Hepatocellular carcinoma (HCC), a prevalent and highly malignant form of liver cancer, poses significant global health challenges. Previous studies have suggested that alterations in cleavage and polyadenylation specificity factors (CPSFs) play a role in the development and prognosis of HCC. Despite these insights, a thorough evaluation of CPSFs' expression levels, prognostic value and association with immune infiltration in HCC is lacking. To address this gap, the present study conducted a systematic analysis leveraging multiple bioinformatics databases to elucidate the functions of CPSFs in HCC. To comprehensively investigate the role of CPSFs in HCC, a diverse array of bioinformatics tools and publicly accessible datasets were utilized. The present study investigated the gene expression patterns, clinicopathological correlations, and diagnostic and prognostic capabilities of CPSFs. Furthermore, genetic variations, co-expression networks and the role of CPSFs in immune cell infiltration and tumor-related pathways were examined. To elucidate the biological functions of CPSF-associated genes, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were integrated. For experimental validation, reverse transcription-quantitative polymerase chain reaction was used to assess gene expression and the Cell Counting Kit-8 assay was utilized to evaluate the effects of CPSFs on HCC cell proliferation. Our analysis offers valuable insights into the molecular mechanisms through which CPSFs contribute to HCC progression. The current findings suggest that CPSFs, particularly CPSF1, CPSF3, CPSF4 and CPSF6, exhibit significant transcriptional upregulation in HCC, with their overexpression closely tied to advanced tumor progression. These CPSFs showed diagnostic and prognostic significance in HCC. Additionally, CPSF expression was associated with immune cell infiltration and activation status. Functional enrichment analysis indicated that CPSF1, CPSF3, CPSF4, CPSF6 and CPSF7 are involved in cancer-related signaling pathways, highlighting their role in tumor immune modulation. Experimental validation demonstrated that the expression of CPSF3 and CPSF7 was notably greater in the HCC cell lines than in the normal liver cells. Knockdown of CPSF3 and CPSF7 inhibited HCC cell proliferation, suggesting their potential oncogenic roles. This research offers an in-depth evaluation of the expression patterns, prognostic relevance and immune modulation-related functions of CPSFs in HCC. The observed upregulation of CPSFs in HCC, coupled with their association with poor clinical outcomes and immune system activation, highlights their potential as prognostic indicators. Nonetheless, additional experimental studies are needed to fully elucidate the molecular mechanisms and clinical significance of CPSFs in HCC.

Caspases (CASPs) are attractive targets for cancer therapy. Many prognostic models based on gene signatures include genes from the CASPs family in diffuse glioma. CASP3, CASP4 and CASP6 in glioma have been studied individually. However, specialized comprehensive analysis of the roles of CASPs family in glioma is lacking. Therefore, this study utilized bioinformatics methods to investigate this issue. CASP1-10 expressionlevels were significantly up-regulated in LGG and GBM and glioma, and varied significantly across different clinical subgroups of glioma and LGG and various cell types, and most of CASP1-10 members showed significant differences in recurrence status of LGG. 10 signatures (CASP1-10) were associated with poor overall survival (OS) in glioma and LGG and GBM. However, pan-cancer survival analysis showed that CASP1-10 were associated with the prognosis of LGG, but not GBM. CASP1-10 were related to poor prognosis of glioma and LGG, except for CASP9, which was the opposite of a protective factor. CASP1-10 were independent prognostic factors for OS in glioma and LGG, except for CASP5, and also for recurrence-free survival (RFS) in LGG. Most of CASP1-10 were also independent prognostic factors for disease-specific survival (DSS) and progression-free interval (PFI) and had diagnostic value in glioma and LGG. Genetic alterations of CASP1-10 genes set were associated with poor prognosis in LGG. CASP1-10 were involved in immune infiltration and programmed cell death in glioma and LGG and GBM, and might promote the apoptosis of immune cells. Compared to GBM, CASP1-10 had a more significant impact on the prognosis, cancer-related pathways, and immune infiltration in LGG, indicating that CASP1-10 might play important roles in the recurrence and progression of LGG, and might be promising therapeutic targets for LGG. Therefore, it is speculated that natural caspase inhibitor p35 may be a promising drug for the treatment of glioma, especially for LGG.

One of the most common and prevalent cancers is laryngeal squamous cell carcinoma (LSCC), which poses a great threat to the life and health of the patient. Nonetheless, it has been demonstrated that ubiquitination is crucial for the development and course of LSCC. Therefore, it is particularly important to identify biomarkers for ubiquitination-related genes (UbRGs) in LSCC.

Differentially expressed genes (DEGs) in the LSCC versus controls were obtained by differential expression analysis. Also, key modular genes associated with LSCC were obtained using weighted gene co-expression network analysis (WGCNA). Next, DEGs, key module genes, and UbRGs were taken to intersect to obtain candidate genes. And then machine algorithms were to screen potential biomarkers, further their diagnostic value were analyzed and validated. Then, therapeutic agents for biomarkers were predict. In addition, the regulatory networks of the biomarkers were mapped. The expression levels of biomarkers were detected in clinical samples using reverse transcription-quantitative PCR (RT-qPCR).

A total of eight candidate genes were acquired by the overlap 1,911 DEGs, the key modular genes of WGCNA, and 1,393 UbRGs. A sum of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) were identified by two machine learning, then these four biomarkers were validated in GSE127165 and the expression trend was consistent with TCGA-LSCC, they were recorded as biomarkers. Moreover, the accuracy of the biomarkers in predicting clinical aspects of LSCC was confirmed by the receiver operating characteristic (ROC) curves. Subsequently, cancers such as malignant neoplasms, colorectal cancers, tumors, and primary malignant neoplasms were significantly associated with the biomarkers, which further suggests that these four biomarkers were strongly associated with cancer. Meanwhile, the drugs garcinol, cocaine, and triazolam, among others, used for LSCC treatment were predicted. Finally, transcription factors (TFs) (BRD4, MYC, AR, and CTCF) were predicted to regulate the biomarkers. RT-qPCR assays illustrated that the expression trends of KAT2B, LNX1 and NBEAL2 remained consistent with the dataset.

The identification of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) associated with UbRGs could ultimately serve as a predictive clinical diagnosis of LSCC and provide insight into the molecular mechanisms of LSCC.

Regulatory T cells (Tregs) are critical for maintaining the stability of the immune system and facilitating tumor escape through various mechanisms. Resting T cells are involved in cell-mediated immunity and remain in a resting state until stimulated, while effector T cells promote immune responses. Here, we investigated the roles of two gene signatures, one for resting Tregs (FOXP3 and IL2RA) and another for effector Tregs (FOXP3, CTLA-4, CCR8 and TNFRSF9) in pan-cancer. Using data from The Cancer Genome Atlas (TCGA), The Cancer Proteome Atlas (TCPA) and Gene Expression Omnibus (GEO), we focused on the expression profile of the two signatures, the existence of single nucleotide variants (SNVs) and copy number variants (CNVs), methylation, infiltration of immune cells in the tumor and sensitivity to different drugs. Our analysis revealed that both signatures are differentially expressed across different cancer types, and correlate with patient survival. Furthermore, both types of Tregs influence important pathways in cancer development and progression, like apoptosis, epithelial-to-mesenchymal transition (EMT) and the DNA damage pathway. Moreover, a positive correlation was highlighted between the expression of gene markers in both resting and effector Tregs and immune cell infiltration in adrenocortical carcinoma, while mutations in both signatures correlated with enrichment of specific immune cells, mainly in skin melanoma and endometrial cancer. In addition, we reveal the existence of widespread CNVs and hypomethylation affecting both Treg signatures in most cancer types. Last, we identified a few correlations between the expression of CCR8 and TNFRSF9 and sensitivity to several drugs, including COL-3, Chlorambucil and GSK1070916, in pan-cancer. Overall, these findings highlight new evidence that both Treg signatures are crucial regulators of cancer progression, providing potential clinical outcomes for cancer therapy.

