Cancer Gene Expression Research Articles

A novel model based on lipid metabolism-related genes associated with immune microenvironment predicts metastasis of breast cancer

BackgroundBreast cancer (BC) is the most prevalent malignant tumor among women worldwide and a significant cause of cancer-related deaths in females. Recent studies have shown that lipid metabolism-related genes (LMRGs) exhibit prognostic potential in various types of tumors, including BC. Our study aimed to establish a novel model to predict the metastasis of BC.MethodsClinical information and corresponding RNA data of patients with BC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering was performed to identify novel molecular subgroups. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues using Expression, microenvironment cell populations counter, microenvironment cell populations counter, and single-sample gene set enrichment analyses were employed to determine the tumor immune microenvironment and immune status of the identified subgroups. Functional analyses, including Gene Ontology and gene set enrichment analyses, were conducted to elucidate the underlying mechanisms. A prognostic risk model was constructed using the Least Absolute Shrinkage and Selection Operator algorithm and multivariate Cox regression analysis.ResultsThis study identified differential gene expression between patients with BC exhibiting metastasis and those without metastasis using public databases. Using the obtained data, we established predictive models based on six LMRGs. Furthermore, consensus clustering and prognostic score grouping analysis revealed that differentially expressed LMRGs influence tumor prognosis by regulating tumor immunity. To facilitate clinical application, we developed a nomogram integrating the risk model and clinical characteristics to accurately predict the prognosis of patients with BC.ConclusionWe developed and validated a novel signature associated with LMRGs for predicting disease-free survival in patients with BC. The expression of LMRGs correlates with the immune microenvironment of patients with BC, providing new insights and improved strategies for the diagnosis and treatment of BC.

Establish TIIC signature score based the machine learning fusion in bladder cancer

BackgroundBladder cancer is a prevalent malignant tumor with high heterogeneity. Current treatments, such as transurethral resection of bladder tumor (TURBT) and intravesical Bacillus Calmette-Guérin (BCG) therapy, still have limitations, with approximately 30% of non-muscle-invasive bladder cancer (NMIBC) progressing to muscle-invasive bladder cancer (MIBC), and a substantial number of MIBC patients experiencing recurrence after surgery. Immunotherapy has shown potential benefits, but accurate prediction of its prognostic effects remains challenging.MethodsWe analyzed bladder cancer RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and used various machine learning algorithms to screen for feature RNAs related to tumor-infiltrating immune cells (TIICs) from single-cell data. Based on these RNAs, we established a TIIC signature score and evaluated its relationship with overall survival (OS) and immunotherapy response in bladder cancer patients.ResultsThe study identified 171 TIIC-RNAs and selected 11 TIIC-RNAs with prognostic value through survival analysis. The TIIC signature score established using a machine learning fusion method was significantly associated with OS and showed good predictive performance in different datasets. Additionally, the signature score was negatively correlated with immunotherapy response, with patients with low TIIC feature scores showing better survival outcomes after immunotherapy. Further biological functional analysis revealed a close association between the TIIC signature score and immune regulation processes, cellular metabolism, and genetic variations.ConclusionThis study successfully constructed and validated an RNA signature scoring system based on tumor-infiltrating immune cell (TIIC) features, which can effectively predict OS and the effectiveness of immunotherapy in bladder cancer patients.

Comprehensive exploration on the role of base excision repair genes in modulating immune infiltration in low-grade glioma

IntroductionGlioma is a brain tumour occurring in all age groups but common in adults. Despite advances in the understanding of tumours, we cannot improve the survival of the patients and do not have an appropriate biomarker for progression and prognosis prediction. The base excision repair mechanism maintains the integrity of the genome, preventing tumour formation. However, continuous chemical damage to the cells results in mutations that escape the repair mechanism and support tumour growth. The tumour microenvironment in cancer is crucial in determining the tumour growth, development, and response to treatments. The present study explored the significance of Base Excision Repair genes (BER) in modulating the tumour microenvironment. MethodsWe used the publically available data sets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to explore the role of the base excision repair gene in the modulating tumour microenvironment. The data was analysed for the expression of base excision repair genes, their correlation with the immune markers, their prognostic potential, and enrichment analysis to understand the pathways they modulate in low-grade glioma (LGG) progression. ResultsThe analysis showed BER genes contribute an integral role in the overall and disease-free survival of LGG. Genes like MUTYH, PNKP, UNG and XRCC1 showed a correlation with the immune infiltration levels and a significant correlation with various immune markers associated with different immune cells, including tumour-associated macrophages. MUTYH, UNG and XRCC1 correlated with IDH1 mutation status, and functional enrichment analysis showed that these genes are enriched in several pathways like Wnt, PD-1 and Integrin signalling. ConclusionOur findings suggest that the BER genes MUTYH, PNKP, UNG and XRCC1 can potentially be prognostic biomarkers and highly correlate with the immune cells of the tumour microenvironment.

