ABSTRACT
PURPOSE: Hepatocellular carcinoma (HCC) is the most prevalent malignancies worldwide. Recently, oxidative phosphorylation (OXPHOS) has received extensive concern as an emerging target in antitumor therapy. However, the OXPHOS-involved underlying genes and clinical utilization in HCC remain worth exploring. The present research aimed to create an OXPHOS-relevant signature in HCC. PATIENTS AND METHODS: In this study, the prognostic signature genes linked with OXPHOS were identified, and prognostic models were built using least absolute shrinkage and selection operator (LASSO) cox regression analysis. Furthermore, the combination study of immune microenvironment and signature genes looked into the involvement of immune cells in signature-based genes in HCC. Following that, chemotherapeutic drug sensitivity and immunotherapy analysis was implemented to predict clinical efficacy in HCC patients. Finally, clinical samples were collected to measure the expression of OXPHOS-related signature genes. RESULTS: Following a series of screens, six prognostic signature genes related with OXPHOS were identified: MRPS23, MPV17, MAPK3, IGF2BP2, CDK5, and IDH2, on which a risk model was built. The findings revealed a significant drop in the survival rate of HCC patients as their risk score increased. Meanwhile, independent prognostic study demonstrated that the risk score could accurately identify HCC patients. Immuno-microenvironmental correlation research suggested that the prognostic characteristics could serve as a reference index for both immunotherapy and chemotherapy. Finally, RT-qPCR exhibited a trend in signature gene expression that was consistent with the results. CONCLUSION: In this study, a total of six prognostic genes associated with OXPHOS were selected and a prognostic model was constructed, providing an essential reference for the study of OXPHOS in HCC.
ABSTRACT
BACKGROUND: The efficacy of neoadjuvant chemotherapy (NAC) in advanced gastric cancer (GC) is still a controversial issue. AIM: To find factors associated with chemosensitivity to NAC treatment and to provide the optimal therapeutic strategies for GC patients receiving NAC. METHODS: The clinical information was collected from 230 GC patients who received NAC treatment at the Central South University Xiangya School of Medicine Affiliated Haikou Hospital from January 2016 to December 2020. Least absolute shrinkage and selection operator logistic regression analysis was used to find the possible predictors. A nomogram model was employed to predict the response to NAC. RESULTS: In total 230 patients were finally included in this study, including 154 males (67.0%) and 76 females (33.0%). The mean age was (59.37 ± 10.60) years, ranging from 24 years to 80 years. According to the tumor regression grade standard, there were 95 cases in the obvious response group (grade 0 or grade 1) and 135 cases in the poor response group (grade 2 or grade 3). The obvious response rate was 41.3%. Least absolute shrinkage and selection operator analysis showed that four risk factors significantly related to the efficacy of NAC were tumor location (P < 0.001), histological differentiation (P = 0.001), clinical T stage (P = 0.008), and carbohydrate antigen 724 (P = 0.008). The C-index for the prediction nomogram was 0.806. The calibration curve revealed that the predicted value exhibited good agreement with the actual value. Decision curve analysis showed that the nomogram had a good value in clinical application. CONCLUSION: A nomogram combining tumor location, histological differentiation, clinical T stage, and carbohydrate antigen 724 showed satisfactory predictive power to the response of NAC and can be used by gastrointestinal surgeons to determine the optimal treatment strategies for advanced GC patients.
ABSTRACT
Drug resistance in tumours has seriously hindered the therapeutic effect. Tumour drug resistance is divided into primary resistance and acquired resistance, and the recent study has found that a significant proportion of cancer cells can acquire stable drug resistance from scratch. This group of cells first enters the drug tolerance state (DT state) under drug pressure, and gradually acquires stable drug resistance through adaptive mutations in this state. Although the specific mechanisms underlying the formation of drug tolerant cells (DTCs) remain unclear, various proteins and signalling pathways have been identified as being involved in the formation of DTCs. In the current review, we summarize the characteristics, molecular mechanisms and therapeutic strategies of DTCs in detail.
ABSTRACT
Ubiquitin is a small protein that can be added onto target protein for inducing target degradation, thereby modulating the activity and stability of protein. Relatively, deubiquitinases (DUBs), a class catalase that can remove ubiquitin from substrate protein, provide a positive regulation of the protein amount at transcription level, post-translational modification, protein interaction, etc. The reversible and dynamic ubiquitination-deubiquitination process plays an essential role in maintaining protein homeostasis, which is critical to almost all the biological processes. Therefore, the metabolic dysregulation of deubiquitinases often lead to serious consequences, including the growth and metastasis of tumors. Accordingly, deubiquitinases can be served as key drug targets for the treatment of tumors. The small molecule inhibitors targeting deubiquitinases has become one of the hot spots of anti-tumor drug research areas. This review concentrated on the function and mechanism of deubiquitinase system in the proliferation, apoptosis, metastasis and autophagy of tumor cells. The research status of small molecule inhibitors of specific deubiquitinases in tumor treatment is introduced, aiming to provide reference for the development of clinical targeted drugs.