Aberrant expression of APOA1 has been reported in various cancers. However, a comprehensive investigation into its role in cancer is currently lacking.

Online websites and databases such as TIMER2.0, GEPIA2, UALCAN and GSCA were used to investigate the relationship between APOA1 expression and prognostic value, immune infiltration, gene mutations, and drug sensitivity. In addition, in vitro CCK-8 and transwell migration and invasion assays were performed to determine the biological functions of APOA1 in gastric cancer (GC) cells.

The pan-cancer analysis showed that APOA1 is differentially expressed in different cancer types and significantly correlated with tumor stages. A survival analysis revealed that APOA1 predicted a poor prognosis in ACC, KIRC, STAD, and a good prognosis in BRCA, OV, and UCEC. We also found that the most common genetic alteration type of APOA1 was deep deletion, and the DNA methylation level of APOA1 decreased in various cancers. Furthermore, APOA1 expression negatively correlated with immune cells infiltration in cancers, including CD4+ T, CD8+ T, and myeloid dendritic cells. For STAD, GO/KEGG enrichment analysis revealed the possible involvement of APOA1 in cholesterol metabolism and PPAR signaling pathway. Finally, we further performed in vitro experiments to verify that overexpression of APOA1 could promote the proliferation, migration and invasion of GC cells.

The results of this study indicate that APOA1 is a potential tumor prognostic biomarker and immunotherapy target. In addition, APOA1 plays an essential role in the proliferation, migration, and invasion of GC cells by vitro experiments.

The estrogen-related receptor family genes (ERRs), including ESRRA, ESRRB, and ESRRG, have been implicated in a few tumors, exhibiting distinct roles through diverse mechanisms. The purpose of our research is to explore the commonalities and underlying mechanism of ERRs in malignancies from a pan-cancer perspective and to validate the role and mechanisms of ESRRG in gallbladder cancer (GBC).

We leveraged public databases such as TCGA and GTEx to systematically investigate the potential functions of ERRs in malignancies. ESRRG expression was analyzed through immunohistochemical staining in gallbladder cancer and cholecystitis tissues. For functional validation, ESRRG was knocked down in GBC cell lines, followed by CCK-8, colony formation, scratch wound healing, Transwell migration, and invasion assays. Western blot, qPCR, and immunofluorescence were performed to evaluate the relationship between ESRRG, PD-L1, and CD8+ T cells.

Compared to adjacent normal tissues, ESRRA is overexpressed in most tumors, ESRRB is generally underexpressed, and ESRRG exhibits significant expression alterations across various tumors. All three ERRs demonstrate significant prognostic value across different cancers. Notably, the strong associations of ERRs with key immunological features-stromal scores, immune cell infiltration, microsatellite instability (MSI), and tumor mutational burden (TMB)-suggest their involvement in immune evasion and their potential utility in guiding immunotherapy strategies. All three ERRs display a positive correlation with advanced tumor stages in cholangiocarcinoma (CHOL). Specifically, in CHOL, ESRRG expression is closely associated with lymphatic metastasis, poorer overall survival, reduced immune infiltration, elevated PD-L1 expression, epithelial-mesenchymal transition (EMT), and DNA damage response. In GBC tissues, we subsequently confirmed that ESRRG expression positively correlates with pathological staging and PD-L1 expression, while negatively correlating with prognosis and CD8+ T cell infiltration. Knockdown of ESRRG in gallbladder cancer cells results in decreased proliferation, migration, and invasion. Moreover, the expression of PD-L1, MSH2, BRCA1, MMP2, and VIMENTIN decreased with ESRRG knockdown.

Our pan-cancer analysis reveals ERRs as critical regulators of tumor immunity and progression, with ESRRG emerging as a key oncogenic driver in GBC. The mechanistic link between ESRRG and PD-L1/EMT suggests its potential as a therapeutic target to enhance immunotherapy efficacy. These findings underscore the need for tissue-specific targeting strategies for ERR family members in precision oncology.

Transcription initiation factor IIE subunit beta (GTF2E2) is a crucial component of the RNA polymerase II transcription initiation complex. There is a lack of more detailed research on the biological function of GTF2E2 in pan-cancer.

We conducted a comprehensive pan-cancer analysis using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) project. Employing a multi-pronged approach with tools including R, Cytoscape, TISIDB, cBioPortal, STRING, GSCALite, and CancerSEA, we investigated GTF2E2's expression patterns, prognostic value, mutational landscape, functional enrichment, and immunological associations across 33 cancer types. Besides, we further validated the bioinformatic results through in vitro experiments in Uterine corpus endometrial carcinoma (UCEC), including western blotting (WB), cell proliferation assays and transwell. DCFH-DA, C11-BODIPY 581/591 and FeRhoNox-1 probes were performed to identify ferroptosis levels in vitro.

GTF2E2 expression was significantly elevated in most cancers compared to normal tissues, with notable diagnostic potential (AUC > 0.7) in 20 cancer types. GTF2E2 expression varied across molecular and immune subtypes and correlated with tumor stage and patient age in several cancers. Functional enrichment analyses highlighted GTF2E2's involvement in key cancer-related and immunological pathways. Notably, GTF2E2 promoted UCEC progression in vitro, and knockdown of GTF2E2 significantly inhibited the proliferation, migration and invasion of UCEC cells. Compared with the control group, GPX4 expression was down-regulated and ACSL4 expression was up-regulated in the GTF2E2-knockdown group. Knockdown of GTF2E2 also increased the intracellular levels of Fe2+, lipid peroxides (LPOs) and reactive oxygen species (ROS).

Our findings underscore GTF2E2's multifaceted roles in cancer biology, highlighting its potential as a diagnostic biomarker, prognostic indicator, and immunotherapeutic target across various malignancies. This investigation has the potential to contribute significantly to a deeper understanding of the substantial involvement of GTF2E2 in human malignancies, particularly UCEC.

Programmed cell death (PCD) dynamically influences breast cancer (BC) prognosis through interactions with the tumor microenvironment (TME). We investigated 13 PCD patterns to decipher their prognostic impact and mechanistic links to TME-driven outcomes. Our study aimed to explore the complex mechanisms underlying these interactions and establish a prognostic prediction model for breast cancer.

Using TCGA and METABRIC datasets, we integrated single-sample gene set enrichment analysis (ssGSEA), weighted gene co-expression network analysis (WGCNA), and Least Absolute Shrinkage and Selection Operator (LASSO) to explore PCD-TME interactions. Multi-dimensional analyses included immune infiltration, genomic heterogeneity, and functional pathway enrichment.

Our results indicated that high apoptosis and pyroptosis activity, along with low autophagy, correlated with favorable prognosis, which was driven by enhanced anti-tumor immunity, including more M1 macrophage polarization and activated CD8+ T cells in TME. PCD-related genes could promote tumor metastasis and poor prognosis via VEGF/HIF-1/MAPK signaling and immune response, including Th1/Th2 cell differentiation, while new tumor event occurrences (metastasis/secondary cancers) were linked to specific clinical features and gene mutation spectrums, including TP53/CDH1 mutations and genomic instability. We constructed a six-gene LASSO model (BCAP31, BMF, GLUL, NFKBIA, PARP3, PROM2) to predict prognosis and identify high-risk BC patients (for five-year survival, AUC = 0.76 in TCGA; 0.74 in METABRIC). Therein, the high-risk subtype patients demonstrated a poorer prognosis, also characterized by lower microenvironment matrix and downregulated immunocyte infiltration. These six gene signatures also showed prognostic value with significant differential expression in gene and protein levels of BC samples.

