Identification of a Four-Gene Signature With Prognostic Significance in Endometrial Cancer Using Weighted-Gene Correlation Network Analysis

Probiotic Clostridium butyricum ameliorates cognitive impairment in obesity via the microbiota-gut-brain axis

Obesity is a risk factor for cognitive dysfunction and neurodegenerative disease, including Alzheimer's disease (AD). The gut microbiota-brain axis is altered in obesity and linked to cognitive impairment and neurodegenerative disorders. Here, we targeted obesity-induced cognitive impairment by testing the impact of the probiotic Clostridium butyricum, which has previously shown beneficial effects on gut homeostasis and brain function. Firstly, we characterized and analyzed the gut microbial profiles of participants with obesity and the correlation between gut microbiota and cognitive scores. Then, using an obese mouse model induced by a Western-style diet (high-fat and fiber-deficient diet), the effects of Clostridium butyricum on the microbiota-gut-brain axis and hippocampal cognitive function were evaluated. Finally, fecal microbiota transplantation was performed to assess the functional link between Clostridium butyricum remodeling gut microbiota and hippocampal synaptic protein and cognitive behaviors. Our results showed that participants with obesity had gut microbiota dysbiosis characterized by an increase in phylum Proteobacteria and a decrease in Clostridium butyricum, which were closely associated with cognitive decline. In diet-induced obese mice, oral Clostridium butyricum supplementation significantly alleviated cognitive impairment, attenuated the deficit of hippocampal neurite outgrowth and synaptic ultrastructure, improved hippocampal transcriptome related to synapses and dendrites; a comparison of the effects of Clostridium butyricum in mice against human AD datasets revealed that many of the genes changes in AD were reversed by Clostridium butyricum; concurrently, Clostridium butyricum also prevented gut microbiota dysbiosis, colonic barrier impairment and inflammation, and attenuated endotoxemia. Importantly, fecal microbiota transplantation from donor-obese mice with Clostridium butyricum supplementation facilitated cognitive variables and colonic integrity compared with from donor obese mice, highlighting that Clostridium butyricum's impact on cognitive function is largely due to its ability to remodel gut microbiota. Our findings provide the first insights into the neuroprotective effects of Clostridium butyricum on obesity-associated cognitive impairments and neurodegeneration via the gut microbiota-gut-brain axis.

Lentinan has a beneficial effect on cognitive deficits induced by chronic Toxoplasma gondii infection in mice

BACKGROUND

Toxoplasma gondii (T. gondii) is increasingly considered a risk factor for neurodegenerative diseases. However, there is only limited information on the development of drugs for T. gondii infection. Lentinan from Lentinula edodes is a bioactive ingredient with the potential to enhance anti-infective immunity. The present study aimed to investigate the neuroprotective effect of lentinan on T. gondii-associated cognitive deficits in mice.

METHODS

A chronic T. gondii infection mouse model was established by administering 10 cysts of T. gondii by gavage. Lentinan was intraperitoneally administered 2 weeks before infection. Behavioral tests, RNA sequencing, immunofluorescence, transmission electron microscopy and Golgi-Cox staining were performed to assess the effect of lentinan on cognitive deficits and neuropathology in vivo. In vitro, the direct and indirect effects of lentinan on the proliferation of T. gondii tachyzoites were evaluated in the absence and presence of BV-2 cells, respectively.

RESULTS

Lentinan prevented T. gondii-induced cognitive deficits and altered the transcriptome profile of genes related to neuroinflammation, microglial activation, synaptic function, neural development and cognitive behavior in the hippocampus of infected mice. Moreover, lentinan reduced the infection-induced accumulation of microglia and downregulated the mRNA expression of proinflammatory cytokines. In addition, the neurite and synaptic ultrastructural damage in the hippocampal CA1 region due to infection was ameliorated by lentinan administration. Lentinan decreased the cyst burden in the brains of infected mice, which was correlated with behavioral performance. In line with this finding, lentinan could significantly inhibit the proliferation of T. gondii tachyzoites in the microglial cell line BV2, although lentinan had no direct inhibitory effect on parasite growth.

CONCLUSIONS

Lentinan prevents cognitive deficits via the improvement of neurite impairment and synaptic loss induced by T. gondii infection, which may be associated with decreased cyst burden in the brain. Overall, our findings indicate that lentinan can ameliorate T. gondii-related neurodegenerative diseases.