Comprehensive analysis of Epha10 as a predictor of clinical prognosis and immune checkpoint therapy efficacy in non-small cell lung cancer

The EphA family belongs to a large group of membrane receptor tyrosine kinases. Emerging evidence indicates that the EphA family participates in tumour occurrence and progression. Nonetheless, the expression patterns and prognostic values of the nine EphAs in non-small cell lung cancer (NSCLC) have rarely been studied before. In the current study, we comprehensively analysed the expression and prognostic role of EphA family members by different means. The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis databases were used to investigate the expression of EphAs in NSCLC. The cBioPortal database was applied to analyse the prognostic values and genetic mutations of EphAs.We discovered that the expression of EphA10 was significantly higher in NSCLC tissues than in adjacent noncancerous tissues, and survival analyses showed that a higher level of EphA10 predicted poor prognosis. Further exploration into the role of EphA10 by ESTIMATE, CIBERSORT, and ssGSEA analysis found that it was also related to immune infiltration and higher expression of targets of ICI targets. In conclusion, this study revealed that among the EphA family members, EphA10 played an oncogenic role and was a promising biomarker for poor prognosis and better immunotherapy response in NSCLC.

ANXA5 predicts prognosis and immune response and mediates proliferation and migration in head and neck squamous cell carcinoma

BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common malignancy that often develops unnoticed. Typically, these tumors are identified at advanced stages, resulting in a relatively low chance of successful treatment. Anoikis serves as a natural defense against the spread of tumor cells, meaning circumventing anoikis can effectively inhibit tumor metastasis. Nonetheless, studies focusing on anoikis in the context of HNSCC remain scarce. MethodsAnoikis-related genes (ARGs) were identified by using the GeneCards and Harmonizome databases. Expression data of these genes and relevant clinical features were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A LASSO regression and a prognostic risk score model were developed to determine their prognostic significance. The analysis included the use of the CIBERSORT algorithm to quantify immune and stromal cell presence. Furthermore, in vitro and in vivo, we confirmed the expression and functional roles of proteins and mRNA of genes independently predictive of prognosis. ResultsThe study identified eight genes linked to prognosis (ANXA5, BAK1, CDKN2A, PPARG, CCR7, MAPK11, CRYAB, CRYBA1) and developed a prognostic model that effectively forecasts the survival outcomes for patients with HNSCC. A higher survival likelihood is associated with lower risk scores. In addition, a significant relationship was found between immune and risk score, and ANXA5 deletion promoted the killing of HNSCC cells by activated CD8+ T cells. During the screening process, 65 different chemotherapeutic drugs were found to have significant differences in IC50 values when comparing high- and low-risk categories. ANXA5 emerged as a gene with independent prognostic significance, exhibiting notably elevated protein and mRNA levels in HNSCC tissue compared to non-tumorous tissue. The suppression of ANXA5 gene activity resulted in a substantial decrease in both the growth and mobility of HNSCC cells. Animal model experiments demonstrated that inhibiting ANXA5 suppressed HNSCC growth and migration in vivo. ConclusionThrough bioinformatics, a prognostic risk model of high precision was developed, offering valuable insights into the survival rates and immune responses in patients with HNSCC. ANXA5 is highlighted as a significant prognostic factor among the identified genes, indicating its promise as a potential therapeutic target for those with HNSCC.