Our study provided a comprehensive landscape of the cancer survival difference and related PCD-TME interaction axis and highlighted that high-apoptosis/pyroptosis states caused favorable prognosis, underlying mechanisms closely related with the TME where anti-tumor immunity would be beneficial for patient prognosis. These findings highlighted the model's potential for risk stratification in BC.

The study focuses on the VRAC channel and its significant roles in cancer development. It addresses a research gap by conducting a pan-cancer analysis with multi-omics bioinformatics tools, integrating data from the Human Protein Atlas (HPA) and Genotype-Tissue Expression (GTEx) datasets to examine mRNA expression patterns of its Leucine Rich Repeat Containing 8 (LRRC8) subunits in various tissues and cancers. The study links variations in LRRC8s expression with patient outcomes and includes analyses of DNA and RNA methylation. The study reveals significant correlations between LRRC8s expression and immune cell infiltration, as well as a positive association with cancer-associated fibroblasts and key immune regulators such as major histocompatibility complex (MHCs) and chemokines. Furthermore, the research suggests that LRRC8s are involved in cancer-signalling pathways, which may offer new therapeutic targets. Additionally, a drug sensitivity analysis shows that LRRC8 subunits affect drug responses differently, supporting the use of personalized therapeutic strategies. In conclusion, the study emphasizes the significance of VRAC subunits in cancer biology and suggests their potential as biomarkers and targets in cancer immunotherapy and personalized medicine.

Cholangiocarcinoma (CCA) is an epithelial bile duct cancer frequently found at an advanced stage, leading to poor response to current therapies. Although gemcitabine (GEM) and cisplatin (CIS) are the current gold-standard for treating unresectable CCA, GEM resistance often occurs. To predict the response to GEM, we evaluated chromosomal aberrations using a chromosome microarray, and their association with GEM response by histoculture drug response assay. Our findings revealed principal component analysis and orthogonal partial-least square discriminant analysis cross validated score plot between response and non-response groups were different. Different signature patterns of chromosomes between response and non-response groups analyzed by heatmap analysis identified 34 regions of 15 chromosomes. An increased signal in responders and a decreased signal in non-responders were found in regions 4q32.1, 5q12.3, 10q21.3, 11p11.2, 11q14.2, 16p11.2, 17q22, 21q21.3 and 22q12.3. In contrast, a high signal in non-responders and low signal in responders were seen in regions 2q37.2, 11q14.1, 16q22.3 and 16q23.3. High signal of CDH13 and TENM4 were demonstrated in GEM non-response, while a high CWC27 signal was noted in GEM response. This signature pattern could provide the knowledge to improve a predictive biomarker for GEM response, benefitting for individual CCA patient management and chemotherapeutic selection.

Glioblastoma is an aggressive cancer that affects the brain. The Homeobox B and D (HOXB/D) family has been linked to tumor progression, but their exact mechanism remains unclear.

This study aimed to identify critical HOXB/D family members associated with glioblastoma and analyze their expression in glioblastoma using the GEPIA2 database. The study also assessed genetic alterations, their related transcription factors, miRNAs, gene-gene interactions, and correlations between their expression and immune infiltration using databases like cBioPortal, miRNet, GeneMANIA, and GSCA.

We showed that HOXB2/3/7 and HOXD3/8/9/10/11/13 expression was higher in glioblastoma samples compared to normal samples. Increased expression of HOXB2/5/8/9/13 was associated with negative effects on overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS), while overexpression of HOXB2/5/9 was linked to inferior PFS. Heightened levels of HOXD4/9, HOXD9/11, and HOXD9/10/11 expression in glioblastoma patients were correlated with unfavorable outcomes in terms of OS, DSS, and PFS. HOXB/D genes were related to 20 different genes, mainly enriched in the Activation of HOX Genes During Differentiation R-HSA-5619507 pathway. Immune cells were linked to specific genes in glioblastoma, with HOXB2 and HOXD3 expression potentially causing resistance to Methotrexate and Z-LLNle-CHO, HOXB7 indicating sensitivity to Lapatinib but resistance to 18 other small molecules, HOXD8 leading to resistance against 5 small molecules, and upregulated HOXD9, HOXD10, and HOXD13 suggesting sensitivity to 2, 4, and 9 small molecules, respectively.

Taken together, we showed contribution of HOXB and HOXD genes in the carcinogenic processes and proposed them as possible targets for treatment options.

Kidney renal clear cell carcinoma (KIRC), the predominant subtype of renal cell carcinoma, poses significant health risks. The rapid progression and resistance to targeted therapies highlight the need for new tumor markers and therapeutic targets. FADS1, part of the fatty acid desaturase family, regulates fatty acid synthesis and participates in lipid metabolism. However, its role in KIRC is not well-studied.

The study utilized bioinformatics analysis through the TCGA database and other platforms to identify FADS1 expression levels in KIRC. Twenty pairs of KIRC clinical tissue samples were used for qPCR verification. Meanwhile, eight pairs of KIRC clinical tissue samples were used for Western blot verification. Conduct statistical evaluation, including Wilcoxon rank sum test and Kaplan-Meier analysis, to explore the correlation between FADS1 expression and clinical pathological features and immune infiltration. In addition, in vitro experiments were conducted to confirm the biological function of FADS1.

The findings indicated that FADS1 is highly expressed in KIRC and contributes to tumor development. FADS1's role in lipid metabolism leads to lipid accumulation within tumor cells, which may influence the occurrence and progression of KIRC. TIMER analysis revealed a correlation between FADS1 expression and the infiltration levels of various immune cells, indicating its potential role in modulating immune characteristics.

FADS1 could serve as a prognostic biomarker associated with immunity in KIRC, highlighting its potential as a diagnostic and therapeutic target. The study underscores the importance of further research into FADS1's role in lipid metabolism and immune infiltration to develop effective therapeutic strategies.

Lysyl oxidases (LOX/LOXL1-4) are crucial for cancer progression, yet their transcriptional regulation, potential therapeutic targeting, prognostic value and involvement in immune regulation remain poorly understood. This study comprehensively evaluates LOX/LOXL expression in cancer and highlights cancer types where targeting these enzymes and developing LOX/LOXL-based prognostic models could have significant clinical relevance.

We assessed the association of LOX/LOXL expression with survival and drug sensitivity via analyzing public datasets (including bulk and single-cell RNA sequencing data of six datasets from Gene Expression Omnibus (GEO), Chinese Glioma Genome Atlas (CGGA) and Cancer Genome Atlas Program (TCGA)). We performed comprehensive machine learning-based bioinformatics analyses, including unsupervised consensus clustering, a total of 10 machine-learning algorithms for prognostic prediction and the Connectivity map tool for drug sensitivity prediction.

The clinical significance of the LOX/LOXL family was evaluated across 33 cancer types. Overexpression of LOX/LOXL showed a strong correlation with tumor progression and poor survival, particularly in glioma. Therefore, we developed a novel prognostic model for glioma by integrating LOX/LOXL expression and its co-expressed genes. This model was highly predictive for overall survival in glioma patients, indicating significant clinical utility in prognostic assessment. Furthermore, our analysis uncovered a distinct LOXL2-overexpressing malignant cell population in recurrent glioma, characterized by activation of collagen, laminin, and semaphorin-3 pathways, along with enhanced epithelial-mesenchymal transition. Apart from glioma, our data revealed the role of LOXL3 overexpression in macrophages and in predicting the response to immune checkpoint blockade in bladder and renal cancers. Given the pro-tumor role of LOX/LOXL genes in most analyzed cancers, we identified potential therapeutic compounds, such as the VEGFR inhibitor cediranib, to target pan-LOX/LOXL overexpression in cancer.

