Background: Hepatocellular carcinoma (HCC) is a malignant tumor associated with high morbidity and mortality. Therefore, it is of great importance to develop effective prognostic models and guide clinical treatment in HCC. Protein lactylation is found in HCC tumors and is associated with HCC progression. Methods: The expression levels of lactylation-related genes were identified from the TCGA database. A lactylation-related gene signature was constructed using LASSO regression. The prognostic value of the model was assessed and further validated in the ICGC cohort, with the patients split into two groups based on risk score. Glycolysis and immune pathways, treatment responsiveness, and the mutation of signature genes were analyzed. The correlation between PKM2 expression and the clinical characteristics was investigated. Results: Sixteen prognostic differentially expressed lactylation-related genes were identified. An 8-gene signature was constructed and validated. Patients with higher risk scores had poorer clinical outcomes. The two groups were different in immune cell abundance. The high-risk group patients were more sensitive to most chemical drugs and sorafenib, while the low-risk group patients were more sensitive to some targeted drugs such as lapatinib and FH535. Moreover, the low-risk group had a higher TIDE score and was more sensitive to immunotherapy. PKM2 expression correlated with clinical characteristics and immune cell abundance in the HCC samples. Conclusions: The lactylation-related model exhibited robust predictive efficiency in HCC. The glycolysis pathway was enriched in the HCC tumor samples. A low-risk score indicated better treatment response to most targeted drugs and immunotherapy. The lactylation-related gene signature could be used as a biomarker for the effective clinical treatment of HCC.

Background: Afatinib, a second-generation tyrosine kinase inhibitor (TKI), exerts its radiosensitive effects in nasopharyngeal carcinoma (NPC). However, the detailed mechanism of afatinib-mediated sensitivity to radiation is still obscure in NPC. Methods: Quantitative phosphorylated proteomics and bioinformatics analysis were performed to illustrate the global phosphoprotein changes. The activity of the CD44-Stat3 axis and Epithelial-Mesenchymal Transition (EMT)-linked markers were evaluated by Western blotting. Wound healing and transwell assays were used to determine the levels of cell migration upon afatinib combined IR treatment. Cell proliferation was tested by CCK-8 assay. A pharmacological agonist by IL-6 was applied to activate Stat3. The xenograft mouse model was treated with afatinib, radiation or a combination of afatinib and radiation to detect the radiosensitivity of afatinib in vivo. Results: In the present study, we discovered that afatinib triggered global protein phosphorylation alterations in NPC cells. Further, bioinformatics analysis indicated that afatinib inhibited the CD44-Stat3 signaling and subsequent EMT process. Moreover, functional assays demonstrated that afatinib combined radiation treatment remarkably impeded cell viability, migration, EMT process and CD44-Stat3 activity in vitro and in vivo. In addition, pharmacological stimulation of Stat3 rescued radiosensitivity and biological functions induced by afatinib in NPC cells. This suggested that afatinib reversed the EMT process by blocking the activity of the CD44-Stat3 axis. Conclusion: Collectively, this work identifies the molecular mechanism of afatinib as a radiation sensitizer, thus providing a potentially useful combination treatment and drug target for NPC radiosensitization. Our findings describe a new function of afatinib in radiosensitivity and cancer treatment.

Lung adenocarcinoma (LUAD) is one of the most malignant tumors with high morbidity and mortality worldwide due to the lack of reliable methods for early diagnosis and effective treatment. It’s imperative to study the mechanism of its development and explore new biomarkers for early detection of LUAD. In this study, the Gene Expression Omnibus (GEO) dataset GSE43458 and The Cancer Genome Atlas (TCGA) were used to explore the differential co-expressed genes between LUAD and normal samples. Three hundred sixity-six co-expressed genes were identified by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) method. Those genes were mainly enriched in ameboidal-type cell migration (biological process), collagen-containing extracellular matrix (cell component), and extracellular matrix structure constituent (molecular function). The protein-protein network (PPI) was constructed and 10 hub genes were identified, including IL6, VWF, CDH5, PECAM1, EDN1, BDNF, CAV1, SPP1, TEK, and SELE. The expression level of hub genes was validated in the GEPIA database, compared with normal tissues, VWF is lowly expressed and SPP1 is upregulated in LUAD tissues. The survival analysis showed increased expression of SPP1 indicated unfavorable prognosis whereas high expression of VWF suggested favorable prognosis in LUAD (p < 0.05). Based on the immune infiltration analysis, the relationship between SPP1 and VWF expression and macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD. Quantitative real-time PCR (qRT-PCR) and western blotting were used to validate the expression of VWF and SPP1 in normal human bronchial epithelial (HBE) cell and three LUAD cell lines, H1299, H1975, and A549. Immunohistochemistry (IHC) was further performed to detect the expression of VWF in 10 cases LUAD samples and matched normal tissues. In summary, the data suggest that VWF is a potential novel biomarker for prognosis of LUAD.