have suggested that serpin family C member 1(SERPINC1) is involved in the development of a variety of tumours, but its effect on colorectal cancer progression has been poorly elucidated.

METHODS

Based on the GEO database, this study identifies the core gene SERPINC1 associated with liver metastasis in CRC. We used transcriptomic data and immunohistochemical staining to explore the expression of SERPINC1 in normal, cancer, and liver metastases tissue from CRC patients. Clinical data obtained from our hospital were used to explore the impact of SERPINC1 on the prognosis of colon cancer patients. Mechanistically, the biological functions exerted by SERPINC1 in CRC were predicted by bioinformatics, and the results were validated by the results of the experiments in vitro. Cell lines with knockdown of SERPINC1 were performed a series assay such as trans well, CCK-8 and colony formation assay to explore the relationship between SERPINC1 and proliferation and metastasis of CRC cells. Finally, the effect of SERPINC1 on the sensitivity of colon cancer patients to immune checkpoint therapy was evaluated.

RESULTS

In CRC liver metastatic tissues, we found significantly high expression of SERPINC1. Briefly, 212 CRC cohorts showed that SERPINC1 was significantly associated with TNM stage and plasma CA19-9 and CEA in CRC patients. Univariate and multivariate Cox demonstrated that SERPINC1 was significantly associated with 5-year survival after radical surgery for colorectal cancer (p < 0.001). Bioinformatics predicted that SERPINC1 affects metastasis of colon cancer through epithelial-mesenchymal transition (EMT). Colony formation assay and CCK-8 assay showed that SERPINC1 promotes malignant proliferation of CRC cells, trans well assay showed that SERPINC1 promotes distant migratory behaviour of CRC cells and protein blotting assay showed that SERPINC1 may promote migration by promoting the TGF-β1-mediated EMT of CRC cells. In addition, several immunotherapy cohorts also reflected that the expression of SERPINC1 reduced the sensitivity of CRC patients to immune checkpoint therapy.

CONCLUSION

Our study identified SERPINC1 as a novel liver metastasis-associated gene in CRC. Targeting SERPINC1 may be a novel therapeutic strategy for patients with liver metastases from CRC.

Troponin T1 in tumorigenesis and immune modulation: Insights into multiple cancers and kidney renal clear cell carcinoma

Troponin T1 (TNNT1) plays a crucial role in muscle contraction but its role in cancer, particularly in kidney renal clear cell carcinoma (KIRC), is not well-understood. This study explores the expression, clinical significance and biological functions of TNNT1 in various cancers, with an emphasis on its involvement in KIRC. We analysed TNNT1 expression in cancers using databases like TCGA and GTEx, assessing its prognostic value, mutation patterns, methylation status and functional implications. The study also examined TNNT1's effect on the tumour microenvironment and drug sensitivity in KIRC, complemented by in vitro TNNT1 knockdown experiments in KIRC cells. TNNT1 is overexpressed in several cancers and linked to adverse outcomes, showing frequent upregulation mutations and abnormal methylation. Functionally, TNNT1 connects to muscle and cancer pathways, affects immune infiltration and drug responses, and its overexpression in KIRC is associated with advanced disease and reduced survival. Knocking down TNNT1 curbed KIRC cell growth. TNNT1's aberrant expression plays a significant role in tumorigenesis and immune modulation, highlighting its value as a prognostic biomarker and a potential therapeutic target in KIRC and other cancers. Further studies are essential to understand TNNT1's oncogenic mechanisms in KIRC.

Identification of ANKRD13D as a potential target in renal cell carcinomas

BACKGROUND

The correlation of the expression of ankyrin repeat domain (ANKRD) family members with renal cell carcinoma prognosis was investigated.

METHODS

The GEPIA2, GEO2R, UALCAN, GDC, OncoLnc, TIMER, PanglaoDB, CancerSEA, and Tabula Muris databases were used. Twelve ANKRD family members were identified as having overexpressed renal cell carcinoma samples. The ANKRD13D was identified as a renal cell carcinoma-specific target by cross-referencing the multiple survival databases. To clarify the role of ANKRD13D, the expression of NAKRD13D was analyzed at the single-cell level.

