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PubMed2025

An anti-androgen resistance-related gene signature acts as a prognostic marker and increases enzalutamide efficacy via PLK1 inhibition in prostate cancer.

BACKGROUND: Anti-androgen resistance remains a major clinical challenge in the treatment of prostate cancer (PCa), leading to disease progression and treatment failure. Despite extensive research on resistance mechanisms, a reliable prognostic model for predicting patient outcomes and guiding therapeutic strategies is still lacking. This study aimed to develop a novel gene signature related to anti-androgen resistance and evaluate its prognostic and therapeutic implications. METHODS: Anti-androgen resistance-related differentially expressed genes (ARRDEGs) were identified through transcriptomic analysis of enzalutamide- and dual enzalutamide abiraterone-resistant PCa cell lines from the GEO database. Functional enrichment analysis was performed to determine the biological roles of these genes. A prognostic gene signature was developed using univariate Cox regression, LASSO, and multivariate Cox regression models. The model was validated in independent PCa cohorts from The Cancer Genome Atlas (TCGA). Additionally, we assessed the correlation between the signature, immune infiltration, immune checkpoint expression, and drug sensitivity. The efficacy of PLK1 inhibition combined with enzalutamide was further explored using in vitro and in vivo experiments. RESULTS: We identified 304 ARRDEGs, from which three key genes (LMNB1, SSPO, and PLK1) were selected to construct a prognostic signature. This gene signature effectively stratified PCa patients into high- and low-risk groups, with the high-risk group exhibiting shorter recurrence-free survival and distinct immune characteristics. High-risk patients demonstrated elevated immune checkpoint expression (B7H3, CTLA-4, B7-1, and TIGIT), increased M2 macrophage infiltration, and enhanced sensitivity to chemotherapy and targeted therapy. Mechanistically, PLK1 inhibition potentiated the antitumor effect of enzalutamide by downregulating SLC7A11 and inducing ferroptosis, providing a potential therapeutic strategy to overcome anti-androgen resistance. CONCLUSION: We established a novel ARRDEGs-based prognostic signature that predicts PCa progression and response to chemotherapy and targeted therapy. The integration of this signature with immune profiling and drug sensitivity analysis provides a valuable tool for precision oncology in PCa. Our findings highlight the potential of PLK1 inhibition as a therapeutic strategy to enhance enzalutamide efficacy and overcome resistance.

Humans↗

PubMed2026

Kynurenine metabolism-related gene signature for prognostic stratification in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health burden with high mortality rates and limited therapeutic options. The identification of reliable biomarkers for early diagnosis and prognosis prediction is urgently needed. Kynurenine metabolism, a critical pathway in immune regulation and tumor progression, has been implicated in various cancers. However, its prognostic value in HCC has not been fully elucidated. This study aimed to develop a prognostic risk model based on kynurenine metabolism-related genes (KMRGs) for HCC patients. METHODS: Transcriptomic and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. Survival analysis and functional enrichment analysis were conducted to validate the predictive performance of the model and to investigate the underlying mechanisms. ALDH8A1 was ultimately identified as a target gene based on survival analysis, and its impact on tumor cell migration was assessed using the HCC cell line. RESULTS: A prognostic model based on seven KMRGs was established. The high-risk group exhibited significantly worse overall survival compared to the low-risk group. Functional enrichment analysis in high-risk patients highlighted significant enrichment in core biological processes, including spliceosome assembly and ribonucleoprotein complex biogenesis. Furthermore, a nomogram integrating the risk score and clinical pathological features was developed, demonstrating moderate predictive performance for HCC prognosis. CONCLUSIONS: This study successfully constructed a prognostic risk model based on seven KMRGs, providing a valuable tool for predicting clinical outcomes in HCC patients. These findings highlight the potential role of kynurenine metabolism in HCC progression and offer new insights for future therapeutic strategies.

ALDH8A1↗

PubMed2026

GCH1, identified by a ferroptosis-related prognostic model, contributes to progression and drug resistance of esophageal cancer.