Our study provides novel insights into the potential value of LOX/LOXL in cancer pathogenesis and treatment, and particularly its prognostic significance in glioma.

Endometrial cancer (EC) is a complex gynecologic malignancy that requires a deeper understanding of its molecular basis to improve therapeutic strategies. In this study, we investigated the role of fatty acid (FA) reprogramming in the progression of EC. We analyzed FA profiles to identify the stage-specific changes and gene expression profiles of key enzymes involved in FA synthesis, desaturation, elongation, transport, and oxidation at different stages of EC. Our results show that EC tissues have lower levels of saturated FA and branched-chain FA, higher levels of very long-chain FA, n-3 polyunsaturated FA (PUFA), and monounsaturated FA, with the exception of myristoleic acid. The differences in n-6 PUFA were inconsistent. Gene expression analysis revealed the upregulation of key enzymes controlling de novo FA synthesis, including ACACA, FASN, SCD1, and ELOVL1. In contrast, the expression of genes related to FA transport in the cell and β-oxidation was downregulated. The expression of some genes related to PUFA metabolism was upregulated, while others were downregulated. These results demonstrate a reprogramming of lipid metabolism in EC tissues and suggest potential targets for novel therapeutic interventions in EC.

Nod-like receptor family pyrin domain containing 1 (NLRP1) serves as the central component of the inflammasome complex and has emerged as a potential contributor to cancer development. Despite accumulating evidence, a comprehensive assessment of NLRP1 across various cancer types has yet to be undertaken.

Several databases have evaluated NLRP1 expression across various cancer types in The Cancer Genome Atlas (TCGA). Additionally, studies have investigated the correlation between NLRP1 and various survival metrics, infiltration of cancer-associated fibroblasts, genetic alterations, drug sensitivity, and promoter methylation. Furthermore, research has explored the potential roles of NLRP1 and its interactions with other proteins.

Our analysis revealed decreased expression of NLRP1 in BLCA, BRCA, KICH, LUAD, LUSC, PRAD, and UCEC tumor tissues compared to normal tissues. We identified a significant correlation between NLRP1 expression and various cancer survival parameters, genetic mutations, and immune infiltration of cancer-associated fibroblasts. Furthermore, we observed that NLRP1 expression is regulated by promoter DNA methylation in ESCA. Abnormal expression of NLRP1 was associated with decreased sensitivity to multiple anti-tumor drugs and small compounds. NLRP1 was found to be involved in pathways associated with T cell receptors and chemokines.

Reduced NLRP1 expression contributes to cancer progression and holds potential as a crucial biomolecular marker for diagnostic, prognostic, and personalized therapeutic interventions across different malignancies.

Protein Tyrosine Phosphatase Non-Receptor Type 6 (PTPN6) plays a crucial regulatory role in cellular processes and has been implicated in oncogenesis. This pan-cancer analysis aimed to elucidate PTPN6's involvement across various cancer types, with a particular emphasis on its association with tumor immunity. We analyzed PTPN6 expression data from open access databases using various statistical techniques, including survival analysis, genetic heterogeneity analysis, immune profiling, single-cell analysis, drug sensitivity analysis, and protein interaction analysis. We also conducted in vitro experiments utilizing colorectal cancer cell lines to validate PTPN6's functional role. PTPN6 exhibited distinct expression patterns across cancers, and its prognostic significance was apparent in several cancer types, particularly in glioblastoma, sarcoma, and melanoma. We observed correlations between PTPN6 and immune genes/cell infiltration in these cancers, suggesting a potential role in modulating the tumor immune microenvironment. Single-cell analysis revealed that PTPN6 is predominantly localized in macrophages, B cells, and dendritic cells within the tumor microenvironment, implying its involvement in regulating immune cell function. Enrichment analysis highlighted PTPN6's role in immune-related pathways. Drug sensitivity analysis identified specific drugs, including PAC-1, SNX-2112, BELINOSTAT, VORINOSTAT, TPCA-1, and PHA-893,888, whose efficacy may be influenced by PTPN6 expression. Knocking down PTPN6 expression inhibited the proliferation and migration of colorectal cancer cells in vitro, confirming its oncogenic role in this cancer type. This pan-cancer analysis establishes PTPN6's multifaceted influence on tumor immunity and its potential as a biomarker and therapeutic target.

Breast cancer (BC) is the leading cancer among women globally, which has the highest incidence and mortality rate in over a hundred countries. This study was intended to discover a new prognostic biomarker, facilitating personalized treatment approaches.

RNA sequencing data from The Cancer Genome Atlas database and Gene Expression Omnibus database were utilized to download to evaluate expression levels and prognostic significance of Keratin 14 (KRT14). Methylation of KRT14 was also assessed. The CIBERSORT and single-sample gene set enrichment analysis algorithms were applied to explore the connection between KRT14 and the tumor microenvironment. Primary drugs' sensitivity and potential small molecule therapeutic compounds were analyzed through the "pRRophetic" R package and the Connectivity Map. The prognostic value of KRT14 was additionally corroborated through a comparison of protein levels in peritumoral and cancerous tissues via immunohistochemistry. Moreover, an immune-related prognostic model based on KRT14 was designed to enhance the prediction accuracy for the prognosis of BC patients.

The study found that KRT14 expression was generally downregulated in BC, correlating strongly with poor prognosis. Compared to normal tissues, the methylation level of KRT14 was higher in BC tissues. Lower expression of KRT14 was linked to decreased anti-tumoral immune cells infiltration and increased immunosuppressive cells infiltration. Sensitivity to various key therapeutic drugs was lower in groups with diminished KRT14 expression. In addition, several potential anti-BC small molecule compounds were identified. The model designed in this study significantly enhanced the predictive capability for BC patients compared to predictions based solely on KRT14 expression levels.

Overall, KRT14 was closely correlated with the prognosis in BC, making it a reliable biomarker.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, particularly due to advanced-stage metastasis. P-cadherin (CDH3), a potential therapeutic target, is highly expressed in CRC tissues and associated with poor prognosis and metastasis. However, the mechanisms underlying its role in CRC progression and its translational potential remain poorly understood.

This study integrated multiple public databases (TCGA, HCMDB, UALCAN, HPA, UniProt, cBioPortal, and GEO) to evaluate CDH3 expression, construct a prognostic model, and perform functional and translational analyses. Immunohistochemistry was used to validate CDH3 protein expression in clinical samples. Additional analyses included correlations with clinicopathological parameters, immune infiltration (TIDE, TISIDB), functional enrichment (KEGG, GSEA), drug sensitivity (GSCA), and molecular docking (MOE). Single-cell sequencing (CancerSEA, HPA) was also conducted to explore CDH3's role at the single-cell level.

CDH3 expression was significantly elevated in CRC tissues and correlated with poor prognosis, recurrence, and metastasis. CDH3 expression was associated with the infiltration of resting immune cells, particularly dendritic cells, and enrichment analysis revealed its critical role in CRC metastasis through extracellular matrix (ECM) and local adhesion pathways. Notably, afatinib emerged as a promising candidate for targeting CDH3 via "drug repositioning," a process involving the repurposing of existing drugs for new therapeutic applications.

This study provides novel insights into CDH3's role in CRC metastasis and its potential as a therapeutic target. The translational potential of CDH3, including its integration with immunotherapy and drug repositioning strategies, offers a promising avenue for the treatment of metastatic CRC.

The SUSD3 protein, marked by the Sushi domain, plays a key role in cancer progression, with its expression linked to tumor advancement and patient prognosis. Altered SUSD3 levels could serve as a predictive biomarker for cancer progression. Recognized as a novel susceptibility marker, SUSD3 presents a promising target for antibody-based therapies, offering a potential approach for the prevention, diagnosis, and treatment of breast cancer.