RESULTS

ANKRD13D was mainly expressed in immune cells and positively correlated with Treg cell infiltration. The expression of ANKRD13D was also positively correlated with PDCD1, CTLA4, LAG3, TNFSF14, and ISG20. The overexpression of ANKRD13D in Treg was confirmed using reverse transcription-quantitative polymerase chain reaction. The structure of ANKRD13D was predicted using AlphaFold.

CONCLUSION

In conclusion, we identified ANKRD13D as a key immune regulator, and targeting ANKRD13D with immune checkpoints blockade may be a promoting strategy for renal cell carcinoma immunotherapy.

Experimental Validation and Multi-omics Analysis Identified ARPC1A as a Novel Oncogene and Potential Therapeutic Target in Glioblastoma

Actin-related protein 2/3 complex subunit 1A (ARPC1A) is implicated in several cancers due to its critical role in regulating actin polymerization. However, the exact mechanism of ARPC1A in cancer remains unclear. This study aims to investigate the biological role of ARPC1A in various cancers and the regulatory role of ARPC1A in glioblastoma multiforme (GBM). We analyzed the expression differences, prognostic value, mutations, immune infiltration, immune microenvironment, and single-cell level correlations of ARPC1A in various cancers. Furthermore, we employed gene set enrichment analysis (GSEA) and functional experiments to elucidate the regulatory mechanisms of ARPC1A on GBM. Importantly, we assessed the role of ARPC1A in temozolomide (TMZ) resistance of GBM. ARPC1A expression was up-regulated in most cancer tissues and was associated with poorer prognosis. Genomic mutation analysis revealed that the predominant type of ARPC1A mutation in tumors was amplification. ARPC1A expression was negatively correlated with B-cell and immune scores in most tumors. Both GSEA and single-cell sequencing have revealed that ARPC1A promotes tumor proliferation and epithelial-mesenchymal transition. In vitro experiments confirmed that ARPC1A knockdown inhibited the proliferation and metastatic ability of GBM cells. Notably, silencing ARPC1A reduced TMZ resistance in GBM cells. This study highlights the prognostic value of ARPC1A in various tumors and its potential for application in immunotherapy. Meanwhile, the modulation of GBM malignant behavior and TMZ resistance by ARPC1A provides a new approach for personalized and precise treatment of GBM.

Exploring cutting-edge strategies for drug repurposing in female cancers - An insight into the tools of the trade

Female cancers, which include breast and gynaecological cancers, represent a significant global health burden for women. Despite advancements in research pertinent to unearthing crucial pathological characteristics of these cancers, challenges persist in discovering potential therapeutic strategies. This is further exacerbated by economic burdens associated with de novo drug discovery and clinical intricacies such as development of drug resistance and metastasis. Drug repurposing, an innovative approach leveraging existing FDA-approved drugs for new indications, presents a promising avenue to expedite therapeutic development. Computational techniques, including virtual screening and analysis of drug-target-disease relationships, enable the identification of potential candidate drugs. Integration of diverse data types, such as omics and clinical information, enhances the precision and efficacy of drug repurposing strategies. Experimental approaches, including high-throughput screening assays, in vitro, and in vivo models, complement computational methods, facilitating the validation of repurposed drugs. This review highlights various target mining strategies based on analysis of differential gene expression, weighted gene co-expression, protein-protein interaction network, and host-pathogen interaction, among others. To unearth drug candidates, the technicalities of leveraging information from databases such as DrugBank, STITCH, LINCS, and ChEMBL, among others are discussed. Further in silico validation techniques encompassing molecular docking, pharmacophore modelling, molecular dynamic simulations, and ADMET analysis are elaborated. Overall, this review delves into the exploration of individual case studies to offer a wide perspective of the ever-evolving field of drug repurposing, emphasizing the multifaceted approaches and methodologies employed for the same to confront female cancers.

