Identification of several senescence-associated genes signature in head and neck squamous cell carcinoma

TMCO1, as a potential biomarker of prognosis and immunotherapy response, regulates head and neck squamous cell carcinoma proliferation and migration

Transmembrane and coiled-coil domains 1 (TMCO1), an endoplasmic reticulum transmembrane protein, actively regulates intracellular Ca2+ concentration and is associated with poor prognosis in several cancers. This study shows that TMCO1 is a potential biological prognostic indicator and therapeutic target for head and neck squamous cell carcinoma (HNSCC) by regulating the proliferation and migration of cancer cells, especially migration. We obtained TMCO1 expression data of HNSCC and normal tissues from The Cancer Genome Atlas (TCGA) and other databases and verified them with immunohistochemical staining. The results showed that high TMCO1 expression was significantly associated with HNSCC survival and tumor progression and was an independent prognostic factor for HNSCC. In addition, nomogram and receiver operating characteristic (ROC) curve, gene ontology, gene concentration and gene network analysis were used to reveal the function and regulatory mechanism of TMCO1. In vitro experiments confirmed that TMCO1 could promote proliferation, migration, invasion, adhesion and clonal formation of HNSCC cells. Furthermore, we analyzed the relationship between TMCO1 and tumor microenvironment, immune infiltration, immunotherapy and drug sensitivity, and found that patients with low TMCO1 expression were more suitable for immunotherapy, and suggested the selection of chemotherapy drugs. In conclusion, TMCO1 is a reliable biomarker in HNSCC, offering valuable guidance for clinical diagnosis and therapeutic strategies. These findings highlight its potential as a target for precision oncology in HNSCC.

Development of a novel senescence-related gene signature to predict clinical outcomes, immune landscape, and chemotherapeutic sensitivity in oral squamous cell carcinoma

BACKGROUND

Cellular senescence significantly associates with tumor initiation, progression, and therapeutic response across multiple cancers. Here, we sought to develop a novel senescence-related genes (SRGs)-derived signature for oral squamous cell carcinoma (OSCC) prognostication and therapeutic response prediction.

METHODS

OSCC-specific SRG prognostic signature was established with univariate Cox regression, Kaplan-Meier survival, and LASSO-penalized multivariate Cox regression analyses. A SRG nomogram integrating this signature and selected clinicopathological parameters were constructed by multivariate Cox regression. SiRNA-mediated gene knockdown was exploited to validate its function in vitro. The utilities of SRG signature in predicting immune status and chemotherapeutic sensitivities were analyzed.

RESULTS

The prognostic performance of SRG signature/nomogram was satisfactory in multiple independent cohorts. CDK1 knockdown induced senescence phenotype in vitro. Moreover, SRG signature scores negatively correlated with tumor-infiltrating immune cells and associated with multiple chemotherapeutic drug sensitivities.

CONCLUSIONS

Our results established SRG-derived signature/nomogram as powerful predictors for prognosis and chemotherapeutic response for OSCC.

Comprehensive genomics analysis of aging related gene signature to predict the prognosis and drug resistance of colon adenocarcinoma

Background: Colon adenocarcinoma (COAD) is a heterogeneous tumor and senescence is crucial in the occurrence of cancer. This study aimed to identify senescence-based subtypes and construct a prognostic signature to predict the prognosis and guide immunotherapy or chemotherapy decisions for COAD patients. Methods: Based on the single-cell RNA sequencing (scRNA-seq) data of 13 samples from the Gene Expression Omnibus (GEO) database, we assessed cellular senescence characteristics. Transcriptome data, copy number variations (CNVs) and single nucleotide variations (SNVs) data were obtained from The Cancer Genome Atlas (TCGA) database. GSE39582 and GSE17537 were used for validation. Senescence subtypes were identified using unsupervised consensus clustering analysis, and a prognostic signature was developed using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO). Response of risk groups to chemotherapy was predicted using the half-maximal inhibitory concentration (IC50) values. We further analyzed the relationship between risk gene expression and methylation level. The prediction performance was assessed by nomogram. Results: Senescence-related pathways were highly enriched in malignant cells and bulk RNA-seq verified cellular senescence. Three senescence subtypes were identified, in which patients in clust3 had poorest prognosis and higher T stage, accompanied with higher tumor mutation burden (TMB) and mutations, activated inflammatory response, more immune cell infiltration, and higher immune escape tendency. A senescence-based signature using 11 genes (MFNG, GPRC5B, TNNT1, CCL22, NOXA1, PABPC1L, PCOLCE2, MID2, CPA3, HSPA1A, and CALB1) was established, and accurately predicted a lower prognosis in high risk patients. Its robustness was validated by external cohort. Low risk patients were more sensitive to small molecule drugs including Erlotinib, Sunitinib, MG-132, CGP-082996, AZ628, Sorafenib, VX-680, and Z-LLNle-CHO. Risk score was an independent prognostic factor and nomogram confirmed its reliability. Four risk genes (CALB1, CPA3, NOXA1, and TNNT1) had significant positive correlation with their methylation level, while six genes (CCL22, GPRC5B, HSPA1A, MFNG, PABPC1L, and PCOLCE2) were negatively correlated with their methylation level. Conclusion: This study provides novel understanding of heterogeneity in COAD from the perspective of senescence, and develops signatures for prognosis prediction in COAD.