OBJECTIVE: Esophageal cancer has a poor prognosis and limited treatment options. Ferroptosis, an iron-dependent cell death pathway, is a promising therapeutic target; however, its significance in esophageal cancer remains largely unexplored. Here, we investigated the prognostic significance of ferroptosis-related genes in esophageal cancer and identified a key functional regulator that may serve as a therapeutic target. METHODS: We analyzed ferroptosis-related gene expression profiles with The Cancer Genome Atlas-Esophageal Carcinoma (TCGA-ESCA) cohort and constructed a prognostic risk model using LASSO Cox regression analysis. Among the genes in this model, GTP cyclohydrolase 1 (GCH1) was selected for functional investigation, based on its established role in antioxidant defense. Subsequently, in vitro experiments were performed to assess the effects of GCH1 knockdown on cell proliferation, migration, clonogenicity, and ferroptosis-related biochemical indicators. The role of GCH1 in antitumor immunity was evaluated through co-culture of esophageal cancer cells with activated T cells, and drug sensitivity was assessed using cytotoxicity assays. RESULTS: A prognostic model consisting of nine ferroptosis-related genes (STC2, TRIB3, HMGB3, CXCL8, GCH1, PARP10, APOE, MTIM, and GPER1) with reliable risk stratification was constructed. The prognostic model could reflect the differences in drug responses and immune cell infiltration. GCH1 knockdown suppressed esophageal cancer cell proliferation, migration, and clonogenicity. Furthermore, GCH1 knockdown increased the intracellular levels of reactive oxygen species, lipid peroxidation, and ferrous iron (Fe2+). Co-culture assays demonstrated that GCH1 knockdown in tumor cells increased the production of granzyme B and interferon-γ by CD8+ T cells. Moreover, GCH1 silencing sensitized esophageal cancer cells to both sorafenib and cisplatin. CONCLUSIONS: This study established a ferroptosis-related prognostic model for esophageal cancer and identified GCH1 as a critical regulator that contributes to esophageal cancer progression and drug resistance. These findings suggest that targeting GCH1 may be a promising strategy to improve drug sensitivity and clinical outcomes in esophageal cancer.

Esophageal cancer↗

PubMed2026

Machine learning prognostic model and drug survival analysis for lung adenocarcinoma in the context of radiotherapy.

BACKGROUND: Patients with lung adenocarcinoma (LUAD) receiving radiotherapy represent an important but underexplored clinical subgroup. These patients often undergo concomitant pharmacologic treatments, yet the prognostic impact and underlying determinants of such combined regimens remain poorly understood. OBJECTIVE: This retrospective observational study aimed to develop and validate a radiotherapy-specific machine learning prognostic model for LUAD and to compare survival across concomitant pharmacologic regimens. METHODS: In this retrospective observational study, using genomic and clinical data from TCGA, a radiotherapy-specific prognostic model for LUAD was developed and validated through ten machine learning algorithms. Survival analyses were conducted across distinct concomitant pharmacologic strategies, followed by functional enrichment to elucidate molecular mechanisms underlying differential outcomes. RESULTS: Demonstrating robust prognostic abilities, the model efficiently sorted patients into high- and low-risk categories. Both treatment type and risk score independently predicted overall survival, with significant interaction effects. Low-risk patients receiving targeted or combination therapy-mainly erlotinib, gefitinib, or bevacizumab-exhibited substantially improved survival compared with those receiving conventional chemotherapy. Enrichment of "Exogenous peptide presentation," "MHC class II assembly," "Peptide-MHC II assembly," and "Symbiotic interaction" pathways indicated immune modulation and host-tumor crosstalk as key mediators of treatment efficacy. CONCLUSION: This study establishes a radiotherapy-specific prognostic model for lung adenocarcinoma, demonstrating distinct molecular and therapeutic heterogeneity and highlighting the superior survival benefit of targeted combination therapy in low-risk patients.

Humans↗

PubMed1975

A staging system for hepatocellular carcinoma: prognostic factors in Ugandan patients.

A staging scheme for hepatocellular carcinoma was presented at an International Symposium on Liver Cancer in Kampala, Uganda in 1971. Historical, clinical, and laboratory aspects of that staging scheme were examined for prognostic significance in 72 untreated patients with this disease studied at the Uganda Cancer Institute. The median survival for the entire group was 1 month. The presence of a serum bilirubin concentration of greater than 2 mg/100 ml or weight loss greater than 25 percent of body weight were the poorest prognostic features. Other factors with prognostic significance were visible abdominal collateral circulation, ascites, tumor differentiation, and serum levels of alkaline phosphatase, SGOT, alpha fetoprotein, and proline hydroxylase. A modified staging scheme is presented which defines three prognostically different groups of Ugandan patients. It is hoped this staging scheme will serve as a stimulus for analysis of similar prognostic features in other populations of patients with hepatocellular carcinoma.