DeepGRNCS: deep learning-based framework for jointly inferring gene regulatory networks across cell subpopulations

Inferring gene regulatory networks (GRNs) allows us to obtain a deeper understanding of cellular function and disease pathogenesis. Recent advances in single-cell RNA sequencing (scRNA-seq) technology have improved the accuracy of GRN inference. However, many methods for inferring individual GRNs from scRNA-seq data are limited because they overlook intercellular heterogeneity and similarities between different cell subpopulations, which are often present in the data. Here, we propose a deep learning-based framework, DeepGRNCS, for jointly inferring GRNs across cell subpopulations. We follow the commonly accepted hypothesis that the expression of a target gene can be predicted based on the expression of transcription factors (TFs) due to underlying regulatory relationships. We initially processed scRNA-seq data by discretizing data scattering using the equal-width method. Then, we trained deep learning models to predict target gene expression from TFs. By individually removing each TF from the expression matrix, we used pre-trained deep model predictions to infer regulatory relationships between TFs and genes, thereby constructing the GRN. Our method outperforms existing GRN inference methods for various simulated and real scRNA-seq datasets. Finally, we applied DeepGRNCS to non-small cell lung cancer scRNA-seq data to identify key genes in each cell subpopulation and analyzed their biological relevance. In conclusion, DeepGRNCS effectively predicts cell subpopulation-specific GRNs. The source code is available at https://github.com/Nastume777/DeepGRNCS.

P4HA2 contributes to head and neck squamous cell carcinoma progression and EMT through PI3K/AKT signaling pathway

Head and neck squamous cell carcinoma (HNSCC) can be defined as a deadly illness with a dismal prognosis in advanced stages. Therefore, we seek to examine P4HA2 expression and effect in HNSCC, along with the underlying mechanisms. This study utilized integrated bioinformatics analyses to evaluate the P4HA2 expression pattern, prognostic implication, and probable function in HNSCC. The study conducted various in vitro experiments, including colony formation, CCK-8, flow cytometry, wound healing, and transwell assays, on the human HNSCC cell line CAL-27 to examine the involvement of P4HA2 in HNSCC progression. Moreover, western blotting was used to investigate epithelial-mesenchymal transition (EMT) markers and PI3K/AKT pathway markers to elucidate the underlying mechanisms. P4HA2 expression was significantly enhanced in HNSCC, and its overexpression was correlated to tumor aggressiveness and a poor prognosis in patients. Based on in vitro experiments, the overexpressed P4HA2 enhanced cell proliferation, migration, invasion, as well as EMT while reducing apoptosis, whereas P4HA2 silencing exhibited the reverse effect. P4HA2 overexpression enhanced PI3K/AKT phosphorylation in HNSCC cells. Moreover, LY294002 was observed to counteract the effects of upregulated P4HA2 on proliferation, migration, invasion, and EMT in HNSCC. Collectively, we indicated that P4HA2 promoted HNSCC progression and EMT via PI3K/AKT signaling pathway.

A novel signature incorporating genes related to lipid metabolism and immune for prognostic and functional prediction of breast cancer

PURPOSE

Breast cancer prognosis and functioning have not been thoroughly examined in relation to immunological and lipid metabolism. However, there is a lack of prognostic and functional analyses of the relationship between lipid metabolism and immunity in breast cancer.

METHODS

DEGs in breast cancer were obtained from UCSC database, and lipid metabolism and immune-related genes were obtained from GSEA and Immune databases. A predictive signature was constructed using univariate Cox and LASSO regression on lipid metabolism and immune-related DEGs. The signature's prognostic significance was assessed using Kaplan-Meier, time-dependent ROC, and risk factor survival scores. Survival prognosis, therapeutic relevance, and functional enrichment were used to mine model gene biology. We selected IL18, which has never been reported in breast cancer before, in the signature to learn more about its function, potential to predict outcome, and immune system role. RT-PCR was performed to verify the true expression level of IL18.

RESULTS

A total of 136 DEGs associated with breast cancer responses to both immunity and lipid metabolism. Nine key genes (CALR, CCL5, CEPT, FTT3, CXCL13, FLT3, IL12B, IL18, and IL24, p < 1.6e-2) of breast cancer were identified, and a prognostic was successfully constructed with a good predictive ability. IL18 in the model also had good clinical prognostic guidance value and immune regulation and therapeutic potential. Furthermore, the expression of IL18 was higher than that in paracancerous tissue.

CONCLUSIONS

A unique predictive signature model could effectively predict the prognosis of breast cancer, which can not only achieve survival prediction, but also screen out key genes with important functional mechanisms to guide clinical drug experiments.

