PANoptosis is a newly-discovered cell death pathway that involves crosstalk and co-ordination between pyroptosis, apoptosis, and necroptosis processes. However, the roles of PANoptosis-related genes (PRGs) in prognosis and immune landscape of colon cancer remain widely unknown. Here, we performed a bioinformatics analysis of expression data of nineteen PRGs identified from previous studies and clinical data of colon cancer patients obtained from TCGA and GEO databases. Colon cancer cases were divided into two PRG clusters, and prognosis-related differentially expressed genes (PRDEGs) were identified. The patient data were then separated into two corresponding distinct gene clusters, and the relationship between the risk score, patient prognosis, and immune landscape was analyzed. The identified PRGs and gene clusters correlated with patient survival and immune system and cancer-related biological processes and pathways. A prognosis signature based on seven genes was identified, and patients were divided into high-risk and low-risk groups based on the calculated risk score. A nomogram model for prediction of patient survival was also developed based on the risk score and other clinical features. Accordingly, the high-risk group showed worse prognosis, and the risk score was related to immune cell abundance, cancer stem cell (CSC) index, checkpoint expression, and response to immunotherapy and chemotherapeutic drugs. Results of quantitative real-time polymerase chain reaction (qRT-PCR) showed that LGR5 and VSIG4 were differentially expressed between normal and colon cancer samples. In conclusion, we demonstrated the potential of PANoptosis-based molecular clustering and prognostic signatures for prediction of patient survival and tumor microenvironment (TME) in colon cancer. Our findings may improve our understanding of the role of PANoptosis in colon cancer, and enable the development of more effective treatment strategies.
Collagen triple helix repeat containing-1 (CTHRC1), highly expressed in multiple human solid tumors, has been identified as a tumor associated protein. However, its specific role and mechanism with immune infiltrates in gastric cancer are still unclear. In this study, we systematically explored and validated the expression and prognostic value of CTHRC1 in gastric cancer by integrating the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Genome Sequence Archive (GSA) datasets. Compared to adjacent normal tissues, we observed that CTHRC1 was highly overexpressed in tumor sample of multiple cancers. It was revealed that CTHRC1 overexpression was positively correlated with the T stage in gastric cancer but not lymph nodes metastasis from TCGA dataset. In addition, CTHRC1 expression may induce tumor associated macrophage infiltration though GRN/TNFRSF1A and AnxA1/FPR1 pathways and also tumor angiogenesis in gastric cancer. In this context, our results indicate that CTHRC1 plays a pivotal role in regulating the angiogenesis and macrophage infiltration in tumor microenvironment, and also can predict poor prognosis in gastric cancer, suggesting that CTHRC1 might be a promising novel immunotherapy and angiogenesis target for gastric cancer.