Cholangiocarcinoma (CCA) is a lethal malignancy in the hepatobiliary system, with dysregulated protein expression and phosphorylation signaling. However, the protein and phosphorylation signatures of CCAs are little-known. Here, we performed the proteomic and phosphoproteomic profiling of tumors and normal adjacent tissues (NATs) from patients with CCA and predicted eleven PKs high-potentially related to CCA with a comprehensive inference of the functional protein kinases (PKs) (CifPK) pipeline. Besides the two known CCA-associated PKs, we screened the remaining candidates and uncovered five PKs as novel regulators in CCA. Specifically, the protein kinase D (PKD) family members, including PRKD1, PRKD2, and PRKD3, were identified as critical regulators in CCA. Moreover, the pan-inhibitor of the PKD family, 1-naphthyl PP1 (1-NA-PP1), was validated as a potent agent for inhibiting the proliferation, migration, and invasion ability of CCA cells. This study reveals new PKs associated with CCA and suggests PRKD kinases as novel treatment targets for CCA.

Hepatocellular Carcinoma (HCC) is related to dysregulated lipid metabolism and immunosuppressive microenvironment. This study developed a genetic risk model using lipid metabolism-related genes to predict survival and immune patterns in HCC patients. Differentially expressed genes (DEGs) related to lipid metabolism were identified in HCC via the TCGA-LIHC dataset. A risk model for survival prediction was constructed via DEGs related to survival. The immune signature associated with the risk model was also evaluated by the CIBERSORT algorithm, tumor immune dysfunction and exclusion algorithm, and single sample gene set enrichment analysis. This study identified six lipid metabolism-related genes, ADH4, LCAT, CYP2C9, CYP17A1, LPCAT1, and ACACA, to construct a lipid metabolism-related gene risk model that can divide HCC patients into low- and high-risk groups. Internal and external validation verified that the risk model could be a signature that could effectively predict HCC patient prognosis. High-risk patients showed disrupted immune cell profiles, reduced tumor-killing capacity, and increased expression of immune checkpoint genes. However, they responded more favorably to immune checkpoint inhibitor (ICB) therapy. The top ten hub genes related to the risk model were associated with tumor progression and deteriorating prognosis. In vitro experiments verified that the downregulation of the top 1 hub gene CDK1 was correlated to the HCC cell proliferation. The risk model constructed using lipid metabolism-related genes could effectively predict prognosis and was related to the immunosuppressive microenvironment and ICB immunotherapy. The hub genes related to the risk model were potential therapeutic targets.

Biliary atresia (BA) is a severe and progressive biliary obstructive disease in infants that requires early diagnosis and new therapeutic targets. This study employed bioinformatics methods to identify diagnostic biomarkers and potential therapeutic targets for BA. Our analysis of mRNA expression from Gene Expression Omnibus datasets revealed 3,273 differentially expressed genes between patients with BA and those without BA (nBA). Weighted gene coexpression network analysis determined that the turquoise gene coexpression module, consisting of 298 genes, is predominantly associated with BA. The machine learning method then filtered out the top 2 important genes, CXCL8 and TMSB10, from the turquoise module. The area under receiver operating characteristic curves for TMSB10 and CXCL8 were 0.961 and 0.927 in the training group and 0.819 and 0.791 in the testing group, which indicated a high diagnostic value. Besides, combining TMSB10 and CXCL8, a nomogram with better diagnostic performance was built for clinical translation. Several studies have highlighted the potential of CXCL8 as a therapeutic target for BA, while TMSB10 has been shown to regulate cell polarity, which was related to BA progression. Our analysis with qRT PCR and immunohistochemistry also confirmed the upregulation of TMSB10 at mRNA and protein levels in BA liver samples. These findings highlight the sensitivity of CXCL8 and TMSB10 as diagnostic biomarkers and their potential as therapeutic targets for BA.

Background The role of hypoxia and immunity in the progression of hepatocellular carcinoma (HCC) was highly critical. However, there were few application-based studies on hypoxia and immune molecules in HCC prognosis prediction. This study aims to reveal the prognostic significance of hypoxia- and immune-related genes in HCC. Methods We identified the hypoxia- and immune-related differentially expressed genes (HIDEGs) from the Cancer Genome Atlas (TCGA). Seven HIDEGs associated with the prognosis of HCC were identified with the Cox regression and LASSO analysis. The prognosis model was validated in both the TCGA (n = 420) and Gene Expression Omnibus (GEO) (GSE14520-GPL3921, n = 222) databases. CIBERSORT was applied to measure the fractions of immune cell types. The drug sensitivity analysis was used to evaluate the applicability of drug treatment to HCC patients. The effect of ADM on the malignant biological behaviors of HCC was measured by plate colony formation assay, Cell Counting Kit-8 (CCK-8) assay, scratch wound assay and Transwell migration and invasion assays. Results We identified 78 HIRDEGs associated with survival time in HCC, among them, seven genes were chosen to construct a prognosis model. The prognosis model showed good performance in predicting prognosis in HCC patients in both the TCGA (n = 420) and Gene Expression Omnibus (GEO) (GSE14520-GPL3921, n = 222) databases. Based on the median risk score, HCC patients were classified into high- and low-risk groups. The high-risk group suffered worse survival time and contained higher proportions of M0/M1 macrophages and monocytes, and showed greater expression of classical immune checkpoints, including PD-1, PD-L1, and CTLA4. Furthermore, we presented that ADM was up-regulated by hypoxia, and silencing its expression suppressed HCC cells proliferation, migration, and invasion in vitro. Conclusion The hypoxia- and immune-related signatures are promising biomarkers for HCC prognosis. ADM might be a novel target for HCC treatment.

Breast cancer remains one of the most deadly cancers, highlighting the urgent need for better prognostic markers and treatment targets. Emerging evidence suggests that inflammation-driven immune dysregulation plays a pivotal role in breast cancer progression and therapy resistance. Single-cell RNA sequencing and comprehensive gene network analysis based on inflammation identified FLT3LG as a crucial protective factor in breast cancer. Tumors with lower FLT3LG expression showed poorer survival outcomes across multiple patient cohorts. Functional analysis revealed its role in immune regulation, particularly in the activation of B cells and T cells, as well as in chemokine signaling. Genetic profiling revealed distinct mutation patterns: PIK3CA mutations were enriched in tumors with high FLT3LG expression, whereas TP53 mutations predominated in tumors with low FLT3LG expression. Correlations with immune cell infiltration and checkpoint markers suggested that FLT3LG may predict enhanced responses to immune checkpoint inhibitors and certain targeted drugs. These findings support its potential as a multifunctional biomarker for prognosis and therapeutic decision making in breast cancer.