Using the HPA and GeneMANIA platforms, the distribution of SUSD3 protein across tissues was analyzed, while expression levels in tumor and healthy tissues were compared using The Cancer Genome Atlas data. The TISCH and STOmics DB databases facilitated the mapping of SUSD3 expression in different cell types and its spatial relationship with cancer markers. Univariate Cox regression assessed the prognostic significance of SUSD3 expression in various cancers. Genomic alterations of SUSD3 were explored through the cBioPortal database. The potential of SUSD3 as a predictor of immunotherapy response was investigated using TIMER2.0, and GSEA/GSVA identified related biological pathways. Drugs targeting SUSD3 were identified through CellMiner, CTRP, and GDSC databases, complemented by molecular docking studies. In vitro experiments demonstrated that SUSD3 knockdown in breast cancer cell lines significantly reduced proliferation and migration.

SUSD3 expression variations in pan-cancer cohorts are closely linked to the prognosis of various malignancies. In the tumor microenvironment (TME), SUSD3 is predominantly expressed in monocytes/macrophages and CD4+ T cells. Research indicates a strong correlation between SUSD3 expression and key cancer immunotherapy biomarkers, immune cell infiltration, and immunomodulatory factors. To explore its immune regulatory role, StromalScore, ImmuneScore, ESTIMATE, and Immune Infiltration metrics were employed. Molecular docking studies revealed that selumetinib inhibits tumor cell proliferation. Finally, SUSD3 knockdown reduced cancer cell proliferation and migration.

These findings provide valuable insights and establish a foundation for further exploration of SUSD3's role in pan-carcinomas. Additionally, they offer novel perspectives and potential targets for the development of innovative therapeutic strategies in cancer treatment.

Endometriosis-associated ovarian cancer (EAOC), an aggressive form of malignant ovarian neoplasm with origins in endometriosis (EM), has risen to prominence recently. Despite extensive investigation, the precise pathophysiology remains elusive.This article explores new autophagy-related DEG genes between EM and EAOC, and investigates CXCL12's expression and prognostic relevance across pan-cancer.

From Gene Expression Omnibus (GEO), we retrieved gene sequencing data to uncover DEGs. We carried out enrichment analysis, PPI network construction and explored CXCL12's multi-database expression and prognostic significance employing the analytical tools of ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter. Subsequently, assessing the relationship between CXCL12 expression and immune presence in cancer utilizing GEPIA and TIMER. Lastly, CXCL12, IL17, STAT3, and FOXP3 protein expressions were determined through immunohistochemistry analysis in EAOC, EM, and normal endometrial tissues.

Two DEGs were discovered and enrichment analysis indicated virus-cytokine/receptor interactions, chemokine signaling, and cytokine-cytokine receptor interplay as pivotal in EAOC. Notably, cancerous tissues exhibited reduced CXCL12 levels compared with non-malignant tissues across cancers. CXCL12, IL17, STAT3, Th17/Treg ratio, and FOXP3 expressions were also lower in EAOC than EM and normal tissues. Additionally, CXCL12 expression was related to stage, survival, immune subtype, and molecular classification across cancers.

In conclusion, our study implicates CXCL12 and altered Th17/Treg balance in progression from EM to EAOC. CXCL12 emerges as a predictive marker for cancer progression across various tumors and is associated with inflammatory response.

Cancer remains a leading cause of mortality worldwide, with human exonuclease 1 (EXO1) emerging as a key player in DNA repair and damage response pathways, critical for genomic stability and tumor evolution. The aim of this study was to conduct a comprehensive pan-cancer analysis to elucidate the multifaceted roles of EXO1 in various malignancies. Leveraging public databases including TCGA, GTEx, HPA, cBioPortal, UALCAN, STRING, CancerSEA and TISIDB database, we examined EXO1's expression, diagnostic potential, prognostic significance, mutational characteristics, functional roles, and immunological effects across different cancer types. EXO1 was found to be upregulated in multiple cancers, with significant diagnostic potential as indicated by high AUC values in ROC analyses. Elevated EXO1 expression correlated with adverse prognosis in several cancer types, including breast, lung, and pancreatic cancers. Epigenetic alterations, including DNA methylation and mRNA modifications, were also associated with EXO1 expression. Enrichment analyses identified EXO1-related genes involved in DNA recombination, replication, and repair, with GSEA implicating EXO1 in cell cycle regulation and DNA processing pathways. Importantly, immunogenomic analyses revealed EXO1's significant role in modulating the tumor microenvironment, as it is associated with immune cell infiltration and cytokine expression, suggesting its involvement in tumor immunology and immune response regulation. These results implied that EXO1 as a significant biomarker with prognostic and diagnostic potential across various malignancies, suggesting its potential as a therapeutic target and its involvement in immunomodulatory processes within the tumor microenvironment.

The heterogeneity of head and neck squamous cell carcinoma (HNSCC) poses a significant challenge to treatment, underscoring the urgent need for more precise and personalized therapeutic approaches. CD8+ T cells, integral components of the tumor immune microenvironment, have emerged as key targets for immunotherapy. Our research has established a correlation between a decrease in CD8+ T cell score and a poor clinical prognosis, highlighting the prognostic value of this biomarker. By analyzing the gene expression related to CD8+ T cells, we have differentiated HNSCC into cold and hot tumor subtypes, uncovering disparities in clinical prognosis and responses to immunotherapy. Utilizing eight machine learning methods, we identified the key gene OLR1. Single-cell analysis of HNSCC tissues and peripheral blood, along with spatial transcriptome analysis, revealed that OLR1 predominantly functions in macrophages, modulating the immune microenvironment of HNSCC. The expression level of OLR1 may serve as a predictive marker for immunotherapy responses. Moreover, drug sensitivity analysis and molecular docking studies have indicated that simvastatin and pazopanib are potential inhibitors of OLR1. These findings suggest that simvastatin and pazopanib could open up innovative potential therapeutic avenues for individuals with HNSCC.

Previous studies indicate that MAF BZIP Transcription Factor F (MAFF) facilitates ectopic metastasis and tumor cell migration. While its role in neoplasm progression is recognized, a thorough pan-cancer analysis of MAFF's impact remains pending.

MAFF expression across normal and tumor tissues was analyzed using transcriptomic data from Genomic Data Commons (GDC) and UCSC XENA, with protein details from Human Protein Atlas (HPA) and GeneMANIA. Tumor Immune Single-cell Hub (TISCH) and Spatial Transcriptomics Omics DataBase (STOmics DB) identified MAFF expression in the tumor microenvironment (TME). MAFF's prognostic significance and immune-related gene associations were evaluated through univariate Cox regression, TIMER2.0 immune cell infiltration analysis, and Spearman correlation. Critical pathways were identified using Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), while molecular docking explored anticancer agent interactions.

MAFF expression varies across cancers, affecting tumor prognosis, notably in monocytes/macrophages and endothelial cells. Copy number variation (CNV) positively correlates with MAFF expression, while methylation shows inverse correlation. MAFF mutations significantly affect LGG patient prognosis and correlate with immune therapy responses. ESTIMATE and immune profiling linked MAFF to immunosuppression pathways. Molecular docking identified MAFF-targeted drugs, with validated effects on breast cancer and endometrial cancer cell survival and migration in vitro.

Multi-omics analysis identified MAFF as a potential prognostic marker correlating with tumor immunity and microenvironment, suggesting its value for personalized cancer immunotherapy, particularly in BRCA and UCEC.

