eIF3f Mediates SGOC Pathway Reprogramming by Enhancing Deubiquitinating Activity in Colorectal Cancer.

Numerous studies have demonstrated that individual proteins can moonlight. Eukaryotic Initiation translation factor 3, f subunit (eIF3f) is involved in critical biological functions; however, its role independent of protein translation in regulating colorectal cancer (CRC) is not characterized. Here, it is demonstrated that eIF3f is upregulated in CRC tumor tissues and that both Wnt and EGF signaling pathways are participating in eIF3f's oncogenic impact on targeting phosphoglycerate dehydrogenase (PHGDH) during CRC development. Mechanistically, EGF blocks FBXW7ß-mediated PHGDH ubiquitination through GSK3ß deactivation, and eIF3f antagonizes FBXW7ß-mediated PHGDH ubiquitination through its deubiquitinating activity. Additionally, Wnt signals transcriptionally activate the expression of eIF3f, which also exerts its deubiquitinating activity toward MYC, thereby increasing MYC-mediated PHGDH transcription. Thereby, both impacts allow eIF3f to elevate the expression of PHGDH, enhancing Serine-Glycine-One-Carbon (SGOC) signaling pathway to facilitate CRC development. In summary, the study uncovers the intrinsic role and underlying molecular mechanism of eIF3f in SGOC signaling, providing novel insight into the strategies to target eIF3f-PHGDH axis in CRC.

Bibliometric analysis of single-cell sequencing researches on immune cells and their application of DNA damage repair in cancer immunotherapy.

Introduction: In recent decades, single-cell sequencing technology has developed rapidly and used widely in various fields of life sciences, especially for the detection of immune cells. A bibliometric analysis of single-cell sequencing research work on immune cells published during the 2011-2021 period should provide new insight on the use of single-cell sequencing. Methods: We screened 1,460 publications on single-cell sequencing on immune cells according to the publication date, article type, language, and country. Reults: The United States published the first and largest number of articles, while China's research started relatively late, but ranked second in the number of publications. T cells were the most commonly studied immune cells by single-cell sequencing, followed by mononuclear macrophages. Cancer biology was the most common field of immune cell research by single-cell sequencing. Single-cell sequencing studies using γδ T cells were mainly in the fields of cancer biology and cell development, and focused over time from cell surface receptor to cell function. Through in-depth analysis of the articles on single-cell sequencing of T cells in the oncology field, our analysis found that immunotherapy and tumor microenvironment were the most popular research directions in recent years. Discussion: The combination of DNA damage repair and immunotherapy seems to provide a new strategy for cancer therapy.

A retrospective analysis based on multiple machine learning models to predict lymph node metastasis in early gastric cancer.

Background: Endoscopic submucosal dissection has become the primary option of treatment for early gastric cancer. However, lymph node metastasis may lead to poor prognosis. We analyzed factors related to lymph node metastasis in EGC patients, and we developed a construction prediction model with machine learning using data from a retrospective series. Methods: Two independent cohorts' series were evaluated including 305 patients with EGC from China as cohort I and 35 patients from Spain as cohort II. Five classifiers obtained from machine learning were selected to establish a robust prediction model for lymph node metastasis in EGC. Results: The clinical variables such as invasion depth, histologic type, ulceration, tumor location, tumor size, Lauren classification, and age were selected to establish the five prediction models: linear support vector classifier (Linear SVC), logistic regression model, extreme gradient boosting model (XGBoost), light gradient boosting machine model (LightGBM), and Gaussian process classification model. Interestingly, all prediction models of cohort I showed accuracy between 70 and 81%. Furthermore, the prediction models of the cohort II exhibited accuracy between 48 and 82%. The areas under curve (AUC) of the five models between cohort I and cohort II were between 0.736 and 0.830. Conclusions: Our results support that the machine learning method could be used to predict lymph node metastasis in early gastric cancer and perhaps provide another evaluation method to choose the suited treatment for patients.

Microecological treatment of hyperuricemia using Lactobacillus from pickles.

BACKGROUND: Hyperuricemia is one of the important risk factors for gout, arteriosclerosis, cardiovascular and cerebrovascular disease. Lactobacillus has attracted much attention due to its role in the regulation of intestinal function and tumor resistance, but its ability to reduce uric acid is unclear. Pickles are a traditional fermented food rich in lactic acid bacteria (LAB). RESULTS: LAB strains were isolated from 18 pickles and their tolerance to acid bile salts, trypsin, pepsin were evaluated after screening by nucleoside degradation. 16S rDNA sequence analysis was used to identify LAB strains. Furthermore, we established rat model of hyperuricemia and demonstrated that Lactobacillus could alleviate hyperuricemia and reduce kidney injury. CONCLUSION: This study suggests that microecological treatment with Lactobacillus represents a feasible option for patients with chronic hyperuricemia.

miR-1245a promotes the proliferation and invasion of colon adenocarcinoma by targeting BRCA2.

BACKGROUND: Colon adenocarcinoma (CA) is the most common one with poor survival in colon cancer. This study aims to investigate the effect of miR-1245a on the process of CA cells and its target gene BRCA2. METHODS: The expression of CA tissues and cells were evaluated by q RT-PCR. Then we explore the association between expression of miR-1245a and prognosis in the CA patients from the TCGA database. CCK8 assays, colony formation assays were performed to explore the effect of miR-1245a in CA cell proliferation. The invasion ability of CA cells was evaluated by Transwell assays. Western blot was performed to assess the BRCA2 expression. Luciferase reporter assay was employed to scrutinize the relationship between miR-1245a and BRCA2. Finally, rescue experiments were performed through BRCA2 downregulation and miR-1245a inhibitors by using colony formation assay and Transwell invasion assay. RESULTS: miR-1245a is upregulated in CA cells and tissues. Additionally, the high expression of miR-1245a was related to poor survival. CCK8 assays, colony formation assays and Transwell assays showed that miR-1245a promotes the proliferation and invasion of CA cells. The luciferase reporter assay indicated that miR-1245a targeted BRCA2 and inhibited its expression. The rescue experiment further showed that miR-1245a could restore the effect of BRCA2 on CA. CONCLUSIONS: miR-1245a promotes the proliferation and invasion of CA by targeting BRCA2.Our results suggested that miR-1245a could be a potential biomarker for CA progression.