Immune checkpoint gene signature assesses immune infiltration profiles in bladder cancer and identifies KRT23 as an immunotherapeutic target

BackgroundIn the past few decades, researchers have made promising progress, including the development of immune checkpoint inhibitors (ICIs) in the therapy of bladder cancer (BLCA). Existing studies mainly focus on single immune checkpoint inhibitors but lack relevant studies on the gene expression profiles of multiple immune checkpoints.MethodsRNA-sequencing profiling data and clinical information of BLCA patients and normal human bladder samples were acquired from the Cancer Genome Atlas and Gene Expression Omnibus databases and analyzed to identify different expression profiles of immune checkpoint genes (ICGs) after consensus clustering analysis. Based on the 526 intersecting differentially expressed genes, the LASSO Cox regression analysis was utilized to construct the ICG signature.ResultsAccording to the expression of ICGs, BLCA patients were divided into three subtypes with different phenotypic and mechanistic characteristics. Furthermore, the developed ICG signature were independent predictors of outcome in BLCA patients, and was correlated with the immune infiltration, the expression of ICGs and chemotherapeutic effect.ConclusionsThis study systematically and comprehensively analyzed the expression profile of immune checkpoint genes, and established the ICG signature to investigate the differences in ICGs expression and tumor immune microenvironment, which will help risk stratification and accelerate precision medicine. Finally, we identified KRT23 as the most critical model gene, and highlighted KRT23 as a potential target to enhance immunotherapy against BLCA.

BRD4 expression and its regulatory interaction with miR-26a-3p, DLG5-AS1, and JMJD1C-AS1 lncRNAs in gastric cancer progression

Gastric cancer remains a significant health challenge despite advancements in diagnosis and treatment. Early detection is critical to reducing mortality, necessitating the investigation of molecular mechanisms underlying gastric cancer progression. This study focuses on BRD4 expression and its correlation with miR-26a-3p, DLG5-AS1, and JMJD1C-AS1 lncRNAs in gastric cancer. Analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets revealed significant upregulation of BRD4 in gastric cancer tissues compared to normal tissues, correlating negatively with miR-26a-3p and positively with DLG5-AS1 and JMJD1C-AS1 lncRNAs. Quantitative RT-PCR confirmed these findings in 25 gastric cancer tissue samples and 25 normal samples. BRD4's overexpression was associated with reduced survival rates and older patient age. MiR-26a-3p, a known tumor suppressor, showed decreased expression in gastric cancer tissues, with ROC analysis suggesting it, alongside BRD4, as a potential diagnostic biomarker. Additionally, bioinformatics predicted miR-26a-3p’s interaction with BRD4 mRNA. Upregulated lncRNAs DLG5-AS1 and JMJD1C-AS1 likely act as competing endogenous RNAs, sponging miR-26a-3p, thus promoting BRD4 dysregulation. These lncRNAs have not been previously studied in gastric cancer. The findings propose a novel BRD4/lncRNA/miRNA regulatory axis in gastric cancer, highlighting the potential of BRD4, DLG5-AS1, and JMJD1C-AS1 as biomarkers for early diagnosis. Further studies with larger sample sizes and in vivo and in vitro experiments are needed to elucidate this regulatory mechanism’s role in gastric cancer progression.

Deregulation of mitochondrial gene expression in cancer: mechanisms and therapeutic opportunities.

"Reprogramming of energy metabolism" was first considered an emerging hallmark of cancer in 2011 by Hanahan & Weinberg and is now considered a core hallmark of cancer. Mitochondria are the hubs of metabolism, crucial for energetic functions and cellular homeostasis. The mitochondrion's bacterial origin and preservation of their own genome, which encodes proteins and RNAs essential to their function, make them unique organelles. Successful generation of mitochondrial gene products requires coordinated functioning of the mitochondrial 'central dogma,' encompassing all steps necessary for mtDNA to yield mitochondrial proteins. Each of these processes has several levels of regulation, including mtDNA accessibility and protection through mtDNA packaging and epigenetic modifications, mtDNA copy number through mitochondrial replication, mitochondrial transcription through mitochondrial transcription factors, and mitochondrial translation through mitoribosome formation. Deregulation of these mitochondrial processes in the context of cancers has only recently been appreciated, with most studies being correlative in nature. Nonetheless, numerous significant associations of the mitochondrial central dogma with pro-tumor phenotypes have been documented. Several studies have even provided mechanistic insights and further demonstrated successful pharmacologic targeting strategies. Based on the emergent importance of mitochondria for cancer biology and therapeutics, it is becoming increasingly important that we gain an understanding of the underpinning mechanisms so they can be successfully therapeutically targeted. It is expected that this mechanistic understanding will result in mitochondria-targeting approaches that balance anticancer potency with normal cell toxicity. This review will focus on current evidence for the dysregulation of mitochondrial gene expression in cancers, as well as therapeutic opportunities on the horizon.