Adult↗

PubMed2025

Identification and validation of prognostic genes associated with mitochondrial nuclear genes in gastric cancer.

Mitochondrial-related nuclear genes (MNGs) have shown great importance in cancer diagnosis and prognosis, but their role in gastric cancer (GC) remains unclear. GC-related transcriptome data from the gene expression omnibus and cancer genome atlas databases were analyzed to identify differentially expressed MNGs. A prognostic risk model was constructed through univariate Cox and least absolute shrinkage and selection operator regression, validated by Kaplan-Meier (K-M) survival curve and receiver operating characteristic curve. This was followed by immune infiltration analysis, independent prognostic analysis, functional enrichment analysis, drug sensitivity analysis, drug prediction, molecular docking and construction of regulatory networks. Three prognostic genes (ATP8A2, COX15 and TARS2) were identified. The expression of TARS2 and COX15 was positively correlated with CNV, while ATP8A2 was unaffected. The risk model and nomogram, integrating risk score and clinicopathological factors, exhibited excellent predictive performance. A significant correlation was observed between prognostic genes and differential immune cells, such as T cells, B cells, and NK cells. BMS-754807, Gefitinib, JQ1, Lapatinib, and Sapitinib exhibited significant differences in sensitivity between the high-risk group and the low-risk group. The results of molecular docking showed TP8A2 has stable binding ability with cytosine, COX15 with indomethacin, and TARS2 with bisacodyl. RT-qPCR revealed downregulation of ATP8A2 and upregulation of COX15 and TARS2 in GC samples. MNGs, including ATP8A2, COX15, and TARS2, demonstrated significant associations with immune infiltration, CNV, and prognostic outcomes of GC.

Humans↗

PubMed2026

Prognostic Value of Circulating Tumor DNA-Based Minimal Residual Disease for Recurrence-Free Survival in Resectable Gastric Cancer: A Systematic Review and Meta-Analysis with Serial Monitoring Analysis.

BACKGROUND: Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) is an emerging biomarker, but its utility in resectable gastric cancer remains incompletely characterized. METHODS: We conducted a systematic review and meta-analysis of eight studies (520 patients) to evaluate the prognostic value of ctDNA-based MRD for recurrence-free survival (RFS) and overall survival (OS) in resectable gastric cancer. RESULTS: In localized resectable gastric cancer (Stage I-III), the setting in which postoperative ctDNA most coherently represents true molecular residual disease after curative-intent surgery, postoperative ctDNA positivity was associated with diminished recurrence-free survival (RFS: HR 12.26, 95% CI 3.30-45.52) and overall survival (OS: HR 8.57, 95% CI 3.06-23.98). The test for subgroup differences between localized and mixed-stage cohorts was not statistically significant (P = 0.57), and the numerically higher HR in the localized subgroup should therefore not be interpreted as evidence of a quantitatively stronger prognostic effect. Postoperative ctDNA detection demonstrated substantially stronger prognostic value (overall RFS: HR 10.00, 95% CI 4.53-22.10) compared to preoperative assessment (HR 2.17, 95% CI 1.10-4.28). Both tumor-informed and tumor-agnostic strategies effectively stratified high-risk patients. However, these effect sizes should be interpreted cautiously given the small number of studies and substantial heterogeneity (I2 = 65-72%). Results from mixed-stage cohorts including Stage IV disease are supportive but should not be considered equivalent to localized-disease findings, as ctDNA in metastatic disease reflects persistent systemic burden rather than minimal residual disease in the postoperative sense. CONCLUSIONS: Postoperative ctDNA-based MRD shows a consistent adverse prognostic association in resectable gastric cancer, with localized disease (Stage I-III) representing the most biologically and clinically coherent setting for interpretation. However, the large pooled hazard ratios (HR 10.00-12.26) should be interpreted as a directionally consistent signal rather than precise quantitative estimates, given the small number of studies, wide confidence intervals, and substantial heterogeneity (I2 = 65-73%). This heterogeneity is largely driven by substantial variation in postoperative sampling timing (4 days to 16 weeks) and ctDNA assay characteristics (platform, sensitivity, coverage, variant filtering, and positivity thresholds), which require standardization in future studies. While ctDNA is prognostically valuable, its clinical utility remains unestablished. Prospective randomized trials are needed to determine whether ctDNA-guided strategies improve patient outcomes before routine clinical implementation can be recommended.

