Prediction of prognosis of patients with hepatocellular carcinoma based on immune-related score.

BACKGROUND: Immune-related scores are currently used for prognostic evaluation and as an immunotherapy reference in various cancers. However, the relationship between immune-related score and hepatocellular carcinoma (HCC) prognosis has not yet been investigated. This study aimed to explore the clinical application value of immune-related score for predicting HCC prognosis-related indicators including disease-free survival (DFS) and overall survival (OS), and to construct a clinical nomogram prediction model related to verification. METHODS: This study included 284 HCC patients who were selected from the Cancer Genome Atlas (TCGA) database and linked to the immune-related score downloaded from the public platform. A Cox proportional hazards regression model was used to estimate the adjusted risk ratio, and a nomogram was constructed based on multivariate analysis results and clinical significance. The model was internally verified by bootstrap. The performance of the prediction model was evaluated using the C-index and calibration curves. RESULTS: Patients were divided into three subgroups according to the immune-related score level. Compared with patients in the low immune-related score group, the DFS of patients in the medium and high immune-related score groups was significantly prolonged (HR: 0.53, 95% CI: 0.32-0.87; HR: 0.37, 95% CI: 0.21-0.63, respectively). The OS of patients in the medium and high immune-related score groups was also significantly prolonged (HR: 0.43, 95% CI: 0.20-0.95, p = 0.038; HR: 0.29, 95% CI: 0.14-0.58, p < 0.001, respectively). The C-indexes for predicting DFS and OS were 0.687 (95% CI: 0.665-0.700) and 0.743 (95% CI: 0.709-0.776), respectively. The calibration curves of 3-year and 5-year DFS and OS showed that the results predicted by the nomogram were in good agreement with the actual observations. CONCLUSIONS: Moderate/high-grade immune-related score was significantly associated with better DFS and OS in HCC patients. In addition, a nomogram for prognosis estimation can help clinicians predict the survival status of patients.

Stand Up to Stand Out: Natural Dietary Polyphenols Curcumin, Resveratrol, and Gossypol as Potential Therapeutic Candidates against Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

The COVID-19 pandemic has stimulated collaborative drug discovery efforts in academia and the industry with the aim of developing therapies and vaccines that target SARS-CoV-2. Several novel therapies have been approved and deployed in the last three years. However, their clinical application has revealed limitations due to the rapid emergence of viral variants. Therefore, the development of next-generation SARS-CoV-2 therapeutic agents with a high potency and safety profile remains a high priority for global health. Increasing awareness of the "back to nature" approach for improving human health has prompted renewed interest in natural products, especially dietary polyphenols, as an additional therapeutic strategy to treat SARS-CoV-2 patients, owing to its good safety profile, exceptional nutritional value, health-promoting benefits (including potential antiviral properties), affordability, and availability. Herein, we describe the biological properties and pleiotropic molecular mechanisms of dietary polyphenols curcumin, resveratrol, and gossypol as inhibitors against SARS-CoV-2 and its variants as observed in in vitro and in vivo studies. Based on the advantages and disadvantages of dietary polyphenols and to obtain maximal benefits, several strategies such as nanotechnology (e.g., curcumin-incorporated nanofibrous membranes with antibacterial-antiviral ability), lead optimization (e.g., a methylated analog of curcumin), combination therapies (e.g., a specific combination of plant extracts and micronutrients), and broad-spectrum activities (e.g., gossypol broadly inhibits coronaviruses) have also been emphasized as positive factors in the facilitation of anti-SARS-CoV-2 drug development to support effective long-term pandemic management and control.

Oral GS-441524 derivatives: Next-generation inhibitors of SARS-CoV-2 RNA-dependent RNA polymerase.

GS-441524, an RNA-dependent RNA polymerase (RdRp) inhibitor, is a 1'-CN-substituted adenine C-nucleoside analog with broad-spectrum antiviral activity. However, the low oral bioavailability of GS-441524 poses a challenge to its anti-SARS-CoV-2 efficacy. Remdesivir, the intravenously administered version (version 1.0) of GS-441524, is the first FDA-approved agent for SARS-CoV-2 treatment. However, clinical trials have presented conflicting evidence on the value of remdesivir in COVID-19. Therefore, oral GS-441524 derivatives (VV116, ATV006, and GS-621763; version 2.0, targeting highly conserved viral RdRp) could be considered as game-changers in treating COVID-19 because oral administration has the potential to maximize clinical benefits, including decreased duration of COVID-19 and reduced post-acute sequelae of SARS-CoV-2 infection, as well as limited side effects such as hepatic accumulation. This review summarizes the current research related to the oral derivatives of GS-441524, and provides important insights into the potential factors underlying the controversial observations regarding the clinical efficacy of remdesivir; overall, it offers an effective launching pad for developing an oral version of GS-441524.

