Identification of Ten-Gene Related to Lipid Metabolism for Predicting Overall Survival of Breast Invasive Carcinoma

Suppressing mitochondrial inner membrane protein (IMMT) inhibits the proliferation of breast cancer cells through mitochondrial remodeling and metabolic regulation

Metabolic reprogramming is widely recognized as a hallmark of malignant tumors, and the targeting of metabolism has emerged as an appealing approach for cancer treatment. Mitochondria, as pivotal organelles, play a crucial role in the metabolic regulation of tumor cells, and their morphological and functional alterations are intricately linked to the biological characteristics of tumors. As a key regulatory subunit of mitochondria, mitochondrial inner membrane protein (IMMT), plays a vital role in degenerative diseases, but its role in tumor is almost unknown. The objective of this research was to investigate the roles that IMMT play in the development and progression of breast cancer (BC), as well as to elucidate the underlying biological mechanisms that drive these effects. In this study, it was confirmed that the expression of IMMT in BC tissues was significantly higher than that in normal tissues. The analysis of The Cancer Genome Atlas (TCGA) database revealed that IMMT can serve as an independent prognostic factor for BC patients. Additionally, verification in clinical specimens of BC demonstrated a positive association between high IMMT expression and larger tumor size (> 2 cm), Ki-67 expression (> 15%), and HER-2 status. Furthermore, in vitro experiments have substantiated that the suppression of IMMT expression resulted in a reduction in cell proliferation and alterations in mitochondrial cristae, concomitant with the liberation of cytochrome c, but it did not elicit mitochondrial apoptosis. Through Gene Set Enrichment Analysis (GSEA) analysis, we have predicted the associated metabolic genes and discovered that IMMT potentially modulates the advancement of BC through its interaction with 16 metabolic-related genes, and the changes in glycolysis related pathways have been validated in BC cell lines after IMMT inhibition. Consequently, this investigation furnishes compelling evidence supporting the classification of IMMT as prognostic marker in BC, and underscoring its prospective utility as a novel target for metabolic therapy.

The oxidative aging model integrated various risk factors in type 2 diabetes mellitus at system level

Background

Type 2 diabetes mellitus (T2DM) is a chronic endocrine metabolic disease caused by insulin dysregulation. Studies have shown that aging-related oxidative stress (as "oxidative aging") play a critical role in the onset and progression of T2DM, by leading to an energy metabolism imbalance. However, the precise mechanisms through which oxidative aging lead to T2DM are yet to be fully comprehended. Thus, it is urgent to integrate the underlying mechanisms between oxidative aging and T2DM, where meaningful prediction models based on relative profiles are needed.

Methods

First, machine learning was used to build the aging model and disease model. Next, an integrated oxidative aging model was employed to identify crucial oxidative aging risk factors. Finally, a series of bioinformatic analyses (including network, enrichment, sensitivity, and pan-cancer analyses) were used to explore potential mechanisms underlying oxidative aging and T2DM.

Results

The study revealed a close relationship between oxidative aging and T2DM. Our results indicate that nutritional metabolism, inflammation response, mitochondrial function, and protein homeostasis are key factors involved in the interplay between oxidative aging and T2DM, even indicating key indices across different cancer types. Therefore, various risk factors in T2DM were integrated, and the theories of oxi-inflamm-aging and cellular senescence were also confirmed.

Conclusion

In sum, our study successfully integrated the underlying mechanisms linking oxidative aging and T2DM through a series of computational methodologies.

Scientometric analysis of lipid metabolism in breast neoplasm: 2012-2021

Introduction: In recent years, more and more studies have proved that lipid metabolism plays an essential role in breast cancer's proliferation and metastasisand also has a specific significance in predicting survival. Methods: This paper collected data from 725 publications related to lipid metabolism in breast neoplasm from 2012 to 2021 through the Web of Science Core Collection database. Bibliometrix, VOSviewer, and CiteSpace were used for the scientometrics analysis of countries, institutions, journals, authors, keywords, etc. Results: The number of documents published showed an increasing trend, with an average annual growth rate of 14.49%. The United States was the most productive country (n = 223, 30.76%). The journals with the largest number of publications are mostly from developed countries. Except for the retrieved topics, "lipid metabolism" (n = 272) and "breast cancer" (n = 175), the keywords that appeared most frequently were "expression" (n = 151), "fatty-acid synthase" (n = 78), "growth" (n = 72), "metabolism" (n = 67) and "cells" (n = 66). Discussion: These findings and summaries help reveal the current research status and clarify the hot spots in this field.

APOL4, a Novel Immune-Related Prognostic Biomarker for Glioma

Glioma is the common, most aggressive and poorest prognostic tumor type in the brain. More and more biomarkers associated with glioma treatment, prognosis, and immunity are being discovered. Here, we aimed to explore the underlying biological functions and prognostic predictive value of Apolipoprotein L4 (APOL4) in glioma. We downloaded the expression data of APOL4 and clinical information from several databases and used R software for preprocessing. The clinical significance of APOL4 in a glioma outcome was explored by the Cox regression analysis and Kaplan–Meier survival analysis. In addition, immune infiltrates and microenvironmental indicators were assessed by CIBERSORT and TIMER. GO and KEGG analyses were used to analyze the potential functions of APOL4 in gliomas. APOL4 expression was increased in glioma specimens compared to normal tissues and correlated dramatically with the WHO grade. A survival analysis showed a shorter overall survival (OS) in glioma patients with APOL4 overexpression, and a Cox regression analysis showed that APOL4 was an independent prognostic factor for the OS of glioma patients. GSEA, GO, and KEGG enrichment analyses showed remarkable enrichment in immune-related pathways. APOL4 expression was positively correlated with immune infiltration (including DC cells, neutrophils, CD8+ T cells, B cells, macrophages, CD4+ T cells, etc.) and microenvironmental parameters (including immune, stromal, and ESTIMATE scores) in gliomas. Glioma patients with a higher expression of APOL4 may be more sensitive to immune checkpoint inhibitors (ICI). In conclusion, these findings suggest that APOL4 is associated with the tumor grade and immune infiltrates; APOL4 may be a new and potential biomarker for therapeutic and prognostic evaluations that may further suggest the therapeutic efficacy of immunotherapy.