Development of a KRAS-Associated Metabolic Risk Model for Prognostic Prediction in Pancreatic Cancer.

BACKGROUND: KRAS was reported to affect some metabolic genes and promote metabolic reprogramming in solid tumors. However, there was no comprehensive analysis to explore KRAS-associated metabolic signature or risk model for pancreatic cancer (PC). METHODS: In the current study, multiple bioinformatics analyses were used to identify differentially expressed metabolic genes based on KRAS mutation status in PC. Then, we developed and validated a prognostic risk model based on the selected KRAS-associated metabolic genes. Besides, we explored the association between the risk model and the metabolic characteristics as well as gemcitabine-associated chemoresistance in PC. RESULTS: 6 KRAS-associated metabolic genes (i.e., CYP2S1, GPX3, FTCD, ENPP2, UGT1A10, and XDH) were selected and enrolled to establish a prognostic risk model. The prognostic model had a high C-index of 0.733 for overall survival (OS) in TCGA pancreatic cancer database. The area under the curve (AUC) values of 1- and 3-year survival were both greater than 0.70. Then, the risk model was validated in two GEO datasets and also presented a satisfactory discrimination and calibration performance. Further, we found that the expression of some KRAS-driven glycolysis-associated genes (PKM, GLUT1, HK2, and LDHA) and gemcitabine-associated chemoresistance genes (i.e., CDA and RMM2) was significantly upregulated in high-risk PC patients evaluated by the risk model. CONCLUSIONS: We constructed a risk model based on 6 KRAS-associated metabolic genes, which predicted patients' survival with high accuracy and reflected tumor metabolic characteristics and gemcitabine-associated chemoresistance in PC.

SLC39A10 Upregulation Predicts Poor Prognosis, Promotes Proliferation and Migration, and Correlates with Immune Infiltration in Hepatocellular Carcinoma.

BACKGROUND: Recent evidence has shown that Solute Carrier Family 39 Member 10 (SLC39A10) promoted tumor progression in several cancer types. The study intended to explore the expression and function of SLC39A10 in hepatocellular carcinoma (HCC). METHODS: Multiple bioinformatics analyses were used to evaluate SLC39A10 expression and potential role in HCC. Quantitative real-time polymerase chain reaction and immunohistochemistry were used to confirm SLC39A10 expression. Intro studies were performed to assess the effects of SLC39A10 on HCC cells proliferation and migration. Furthermore, flow cytometry was conducted to identify its specific function in apoptosis of HCC. RESULTS: SLC39A10 was significantly over-expressed in HCC samples from both bioinformatic databases and our cohort. Survival analyses suggested patients with high expression of SLC39A10 had poor overall survival and disease-free survival (P-value <0.01). Further, the expression of SLC39A10 was positively correlated with tumor-infiltrating lymphocytes and some immune checkpoints like CTLA4, TIM3 and TGFB1. In HCC cell lines, SLC39A10 knockdown inhibited cells proliferation and migration, but promoted apoptosis. CONCLUSION: An increased SLC39A10 expression was found and served as an unfavorable indicator of survival in HCC. Further studies suggested SLC39A10 promotes tumor aggressiveness and may provide a novel target for HCC therapy.

Identification of Prognostic and Therapeutic Biomarkers among FAM83 Family Members for Pancreatic Ductal Adenocarcinoma.

Family with sequence similarity 83 (FAM83) members were shown recently to have oncogenic effect in a variety of cancer types, but the biological roles and prognostic value of FAM83 family in pancreatic ductal adenocarcinoma remain unknown. In the current study, the clinical significance and molecular function of the FAM83 family were assessed by multiple bioinformatics analysis. Besides, potential associations between differentially expressed genes (DEGs) of FAM83 family and antitumor immunity were evaluated using TIMER and TISIDB analyses. As the results show, FAM83A, FAM83D, FAM83E, and FAM83H were significantly upregulated in PDAC and were identified as DEGs. Higher expression of FAM83A, FAM83B, FAM83D, FAM83E, and FAM83H were associated with advanced tumor stage or worse patient prognosis. Importantly, the overexpression of DEGs was found to be significantly correlated with activated KRAS and loss of SMAD4, which are important drivers for PDAC. Further, FAM83A, FAM83D, and FAM83H were associated with CD8+ T cell, Gamma Delta T cell, and CD4+ T cell infiltration in PDAC and FAM83H was found closely correlated with some immunomodulators including immunoinhibitors, immunostimulators, and MHC molecules. In conclusion, FAM83A, FAM83D, FAM83E, and FAM83H have significant prognostic value in PDAC and they may play important roles in regulating tumor progression and the immune cell infiltration.