Humans↗

PubMed2025

Comprehensive investigation identifies CPSF3 as a novel prognostic and oncogenic biomarker in bladder cancer.

BACKGROUND: Bladder cancer (BC) remains a prevalent malignancy worldwide, with rising incidence rates each year. Despite progress in therapeutic strategies, many patients suffer recurrence or progression, emphasizing the urgent need for novel prognostic biomarkers and therapeutic targets. This research evaluated the prognostic relevance and functional role of Cleavage and Polyadenylation Specificity Factor 3 (CPSF3) in BC. METHODS: We analyzed CPSF3 expression using The Cancer Genome Atlas data and immunohistochemistry on a cohort of 203 BC patients. A nomogram incorporating CPSF3 expression was developed based on CPSF3 expression for prediction of overall survival and disease-free survival. Immune infiltration analyses and transcriptome sequencing were performed to explore underlying biological mechanisms. In vitro and in vivo experiments were utilized to examine the results of CPSF3 silencing on bladder cancer cell growth, colony-forming ability and cell cycle transitions. RESULTS: Elevated CPSF3 expression was significantly linked to unfavorable overall survival and disease-free survival both in TCGA datasets and our cohort. The CPSF3-based nomogram outperformed conventional prognostic models. CPSF3 expression was associated with tumor-infiltrating immune cells and immune checkpoint markers. Enrichment analysis revealed CPSF3 enrichment in cell cycle-related pathways. Suppression of CPSF3 expression led to marked reductions in cell proliferation, colony formation, tumor growth in animal models and inhibited G1 to S phase progression. CONCLUSION: CPSF3 is a promising prognostic biomarker for BC and may play a crucial role in BC progression. Incorporating CPSF3 into clinical prognostic models may enhance prediction of patient outcomes. CPSF3 may represent a promising therapeutic target for BC management.

Bladder cancer↗

PubMed2026

Prognostic model based on calcium-related genes predicts prognosis and reveals the immune landscape of acute myeloid leukemia.

Acute myeloid leukemia (AML) exhibits heterogeneous outcomes and lacks reliable prognostic markers. As a critical regulator of cell fate, the prognostic value of calcium signaling in AML requires investigation. This study aimed to construct a calcium-related gene (CRG)-based prognostic model for AML. Differential analysis on RNA-seq data was conducted for AML from The Cancer Genome Atlas and Gene Expression Omnibus (GEO). Intersecting differentially expressed genes and CRGs yielded AML-associated differentially expressed CRGs (DECRGs). A prognostic model was developed using univariate/multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) and validated in a GEO dataset. Bioinformatics analyses explored the links between risk groups and immune characteristics, genomic mutations, and drug sensitivity. Key genes' effects on cell proliferation, apoptosis, and differentiation were verified in vitro using CCK-8 assay, colony formation assay, and flow cytometry. The 13-DECRG-based model distinguished high- and low-risk patients in both training and validation cohorts, with high-risk patients showing a worse prognosis. The risk score was an independent prognostic factor. Immune analysis revealed a unique immune microenvironment for the high-risk group. CAMK2A overexpression inhibited cell proliferation and colony-forming ability, promoted cell apoptosis, and induced an increased proportion of CD11b- and CD14-positive cells. In vitro experiments indicated CAMK2A-induced suppression of AML cells' malignant phenotype by activating the P53 signaling pathway. An AML CRG-based model with favorable risk stratification performance was constructed. In vitro experiments revealed CAMK2A-induced inhibition of the malignant phenotype via suppressing proliferation, promoting apoptosis, and facilitating myeloid differentiation in AML cells. This study provides novel evidence for understanding CRGs in AML as well as the potential functions of CAMK2A.

Journal Article↗

PubMed2025

Construction and accuracy assessment of an efferocytosis-related prognostic model for ovarian cancer: A diagnostic accuracy study.