FAM family gene prediction model reveals heterogeneity, stemness and immune microenvironment of UCEC

Background: Endometrial cancer (UCEC) is a highly heterogeneous gynecologic malignancy that exhibits variable prognostic outcomes and responses to immunotherapy. The Familial sequence similarity (FAM) gene family is known to contribute to the pathogenesis of various malignancies, but the extent of their involvement in UCEC has not been systematically studied. This investigation aimed to develop a robust risk profile based on FAM family genes (FFGs) to predict the prognosis and suitability for immunotherapy in UCEC patients. Methods: Using the TCGA-UCEC cohort from The Cancer Genome Atlas (TCGA) database, we obtained expression profiles of FFGs from 552 UCEC and 35 normal samples, and analyzed the expression patterns and prognostic relevance of 363 FAM family genes. The UCEC samples were randomly divided into training and test sets (1:1), and univariate Cox regression analysis and Lasso Cox regression analysis were conducted to identify the differentially expressed genes (FAM13C, FAM110B, and FAM72A) that were significantly associated with prognosis. A prognostic risk scoring system was constructed based on these three gene characteristics using multivariate Cox proportional risk regression. The clinical potential and immune status of FFGs were analyzed using CiberSort, SSGSEA, and tumor immune dysfunction and rejection (TIDE) algorithms. qRT-PCR and IHC for detecting the expression levels of 3-FFGs. Results: Three FFGs, namely, FAM13C, FAM110B, and FAM72A, were identified as strongly associated with the prognosis of UCEC and effective predictors of UCEC prognosis. Multivariate analysis demonstrated that the developed model was an independent predictor of UCEC, and that patients in the low-risk group had better overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores exhibited good prognostic power. Patients in the low-risk group exhibited a higher tumor mutational load (TMB) and were more likely to benefit from immunotherapy. Conclusion: This study successfully developed and validated novel biomarkers based on FFGs for predicting the prognosis and immune status of UCEC patients. The identified FFGs can accurately assess the prognosis of UCEC patients and facilitate the identification of specific subgroups of patients who may benefit from personalized treatment with immunotherapy and chemotherapy.

Investigation of Transcriptome Patterns in Endometrial Cancers from Obese and Lean Women

Endometrial cancer is the most common gynaecological malignancy in developed countries. One of the largest risk factors for endometrial cancer is obesity. The aim of this study was to determine whether there are differences in the transcriptome of endometrial cancers from obese vs. lean women. Here we investigate the transcriptome of endometrial cancer between obese and lean postmenopausal women using rRNA-depleted RNA-Seq data from endometrial cancer tissues and matched adjacent non-cancerous endometrial tissues. Differential expression analysis identified 12,484 genes (6370 up-regulated and 6114 down-regulated) in endometrial cancer tissues from obese women, and 6219 genes (3196 up-regulated and 3023 down-regulated) in endometrial cancer tissues from lean women (adjusted p-value < 0.1). A gene ontology enrichment analysis revealed that the top 1000 up-regulated genes (by adjusted p-value) were enriched for growth and proliferation pathways while the top 1000 down-regulated genes were enriched for cytoskeleton restructure networks in both obese and lean endometrial cancer tissues. In this study, we also show perturbations in the expression of protein coding genes (HIST1H2BL, HIST1H3F, HIST1H2BH, HIST1H1B, TTK, PTCHD1, ASPN, PRELP, and CDH13) and the lncRNA MBNL1-AS1 in endometrial cancer tissues. Overall, this study has identified gene expression changes that are similar and also unique to endometrial cancers from obese vs. lean women. Furthermore, some of these genes may serve as prognostic biomarkers or, possibly, therapeutic targets for endometrial cancer.

Study on the Predictive Value of P53 Protein Expression in Brain Metastasis in NSCLC and the Mechanism of miR-424 Reversing Platinum Resistance in NSCLC

In order to analyze the predictive value of P53 protein expression in brain metastases in NSCLC and the mechanism of miR-424 reversing platinum resistance in NSCLC, a retrospective analysis is conducted in this study. Eighty-two NSCLC patients who received relevant diagnosis and treatment in our hospital from September 2020 to September 2021 are chosen. The prognosis of the patients is observed, and the patients were divided into two groups according to the occurrence of BMS. The comparison of clinical baseline data and the expression of P53 protein and miR-424 after surgery are performed. Furthermore, the predictive value of the P53 protein gene on the occurrence of BMS in NSCLC is analyzed by the ROC curve, and the expression of miR-424 in serum of the patients before and after drug resistance is compared. The results demonstrate that the expression of P53 protein has a high predictive value for predicting the occurrence of BRAIN metastases in NSCLC patients. Also, the high expression of miR-424 suggests that it is closely related to the occurrence of platinum resistance in NSCLC patients.

