Integrating Machine Learning and Bulk and Single-Cell RNA Sequencing to Decipher Diverse Cell Death Patterns for Predicting the Prognosis of Neoadjuvant Chemotherapy in Breast Cancer

International Journal of Molecular Sciences, Год журнала: 2025, Номер 26(8), С. 3682 - 3682

Опубликована: Апрель 13, 2025

Breast cancer (BRCA) continues to pose a serious risk women’s health worldwide. Neoadjuvant chemotherapy (NAC) is critical treatment strategy. Nevertheless, the heterogeneity in outcomes necessitates identification of reliable biomarkers and prognostic models. Programmed cell death (PCD) pathways serve as factor tumor development response. However, relationship between diverse patterns PCD NAC BRCA remains unclear. We integrated machine learning multiple bioinformatics tools explore association 19 prognosis within cohort 921 patients treated with from seven multicenter cohorts. A model based on PCD-related genes (PRGs) was constructed evaluated using combination 117 algorithms. Immune infiltration analysis, mutation pharmacological single-cell RNA sequencing (scRNA-seq) were conducted genomic profile clinical significance these BRCA. Immunohistochemistry (IHC) employed validate expression select (UGCG, BTG22, TNFRSF21, MYB) tissues. PRGs by signature comprising 20 DEGs forecast patients. The demonstrated excellent predictive accuracy, high concordance index (C-index) 0.772, validated across independent datasets. Our results strong developed survival prognosis, pathological features, immune infiltration, microenvironment (TME), gene mutations, drug sensitivity for Moreover, IHC studies further that certain tissues significantly associated efficacy emerged an autonomous predictor influencing outcome are first integrate bulk scRNA-seq decode various mechanisms unique model, PRGs, provides novel comprehensive strategy predicting This not only aids understanding underlying but also offers insights into personalized strategies, potentially improving patient outcomes.

Язык: Английский

Identification of potential novel targets for treating inflammatory bowel disease using Mendelian randomization analysis

International Journal of Colorectal Disease, Год журнала: 2024, Номер 39(1)

Опубликована: Окт. 16, 2024

Inflammatory bowel disease (IBD) is a complex autoimmune disorder, although some medications are available for its treatment. However, the long-term efficacy of these drugs remains unsatisfactory. Therefore, there need to develop novel drug targets IBD

Язык: Английский