Nomogram for prediction of peritoneal metastasis risk in colorectal cancer.

Objective: Peritoneal metastasis is difficult to diagnose using traditional imaging techniques. The main aim of the current study was to develop and validate a nomogram for effectively predicting the risk of peritoneal metastasis in colorectal cancer (PMCC). Methods: A retrospective case-control study was conducted using clinical data from 1284 patients with colorectal cancer who underwent surgery at the First Affiliated Hospital of Guangxi Medical University from January 2010 to December 2015. Least absolute shrinkage and selection operator (LASSO) regression was applied to optimize feature selection of the PMCC risk prediction model and multivariate logistic regression analysis conducted to determine independent risk factors. Using the combined features selected in the LASSO regression model, we constructed a nomogram model and evaluated its predictive value via receiver operating characteristic (ROC) curve analysis. The bootstrap method was employed for repeated sampling for internal verification and the discrimination ability of the prediction models evaluated based on the C-index. The consistency between the predicted and actual results was assessed with the aid of calibration curves. Results: Overall, 96 cases of PMCC were confirmed via postoperative pathological diagnosis. Logistic regression analysis showed that age, tumor location, perimeter ratio, tumor size, pathological type, tumor invasion depth, CEA level, and gross tumor type were independent risk factors for PMCC. A nomogram composed of these eight factors was subsequently constructed. The calibration curve revealed good consistency between the predicted and actual probability, with a C-index of 0.882. The area under the curve (AUC) of the nomogram prediction model was 0.882 and its 95% confidence interval (CI) was 0.845-0.919. Internal validation yielded a C-index of 0.868. Conclusion: We have successfully constructed a highly sensitive nomogram that should facilitate early diagnosis of PMCC, providing a robust platform for further optimization of clinical management strategies.

Bioactive natural products in COVID-19 therapy.

The devastating COVID-19 pandemic has caused more than six million deaths worldwide during the last 2 years. Effective therapeutic agents are greatly needed, yet promising magic bullets still do not exist. Numerous natural products (cordycepin, gallinamide A, plitidepsin, telocinobufagin, and tylophorine) have been widely studied and play a potential function in treating COVID-19. In this paper, we reviewed published studies (from May 2021 to April 2022) relating closely to bioactive natural products (isolated from medicinal plants, animals products, and marine organisms) in COVID-19 therapy in vitro to provide some essential guidance for anti-SARS-CoV-2 drug research and development.

Patients with chronically diseased livers have lower incidence of colorectal liver metastases: a meta-analysis.

BACKGROUND: 70 years ago, it was put forward that the diseased liver was not a favorable soil for metastatic tumor cells. In addition, a few studies have demonstrated that rare occurrence of colorectal liver metastases among patients with fatty liver, cirrhosis or chronic hepatitis B and C virus infection. We performed a meta-analysis to verify the association between the incidences of colorectal liver metastases with chronically diseased livers. METHODS: Relevant studies were identified by a search of electronic database PubMed, Cochrane Library, OVID, Web of Science and CNKI (up to February 24, 2014). Pooled odds ratio (OR) with 95% confidence interval (CI) was calculated using random- or fixed-effect models when appropriate. Meta-analysis and publication bias (Bgger's test) was evaluated with STATA 12.0. RESULTS: A total of 10,349 colorectal cancer patients from 10 studies were included. The meta-analysis result showed there was a significant difference in the incidences of colorectal liver metastases between patients with normal and chronically diseased livers (OR = 0.32; 95% CI 95%: 0.26-0.38, P = 0.000 fixed-effects model). The result of Begg's test (Pr>|z| = 0.089; P>0.05) revealed no publication bias. CONCLUSIONS: The results of this meta-analysis demonstrated that patients with chronically diseased livers had significantly lower incidences of colorectal liver metastases than those with normal livers.