Methylation-related differentially expressed genes as potential prognostic biomarkers for cervical cancer

AimTo discover novel methylation-related differentially expressed genes (MRDEGs) for cervical cancer, with a focus on their potential for early diagnosis and prognostic assessment. Materials & methodsWe integrated data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. TCGA-MRDEGs were identified by analyzing differentially methylated genes (DMGs) and their correlation with gene expression. We examined GEO datasets GSE39001, GSE9750, and GSE46306 for GEO-MRDEGs. Overlapping MRDEGs were subjected to overall survival (OS) analysis to identify prognostic markers. The expression and methylation levels of these genes were validated in a total of 30 tissue samples, comprising 20 from cervical cancer patients and 10 from normal cervical tissues, using qRT-PCR and MassARRAY EpiTYPER Assay. ResultsA total of 314 TCGA-MRDEGs and 40 GEO-MRDEGs were identified. Intersection analysis yielded 10 overlapping MRDEGs. Notably, NOVA1, GSTM5, TRHDE, and CXCL12 were found to have reduced expression and increased methylation in cervical cancer, which correlated with poor prognosis. The methylation status and expression levels of these genes were confirmed in tissue specimens. ConclusionWe identified four MRDEGs as potential prognostic biomarkers for cervical cancer. Their clinical utility is highlighted, but further validation in larger cohorts is required to establish their clinical significance.

Oncogenic transcription factors instruct promoter-enhancer hubs in individual triple negative breast cancer cells.

Sequencing-based mapping of ensemble pairwise interactions among regulatory elements support the existence of topological assemblies known as promoter-enhancer hubs or cliques in cancer. Yet, prevalence, regulators, and functions of promoter-enhancer hubs in individual cancer cells remain unclear. Here, we systematically integrated functional genomics, transcription factor screening, and optical mapping of promoter-enhancer interactions to identify key promoter-enhancer hubs, examine heterogeneity of their assembly, determine their regulators, and elucidate their role in gene expression control in individual triple negative breast cancer (TNBC) cells. Optical mapping of individual SOX9 and MYC alleles revealed the existence of frequent multiway interactions among promoters and enhancers within spatial hubs. Our single-allele studies further demonstrated that lineage-determining SOX9 and signaling-dependent NOTCH1 transcription factors compact MYC and SOX9 hubs. Together, our findings suggest that promoter-enhancer hubs are dynamic and heterogeneous topological assemblies, which are controlled by oncogenic transcription factors and facilitate subtype-restricted gene expression in cancer.

Cinobufagin treatments suppress tumor growth by enhancing the expression of cuproptosis-related genes in liver cancer.

Cuproptosis is a recently discovered form of regulated cell death triggered by excess copper (Cu) strongly influenced by the import, export, and intracellular utilization of Cu known as Cu homeostasis. Cinobufagin (CB) is a well-known Chinese medicine for its apoptosis-inducing role; however, its function on cuproptosis is poorly understood. To evaluate the effect of CB on inducing cell death through cuproptosis, we used RNA-seq data of HepG2-treated cells with CB to understand Cuproptosis genes. By using CCK-8 assay, Ross assay, GSH assay, and qRT-PCR, we found that CB could enhance cuproptosis in primary liver cancer cell lines, especially by increasing copper transporters CTR1, CTR2, and LIAS and downregulation of copper efflux transporters ATP7A and ATP7B resulted in increased reactive oxygen species (ROS) production, copper ionophores while reduced intracellular copper chelator glutathione (GSH) synthesis. In conclusion, our findings indicated that CB by increasing cuproptosis-related genes can mediate higher cell cytotoxicity against HepG2 and HUH7 and could provide a new insight into mechanisms of CB as an anti-tumor agent for targeting liver cancer.

