Comprehensive analysis of basement membrane-related gene based on single-cell and bulk RNA sequencing data to predict prognosis and evaluate immune characteristics in colorectal cancer.

AIMS: Basement membrane-related genes (BMs) participate in regulating cell polarity, invasion, metastasis, and survival across different tumor types. Nevertheless, the specific functions of BMs in colorectal cancer (CRC) remain uncertain. METHODS: To investigate the clinical relevance of BMs in CRC, we retrieved both gene expression and clinical data from The Cancer Genome Atlas (TCGA) datasets for subsequent analysis. The Kaplan-Meier (K-M) survival curve was employed to evaluate prognosis in high- and low-risk groups. Furthermore, additional analyses, including nomogram construction, functional enrichment, examination of the tumor immune microenvironment, prediction of small-molecule drugs, and more, were conducted to delve into the significance of BM-related signatures in CRC. Single-cell data from seven CRC patients were obtained from the TISCH2 database, and expression validation and cell source exploration of BM-related signatures were performed. Lastly, the expression and function of TIMP1, a key gene in BMs that may play a role in the progression of CRC, was validated in vitro through a series of basic experiments. RESULTS: We constructed a seven BMs-based model to categorize CRC patients into high-risk and low-risk groups. K-M survival analysis indicated a poorer prognosis for high-risk CRC patients. Cox regression analysis further identified the risk score as an independent prognostic factor for CRC patients. The nomogram model exhibited superior discrimination and calibration abilities of CRC patients. Based on the results from GO/KEGG and GSEA, genes in the high-risk subgroup were implicated in immune-related pathways and exhibited a positive correlation with immune checkpoints. In single-cell data, we found that TIMP1 is highly expressed in many cells, especially in malignant tumor cells. We also observed up-regulation of TIMP1 in CRC cell lines, promoting cancer invasion and migration in vitro. CONCLUSIONS: Our study has discovered a novel prognostic index derived from BM-related genes in CRC patients. Specifically, the new model enables patient stratification, improving the selection of individuals likely to benefit from immunotherapy.

Comprehensive characterization of adipogenesis-related genes in colorectal cancer for clinical significance and immunogenomic landscape analyses.

OBJECTIVE: Colorectal cancer (CRC) is a major global health concern, necessitating the identification of biomarkers and molecular subtypes for improved clinical management. This study aims to evaluate the clinical value of adipogenesis-related genes and molecular subtypes in CRC. METHODS: A comprehensive analysis of adipogenesis-related genes in CRC was performed using publicly available datasets (TCGA and GEO database) and bioinformatics tools. Unsupervised cluster analysis was employed to identify the molecular subtypes of CRC, while LASSO regression analysis was utilized to develop a risk prognostic model. The immunogenomic patterns and immunotherapy analysis were used to predict patient response to immunotherapy. Furthermore, qPCR analysis was conducted to confirm the expression of the identified key genes in vitro. RESULTS: Through the analysis of RNAseq data from normal and tumor tissues, we identified 50 differentially expressed genes. Unsupervised cluster analysis identified two subtypes (Cluster A and Cluster B) with significantly different survival outcomes. Cluster A and B displayed differential immune cell compositions and enrichment in specific biological pathways, providing insights into potential therapeutic targets. A risk-scoring model was developed using five ARGs, which successfully classified patients into high and low-risk groups, showing distinct survival outcomes. The model was validated and showed robust predictive performance. High-risk patients exhibited altered immune cell proportions and gene expression patterns compared to low-risk patients. In qPCR validation, four out of the five key genes were consistent with the results of bioinformatics analysis. CONCLUSION: Overall, the findings of our investigation offer valuable understanding regarding the clinical relevance of ARGs and molecular subtypes in CRC, laying the groundwork for improved precision medicine applications and personalized treatment modalities.

Transcription activation of SPINK4 by ELF-1 augments progression of colon cancer by regulating biological behaviors.

BACKGROUND: SPINK4 was highly expressed in colorectal cancer and resulted in worse prognosis of colorectal cancer patients. However, the expression and function of SPINK4 in colon cancer have not been revealed. METHODS: Analysis from GEPIA website showed the expression and function of SPINK4 in colon cancer samples. Colon cancer cell lines were applied to detect the biological function of SPINK4. Functionally, the transcriptional factor of SPINK4 has been predicted and verified. Finally, the associations between transcriptional factor and SPINK4 have been confirmed. RESULTS: SPINK4 expression was obviously increased in colon cancer samples. HCT-116 and DXH-1 cells in si-SPINK4-1 or si-SPINK4-2 group displayed an obvious reduction in its proliferation, cell cycle, invasion and migration compared to those in the si-control group. Moreover, transcriptional factor ELF-1 bound to the promoter of SPINK4 and affected its expression in colon cancer cells. High ELF-1 expression was presented in colon cancer samples and resulted in worse prognosis of colon cancer patients. Additionally, si-SPINK4 antagonized the function of ELF-1 overexpression in modulating colon cancer cell proliferation, cell cycle and mobility. CONCLUSIONS: Our findings afforded a theoretical basis for further research on the treatment of colon cancer based on the control of ELF-1/SPINK4 expression.

Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer.

Background: Inflammation and immune cell dysfunction have been widely known as an essential role in the tumorigenesis of colorectal cancer (CRC). Yet, the role of tumor inflammation signature (TIS) associated with CRC prognosis, immune infiltration, and drug resistance remained unknown. Method: The transcriptome sequencing data, as well as clinical data of CRC from the public dataset, were acquired for further investigation. Inflammation-related gene expression patterns were obtained and analyzed. Bioinformatics methods were used to build a prognostic TIS, and its prediction accuracy was verified by using ROC curve analyses. The independent prognostic factors in CRC were identified through multivariable Cox regression analysis. In addition, the specific features of the immunological landscape between low- and high-risk CRC cohorts were analyzed. Results: We firstly screened the differentially expressed inflammation-related genes in CRC and constructed a prognostic TIS. We further classified CRC patients into high or low TIS score groups based on the optimal cutoff of prognostic TIS, and patients with high-risk scores had shorter overall survival (OS) than those in the low-risk cohort. The diagnostic accuracy of TIS was evaluated and confirmed with ROC analysis. The result of the univariate and multivariate analysis found that TIS was directly and independently linked to OS of CRC. Otherwise, an optimal nomogram model based on TIS exhibited a better prognostic accuracy in OS. Finally, the immunological status and immune cell infiltration were observed different in the two-risk cohorts. Conclusion: In summary, the risk model of the TIS in CRC was found to be useful for predicting patient prognosis and guiding individual treatment. This risk signature could also serve as potential biomarkers and immunotherapeutic targets and indicate immunotherapy response for patients with CRC.