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Identification of a PANoptosis-related prognostic model in triple-negative breast cancer, from risk assessment, immunotherapy, to personalized treatment

Jia-Wen Chen^1,2, Rui-Hong Gong³, Chi Teng^1,2

¹Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100193, China.

Heliyon

|October 21, 2024

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Identification Of A Panoptosis-related Prognostic Model In Triple-negative Breast Cancer, From Risk Assessment, Immunotherapy, To Personalized Treatment

This summary is machine-generated.

This study developed a prognostic model using PANoptosis-related genes for triple-negative breast cancer. The model aids in predicting patient outcomes and guiding personalized treatment strategies for this challenging cancer subtype.

Area of Science:

Oncology
Molecular Biology
Genetics

Background:

Triple-negative breast cancer (TNBC) presents a difficult prognosis, necessitating effective prognostic models for clinical management.
PANoptosis, a programmed cell death pathway, impacts tumor progression and patient outcomes, but its role in TNBC prognosis is unclear.

Purpose of the Study:

To investigate the impact of PANoptosis-related genes on triple-negative breast cancer prognosis.
To develop and validate a predictive model for TNBC utilizing PANoptosis-associated genes.

Main Methods:

Collected TNBC clinical data from public databases (GEO, TCGA) and identified 19 PANoptosis-related genes.
Employed consensus clustering to categorize PANoptosis-related subtypes and identified differentially expressed genes.
Developed and validated a prognostic model using LASSO and Cox regression, including nomogram construction for risk assessment.

Main Results:

Identified two PANoptosis-related subtypes in TNBC and 1054 differentially expressed genes.
Constructed a four-gene prognostic model (BTN2A2, CACNA1H, PIGR, S100B) that serves as an independent prognostic indicator.
Validated the model's predictive ability and correlated risk score with age and disease stage; analyzed immune infiltration and drug sensitivity for targeted therapies.

Conclusions:

Successfully developed a novel PANoptosis-related prognostic model for triple-negative breast cancer.
The model offers a new strategy for predicting patient prognosis and informing personalized treatment decisions in TNBC.

Keywords:

Immunotherapy PANoptosis Prognosis Triple-negtive breast cancer Tumor microenvironment