The study aimed to investigate the prognostic significance of efferocytosis-related genes in ovarian cancer (OC) with regard to cancer development, progression, invasion, and metastasis. OC cohorts were assembled from bioinformatics repositories. Utilizing consensus clustering analysis, distinct clusters were delineated based on the intersection of OC-related genes and efferocytosis-related genes. A prognostic signature specific to efferocytosis in OC was developed using data from The Cancer Genome Atlas, validated against the gene expression omnibus database, and subjected to independent prognostic analysis. Subsequently, a nomogram model was formulated. Moreover, investigations encompassed the immune microenvironment, immunotherapy, mutation profiling, drug sensitivity assessments, drug prediction models, and molecular docking analyses. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays were employed to ascertain the mRNA expression levels of key genes. Five key genes, FCGBP, BTN3A3, WDR91, SLC25A45, and BTNL3, were identified as significantly associated with OC. Both datasets and qRT-PCR demonstrated elevated expression levels of FCGBP and WDR91 in OC. Notably, AFLATOXIN B1 exhibited strong binding affinity to SLC25A45, ciclopirox to BTN3A3, and irinotecan to WDR91. The risk score, age, and stage were identified as independent prognostic factors, with the nomogram displaying efficacy in predicting OC patient survival. Variations in the immune cell infiltration profiles, including naive B cells, and expression levels of 6 immune checkpoint genes, such as CTLA4, were notable. High tumor mutation burden scores were associated with improved survival outcomes. Additionally, significant differences in the IC50 values of 123 anticancer drugs were observed between the 2 risk groups. This findings of this study highlight the efficacy of the efferocytosis-associated risk model in predicting the survival outcomes of OC patients, thus providing a novel reference for prognostic prediction in OC patients.

Humans↗

PubMed2024

Exploring the prognostic landscape of oral squamous cell carcinoma through mitochondrial damage-related genes.

Oral squamous cell carcinoma (OSCC), the most prevalent form of oral cancer, poses significant challenges to the medical community due to its high recurrence rate and low survival rate. Mitochondrial Damage-Related Genes (MDGs) have been closely associated with the occurrence, metastasis, and progression of OSCC. Consequently, we constructed a prognostic model for OSCC based on MDGs and identified potential mitochondrial damage-related biomarkers. Gene expression profiles and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Differential analysis was conducted to identify MDGs associated with OSCC. COX analysis was employed to screen seven prognosis-related MDGs and build a prognostic prediction model for OSCC. Cases were categorized into low-risk or high-risk groups based on the optimal risk score threshold. Kaplan-Meier (KM) analysis revealed significant survival differences (P < 0.05). Additionally, the area under the ROC curve (AUC) for patient survival at 1 year, 3 years, and 5 years were 0.687, 0.704, and 0.70, respectively, indicating a high long-term predictive accuracy of the prognostic model. To enhance predictive accuracy, age, gender, risk score, and TN staging were incorporated into a nomogram and verified using calibration curves. Risk scoring based on MDGs was identified as a potential independent prognostic biomarker. Furthermore, BID and SLC25A20 were identified as two potential independent mitochondrial damage-related prognostic biomarkers, offering new therapeutic targets for OSCC.

Humans↗

PubMed2026

Transcriptome-based epigenetic screening identifies DNA hypermethylation signatures as prognostic biomarkers in oral squamous cell carcinoma.

Promoter DNA hypermethylation is a key epigenetic mechanism of gene silencing in cancer, yet the DNA hypermethylome of oral squamous cell carcinoma (OSCC) and its prognostic relevance remain poorly characterized. Here, we systematically identified and validated novel hypermethylated genes with prognostic significance in OSCC using a genome-wide discovery and multi-platform validation strategy. Candidate genes were first identified by pharmacologic demethylation combined with RNA sequencing across OSCC cell lines, then validated by quantitative RT-PCR, methylation-specific PCR, and bisulfite sequencing in OSCC cell lines, normal oral mucosa, and primary OSCC tumors, with independent confirmation in the TCGA-HNSC dataset. Immunohistochemistry confirmed protein-level silencing, and Kaplan-Meier survival analysis assessed prognostic significance across both cohorts. This pipeline identified five candidate genes, GPX3, ANG, CTGF, GPRC5B, and BAMBI, exhibiting cancer-specific promoter hypermethylation associated with transcriptional and protein silencing in OSCC. Validation in oral cavity tumor samples extracted from the TCGA-HNSC dataset confirmed tumor-specific hypermethylation and revealed significant inverse correlations between methylation and expression for GPX3, GPRC5B, and CTGF. Notably, CTGF hypermethylation was independently associated with poor overall survival in both cohorts (institutional cohort, p=0.03; oral tumor subset from TCGA-HNSC, p=0.01), and a combined ANG+CTGF methylation signature showed superior and reproducible prognostic performance across both platforms. Pathway analysis linked these genes to epithelial-mesenchymal transition and interferon response signaling. This study establishes the first validated DNA methylation biomarker panel for OSCC prognosis, identifying CTGF hypermethylation as a robust prognostic driver with translational potential for clinical risk stratification.

