Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer

NXPH4 can be used as a biomarker for pan-cancer and promotes colon cancer progression

NXPH4 promotes cancer proliferation and invasion. However, its specific role and mechanism in cancer remain unclear. Transcriptome and clinical data for pan-cancer were derived from the TCGA database. K-M survival curve and univariate Cox were used for prognostic analysis. CIBERSORT and TIMER algorithms were employed to calculate immune cell infiltration. Gene set enrichment analysis (GSEA) was employed for investigating the function of NXPH4. Western blot verified differential expression of NXPH4 in colon cancer. Functional assays (CCK-8, plate clonogenicity assay, wound healing assay, and Transwell assay) confirmed the impact of NXPH4 on proliferation, invasion, and migration of colon cancer cells. Dysregulation of NXPH4 in pan-cancer suggests its potential as a diagnostic and prognostic marker for certain cancers, including colon and liver cancer. High expression of NXPH4 in pan-cancer might be associated with the increase in copy number and hypomethylation. NXPH4 expression in pan-cancer is substantially linked to immune cell infiltration in the immune microenvironment. NXPH4 expression is associated with the susceptibility to immunotherapy and chemotherapy. Western blot further confirmed the higher expression of NXPH4 in colon cancer. Knockdown of NXPH4 significantly suppresses proliferation, invasion, and migration of colon cancer cell lines HT-29 and HCT116, as validated by functional assays.

SYNPO2 promotes the development of BLCA by upregulating the infiltration of resting mast cells and increasing the resistance to immunotherapy

Synaptopodin 2 (SYNPO2) plays a pivotal role in regulating tumor growth, development and progression in bladder urothelial Carcinoma (BLCA). However, the precise biological functions and mechanisms of SYNPO2 in BLCA remain unclear. Based on TCGA database‑derived BLCA RNA sequencing data, survival analysis and prognosis analysis indicate that elevated SYNPO2 expression was associated with poor survival outcomes. Notably, exogenous SYNPO2 expression significantly promoted tumor invasion and migration by upregulating vimentin expression in BLCA cell lines. Enrichment analysis revealed the involvement of SYNPO2 in humoral immune responses and the PI3K/AKT signaling pathway. Moreover, increased SYNPO2 levels increased the sensitivity of BLCA to PI3K/AKT pathway‑targeted drugs while being resistant to conventional chemotherapy. In in vivo BLCA mouse models, SYNPO2 overexpression increased pulmonary metastasis of 5637 cells. High SYNPO2 expression led to increased infiltration of innate immune cells, particularly mast cells, in both nude mouse model and clinical BLCA samples. Furthermore, tumor immune dysfunction and exclusion score showed that patients with BLCA patients and high SYNPO2 expression exhibited worse clinical outcomes when treated with immune checkpoint inhibitors. Notably, in the IMvigor 210 cohort, SYNPO2 expression was significantly associated with the population of resting mast cells in BLCA tissue following PD1/PDL1 targeted therapy. In conclusion, SYNPO2 may be a promising prognostic factor in BLCA by modulating mast cell infiltration and exacerbating resistance to immune therapy and conventional chemotherapy.

The Role of CPNE7 (Copine-7) in Colorectal Cancer Prognosis and Metastasis

Colorectal cancer (CRC) is one of the most common and deadly cancers in the world. However, no effective treatment for the disease has yet been found. For this reason, several studies are being carried out on the treatment of CRC. Currently, there is limited understanding of the role of CPNE7 (copine-7) in CRC progression and metastasis. The results of this study show that CPNE7 exerts an oncogenic effect in CRC. First, CPNE7 was shown to be significantly up-regulated in CRC patient tissues and CRC cell lines compared to normal tissues according to IHC staining, qRT-PCR, and western blotting. Next, this study used both systems of siRNA and shRNA to suppress CPNE7 gene expression to check the CPNE7 mechanism in CRC. The suppressed CPNE7 significantly inhibited the growth of CRC cells in in vitro experiments, including migration, invasion, and semisolid agar colony-forming assay. Moreover, the modified expression of CPNE7 led to a decrease in the levels of genes associated with epithelial-mesenchymal transition (EMT). The epithelial genes E-cadherin (CDH1) and Collagen A1 were upregulated, and the levels of mesenchymal genes such as N-cadherin (CDH2), ZEB1, ZEB2, and SNAIL (SNAL1) were downregulated after CPNE7 inhibition. This study suggests that CPNE7 may serve as a potential diagnostic biomarker for CRC patients.

Integrative analysis reveals a four-gene signature for predicting survival and immunotherapy response in colon cancer patients using bulk and single-cell RNA-seq data

Background

Colon cancer (CC) ranks as one of the leading causes of cancer-related mortality globally. Single-cell transcriptome sequencing (scRNA-seq) offers precise gene expression data for distinct cell types. This study aimed to utilize scRNA-seq and bulk transcriptome sequencing (bulk RNA-seq) data from CC samples to develop a novel prognostic model.

Methods

scRNA-seq data was downloaded from the GSE161277 database. R packages including "Seurat", "Harmony", and "singleR" were employed to categorize eight major cell types within normal and tumor tissues. By comparing tumor and normal samples, differentially expressed genes (DEGs) across these major cell types were identified. Gene Ontology (GO) enrichment analyses of DEGs for each cell type were conducted using "Metascape". DEGs-based signature construction involved Cox regression and least absolute shrinkage operator (LASSO) analyses, performed on The Cancer Genome Atlas (TCGA) training cohort. Validation occurred in the GSE39582 and GSE33382 datasets. The expression pattern of prognostic genes was verified using spatial transcriptome sequencing (ST-seq) data. Ultimately, an established prognostic nomogram based on the gene signature and age was established and calibrated. Sensitivity to chemotherapeutic drugs was predicted with the "oncoPredict" R package.

Results

Using scRNA-Seq data, we examined 33,213 cells, categorizing them into eight cell types within normal and tumor samples. GO enrichment analysis revealed various cancer-related pathways across DEGs in these cell types. Among the 55 DEGs identified via univariate Cox regression, four independent prognostic genes emerged: PTPN6, CXCL13, SPINK4, and NPDC1. Expression validation through ST-seq confirmed PTPN6 and CXCL13 predominance in immune cells, while SPINK4 and NPDC1 were relatively epithelial cell-specific. Creating a four-gene prognostic signature, Kaplan-Meier survival analyses emphasized higher risk scores correlating with unfavorable prognoses, confirmed across training and validation cohorts. The risk score emerged as an independent prognostic factor, supported by a reliable nomogram. Intriguingly, drug sensitivity analysis unveiled contrasting anti-cancer drug responses in the two risk groups, suggesting significant clinical implications.

Conclusion

We developed a novel prognostic four-gene risk model, and these genes may act as potential therapeutic targets for CC.