Glycolysis-related genes predict prognosis and indicate immune microenvironment features in gastric cancer.

Gastric cancer (GC) is a major contributor to cancer-related mortality. Glycolysis plays a pivotal role in tumor microenvironment (TME) reprogramming. In this research, the functions of glycolysis-associated genes (GRGs) were evaluated to predict the outcome and reveal the characteristics of the immune microenvironment in individuals with stomach cancer. The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) cohort provided gene expression and clinical data for gastric cancer (GC) patients, which were further authenticated using datasets sourced from the Gene Expression Omnibus (GEO). By referencing the Molecular Signatures Database (MSigDB), a total of 326 GRGs were pinpointed. The various subtypes of GC were outlined through consensus clustering, derived from the expression patterns of these GRGs. Utilizing multivariate Cox regression analysis, a multigene risk score model was formulated. Both the CIBERSORT and ESTIMATE algorithms played a pivotal role in assessing the immune microenvironment. To delve into the biological functions of the key genes, wound healing, transwell invasion, and MTT assays were conducted. Based on the expression patterns of GRGs, patients were categorized into two distinct groups: the metabolic subtype, designated as cluster A, and the immune subtype, labeled as cluster B. Patients belonging to cluster B exhibited a poorer prognosis. A prognostic risk score model, formulated upon the expression levels of six key GRGs - ME1, PLOD2, NUP50, CXCR4, SLC35A3, and SRD35A3 - emerged as a viable tool for predicting patient outcomes. The downregulation of CXCR4 notably diminished the glycolytic capacity of gastric cancer (GC) cells, alongside their migratory, invasive, and proliferative capabilities. Intriguingly, despite the adverse prognostic implications associated with both the immune subtype (cluster B) and the high-risk cohort, these groups exhibited a favorable immune microenvironment coupled with elevated expression of immune checkpoint genes. Our investigations revealed a positive correlation between high CXCR4 expression and low ME1 expression with the infiltration of CD8+ T cells, as well as an enhanced responsiveness to treatment with an anti-PD-1 immune checkpoint inhibitor. In this study, we discovered that the expression profiles of GRGs hold the potential to forecast the prognosis of gastric cancer (GC) patients, thereby possibly aiding in clinical treatment decision-making.

T cell receptor clonotype in tumor microenvironment contributes to intratumoral signaling network in patients with colorectal cancer.

Single-cell RNA sequencing (scRNA-seq) has contributed to understanding cellular heterogeneity and immune profiling in cancer. The aim of the study was to investigate gene expression and immune profiling in colorectal cancer (CRC) using scRNA-seq. We analyzed single-cell gene expression and T cell receptor (TCR) sequences in 30 pairs of CRC and matched normal tissue. Intratumoral lymphocytes were measured with digital image analysis. CRC had more T cells, epithelial cells, and myeloid cells than normal colorectal tissue. CRCs with microsatellite instability had more abundant T cells than those without microsatellite instability. Immune cell compositions of CRC and normal colorectal tissue were inversely correlated. CD4 + or CD8 + proliferating T cells, CD4 + effector memory T cells, CD8 + naïve T cells, and regulatory T cells of CRC showed higher TCR clonal expansion. Tumor epithelial cells interacted with immune cells more strongly than normal. T cells, myeloid cells, and fibroblasts from CRCs of expanded T cell clonotypes showed increased expression of genes related to TNF and NFKB signaling and T cell activation. CRCs of expanded T cell clonotypes also showed stronger cellular interactions among immune cells, fibroblasts, and endothelial cells. Pro-inflammatory CXCL and TNF signaling were activated in CRCs of expanded T cell clonotype. In conclusion, scRNA-seq analysis revealed different immune cell compositions, differential gene expression, and diverse TCR clonotype dynamics in CRC. TCR clonality expansion is associated with immune activation through T cell signaling and chemokine signaling. Patients with CRCs of expanded clonotype can be promising candidates for immunotherapy.