Prognostic value and immunological function of cuproptosis-related genes in lung adenocarcinoma

Background

Lung cancer is one of the malignant tumors with the highest morbidity and fatality rates worldwide. The overall survival (OS) of lung adenocarcinoma (LUAD) is poor. Cuproptosis is a copper-triggered modality of mitochondrial cell death, however, its contribution to the emergence of lung cancer is unknown. The clinical implication and immunological function of cuproptosis-related genes (CRGs) in LUAD has yet to be established.

Methods

TCGA, HPA, GEPIA, Kaplan-Meier, TIMER and CancerSEA database were used to explore the prognostic value and biological function of CRGs in LUAD.

Results

CRGs are primarily involved in copper ion transport, the citrate cycle (TCA cycle) and central carbon metabolism in LUAD. The mRNA expression of COA6, UBE2D1, DLAT, SLC25A3, and DBH was significantly increased. The expression of COA6, DLAT, SLC25A3, DBH, and LOXL2 were all strongly associated with the clinicopathological stages in LUAD. Moreover, high expression of COA6, UBE2D1, DLAT, SLC25A3 and LOXL2 was related to poor OS. The expression of SLC25A3 and LOXL2 showed different association with immune cell infiltration. The single cell sequencing demonstrated that CRGs play important roles in the regulation of DNA damage response, inflammation and metastasis in LUAD.

Conclusions

In summary, this study comprehensively uncovered that CRGs could be identified as potential prognostic and immunological biomarkers in LUAD. Our current research could provide a solid theoretical basis for LUAD survival research and clinical decision-making.

TUBB, a robust biomarker with satisfying abilities in diagnosis, prognosis, and immune regulation via a comprehensive pan-cancer analysis

Purpose

TUBB can encode a beta-tubulin protein. At present, the role of TUBB has not been ascertained in cancers. Hence, the importance of further systematic pan-cancer analyses is stressed to explore its value in the diagnosis, prognosis, and immune function of cancers.

Methods

By collecting and handling integrative data from the TCGA, Firehose, UCSC Xena, cBioPortal, GEO, CPTAC, TIMER2.0, TISCH, CellMiner, GDSC, and CTRP databases, we explored the potential diagnostic and prognostic roles of TUBB in pan-cancers from multiple angles. Moreover, the GSEA analysis was conducted to excavate the biological functions of TUBB in pan-cancers. In addition, survival profiles were described, and the differential expressions of TUBB in different molecular subtypes were discussed. Also, we utilized the cMAP function to search drugs or micro-molecules that have an impact on TUBB expressions.

Results

Based on the TCGA data, we found that TUBB was differentially expressed in a variety of tumors and showed an early-diagnostic value. Mutations, somatic copy number alterations, and DNA methylation would lead to its abnormal expression. TUBB expressions had relations with many clinical features. What's more, TUBB expressions were validated to be related to many metabolism-related, metastasis-related, and immune-related pathways. High TUBB expressions were proved to have a great impact on the prognosis of various types of cancers and would affect the sensitivity of some drugs. We also demonstrated that the expression of TUBB was significantly correlated to immunoregulator molecules and biomarkers of lymphocyte subpopulation infiltration.

Conclusion

TUBB and its regulatory genes were systemically analyzed in this study, showing that TUBB had satisfying performances in disease diagnosing and prognosis predicting of multiple cancers. It could remodel the tumor microenvironment and play an integral role in guiding cancer therapies and forecasting responses to chemotherapy.

Inhibition of proteinase-activated receptor 2 (PAR2) decreased the malignant progression of lung cancer cells and increased the sensitivity to chemotherapy

OBJECTIVES

This study aimed to study the effect of protease-activated receptor 2 (PAR2) on the proliferation, invasion, and clone formation of lung cancer cells. It also aimed to evaluate the inhibitory effect of melittin on PAR2 and the anti-lung cancer effect of melittin combined with gefitinib.

METHODS

The correlation between the co-expression of PAR2 and epithelial-mesenchymal transition (EMT) markers was analyzed. PAR2 in A549 and NCI-H1299 cells was knocked down using siRNA. MTT assay, Transwell assay, and colony formation assay were used to detect the effects of PAR2 on cell proliferation, invasion, and clone formation. The anti-cancer effect of PAR2 knockdown on gefitinib treatment was analyzed. The synergistic effect of melittin on gefitinib treatment by inhibiting PAR2 and the underlying molecular mechanism were further analyzed and tested.