Humans↗

PubMed2026

PSMB8: an immune-related prognostic marker for low-grade gliomas.

BACKGROUND: Glioma is the most common primary intracranial tumor in adults. As a subunit of immune proteasome, proteasome subunit beta type-8 (PSMB8) may regulate the progression of glioma via participating in degradation and presentation of tumor antigenic peptides, but its prognostic and clinical applicant usage is under investigation. Therefore, this study aimed to comprehensively evaluate the prognostic significance of PSMB8 in low-grade glioma (LGG) and to elucidate its association with the tumor immune microenvironment and potential as a predictor for immunotherapy response. METHODS: Transcriptome data were downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Gene Expression Omnibus (GEO) repositories. The correlations between PSMB8 expression and the clinicopathological features of LGG were investigated in our study, and the prognostic role of PSMB8 in LGGs was assessed fully and comprehensively. Furthermore, we evaluated the correlation between PSMB8 expression and LGG immune environment via the experiments and bioinformatic analysis. RESULTS: Our results indicated that, PSMB8 were highly expressed in most tumor tissues, including LGG. Lower expression of PSMB8 was significantly correlated with lower World Health Organization (WHO) grade and isocitrate dehydrogenase (IDH) mutation status. Moreover, PSMB8 showed a promising prognostic ability for LGG patients via nomogram model and receiver operating characteristic (ROC) curves. Association analysis showed that PSMB8 expression was associated with immune cell infiltration in a variety of tumors, including LGG. Our experiments validated the positive correlation between PSMB8 expression and M2-macrophage infiltration level in clinical LGG tissues and invasive ability of LGG cell. CONCLUSIONS: PSMB8 could be used as one of the prognostic indicators of LGG and it could regulate the LGG cell migratory and invasive ability. Besides, PSMB8 is expected to be a promising biomarker of cancer immunotherapy.

Low-grade glioma (LGG)↗

PubMed1976

[Prognostic assessment in peripheral facial nerve paralysis with particular reference to electroneurography (author's transl)].

Electrophysiological investigations were carried out on 20 healthy controls and 130 patients with peripheral facial nerve paralysis. The aetiology was as follows: idiopathic (Bell's palsy) in 60 cases, viral in 29, traumatic in 18, postoperative in 4, in connexion with chronic otitis media in 6, diabetes mellitus in 4, positive rheumatological tests in 3, disturbed lipid metabolism in 2, the Melkersson-Rosenthal syndrome in 1, as a complication of pregnancy in 2, and in association with a tumour in 1 case. The compound action potential (CAP) of the orbicularis oris muscle was determinedi n 370 occasions in a right/left comparision, the record of the muscle response was intergrated over the time of action (IAR) on 32 occasions and trison of 255 occasions. The normal values are given in the first place and their dependence of the age of the subject. Then, the prognostic sifnficance of the above-mentioned parameters is investigated in cases of peripheral facial nerve paralysis. It is apparent that the determination of the CAP in a right/left comparison is a valuable prognostic guide as early as the 4th day, insofar as a decrease in this parameter of under 50% can be interpreted as a favourable sign and satisfactory reversal of the paralysis can be expected within 6-8 weeks. By contrast, a decrease of over 70% in the CAP is a bad prognostic sign, indicative of presumably only a poor trend to reversal of the paralysis. An intermediate depression of the CAP in the range of 50-70% signifies an expected moderate recovery within 6-8 weeks ahe case of CAP determination at the time of maximum amplitude depression (as opposed to the 4th day), then a decrease of less than 70% is taken to be indicative of satisfactory functional recovery within 6-8 weeks; a decrease of 95-100% signifies a bad prognosis, whilst a decrease amounting to between 70 and 95% carries an uncertain prognosis. The maximum decrease in amplitude was registered on the 8th day on average; the range lay between the 4th and the 14th day. An exception to these figures was the delayed response of the CAP in the case of 6 patients, 5 of whom showed a maximum decrease during the 3rd week and the last patient as late as the 4th week following the onset of facial nerve paresis. Similar reliance can be placed on the prognostic value of the IAR. however, the decrease in the IAR is smaller than that of the CAP measured on the same potential in a right/left comparison, so that a decrease in the IAR of over 60% can already herald a poor recovery. Repeated determination of the latency in cases of facial nerve paralysis showed that the mean latency value for the entire group of patients was slightly prolonged at the end of the 1st week, but the latency values obtained in any one particular patient are of no prognostic significance. A comparison between CAP and latency values obtained with the opposite (i.e...

