Genetic overlap between breast cancer and sarcopenia - exploring the prognostic implications of SLC38A1 gene expression

Q: What is the main research focus of the study?

The study investigates genetic overlap between breast cancer and sarcopenia and evaluates how SLC38A1 gene expression relates to breast cancer prognosis.

Q: How were the datasets and analyses performed?

Gene expression and clinical data were downloaded from GEO, then processed with R for integration, differential expression analysis, functional enrichment, and protein-protein interaction network construction. COX proportional hazards and survival analyses were used to generate prognostic curves and nomograms, with gene expression validation by qRT-PCR and muscle-area delineation on CT images.

Q: Which findings link SLC38A1 to breast cancer outcomes?

SLC38A1 expression identified by multivariate COX analysis is significantly associated with poor prognosis. Incorporating SLC38A1 into a prognostic model improves survival prediction, and external validation shows higher SLC38A1 expression in breast cancer tissues versus adjacent non-cancerous tissues.

Sep 21, 2026

Uploaded by Clementine

Age-related sarcopenia, marked by declining muscle mass, is linked to worse quality of life and may increase breast cancer recurrence risk and reduce survival. This study analyzes shared genetic mechanisms between breast cancer and skeletal muscle aging. Gene expression datasets and clinical data from GEO are integrated and processed with R, followed by differential gene screening, enrichment, protein-protein interaction network construction, and COX-based survival modeling to build and validate a prognostic framework.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Abstract

Background

Methods

Results

Conclusion

Introduction

Wang et al. BMC Cancer (2024) 24:1533 BMC Cancer [https://doi.org/10.1186/s12885-024-13326-y](https://doi.org/10.1186/s12885-024-13326-y) RESEARCH Open Access Genetic overlap between breast cancer and sarcopenia: exploring the prognostic implications of SLC38A1 gene expression Ye Wang 1, Pei Zhong2, Congjun Wang3, Weijia Huang3 and Hong Yang4* Abstract Background Sarcopenia, an age-related syndrome characterized by a decline in muscle mass, not only affects patients’ quality of life but may also increase the risk of breast cancer recurrence and reduce survival rates. Therefore, investigating the genetic mechanisms shared between breast cancer and sarcopenia is significant for the prevention, diagnosis, and treatment of breast cancer. Methods This study downloaded gene expression datasets and clinical data related to breast cancer and skeletal muscle aging from the GEO database. Data preprocessing, integration, differential gene identification, functional enrichment analysis, and construction of protein-protein interaction networks were performed using R language. Subsequently, COX proportional hazards model analysis and survival analysis were conducted, and survival curves and nomograms were generated. The expression levels of genes in tissues were detected using qRT-PCR, and the Radiant DICOM viewer software was used to delineate the pectoralis major muscle area in CT images. Results We identified 152 differential ly expressed genes (P < . 05) and 226 sarcopenia-related genes (r > .4) associated with skeletal muscle aging. TheTCGA-BRCA dataset revealed 106 genes associated with breast cancer (P < . 05, logFC = 1) . Functional enrichment analysis indicated significant enrichment in cell proliferation and growth pathways. The PPI network identified critical molecules involved in muscle aging and tumor progression. After dimensionality reduction, a strong correlation was observed between the expression of the muscle aging-related gene set and the prognosis of breast cancer patients (P < . 01) . The expression of SLC38A1 identified through multivariate COX analysis was significantly associated with poor prognosis in breast cancer patients (P = . 03) . Incorporating SLC38A1 expression, the prognostic model precisely forecasted breast cancer survival (P < . 01) . External validation confirmed the higher expression of the SLC38A1 gene in breast cancer tissues compared to adjacent non-cancerous tissues (P < . 01) . The SLC38A1 index, calculated in combination with the patient’s age and BMI, can optimize the prognostic prediction model, providing a powerful tool for personalized treatment of breast cancer. Conclusion High SLC38A1 gene expression was significantly associated with poor prognosis in breast cancer patients. The combination of SLC38A1 expression and the pectoralis major muscle area provided an optimized prognostic prediction model, offering a potential tool for personalized breast cancer treatment. *Correspondence: Hong Yang [yanghong@gxmu.edu.cn](yanghong@gxmu.edu.cn) Full list of author information is available at the end of the article © The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permi

FAQs

What is the main research focus of the study?

The study investigates genetic overlap between breast cancer and sarcopenia and evaluates how SLC38A1 gene expression relates to breast cancer prognosis.

How were the datasets and analyses performed?

Gene expression and clinical data were downloaded from GEO, then processed with R for integration, differential expression analysis, functional enrichment, and protein-protein interaction network construction. COX proportional hazards and survival analyses were used to generate prognostic curves and nomograms, with gene expression validation by qRT-PCR and muscle-area delineation on CT images.

Which findings link SLC38A1 to breast cancer outcomes?

SLC38A1 expression identified by multivariate COX analysis is significantly associated with poor prognosis. Incorporating SLC38A1 into a prognostic model improves survival prediction, and external validation shows higher SLC38A1 expression in breast cancer tissues versus adjacent non-cancerous tissues.

Sep 21, 2026

Uploaded by Clementine