Login / Signup

Luminal androgen receptor subtype and tumor-infiltrating lymphocytes groups based on triple-negative breast cancer molecular subclassification.

Miseon LeeTae-Kyung Robyn YooByung Joo ChaeAh Won LeeYoon-Jin ChaJieun LeeSung-Gwe AhnJun Kang
Published in: Scientific reports (2024)
In our previous study, we developed a triple-negative breast cancer (TNBC) subtype classification that correlated with the TNBC molecular subclassification. In this study, we aimed to evaluate the predictor variables of this subtype classification on the whole slide and to validate the model's performance by using an external test set. We explored the characteristics of this subtype classification and investigated genomic alterations, including genomic scar signature scores. First, TNBC was classified into the luminal androgen receptor (LAR) and non-luminal androgen receptor (non-LAR) subtypes based on the AR Allred score (≥ 6 and < 6, respectively). Then, the non-LAR subtype was further classified into the lymphocyte-predominant (LP), lymphocyte-intermediate (LI), and lymphocyte-depleted (LD) groups based on stromal tumor-infiltrating lymphocytes (TILs) (< 20%, > 20% but < 60%, and ≥ 60%, respectively). This classification showed fair agreement with the molecular classification in the test set. The LAR subtype was characterized by a high rate of PIK3CA mutation, CD274 (encodes PD-L1) and PDCD1LG2 (encodes PD-L2) deletion, and a low homologous recombination deficiency (HRD) score. The non-LAR LD TIL group was characterized by a high frequency of NOTCH2 and MYC amplification and a high HRD score.
Keyphrases
  • deep learning
  • machine learning
  • high frequency
  • peripheral blood
  • dna damage
  • transcranial magnetic stimulation
  • dna repair
  • bone marrow
  • transcription factor
  • high resolution
  • smoking cessation