Action Potentials↗

PubMed2025

Identification of key genes related to bone metastasis of breast cancer using bioinformatics methods and construction of a prognostic model.

Breast cancer (BC) ranks among the most prevalent cancers in females, with bone metastasis significantly compromising patients' quality of life and survival rates. Enhancing our comprehension of BC bone metastasis mechanisms at the molecular level holds promise for improving BC treatment and prognosis. Leveraging bioinformatics tools, we integrated multiple datasets, conducted comprehensive analyses across various databases, identified biomarkers associated with BC bone metastasis, and constructed a prognostic model. Firstly, 3 BC bone metastasis-related datasets were downloaded from gene expression omnibus, the data were merged, and batch effects were removed, followed by identification of differentially expressed genes (DEGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DEGs. A protein-protein interaction network was constructed using the STRING database to screen hub genes. Then, survival analysis of hub genes was performed using the Cancer Genome Atlas (TCGA) database. A prognostic model was constructed using key genes with survival differences, and the model was evaluated. Two hundred ninety-two DEGs were identified. Gene ontology and KEGG pathway enrichment analysis yielded 769 biological processes (BPs), 78 cellular components, 43 molecular functions, and 50 KEGG pathways. Fifteen hub genes were selected from the protein-protein interaction network. Survival analysis revealed 6 genes related to BC survival. The prognostic model identified 4 genes with important predictive value for BC prognosis. Our study utilized bioinformatics analysis to identify a series of DEGs related to BC bone metastasis. Based on further selection of hub genes, we constructed a relatively ideal prognostic model for BC, and identified 4 genes (DLGAP5, TPX2, PLK1, and CENPN) with valuable predictive value for BC prognosis.

Humans↗

PubMed2026

MS4A3 as a potential prognostic biomarker for colon cancer: integrated analysis of expression patterns and immune cell infiltration.

BACKGROUND: Membrane Spanning 4-Domains A3 (MS4A3) has been confirmed to possess significant tumor-suppressive potential in various malignancies. However, its expression characteristics and clinical prognostic value in colon cancer (CC) still lack systematic and in-depth investigation. This study aimed to systematically investigate the expression pattern, prognostic value, immune microenvironment association, and biological function of MS4A3 in CC through integrated bioinformatics analyses and experimental validation. METHODS: This study utilized The Cancer Genome Atlas-Colon Adenocarcinoma (TCGA-COAD) cohort to screen for genes significantly associated with CC and combined multiple independent Gene Expression Omnibus (GEO) datasets to validate the expression patterns and prognostic significance of MS4A3. Key biological pathways were identified through gene set enrichment analysis (GSEA), and tumor immune infiltration characteristics were evaluated using the CIBERSORT algorithm. Additionally, the expression of MS4A3 and its impacts on cellular functions were validated at the cellular level through quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, Cell Counting Kit-8 (CCK-8), EdU, Transwell, and TUNEL assays. RESULTS: Analysis of public datasets revealed that MS4A3 is significantly downregulated in CC tissues, and its low expression is an independent risk factor for shortened overall survival (OS). GSEA indicated that MS4A3 downregulation is closely associated with the aberrant activation of the pentose phosphate pathway. Immune infiltration analysis showed that low MS4A3 expression is closely linked to the enrichment of M2 macrophages and neutrophils, as well as the upregulation of multiple immune checkpoint genes. In vitro experiments further confirmed that MS4A3 was lowly expressed in CC cell lines. Its overexpression significantly inhibited CC cell viability, proliferation, migration, and invasion, while simultaneously promoting cell apoptosis. CONCLUSIONS: MS4A3 expression is significantly decreased in CC tissues and is significantly correlated with poor prognosis, suggesting that this gene may serve as a potential prognostic biomarker.

MS4A3↗

PubMed2026

Integrative analysis of single-cell sequencing identifies CD8+ TIM3+ CD101+ T cell-associated genes as prognostic biomarkers in breast cancer.