T cells play diverse roles in cancer immunology, acting as tumor suppressors, cytotoxic effectors, enhancers of cytotoxic T lymphocyte responses and immune suppressors; providing memory and surveillance; modulating the tumor microenvironment (TME); or activating innate immune cells. However, cancer cells can disrupt T cell function, leading to T cell exhaustion and a weakened immune response against the tumor. The expression of exhausted T cell (Tex) markers plays a pivotal role in shaping the immune landscape of multiple cancers. Our aim was to systematically investigate the role of known T cell exhaustion (Tex) markers across multiple cancers while exploring their molecular interactions, mutation profiles, and potential implications for immunotherapy. The mRNA expression profile of six Tex markers, LAG-3, PDCD1, TIGIT, HAVCR2, CXCL13, and LAYN was investigated in pan-cancer. Utilizing data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), The Cancer Proteome Atlas (TCPA), and other repositories, we characterized the differential expression of the Tex markers, their association with the patients' survival outcome, and their mutation profile in multiple cancers. Additionally, we analyzed the effects on cancer-related pathways and immune infiltration within the TME, offering valuable insights into mechanisms of cancer immune evasion and progression. Finally, the correlation between their expression and sensitivity to multiple anti-cancer drugs was investigated extensively. Differential expression of all six markers was significantly associated with KIRC and poor prognosis in several cancers. They also played a potential activating role in apoptosis, EMT, and hormone ER pathways, as well as a potential inhibitory role in the DNA damage response and RTK oncogenic pathways. Infiltration of different immune cells was also found to be associated with the expression of the Tex-related genes in most cancer types. These findings underline that the reviving of exhausted T cells can be used to enhance the efficacy of immunotherapy in cancer patients.

The cell cycle, a critical and intricate biological process, comprises various phases, and its dysregulation plays a pivotal role in tumorigenesis and metastasis. The exploration of cell cycle-based molecular subtypes across pan-cancers, along with the application of synthetic lethality concepts, holds promise for advancing cancer therapies.

A pan-cancer analysis was conducted to assess the cell cycle serves as a reliable signature for classifying molecular subtypes and to understand the potential clinical application of genes as potential drug targets based on synthetic lethality.

Molecular subtypes derived from cell cycle features in certain cancers, particularly kidney-related malignancies, exhibited distinct immune characteristics. Synthetic lethal interactions within the cell cycle pathway were common, with significant genetic interactions further identifying potential drug targets through the exploitation of genetic relationships with key driver genes. Additionally, miRNAs and lncRNAs may influence the cell cycle through miRNA:mRNA interactions and ceRNA networks, thereby enriching the genetic interaction landscape.

These findings suggest that the cell cycle pathway could serve as a promising molecular subtype signature to enhance cancer prognostication and offer potential targets for anticancer drug development through synthetic lethality.

Non-small-cell lung cancer (NSCLC) is one of the most malignant tumors and the leading cause of death from cancer worldwide and is increasing at a massive rate every year. Most NSCLC patients are diagnosed at advanced stages, which is associated with a poor prognosis and a very low 5-year survival rate. Therefore, the purpose of this study is to investigate molecular markers for early diagnosis, prognosis and therapy of NSCLC through the integration of bioinformatics and statistical methods. A total of 93 overlapping differentially expressed genes (oDEGs) were identified between NSCLC and normal samples through Linear Models for Microarray (LIMMA) and Significance Analysis of Microarrays (SAM) methods. Six top-degree oDEGs (CCNA2, CDC6, AURKA, CCNB1, MKI67, and PRC1) were identified as key genes (KGs) through the protein-protein interaction (PPI) network. The predictive accuracy analysis of the identified KGs revealed an accuracy of 96.92 %, with a sensitivity of 91.73 % and a specificity of 98.15 %. KGs associated with 3 molecular functions (MFs), 5 cellular components (CCs), 3 biological processes (BPs), and 4 pathways were identified through FunRich software. Analysis of expression levels using the UALCAN database revealed that KGs are significantly associated with potential early diagnostic biomarkers. Survival analysis using the GEPIA database demonstrated that the KGs possessed strong prognostic power for NSCLC. Finally, seven repurposed candidate drugs ENTRECTINIB, SORAFENIB, CHEMBL1765740, TOZASERTIB, NERVIANO, AZD-1152-HQPA, and SELICICLIB were proposed through molecular docking analysis. In conclusion, the findings of this study have the potential to significantly impact the early diagnosis, prognosis, and treatment of NSCLC.

Few studies revealed that stromal genes regulate the tumor microenvironment (TME). However, identification of key-risk genes in the invasive ductal breast carcinoma-associated stroma (IDBCS) and their associations with the prediction of risk group remains lacking.

This study used the GSE9014, GSE10797, GSE8977, GSE33692, and TGGA BRCA datasets. We explored the differentially expressed transcriptional markers, hub genes, gene modules, and enriched KEGG pathways. We employed a variety of algorithms, such as the log-rank test, the LASSO-cox model, the univariate regression model, and the multivariate regression model, to predict prognostic-risk genes and the prognostic-risk model. Finally, we employed a molecular docking-based study to explore the interaction of sensitive drugs with prognostic-risk genes.

In comparing IDBCS and normal stroma, we discovered 1472 upregulated genes and 1400 downregulated genes (combined ES > 0585 and adjusted p-value < 0.05). The hub genes enrich cancer, immunity, and cellular signaling pathways. We explored the 12 key risk genes (ADAM8, CD86, CSRP1, DCTN2, EPHA1, GALNT10, IGFBP6, MIA, MMP11, RBM22, SLC39A4, and SYT2) in the IDBCS to identify the high-risk group and low-risk group patients. The high-risk group had a lower survival rate, and the constructed ROC curves evaluated the validity of the risk model. Expression validation and diagnostic efficacy revealed that the key stromal risk genes are consistently deregulated in the high-risk group and high stromal samples of the TCGA BRCA cohort. The expression of crucial risk genes, including CD86, CSRP1, EPHA1, GALNT10, IGFBP6, MIA, and RBM22 are associated with drug resistance and drug sensitivity. Finally, a molecular docking study explored several sensitive drugs (such as QL-XII-61, THZ-2-49, AZ628, NG-25, lapatinib, dasatinib, SB590885, and dabrafenib) interacted with these essential risk genes through hydrogen bonds and other chemical interactions.

Exploring essential prognostic-risk genes and their association with the prognosis, diagnostic efficacy, and risk-group prediction may provide substantial clues for targeting the breast cancer stromal key-risk genes.

Endometrial cancer (EC) is a common gynecological malignancy for which polycystic ovarian syndrome (PCOS) has been identified as a significant risk factor. Quercetin, a widely distributed natural flavonoid, has demonstrated potential therapeutic effects in managing both PCOS and EC. However, the specific molecular targets of quercetin in the context of PCOS comorbid with EC (PCOS-EC) remain poorly defined. This study aims to elucidate the therapeutic potential of quercetin for treating PCOS-EC using network pharmacology, molecular dynamics simulations, and in vitro assays. The intersection of 379 PCOS-EC-associated targets with 361 quercetin targets identified 47 potential therapeutic targets of quercetin for PCOS-EC. Gene Ontology enrichment analysis revealed the biological functions, while Kyoto Encyclopedia of Genes and Genomes identified the pathways potentially involved in quercetin's effects against PCOS-EC. Protein-protein interaction network analysis highlighted six overlapping targets, namely, ACTB, AKT1, EGFR, ESR1, PTGS2, and TP53. Molecular docking and molecular dynamics simulations indicated that quercetin bound with high affinity to the hub genes, with AKT1 emerging as a central target. In vitro experiments confirmed that quercetin treatment significantly downregulated AKT expression in EC cells. These findings elucidate potential targets and molecular mechanisms through which quercetin exerts its therapeutic effects.

