Identification and Validation of a Lipid Metabolism-Related Gene Signature for Predicting Prognosis and Immunotherapy Response in Oral Squamous Cell Carcinoma
Jun 2026· Metabolites· Vol 16, pp. 455· 0 citations· 49 references
Medicine
TL;DR
The LMRG signature could serve as a valuable tool for prognosis assessment, risk stratification, and therapy guidance in OSCC, and this study reveals that the risk score was significantly associated with the tumor immune microenvironment.
Abstract
Background/Objectives: Lipid metabolism plays a critical role in tumor progression and immunotherapy efficacy in oral squamous cell carcinoma (OSCC). However, clinically applicable lipid metabolism-based models for predicting prognosis and immunotherapy response remain limited. This study aimed to develop and validate such a model in OSCC. Methods: Using transcriptomic data of OSCC from the TCGA database and a set of lipid metabolism-related genes (LMRGs), we constructed an LMRG-based risk score model via LASSO regression to predict patient survival. This model was subsequently validated using the independent GEO dataset GSE41613. Results: Patients in the high-risk group exhibited significantly poorer overall survival than those in the low-risk group (training cohort: p < 0.0001; validation cohort: p = 0.0086). We also developed a nomogram incorporating the risk score and clinical characteristics, and the risk score was identified as an independent prognostic factor for OSCC patients. Furthermore, the risk score was significantly associated with the tumor immune microenvironment; samples with a lower risk score showed elevated CD8+ T cell infiltration and a better response to immunotherapy. Additionally, the high-risk group exhibited an increased tumor mutation burden and resistance to most chemotherapeutic agents. Notably, several drugs (e.g., obatoclax mesylate) showed significant efficacy in the high-risk group, representing promising therapeutic candidates. Conclusions: This study reveals that the LMRG signature could serve as a valuable tool for prognosis assessment, risk stratification, and therapy guidance in OSCC.
A ferroptosis- and lipid metabolism-related prognostic signature is developed that accurately predicts survival outcomes and immune characteristics in CRC and CRY2 was identified as a critical regulator of tumor growth.
Yu Guo, Yongbo Zou, Min Wang· Annals medicus· 0 citations
This signature stratified patients by prognosis in two geographically distinct external cohorts and generated testable metabolic and immune hypotheses.
Q. Ma, Jianqing Liang, Jin-tian Li et al.· Genes· 0 citations
Telomere maintenance-related genes (TMRGs) are implicated in Colorectal cancer (CRC) development, but their prognostic value and clinical relevance remain insufficiently explored. This study aims to develop a TMRG-based prognostic model and elucidate its clinical utility in CRC management.
The Cancer Genome Atlas database was utilized to download RNA-seq data from 638 CRC and 51 control samples. Differential expressed genes were screened and intersected with 2086 TMRGs, resulting in the identification of 976 TMRGs. Through univariate and multivariate Cox regression analysis, a prognostic model comprising three telomere maintenance-related biomarkers (
PDE1B, TFAP2B, and HSPA1A
) was developed and validated using an external dataset. By integrating the model risk score with clinical features, a nomogram was constructed to predict the survival outcomes of CRC patients. Additionally, an in-depth investigation of the immuno-infiltration, functional variation and drug sensitivity analysis were performed in two risk subgroups defined by the prognostic model. Finally, the functional significance of
PDE1B
in CRC cell lines was investigated through MTT assays, cell colony formation assays, transwell assays and flow cytometry.
A total of 976 DE-TMRGs were enriched in telomere/DNA replication pathways. A three-gene signature (PDE1B, TFAP2B, and HSPA1A) stratified patients into high- and low-risk groups with divergent survival (AUC >0.60, validated externally). High-risk patients had advanced N/M stages, elevated M0/M2 macrophages, reduced CD4
+
memory T cells, and upregulated immune checkpoints. Nomogram integrating risk score, age, and N/M stage accurately predicted 1-/3-/5-year survival. Low-risk patients showed greater 5-fluorouracil sensitivity.
PDE1B
expression was significantly reduced in CRC tissues and correlated with advanced stages. Functional assays confirmed PDE1B overexpression suppressed proliferation, migration, invasion, and induced apoptosis in CRC cells.
This study identifies a moderately predictive telomere maintenance-related gene signature as an independent prognostic predictor in CRC. The risk stratification model effectively discriminates patients with distinct survival patterns, tumor microenvironments, and therapeutic responses, while the integrated nomogram offers additional reference information for survival analysis, albeit with only moderate predictive accuracy. These findings indicate telomere maintenance-related gene signature could serve as a preliminary auxiliary risk stratification tool for postoperative CRC patients,
PDE1B
may also serve as a potential epithelial tumor-suppressor target for future preclinical studies.
Unknown authors· Frontiers in Molecular Biosc...· 0 citations
Introduction: Lipid metabolism contributes to tumor progression and immune regulation in Ewing sarcoma (EwS), but its relationship with prognosis and tumor immune microenvironment (TIME) remains inadequately clarified.
Objectives: This study investigated lipid metabolism-related gene (LMRG) subtypes, their associations with immune microenvironmental characteristics, and the prognostic value of an LMRG-based risk model in EwS.
Methods: Transcriptomic datasets of EwS from GEO (GSE17679; training cohort) and ICGC (validation cohort) were analyzed using computational techniques. LMRG subtypes were identified by consensus clustering. The TIME was inferred using ESTIMATE, TIMER algorithm, and single-sample gene set enrichment analysis (ssGSEA). A multigene risk score model was developed through LASSO and multivariable Cox regression, evaluated with Kaplan–Meier survival curves and time-dependent receiver operating characteristic (ROC) curves. A nomogram was constructed based on the model integrated with clinicopathologic variables.