RESULTS

The expression of PAR2 was upregulated in lung cancer, which was associated with the poor prognosis of lung cancer. PAR2 knockdown inhibited the stemness and EMT of lung cancer cells. It also inhibited the proliferation, invasion, and colony formation of A549 and NCI-H1299 cells. Moreover, PAR2 knockdown increased the chemotherapeutic sensitivity of gefitinib in lung cancer. Melittin inhibited PAR2 and the malignant progression of lung cancer cells. Melittin increased the chemotherapeutic sensitivity of gefitinib in lung cancer by inhibiting PAR2.

CONCLUSION

PAR2 may promote the proliferation, invasion, and colony formation of lung cancer cells by promoting EMT. Patients with a high expression of PAR2 have a poor prognosis. Inhibition of PAR2 increased the chemotherapeutic sensitivity of gefitinib. PAR2 may be a potential therapeutic target and diagnostic marker for lung cancer.

Pan-cancer analysis of prognostic and immunological role of IL4I1 in human tumors: a bulk omics research and single cell sequencing validation

BACKGROUND

Interleukin-4 inducible gene 1 (IL4I1) regulates tumor progression in numerous tumor types. However, its correlation with immune infiltration and prognosis of patients in a pan-cancer setting remains unclear.

METHODS

Data from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), UALCAN, Clinical Proteomic Tumor Analysis Consortium (CPTAC), Gene Expression Omnibus (GEO), cBioPortal, Cancer Single-cell State Atlas (CancerSEA), and Tumor IMmune Estimation Resource(TIMER) databases were used to evaluate IL4I1 expression, clinical features and prognostic effects, gene set enrichment, and correlation with immune cell infiltration, as well as the relationship between IL4I1 methylation and expression and survival prognosis. Correlations with 192 anticancer drugs were also analyzed.

RESULTS

IL4I1 was significantly overexpressed in the majority of tumors, and the imbalance of IL4I1 was significantly correlated with overall survival and pathological stage. Moreover, total IL4I1 protein was increased in cancer. Therefore, IL4I1 may be used as a prognostic biomarker or protective factor in numerous types of cancer. The methylation level of IL4I1 may also be used as a prognostic marker. The functional enrichment of IL4I1 was closely related to the immunomodulatory pathway. In addition, the level of tumor-associated macrophage infiltration was positively correlated with the expression of IL4I1 in pan-cancerous tissues. scRNA-seq analysis suggested that IL4I1 differ significantly among different cells in the tumor microenvironment and was most enriched in macrophages. Various immune checkpoint genes were positively correlated with IL4I1 expression in most tumors. In addition, patients with high IL4I1 expression may be resistant to BMS-754807 and docetaxel, but sensitive to temozolomide.

CONCLUSION

IL4I1 may play a role as promoter of cancer and prognostic indicator in patients. High expression of IL4I1 is associated with the state of tumor immunosuppression and may contribute to tumor-associated macrophage invasion. Therefore, IL4I1 may be a new therapeutic target for the treatment and prognosis of patients with cancer.

Clinical significance of immune-related antigen CD58 in gliomas and analysis of its potential core related gene clusters

Background

The clinical significance of immune-related antigen CD58 in gliomas remains uncertain. The aim of this study was to examine the clinical importance and possible core related genes of CD58 in gliomas.

Methods

Pan-cancer analysis was to observe the association between CD58 and different tumors, glioma RNA sequencing data and clinical sample analyses were used to observe the relationship between CD58 and glioma, shRNA interference models were to observe the impact of CD58 on glioma cell function, and four glioma datasets and two online analysis platforms were used to explore the core related genes affecting the correlation between CD58 and glioma.

Results

High CD58 expression was associated with worse prognosis in various tumors and higher malignancy in glioma. Down regulation of CD58 expression was linked to decreased proliferation, increased apoptosis, and reduced metastasis in glioma cells. The pathways involved in CD58-related effects were enriched for immune cell adhesion and immune factor activation, and the core genes were CASP1, CCL2, IL18, MYD88, PTPRC, and TLR2. The signature of CD58 and its core-related genes showed superior predictive power for glioma prognosis.

Conclusion

High CD58 expression is correlated with more malignant glioma types, and also an independent risk factor for mortality in glioma. CD58 and its core-related genes may serve as novel biomarkers for diagnosing and treating glioma.