Generalized machine learning based on multi-omics data to profile the effect of ferroptosis pathway on prognosis and immunotherapy response in patients with bladder cancer.

INTRODUCTION: Bladder cancer (BLCA) affects millions of people worldwide, with high rates of incidence and mortality. Ferroptosis proves to be a novel form of cell death process that is triggered by oxidative stress. METHODS: We procured a total of 25 single nuclear RNA-seq (snRNA-seq) samples from GSE169379 in GEO database. We obtained different cohorts of BLCA patients from the TCGA and GEO databases for model training and validation. A total of 369 ferroptosis-related genes (FRGs) were selected from the FerrDb database. AUCell analysis was performed to assign ferroptosis scores to all the cell types. Weighted Gene Co-Expression Network Analysis (WGCNA), COX, and LASSO regression analysis were conducted to retain and finalize the genes of prognostic values. Various bioinformatic approaches were utilized to depict immune infiltration profile. We conducted a series of colony formation analysis, flow cytometry and western blot (WB) analysis to determine the role of SKAP1 in BLCA. RESULTS: We divided the cells into high ferroptosis group and low ferroptosis group according to ferroptosis activity score, and then screened 2150 genes most associated with ferroptosis by differential expression analysis, which are related to UV-induced DNA damage, male hormone response, fatty acid metabolism and hypoxia. Subsequently, WGCNA algorithm further screened 741 ferroptosis related genes from the 2150 genes for the construction of prognostic model. Lasso-Cox regression analysis was used to construct the prognostic model, and the prognostic model consisting of 6 genes was obtained, namely JUN, SYT1, MAP3K8, GALNT14, TCIRG1, and SKAP1. Next, we constructed a nomogram model that integrated clinical factors to improving the accuracy. In addition, we performed drug sensitivity analyses in different subgroups and found that Staurosporine, Rapamycin, Gemcitabine, and BI-2536 may be candidates for the drugs treatment in high-risk populations. The ESTIMATE results showed higher stromal scores, immune scores, and ESTIMATE scores in the low-risk group, indicating a higher overall immunity level and immunogenicity of tumor microenvironment (TME) in this group, and tumor immune dysfunction and exclusion (TIDE) analysis confirmed a better response to immunotherapy in the low-risk group. Finally, we selected the oncogene SKAP1 in the prognostic gene for in vitro validation, and found that SKAP1 directly regulated BLCA cell proliferation and apoptosis. CONCLUSION: We identified a set of six genes, JUN, SYT1, MAP3K8, GALNT14, TCIRG1, and SKAP1, that exhibited significant potential in stratification of BLCA patients with varying prognosis. In addition, we uncovered the direct regulatory effect of SKAP1 on BLCA cell proliferation and apoptosis, shedding some light on the role of FRGs in pathogenesis of BLCA.

The kinesin-14 family motor protein KIFC2 promotes prostate cancer progression by regulating p65.

The kinesin-14 motor proteins play important roles in tumor development and drug resistance and have been reported as potential biomarkers or therapeutic targets for tumor treatment. However, kinesin family member C2 (KIFC2), one of the kinesin-14 motor family members, remains largely unknown in prostate cancer (PCa) progression. Here, we used the GEO and The Cancer Genome Atlas datasets, Western blotting, and immunohistochemistry analyses to detect KIFC2 expression in PCa tissues. Additionally, a series of in vivo and in vitro experiments were utilized to demonstrate the roles of KIFC2 in PCa cells. We found that KIFC2 was highly expressed and positively correlated with the clinicopathological characteristics in PCa. Functional experiments indicated that KIFC2 could promote PCa progression. Furthermore, we performed an analysis of the KEGG and GSEA databases, subcellular fractionation, and immunofluorescence to investigate the potential mechanisms of KIFC2 in PCa. We confirmed that KIFC2 could regulate the NF-κB pathway via mediating NF-κB p65 protein expression and nuclear translocation thereby promoting PCa progression and chemotherapeutic resistance. Together, our results suggest that KIFC2 is overexpressed in PCa. By regulating the NF-κB pathway, KIFC2 may play a crucial role in PCa.