Results: Two molecular subtypes showed distinct survival; the immune-enriched, low-purity subtype had poorer outcomes. A five-gene signature (TXNRD1, FABP5, ORMDL1, RAB5A, DBI) stratified patients into high- and low-risk groups, with AUCs of 0.90–0.94 in the training cohort and 0.58–0.85 in the validation cohort. The risk score was associated with increased ESTIMATE and immune scores, along with reduced tumor purity. The integrated nomogram achieved a C-index of 0.759 with acceptable calibration.
Conclusion: Dysregulated lipid metabolism is intricately linked to the TIME and patient prognosis in EwS. The LMRG-based risk model provides a potentially useful tool for prognostic stratification and highlights potential therapeutic avenues targeting lipid metabolism and immune modulation.
Kailuo Xie, Wenbin Liu, Jin Hu· Eurasian Journal of Medicine...· 0 citations
BACKGROUND
The prognosis for colorectal cancer (CRC) is poor, and the disease is marked by high rates of morbidity and death, highlighting the need for reliable biomarkers. RNA methylation modifications play important roles in cancer biology. However, the integrated role of m6A/m5C/m1A/m7G modifications in CRC has not been fully characterized and requires further investigation.
METHODS
Data from The Cancer Genome Atlas colon adenocarcinoma cohort (TCGA-- COAD) were used as the training set, and GSE17536 served as the validation cohort. We further investigated the probable biological processes and prognostic significance of methylation modifications-related genes in CRC using immune infiltration analysis, enrichment analysis, consistent clustering, Kaplan-Meier (KM) survival analysis, TIMER database exploration, and differential expression analysis. To evaluate the association between risk grade and survival prognosis, medication sensitivity, and immune infiltration, we created the Methylation Modifications Risk Model (MMRM) and confirmed its validity using immunohistochemical (IHC) and immunofluorescence (IF) staining.
RESULTS
Using information from 45 methylation modifications-related genes, consensus clustering to identify 3 categories of patients. There were variations across the three groups in terms of immune cell infiltration, survival, and immunological scores. Then, using LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis, we constructed MMRM that could distinguish between high- and low-risk populations utilizing BCL10, LEPROTL1, DPP7, P4HA1, SLC39A8, and AC008735.2. Using the validation set, KM survival analysis, TIMER database exploration, and IHC and IF staining, its accuracy was further supported. These findings suggest that m6A/m5C/m1A/m7G are associated with the immunological milieu of CRC tumors, and that MMRM is an excellent predictor of CRC patient survival.
DISCUSSION
This study shows that the integrated analysis of multiple RNA methylation modifications provides a more comprehensive view of epitranscriptomic heterogeneity in CRC than single-modification approaches. The association between the MMRM, immune landscape, and immune checkpoint expression suggests the potential mechanistic link between RNA methylation regulation and tumor immune evasion. These findings suggest that multi-modification-based models may improve prognostic accuracy and help identify CRC patients who may benefit from immunotherapy.
CONCLUSION
In this work, we emphasized the correlation between alterations in the CRC immunotumor microenvironment and the m6A/m5C/m1A/m7G subtypes. We developed and validated MMRM, which is useful for predicting treatment sensitivity, immune infiltration, and survival in patients with colorectal cancer. This contributes to the understanding of m6A/m5C/m1A/m7G methylation and may offer potential approaches to the treatment of colorectal cancer.
Ruyue Chen, Zengwu Yao, Lixin Jiang et al.· Current Medicinal Chemistry· 0 citations
BACKGROUND AND STUDY AIMS
Immunotherapy offers promising prospects for esophageal squamous cell carcinoma (ESCC), a highly fatal malignant tumor. Given the association between manganese metabolism and tumor immunity, this study explored the prognostic value and role of manganese-metabolism-related genes (MMRGs) in the ESCC immune microenvironment to uncover their clinical potential.
PATIENTS AND METHODS
Transcriptomic and clinical data of ESCC were retrieved from TCGA and the GEO as training and validation cohorts, respectively. Patients were clustered and subtyped based on MMRGs, with survival compared. A prognostic risk model was constructed using differential analysis, PPI network, and Cox regression; its relationship with immune characteristics, immunotherapy response, and drug sensitivity was evaluated. SLC40A1 was knocked down in vitro, and its effects on cellular function and drug sensitivity were assessed via qRT-PCR, Western blot, colony formation, Transwell, and CCK-8 assays.
RESULTS
ESCC patients were stratified into two MMRG-defined subtypes. Cluster 2 showed significantly worse overall survival (OS) than Cluster 1. An 8-gene prognostic model was established and patients were assigned to RiskScorehigh and RiskScorelow groups. The high-risk group, characterized by worse OS, displayed an immunosuppressive microenvironment with abundant M2 macrophages and high immune-checkpoint expression (PDCD1, CTLA4, TIGIT), along with a lower TIDE score, suggesting potentially greater benefit from immune-checkpoint blockade. The RiskScorehigh group was more sensitive to Gemcitabine and Oxaliplatin, whereas the RiskScorelow group responded better to BI-2536 and NU7441. Cellular functional assays confirmed high expression of SLC40A1 in ESCC cells. SLC40A1 knockdown significantly inhibited cell proliferation, migration, and invasion. Additionally, cells exhibited greater sensitivity to Gemcitabine than to BI-2536.
CONCLUSION
MMRG-based subtyping and the reliable prognostic risk score model provide novel insights for predicting prognosis and developing personalized therapy in ESCC.
Long Li, Ying Zhang, Qi Li et al.· Arab Journal of Gastroentero...· 0 citations