Ferroptosis: Opportunities and Challenges in Treating Endometrial Cancer

Ferroptosis, a new way of cell death, is involved in many cancers. A growing number of studies have focused on the unique role of ferroptosis on endometrial cancer. In this study, we made a comprehensive review of the relevant articles published to get deep insights in the association of ferroptosis with endometrial cancer and to present a summary of the roles of different ferroptosis-associated genes. Accordingly, we made an evaluation of the relationships between the ferroptosis-associated genes and TNM stage, tumor grade, histological type, primary therapy outcome, invasion and recurrence of tumor, and accessing the different prognosis molecular typing based on ferroptosis-associated genes. In addition, we presented an introduction of the common drugs, which targeted ferroptosis in endometrial cancer. In so doing, we clarified the opportunities and challenges of ferroptosis activator application in treating endometrial cancer, with a view to provide a novel approach to the disease.

Protein-based prognostic signature for predicting the survival and immunotherapeutic efficiency of endometrial carcinoma

Background

Endometrial cancer (EC) is the most frequent malignancy of the female genital tract worldwide. Our study aimed to construct an effective protein prognostic signature to predict prognosis and immunotherapy responsiveness in patients with endometrial carcinoma.

Methods

Protein expression data, RNA expression profile data and mutation data were obtained from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA). Prognosis-related proteins in EC patients were screened by univariate Cox regression analysis. Least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis were performed to establish the protein-based prognostic signature. The CIBERSORT algorithm was used to quantify the proportions of immune cells in a mixed cell population. The Immune Cell Abundance Identifier (ImmuCellAI) and The Cancer Immunome Atlas (TCIA) web tools were used to predict the response to immunochemotherapy. The pRRophetic algorithm was used to estimate the sensitivity of chemotherapeutic and targeted agents.

Results

We constructed a prognostic signature based on 9 prognostic proteins, which could divide patients into high-risk and low-risk groups with distinct prognoses. A novel prognostic nomogram was established based on the prognostic signature and clinicopathological parameters to predict 1, 3 and 5-year overall survival for EC patients. The results obtained with Clinical Proteomic Tumor Analysis Consortium (CPTAC), Human Protein Atlas (HPA) and immunohistochemical (IHC) staining data from EC samples in our hospital supported the predictive ability of these proteins in EC tumors. Next, the CIBERSORT algorithm was used to estimate the proportions of 22 immune cell types. The proportions of CD8 T cells, T follicular helper cells and regulatory T cells were higher in the low-risk group. Moreover, we found that the prognostic signature was positively associated with high tumor mutation burden (TMB) and high microsatellite instability (MSI-H) status in EC patients. Finally, ImmuCellAI and TCIA analyses showed that patients in the low-risk group were more inclined to respond to immunotherapy than patients in the high-risk group. In addition, drug sensitivity analysis indicated that our signature had potential predictive value for chemotherapeutics and targeted therapy.

Conclusion

Our study constructed a novel prognostic protein signature with robust predictive ability for survival and efficiency in predicting the response to immunotherapy, chemotherapy and targeted therapy. This protein signature represents a promising predictor of prognosis and response to cancer treatment in EC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09402-w.

Lentinan Supplementation Protects the Gut–Liver Axis and Prevents Steatohepatitis: The Role of Gut Microbiota Involved

The microbiota–gut–liver axis has emerged as an important player in developing nonalcoholic steatohepatitis (NASH), a type of nonalcoholic fatty liver disease (NAFLD). Higher mushroom intake is negatively associated with the prevalence of NAFLD. This study examined whether lentinan, an active ingredient in mushrooms, could improve NAFLD and gut microbiota dysbiosis in NAFLD mice induced by a high-fat (HF) diet. Dietary lentinan supplementation for 15 weeks significantly improved gut microbiota dysbiosis in HF mice, evidenced by increased the abundance of phylum Actinobacteria and decreased phylum Proteobacteria and Epsilonbacteraeota. Moreover, lentinan improved intestinal barrier integrity and characterized by enhancing intestinal tight junction proteins, restoring intestinal redox balance, and reducing serum lipopolysaccharide (LPS). In the liver, lentinan attenuated HF diet-induced steatohepatitis, alteration of inflammation–insulin (NFκB-PTP1B-Akt-GSK3β) signaling molecules, and dysregulation of metabolism and immune response genes. Importantly, the antihepatic inflammation effects of lentinan were associated with improved gut microbiota dysbiosis in the treated animals, since the Spearman's correlation analysis showed that hepatic LPS-binding protein and receptor (Lbp and Tlr4) and pro- and antiinflammatory cytokine expression were significantly correlated with the abundance of gut microbiota of phylum Proteobacteria, Epsilonbacteraeota and Actinobacteria. Therefore, lentinan supplementation may be used to mitigate NAFLD by modulating the microbiota–gut–liver axis.