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An Apoptosis-Related Specific Risk Model for Breast Cancer: From Genomic Analysis to Precision Medicine.

Zhenghang Li1, Haichuan Liu2, Mingzhu Zhang1

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Summary
This summary is machine-generated.

This study developed an eight-gene apoptosis-related gene (ARG) risk model to predict breast cancer (BC) prognosis and immunotherapy response. The model accurately identifies patients likely to benefit from treatment and suggests potential drug sensitivities.

Keywords:
apoptosis-related genesbreast cancerdrug sensitivity analysisimmuno-infiltration analysisprognostic risk model

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Area of Science:

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background:

  • Breast cancer (BC) is a leading global malignancy in women.
  • Apoptosis is crucial in BC progression, yet its link to prognosis and ARGs is under-researched.
  • Limited understanding of ARGs hinders accurate BC prognosis and treatment prediction.

Purpose of the Study:

  • To develop a BC-specific prognostic risk model using apoptosis-related genes (ARGs).
  • To evaluate the model's accuracy in predicting patient prognosis and immunotherapy response.
  • To explore potential therapeutic targets and drug sensitivities associated with the model genes.

Main Methods:

  • Utilized The Cancer Gene Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets.
  • Employed Cox regression for ARG identification and prognostic model construction.
  • Validated model accuracy using Receiver Operator Characteristic (ROC) curves, nomograms, and independent datasets; assessed drug sensitivity via CellMiner.

Main Results:

  • An eight-ARG prognostic model (including PMAIP1, TP53AIP1, TUBA3D, TUBA1C, BCL2A1, EMP1, GSN, F2) was established.
  • The model demonstrated high accuracy and clinical utility in predicting survival and immunotherapy outcomes.
  • Low-risk patients showed increased immune cell infiltration and better immunotherapy response; model genes correlated with sensitivity to targeted drugs.

Conclusions:

  • Successfully developed and validated a novel ARG-based prognostic model for breast cancer.
  • The model offers valuable insights into predicting BC prognosis and immune responses.
  • Findings provide a foundation for future research and personalized treatment strategies in breast cancer.