Sulfiredoxin-1 is a promising novel prognostic biomarker for hepatocellular carcinoma

A refined therapeutic plan based on the machine-learning prognostic model of liver hepatocellular carcinoma

To deeply explore new strategy of the individual therapy for the patients with liver hepatocellular carcinoma (LIHC), we observed gene expression profile in patients with LIHC and made a comprehensive analysis of the inflammation-related phenotypes, we detected a set of characteristic genes associated with the biological activities of tumor cells, among which 3 genes and 2 lncRNAs are tagged on the LIHC prognosis. Then we constructed a novel prognostic model by machine learning, called Inf-PR model, and evaluated the drug sensitivity and immune targets by a series of bioinformatics tools. Ten-fold cross-validation testified that the model achieved excellent performance on prediction and classification of prognostic risks, which was not only able to get more reliable prognosis information than the age, gender, grade and stage, but also exceeded those previously reported similar models. Accordingly, drug sensitivity was detected in different prognostic risk groups, the result displayed that 10 FDA-approved small molecular drugs including lovastatin and sorafenib had higher sensitivities and perturbativities in the high-risk group, and other 15 drugs including doxorubicin and lenvatinib had better sensitivities and perturbativities in the low-risk group. Moreover, it suggested the patients with high risk would better combine with immunotherapy than those with low risk. Taken together, this study presents a new individual precision strategy about drug and target selection to treat LIHC based on this evaluation model, which is a powerful supplement for current anti-tumor therapy.

Hepatocellular carcinoma: Preclinical and clinical applications of nanotechnology with the potential role of carbohydrate receptors

Hepatocellular carcinoma (HCC) is one of the most common types of liver cancer; accounts for 75-85% of cases. The treatment and management of HCC involve different sanative options like surgery, chemotherapy, immunotherapy, etc. Recently, various advancements have been introduced for the diagnosis and targeting of hepatic tumor cells. Among these, biomarkers are considered the primary source for the diagnosis and differentiation of tumor cells. With the advancement in the field of nanotechnology, different types of nanocarriers have been witnessed in tumor targeting. Nanocarriers such as nanoparticles, liposomes, polymeric micelles, nanofibers, etc. are readily prepared for effective tumor targeting with minimal side-effects. The emergence of various approaches tends to improve the effectiveness of these nanocarriers as demonstrated in ample clinical trials. This review focuses on the significant role of carbohydrates such as mannose, galactose, fructose, etc. in the development, diagnosis, and therapy of HCC. Hence, the current focus of this review is to acknowledge various perspectives regarding the occurrence, diagnosis, treatment, and management of HCC.

Antioxidative stress protein SRXN1 can be used as a radiotherapy prognostic marker for prostate cancer

PURPOSE

To explore the mechanisms of radiotherapy resistance and search for prognostic biomarkers for prostate cancer.

METHODS

The GSE192817 and TCGA PRAD datasets were selected and downloaded from the GEO and UCSC Xena databases. Differential expression and functional annotation analyses were applied to 52 tumour cell samples from GSE192817. Then, the ssGSEA or GSVA algorithms were applied to quantitatively score the biological functional activity of samples in the GSE192817 and TCGA PRAD datasets, combined with specific gene sets collected from the Molecular Signatures Database (MSigDB). Subsequently, the Wilcoxon rank-sum test was used to compare the differences in ssGSEA or GSVA scores among cell types or PRAD patients. Moreover, radiotherapy resistance-associated gene screening was performed on DU145 and PC3 cells (prostate cancer cells), and survival analysis was used to evaluate the efficacy of these genes for predicting the prognosis of PRAD patients.

RESULTS

A total of 114 genes that were differentially expressed in more than two different cancer cell types and associated with either sham surgery or radiotherapy treatment (X-ray or photon irradiation) were detected in cancer cells from GSE192817. Comparison of DNA damage-related ssGSEA scores between sham surgery and radiotherapy treatment in prostate cancer cells (DU145 and PC3) showed that photon irradiation was potentially more effective than X-ray treatment. In the TCGA PRAD dataset, patients treated with radiotherapy had much higher "GOBP_CELLULAR_RESPONSE_TO_DNA_DAMAGE_STIMULUS", "GOBP_G2_DNA_DAMAGE_CHECKPOINT" and "GOBP_INTRA_S_DNA_DAMAGE_CHECKPOINT" GSVA scores, and the Wilcoxon rank-sum test p values were 0.0005, 0.0062 and 0.0800, respectively. Furthermore, SRXN1 was upregulated in DU145 cells (resistant to X-ray irradiation compared to PC3 cells) after radiotherapy treatment, and low SRXN1 expression in patients was beneficial to radiotherapy outcomes. The log-rank test p value for PFS was 0.0072.