BACKGROUND: Breast cancer is a prevalent and deadly malignancy that significantly impacts women's quality of life and imposes financial burdens. Despite therapeutic advancements, tumour heterogeneity and frequent relapses remain major challenges. Accordingly, this study aimed to characterize immune features associated with CD8+ TIM3+ CD101+ T cells and develop a prognostic signature for breast cancer. METHODS: This study integrated single-cell and bulk transcriptomic datasets to characterize CD8+ TIM3+ CD101+ T cell (CCT)-related immune features and construct a prognostic signature in breast cancer. Single-cell RNA-seq data were sourced from the Gene Expression Omnibus (GEO) repository, and bulk transcriptomic data were from The Cancer Genome Atlas (TCGA) and GEO databases. Analytical methods included pseudo-time trajectory reconstruction (Monocle2), intercellular signalling analysis (CellChat), functional enrichment (ClusterProfiler), and immune profiling (ssGSEA). Prognostic modeling was conducted using least absolute shrinkage and selection operator (LASSO) Cox regression, with validation via Kaplan-Meier and time-dependent receiver operating characteristic (ROC) analyses. RESULTS: Single-cell analysis identified 17 clusters spanning seven cell types, including T cells, myeloid cells, and epithelial cells. T-cell sub-clustering revealed four subtypes. Pseudotime analysis suggested a potential state-transition relationship between CD8+ CD101- TIM3+ and CD8+ CD101+ TIM3+ T-cell states. A total of 121 differentially expressed genes were enriched in vital biological processes. An 11-gene prognostic model showed strong predictive power across cohorts. Single-cell T-cell reclustering identified a CD8+ CD101+ TIM3+ T-cell subpopulation, which was primarily characterized by the expression of markers such as CD101 and HAVCR2/TIM3. CONCLUSIONS: This study maps cellular heterogeneity and molecular networks in breast cancer, offering insights for targeted therapy and improved prognosis.

Breast invasive carcinoma↗

PubMed2026

The prognostic value and molecular mechanisms of Porphyromonas gingivalis infection-associated differentially expressed genes in oral squamous cell carcinoma.

BACKGROUND: Increasing evidence suggests that Porphyromonas gingivalis (Pg) is associated with oral squamous cell carcinoma (OSCC) development and progression. This study aimed to identify Pg-associated genes with prognostic relevance in OSCC through integrated bioinformatics analysis. METHODS: OSCC-related differentially expressed genes (DEGs) were identified from the The Cancer Genome Atlas (TCGA)-OSCC cohort and intersected with Pg supernatant-associated DEGs from GSE192887. Raw count data were analyzed with DESeq2, whereas transcripts per million (TPM)-transformed expression values were used for downstream visualization and model construction. Weighted gene co-expression network analysis (WGCNA), univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariable Cox modeling were used to develop a seven-gene prognostic signature, which was externally evaluated in GSE41613. Additional analyses examined treatment-associated expression changes in the seven model genes, pairwise correlations among the model genes, and correlations between Pg supernatant-associated differentially expressed gene (PgSDEG)-derived module eigengenes and immune-cell fractions. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed in eight paired OSCC and adjacent non-tumor tissues and in supplemented-brain heart infusion (BHI) vehicle-control and Pg culture-supernatant-treated HOK, HSC-3, and CAL-27 cells. RESULTS: A prognostic signature comprising CXCL8, GAST, HBQ1, PADI3, STC1, TEX19, and TMEM92 was established. The signature showed limited-to-moderate discrimination in the TCGA training cohort, with 1-, 3-, and 5-year areas under the curve (AUCs) of 0.68, 0.69, and 0.69, respectively, and limited discrimination in the GSE41613 external cohort (AUCs: 0.66, 0.67, and 0.61). Kaplan-Meier analysis showed poorer survival in the high-risk group in both cohorts. The GSE192887 analysis showed significant treatment-associated expression changes in all seven genes after Pg culture-supernatant exposure. In paired tissues, CXCL8 and TMEM92 were significantly higher in OSCC tissues, whereas STC1 was not significant after Holm correction. In CAL-27 cells, CXCL8, STC1, and TMEM92 increased significantly after culture-supernatant treatment, whereas the corresponding comparisons were not significant in HOK or HSC-3 cells after adjustment. CONCLUSIONS: This study developed a seven-gene Pg-associated prognostic signature for OSCC and provided complementary transcriptomic, immune-correlation, tissue, and cell-based evidence that placed the signature in biological context. The model showed limited-to-moderate discrimination and is not ready for clinical use. The enrichment, gene-correlation, and immune-correlation findings are hypothesis-generating rather than mechanistic evidence. Further independent validation and dedicated functional studies are required.

Oral squamous cell carcinoma (OSCC)↗