RGS5, the first gene identified in tumor-resident pericytes, plays a crucial role in angiogenesis. However, its effects on immunology and prognosis in human cancer are still mostly unknown. This study investigates the carcinogenic and immunological roles of RGS5 through a comprehensive pan-cancer analysis.

A standardized pan-cancer dataset for RGS5 was obtained from the public database. R software and relevant packages were utilized to analyze the oncogenic and immunological roles. Clinical samples and cellular experiments were conducted to validate RGS5 expression and its biological function in renal cancer.

Bioinformatics analysis revealed that RGS5 is dysregulated in a variety of human malignancies and is significantly associated with patient prognosis. Additionally, RGS5 expression is closely linked to tumor heterogeneity and stemness indicators across different cancer types. Co-expression of RGS5 with genes involved in MHC, immune activation, immunosuppressive proteins, chemokines, and chemokine receptors was observed in various tumors. High expression of RGS5 predicts a good prognosis in patients with renal cancer. In the renal cancer cohort, RGS5 expression strongly correlated with the distribution of tumor-associated fibroblasts. Silencing RGS5 expression can affect the proliferation, migration, and invasion of renal carcinoma cells.

RGS5 expression in tumors is intricately associated with various clinical features, particularly concerning tumor progression and patient prognosis.

UBA1 and UBA6 are classic ubiquitin-activating E1 enzymes, which participate in the ubiquitination degradation of intracellular proteins and are closely related to the occurrence and development of various diseases and tumors. However, at present, comprehensive analysis has not been used to study the role of UBA family in cancers.

We extracted the relevant data of cancer patients from the TCGA database and studied the relationship between the expression patterns of UBA family and the survival rate, and stage of patients in pan-cancer, especially breast cancer (BRCA), colorectal cancer (COAD), renal cancer (KIRC) and lung adenocarcinoma (LUAD). In addition, we also evaluated their impact on immune infiltration using TISIDB database and R packages.

UBA1 and UBA6 are highly expressed in most cancer types, which may be associated with poor prognosis of patients. This study also investigated their expression had a closely tie with clinical stages in some specific tumors. Furthermore, this study also demonstrated that these genes were closely related to immune score, immune subtypes and tumor infiltrating immune cells.

Our study demonstrated that the differential expression of the UBA family, along with their associated survival landscape and immune infiltration across various cancer types, holds potential as biomarkers linked to cancer immune infiltration. This finding offers a novel perspective for informing the direction of cancer treatment strategies.

Leucine-rich α-2 glycoprotein 1 (LRG1) is a secreted glycoprotein implicated in various diseases, yet its role across multiple cancers remains insufficiently explored. Consequently, we conducted a comprehensive bioinformatics analysis, exploring LRG1 expression patterns, prognostic implications, and potential therapeutic associations in a pan-cancer context. Additionally, we collected gene expression and clinical data from patients with kidney renal clear cell carcinoma (KIRC) from TCGA, conducting gene set enrichment analysis (GSEA) and Cox proportional hazards regression analysis to explore the potential regulatory role of LRG1 in KIRC. Our study revealed that LRG1 expression is upregulated in 18 cancer types, with elevated levels correlating with poor prognostic outcomes in several cancers, notably KIRC. Epigenetic analysis showed hypomethylation in the LRG1 promoter region, potentially contributing to the overexpression of LRG1. Moreover, LRG1 expression was linked to immunotherapeutic responses and altered drug sensitivities, particularly influencing the efficacy of tyrosine kinase inhibitors. In KIRC, high LRG1 expression was associated with the activation of key pathways, including angiogenesis, epithelial-mesenchymal transition (EMT), and hypoxia signalling. We identified key gene pairs interacting with LRG1 in KIRC, including CARD14 and CYP8B1, with CARD14 overexpression correlating with poorer clinical outcomes and CYP8B1 indicating a favourable prognosis. In conclusion, LRG1 emerges as a potential biomarker for prognosis and immunotherapy responsiveness in both pan-cancer and KIRC contexts. This study provides a theoretical foundation for further research on the therapeutic potential of target regulating LRG1 in cancer treatment.

The heterogeneity of pre-eclampsia (PE) complicates its pathogenesis, which remains incompletely understood. Emerging evidence indicates a significant role of metabolism in the pathophysiology of PE. We procured the PE dataset from the Gene Expression Omnibus database and sourced a published compilation of metabolism-related genes, then employed consensus clustering to classify PE subtypes. Subsequently, we examined the relationships of these subtypes with metabolic features and immune infiltration. Feature genes were identified using weighted gene co-expression network analysis (WGCNA) and further scrutinized through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. To refine the selection of feature genes, we applied two machine learning algorithms. Additionally, we assessed the expression profiles of RAG1, RBBP7, RFTN2, SPATA7, and ZNF16 at the single-cell RNA sequencing (scRNA-seq) level. Finally, we validated the diagnostic value and expression of these genes using PE datasets and quantitative reverse transcription-PCR (qRT-PCR) analysis. We identified three PE subtypes on the basis of the number of distinct metabolic characteristics, namely Metabolism Correlated (MC) A (MCA), MCB, and MCC subclasses. Through WGCNA, we pinpointed 101 metabolic genes that were strongly associated with PE progression. Machine learning algorithms helped to narrow the list to five key signature genes, which were then used to construct a predictive model offering significant clinical benefits for PE patients. qRT-PCR analysis confirmed that these genes are closely linked to PE progression, while scRNA-seq data revealed high expression of RBBP7 in trophoblast cells. In conclusion, the five genes identified here-RAG1, RBBP7, RFTN2, SPATA7, and ZNF16-were found to be strongly associated with PE progression.

Cell death resistance significantly contributes to poor therapeutic outcomes in various cancers. PANoptosis, a unique inflammatory programmed cell death (PCD) pathway activated by specific triggers and regulated by the PANoptosome, possesses key features of apoptosis, pyroptosis, and necroptosis, but these cannot be accounted for by any of the three PCD pathways alone. While existing studies on PANoptosis have predominantly centered on infectious and inflammatory diseases, its role in cancer malignancy has been understudied. In this comprehensive investigation, we conducted pan-cancer analyses of PANoptosome component genes across 33 cancer types. We characterized the genetic, epigenetic, and transcriptomic landscapes, and introduced a PANoptosome-related potential index (PANo-RPI) for evaluating the intrinsic PANoptosome assembly potential in cancers. Our findings unveil PANo-RPI as a prognostic factor in numerous cancers, including KIRC, LGG, and PAAD. Crucially, we established a significant correlation between PANo-RPI and tumor immune responses, as well as the infiltration of diverse lymphoid and myeloid cell subsets across nearly all cancer types. Moreover, a high PANo-RPI was consistently associated with improved immunotherapy response and efficacy, as evidenced by re-analysis of multiple immunotherapy cohorts. In conclusion, our study suggests that targeting PANoptosome components and modulating PANoptosis may hold tremendous therapeutic potential in the context of cancer.

The progestin and adipoQ receptor family member, PAQR11, is recognized for its roles in vesicle trafficking, mitogenic signaling, and metastatic spread, positioning it as a crucial regulator in cancer biology. PAQR11 influences lipid metabolism and susceptibility to ferroptosis in cancer cells. This study aims to investigate the prognostic significance of PAQR11, its relevance to immune responses, and its association with drug sensitivity across various cancer types. By elucidating these aspects, the research seeks to assess PAQR11's potential as a biomarker and therapeutic target in oncology.

We conducted a comprehensive bioinformatics analysis using publicly available pan-cancer datasets from TCGA, GEO, UALCAN, TIMER, GEPIA2, KM plotter, and TISIDB. This analysis encompassed gene expression profiles across 33 cancer types, with a focus on PAQR11's expression patterns, prognostic significance, and immunological relevance. In addition, the study explored the correlation between PAQR11 expression and drug sensitivity, alongside its molecular and pathological characteristics in various tumors.