CONCLUSIONS

Radiotherapy can damage DNA and induce oxidative stress to kill tumour cells. In this study, we found that SRXN1, as an antioxidative stress gene, plays an important role in radiotherapy for prostate cancer treatment, and this gene is also a potential biomarker for predicting the prognosis of patients treated with radiotherapy.

Analysis of risk factors of hepatocellular carcinoma and establishment of a clinical prognosis model

Liver cancer is a common malignancy of the digestive system. Hepatocellular carcinoma (HCC) accounts for the most majority of these tumors and it has brought a heavy medical burden to underdeveloped countries and regions. Many factors affect the prognosis of HCC patients, however, there is no specific statistical model to predict the survival time of clinical patients. This study derived a risk factor signature of HCC and reliable clinical prediction model by statistically analyzing The Surveillance, Epidemiology, and End Results (SEER) database patient information using an open source package in the python environment.

Apigenin Induced Apoptosis by Downregulating Sulfiredoxin Expression in Cutaneous Squamous Cell Carcinoma

Cutaneous squamous cell carcinoma (cSCC) is the second carcinoma in nonmelanoma skin cancer (NMSC). Sulfiredoxin (Srx) is an antioxidant protein with a role in maintaining redox homeostasis. And Srx has an oncogenic role in skin tumorigenesis. In the current study, we found that apigenin, as a natural flavonoid, downregulated the expression of Srx protein in cSCC cell lines. Apigenin also inhibited the ability of cell proliferation and migration and induced apoptosis in cSCC cell lines. Our results also showed that apigenin induced apoptosis via the activation of the mitogen-activated protein kinase (MAPK) signaling pathway, as well as downregulated Srx expression in cSCC cell lines. Importantly, the effect of downregulation Srx by apigenin has been rescued with the inhibitor of the MAPK signaling pathway intervention. And induced apoptosis by apigenin was partially attenuated by the addition of MAPK inhibitor, Binimetinib. Our research revealed that apigenin induced apoptosis by downregulation of Srx expression through regulating the MAPK signaling pathway in cSCC cells, thus providing evidence of its applicability as a potentially effective therapeutic agent for cSCC treatment.

Identification of ferroptosis-related genes for overall survival prediction in hepatocellular carcinoma

Ferroptosis is a novel type of cell death depending on iron and is strongly related to the development of tumors. Hepatocellular carcinoma (HCC) is a malignancy with high incidence. Despite some reports demonstrating the relation between ferroptosis-related genes and HCC, more details have not been excavated. In the present study, we collected and analyzed HCC patients' datasets from the TCGA-LIHC project and ICGC portal, respectively. Through the bioinformatic methods, we screened 126 differentially expressed genes. Then a prognostic model was established with four genes (GPX2, MT3, PRDX1, and SRXN1). PRDX1 is the hub gene of the prognosis model and has a high expression in hepatocellular carcinoma tumor tissue and cell lines. We further found that silencing PRDX1 increased the accumulation of ferrous ions and lipid peroxidation accumulation in HEPG2 cells and promoted ferroptosis in hepatocellular carcinoma. In conclusion, the study demonstrated the four-gene signature can be used to predict HCC prognosis. It also revealed the potential function of the ferroptosis-related gene PRDX1 in HCC, which can be a biomarker of the prediction for HCC outcome.

Sulfiredoxin-1 is a promising novel prognostic biomarker for hepatocellular carcinoma

Identifying novel prognostic biomarkers for hepatocellular carcinoma (HCC) and then, develop an effective individualized treatment strategy remain extremely warranted. The prognostic role of sulfiredoxin-1(SRXN1), an antioxidant enzyme, remains unknown in HCC. This study aimed to explore the prognostic implications of SRXN1 in HCC patients after partial hepatectomy. The expression of SRXN1 in HCC and normal tissue were analyzed using the patients from the public databases and Zhongshan Hospital. The Cox regression, Kaplan-Meier survival analysis, and time-dependent receiver operating characteristic curves were performed to identify the predictive role of SRXN1 expression on HCC patients. A prognostic nomogram based on SRXN1 expression was constructed and validated to further confirm the predictive power of SRXN1 as a prognostic biomarker. Finally, functional enrichment analysis and protein-protein interaction network analysis of SRXN1 and its associated genes were conducted. The results showed that SRXN1 was upregulated in HCC samples compared with the normal liver tissues. Patients with SRXN1 upregulation had shorter survival time. SRXN1 overexpression was significantly correlated with advanced clinicopathological parameters. The prognostic nomogram based on SRXN1 expression was proved to be more accurate than routine staging systems for the prediction of overall survival. Protein-protein interaction network analysis demonstrated the first neighbor genes of SRXN1 mainly participated in response to oxidative stress. In brief, SRXN1 could be a prognostic biomarker for the management of HCC.