Evaluation of the Rock1 and microRNA-148a expression in biopsies collected from patients with Helicobacter pylori induced gastritis

BackgroundHelicobacter pylori infection is one of the most common chronic bacterial infections, especially in developing countries. MicroRNA-148a is involved in the regulation of various genes, including Rock1, which is altered in gastric cancer. Decreased expression of mir-148a leads to tumor metastasis and increased Rock1 gene expression in gastric cancer. This study aimed to investigate the expression of these genes in biopsies collected from patients with H. pylori induced gastritis.MethodsInformed consent forms were gotten from the studied patients with gastritis who needed endoscopy. Gastric biopsies were taken by a gastroenterologist from patients with inflammation. Rapid urease test, stool antigen detection, and histopathological staining were used to determine the H. pylori infected patients. Real time PCR was used to evaluate the miRNA and Rock1 expression levels.ResultsThe Rock1 expression level in biopsies that were positive for H. pylori was significantly increased compared to our control gastritis group that were H. pylori-negative, but the results were not statistically significant. Moreover, the mir-148a expression level in H. pylori-positive patients with gastritis was increased compared to our control group. However, the results were not statistically significant. We did not find a significant relation between the expression levels of Rock1 and mir-148a in samples with gastritis infected or uninfected by H. pylori. This result may be due to the small sample size.ConclusionWe suggest that this test should be carried out with more samples, and the comparison should be done between biopsies with inflammation and no inflammation in a patient.

Discovery of an 8-oxoguanine regulator PCBP1 inhibitor by virtual screening and its synergistic effects with ROS-modulating agents in pancreatic cancer.

Introduction: Drugs that target reactive oxygen species (ROS) metabolism have progressed the treatment of pancreatic cancer treatment, yet their efficacy remains poor because of the adaptation of cancer cells to high concentration of ROS. Cells cope with ROS by recognizing 8-oxoguanine residues and processing severely oxidized RNA, which make it feasible to improve the efficacy of ROS-modulating drugs in pancreatic cancer by targeting 8-oxoguanine regulators. Methods: Poly(rC)-binding protein 1 (PCBP1) was identified as a potential oncogene in pancreatic cancer through datasets of The Cancer Genome Atlas (TCGA) project and Gene Expression Omnibus (GEO). High-throughput virtual screening was used to screen out potential inhibitors for PCBP1. Computational molecular dynamics simulations was used to verify the stable interaction between the two compounds and PCBP1 and their structure-activity relationships. In vitro experiments were performed for functional validation of silychristin. Results: In this study, we identified PCBP1 as a potential oncogene in pancreatic cancer. By applying high-throughput virtual screening, we identified Compound 102 and Compound 934 (silychristin) as potential PCBP1 inhibitors. Computational molecular dynamics simulations and virtual alanine mutagenesis verified the structure-activity correlation between PCBP1 and the two identified compounds. These two compounds interfere with the PCBP1-RNA interaction and impair the ability of PCBP1 to process RNA, leading to intracellular R loop accumulation. Compound 934 synergized with ROS agent hydrogen peroxide to strongly improve induced cell death in pancreatic cancer cells. Discussion: Our results provide valuable insights into the development of drugs that target PCBP1 and identified promising synergistic agents for ROS-modulating drugs in pancreatic cancer.

Characterization of SUSD3 as a novel prognostic biomarker and therapeutic target for breast cancer.