Our findings demonstrate elevated PAQR11 expression levels across multiple cancer types, which significantly correlate with patient prognostic outcomes. The analysis further revealed PAQR11's involvement in immunological and epigenetic processes, underscoring its critical role in cancer progression and treatment response. Notably, a strong correlation between PAQR11 expression and drug sensitivity was identified, suggesting its potential influence on the initiation and progression of various cancers and highlighting its promise as a therapeutic target.

The comprehensive analysis of PAQR11 underscores its significance as a biomarker for cancer prognosis and its role in regulating immunological and epigenetic processes. These findings offer valuable insights that could inform early detection strategies and the development of novel therapeutic approaches. Further exploration and validation of PAQR11 are essential, highlighting the need for its integration into future oncological research and treatment strategy development.

Not applicable.

Netrin-1 (NTN1) is a laminin-related secreted protein involved in axon guidance and cell migration. Previous research has established a significant connection between NTN1 and nervous system development. In recent years, mounting evidence indicates that NTN1 also plays a crucial role in tumorigenesis and tumor progression. For instance, inhibiting Netrin-1 has been shown to suppress tumor growth and epithelial-mesenchymal transition (EMT) characteristics in endometrial cancer. To further elucidate the influence of genes on tumors, we utilized a variety of machine learning techniques and found that NTN1 is strongly linked to multiple cancer types, suggesting it as a potential therapeutic target. This study aimed to elucidate the role of NTN1 in pan-cancer using multi-omics data and explore its potential as a prognostic biomarker in SKCM. Analysis of the TCGA, GTEx, and UALCAN databases revealed significant differences in NTN1 expression at both the mRNA and protein levels. Prognostic value was evaluated through univariate Cox regression and Kaplan-Meier methods. Mutation and methylation analyses were conducted using the cBioPortal and SMART databases. We identified genes interacting with and correlated to NTN1 through STRING and GEPIA2, respectively. Subsequently, we performed GO and KEGG enrichment analyses. The results suggested that NTN1 might be involved in crucial biological processes and pathways related to cancer development and progression, including cell adhesion, axon guidance, immune response, and various signaling pathways. We then explored the correlation between NTN1 and immune infiltration as well as immunotherapy using the ESTIMATE package, TIMER2.0, TISIDB, TIDE, TIMSO, and TCIA. The relationship between NTN1 and tumor heterogeneity, stemness, DNA methyltransferases, and MMR genes was also examined. Lastly, we constructed a nomogram based on NTN1 in SKCM and investigated its association with drug sensitivity. NTN1 expression was significantly associated with tumor immune infiltration, molecular subtypes, and clinicopathological features in various cancers. Genetic analysis revealed that Deep deletions were the most common type of NTN1 alteration. Additionally, a positive correlation was observed between NTN1 CNAs and its expression levels. In most cancers, NTN1 showed positive correlations with immune and stromal scores, as well as with specific immune cell populations. Its predictive value for immunotherapy response was comparable to that of tumor mutational burden. Furthermore, NTN1 exhibited positive correlations with tumor heterogeneity, stemness, DNA methyltransferase genes, and MMR genes. In SKCM, NTN1 was identified as an independent risk factor and demonstrated potential associations with multiple drugs. NTN1 exhibits substantial clinical utility as a prognostic marker and indicator of immune response across various tumor types. This comprehensive analysis provides insights into its potential implications in pan-cancer research.

Centromere protein N (CENPN), located on chromosome 16q23.2, encodes vital nucleosome-associated complexes that are essential for dynamic assembly processes. CENPN plays a pivotal role in regulating cell proliferation and cell cycle progression by influencing mitotic events. Despite its potential importance, the precise functional role and regulatory mechanisms of CENPN in diverse malignancies remain largely unexplored. This study aimed to elucidate the role of CENPN in human cancers and evaluate its prognostic significance.

Investigate the role of CENPN in various malignancies, we leveraged data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. We employed a comprehensive suite of web platforms and software tools for data analysis, including R, Cytoscape, an integrated repository portal for tumor-immune system interactions (TISIDB), CBio Cancer Genomics Portal (cBioPortal), Search Tool for the Retrieval of Interaction Gene/Proteins (STRING), Gene Set Cancer Analysis (GSCALite), and a cancer single-cell state atlas (CancerSEA).

The findings demonstrated that CENPN expression was elevated in the majority of cancer types and differentially expressed across molecular and immune subtypes. Functional enrichment analysis in multiple tumors also identified possible pathways of CENPN involvement in tumorigenesis. Its expression positively correlated with Th2 and Tcm cells in most cancers. It is also correlated with genetic markers of immunomodulators in various cancers.

Overall, CENPN expression is closely related to cancers and has the potential to act as a cancer biomarker.

Cancer remains one of the most significant public health challenges worldwide. A widely recognized hallmark of cancer is the ability to sustain proliferative signaling, which is closely tied to various cell cycle processes. Centromere Protein A (CENPA), a variant of the standard histone H3, is crucial for selective chromosome segregation during the cell cycle. Despite its importance, a comprehensive pan-cancer bioinformatic analysis of CENPA has not yet been conducted.

Data on genomes, transcriptomes, and clinical information were retrieved from publicly accessible databases. We analyzed CENPA's genetic alterations, mRNA expression, functional enrichment, association with stemness, mutations, expression across cell populations and cellular locations, link to the cell cycle, impact on survival, and its relationship with the immune microenvironment. Additionally, a prognostic model for glioma patients was developed to demonstrate CENPA's potential as a biomarker. Furthermore, drugs targeting CENPA in cancer cells were identified and predicted using drug sensitivity correlations and protein-ligand docking.

CENPA exhibited low levels of gene mutation across various cancers. It was found to be overexpressed in nearly all cancer types analyzed in TCGA, relative to normal controls, and was predominantly located in the nucleus of malignant cells. CENPA showed a strong association with the cancer cell cycle, particularly as a biomarker for the G2 phase. It also emerged as a valuable diagnostic and prognostic biomarker across multiple cancer types. In glioma, CENPA demonstrated reliable prognostic potential when used alongside other prognostic factors. Additionally, CENPA was linked to the immune microenvironment. Drugs such as CD-437, 3-Cl-AHPC, Trametinib, BI-2536, and GSK461364 were predicted to target CENPA in cancer cells.

CENPA serves as a crucial biomarker for the cell cycle in cancers, offering both diagnostic and prognostic value.

Acute Myeloid Leukemia (AML) with KMT2A rearrangements (KMT2Ar), found on chromosome 11q23, is often called KMT2A-rearranged AML (KMT2Ar-AML). This variant is highly aggressive, characterized by rapid disease progression and poor outcomes. Growing knowledge of epigenetic changes, especially lactylation, has opened new avenues for investigation and management of this subtype. Lactylation plays a significant role in cancer, inflammation, and tissue regeneration, but the underlying mechanisms are not yet fully understood. This research examined the influence of lactylation on gene expression within KMT2Ar-AML, initially identifying twelve notable lactylation-dependent differentially expressed genes (DEGs). Using advanced machine learning techniques, six key lactylation-associated genes (PFN1, S100A6, CBR1, LDHB, LGALS1, PRDX1) were identified as essential for prognostic evaluation and linked to relevant disease pathways. The study also suggested PI3K inhibitors and Pevonedistat as possible therapeutic options to modulate immune cell infiltration. Our findings confirm the critical role of lactylation in KMT2Ar-AML and identify six key genes that may serve as biomarkers for diagnosis and treatment. In addition to highlighting the need for further validation in clinical settings, these findings contribute to our understanding of KMT2Ar-AML's molecular mechanisms.