Breast cancer (BC) remains a significant global health challenge, contributing substantially to cancer-related deaths worldwide. Its prevalence and associated death rates remain alarmingly high, highlighting the persistent public health burden. The objective of this study was to systematically examine the involvement of SUSD3 (Sushi Domain-Containing 3) in BC, highlighting its crucial role in the pathogenesis and progression of this disease. BC-related gene microarray data, along with corresponding clinicopathological information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Leveraging TIMER and HPA databases, we conducted comparative analyses to evaluate SUSD3 expression in BC. We then analyzed the association between SUSD3 and clinical traits, as well as the prognostic value of SUSD3. SUSD3-related differential expression genes (DEGs) were sent for analysis utilizing GO, KEGG, and GSEA. We utilized SUSD3 mRNA expression to assess immune cells' scores in BC tissues calculated by single-sample enrichment analyses based on "CIBERSORT" R package. Drug sensitivity analysis was used to screen potential drugs sensitive to SUSD3. R software was used for statistical analyses and graphical representation of the data. Our findings confirmed a significant upregulation of SUSD3 expression in BC, which correlated with a favorable prognosis. Clinical correlation analysis further emphasized the strong association between SUSD3 expression and key clinical parameters like estrogen receptor (ER) status, progesterone receptor (PR) status, stage, and T classification in breast cancer. Univariate and multivariate Cox regression analyses showed that SUSD3 could be used as an independent prognostic factor for BC. Differentially expressed genes (DEGs) co-expressed with SUSD3 were significantly associated with various biological processes, such as the cell cycle, DNA replication, p53 signaling pathway, cancer-related pathways, and Wnt signaling pathway, as indicated by gene set enrichment analysis (GSEA). Furthermore, our analysis demonstrated that SUSD3 generally exhibited negative associations with immune modulators. Drug sensitivity analysis revealed positive correlations between SUSD3 and the efficacy of Fulvestrant, Raloxifene, and Fluphenazine. The research emphasizes the significance of SUSD3 as a potential marker for BC, providing insights into the underlying molecular mechanisms implicated in tumorigenesis. SUSD3 holds promise in helping the classification of breast cancer pathological groups, predicting prognosis, and facilitating targeted therapy.

Identification and validation of genes associated with prognosis of cisplatin-resistant ovarian cancer

PurposeTo investigate the role of prognostic genes related to cisplatin resistance in ovarian cancer during disease progression.MethodThe gene expression profile of the NCI-60 cell line was acquired through comprehensive analysis of the GEO database accession GSE116439. We performed a thorough analysis of gene expression differences in samples from seven individuals exposed to cisplatin concentrations of 0 nM compared to seven samples exposed to 15000 nM over a 24-h period. Key genes were initially identified through LASSO regression, followed by their enrichment through differential gene function analysis (GO) and pathway enrichment analysis (KEGG). Subsequently, a prognostic risk model was established for these key genes. The prognostic model's performance was assessed through K-M survival curves and ROC curves. To examine the variance in immune cell infiltration between the high and low-risk groups, CIBERSORTx analysis was employed. Finally, validation of prognostic gene expression in cisplatin-resistant ovarian cancer was carried out using clinical samples, employing RT-qPCR and Western Blot techniques.ResultsA total of 132 differential genes were found between cisplatin resistance and control group, and 8 key prognostic genes were selected by analysis, namely VPS13B, PLGRKT, CDKAL1, TBC1D22A, TAP1, PPP3CA, CUX1 and PPP1R15A. The efficacy of the risk assessment model derived from prognostic biomarkers, as indicated by favorable performance on both Kaplan–Meier survival curves and ROC curves. Significant variations in the abundance of Macrophages M1, T cells CD4 memory resting, T cells follicular helper, and T cells gamma delta were observed between the high and low-risk groups. To further validate our findings, RT-qPCR and Western Blot analyses were employed, confirming differential expression of the identified eight key genes between the two groups.ConclusionVPS13B, TBC1D22A, PPP3CA, CUX1 and PPP1R15A were identified as poor prognostic genes of cisplatin resistance in ovarian cancer, while PLGRKT, CDKAL1 and TAP1 were identified as good prognostic genes. This offers a novel perspective for future advancements in ovarian cancer treatment, suggesting potential avenues for the development of new therapeutic targets.

DCTPP1 Expression as a Predictor of Chemotherapy Response in Luminal A Breast Cancer Patients.

Breast cancer (BRCA) remains a significant global health challenge due to its prevalence and lethality, exacerbated by the development of resistance to conventional therapies. Therefore, understanding the molecular mechanisms underpinning chemoresistance is crucial for improving therapeutic outcomes. Human deoxycytidine triphosphate pyrophosphatase 1 (DCTPP1) has emerged as a key player in various cancers, including BRCA. DCTPP1, involved in nucleotide metabolism and maintenance of genomic stability, has been linked to cancer cell proliferation, survival, and drug resistance. This study evaluates the role of DCTPP1 in BRCA prognosis and chemotherapy response. Data from the Cancer Genome Atlas Program (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) repositories, analyzed using GEPIA and Kaplan-Meier Plotter, indicate that high DCTPP1 expression correlates with poorer overall survival and increased resistance to chemotherapy in BRCA patients. Further analysis reveals that DCTPP1 gene expression is up-regulated in non-responders to chemotherapy, particularly in estrogen receptor (ER)-positive, luminal A subtype patients, with significant predictive power. Additionally, in vitro studies show that DCTPP1 gene expression increases in response to 5-fluorouracil and doxorubicin treatments in luminal A BRCA cell lines, suggesting a hypothetical role in chemoresistance. These findings highlight DCTPP1 as a potential biomarker for predicting chemotherapy response and as a therapeutic target to enhance chemotherapy efficacy in BRCA patients.

Vasculogenic mimicry-related gene prognostic index for predicting prognosis, immune microenvironment in clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is a highly aggressive cancer associated with higher death rates. However, traditional anti-angiogenic therapies have limited effectiveness due to drug resistance. Vascular mimicry (VM) provides a different way for tumors to develop blood vessels without relying on endothelial cells or angiogenesis. However, the intricate mechanisms and interplay between it and the immune microenvironment in ccRCC remain unclear. MethodsA PubMed and GeneCards literature review was conducted to identify VM-related genes (VMRGs). VMRGs expression profiles were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), developing a novel VM risk score model and nomogram for ccRCC. The EBI ArrayExpress database (the validation set) was obtained to validate the prognostic model. The relationship between VMRGs risk score clinical characteristics and immune infiltration was investigated. Finally, the expression of six model VMRGs was validated using single-cell analysis, GEPIA, Human Protein Atlas (HPA), and quantitative Real-time PCR (qRT-PCR). ResultsCox regression analysis and nomogram identified L1CAM, TEK, CLDN4, EFNA1, SERPINF1, and MALAT1 as independent prognostic risk factors, which could be used to stratify the ccRCC population into two risk groups with distinct immune profiles and responsiveness to immunotherapy. The results of single-cell analysis, GEPIA, HPA, and qRT-PCR validated the model genes’ expression. ConclusionsOur novel findings constructed a convenient and reliable 6 gene signatures as potential immunologic and prognostic biomarkers of VM in ccRCC.

FASTKD1 as a diagnostic and prognostic biomarker for STAD: Insights into m6A modification and immune infiltration.

Fas-activated serine/threonine kinase domain 1 (FASTKD1), a known modulator of mitochondrial-mediated cell death and survival processes, has garnered attention for its potential role in various biological contexts. However, its involvement in gastric cancer remains unclear. Thus, the present study aimed to investigate the relationship between FASTKD1 expression and key factors, including clinicopathological characteristics, immune infiltration and m6A modification in stomach adenocarcinoma (STAD). The expression of FASTKD1 was analyzed in STAD and normal adjacent tissues to assess its association with clinicopathological characteristics and survival prognosis. Data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used in this study. Additionally, the findings were validated through immunohistochemical staining. Co-expression analysis of FASTKD1 was performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment analysis, Gene Set Enrichment Analysis (GSEA) and LinkedOmics database analysis. An in-depth analysis was conducted using databases, such as Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), GEO and TCGA to explore the potential correlation between FASTKD1 expression and immune infiltration and m6A modification in STAD. The results revealed that FASTKD1 was significantly upregulated across different tumor types, including STAD. Notably, FASTKD1 was able to distinguish between tumor and normal tissue samples with accuracy. Furthermore, the expression levels of FASTKD1 were significantly associated with clinical stage and survival. Through GO/KEGG enrichment analysis and GSEA, it was revealed that the genes co-expressed with FASTKD1 were active in a variety of biological processes. Within the TIMER, GEPIA and TCGA databases, a notable inverse correlation was observed between FASTKD1 expression and the abundance of immune cell subsets. Notably, significant correlations were established between FASTKD1 and m6A modification genes, YTHDF1 and LRPPRC, in both TCGA and GEO datasets. In conclusion, FASTKD1 may serve a significant role in m6A modification and immune infiltration processes, making it a potentially valuable diagnostic and prognostic biomarker in STAD.