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Differential response to neoadjuvant chemotherapy among 7 triple-negative breast cancer molecular subtypes

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TLDR
The clinical relevancy of the 7-subtype classification of triple-negative breast cancer reported by Lehmann and colleagues is confirmed, and may spur innovative personalized medicine strategies for patients with TNBC.
Abstract
Purpose: The clinical relevancy of the 7-subtype classification of triple-negative breast cancer (TNBC) reported by Lehmann and colleagues is unknown. We investigated the clinical relevancy of TNBC heterogeneity by determining pathologic complete response (pCR) rates after neoadjuvant chemotherapy, based on TNBC subtypes. Experimental Design: We revalidated the Lehmann and colleagues experiments using Affymetrix CEL files from public datasets. We applied these methods to 146 patients with TNBC with gene expression microarrays obtained from June 2000 to March 2010 at our institution. Of those, 130 had received standard neoadjuvant chemotherapy and had evaluable pathologic response data. We classified the TNBC samples by subtype and then correlated subtype and pCR status using Fisher exact test and a logistic regression model. We also assessed survival and compared the subtypes with PAM50 intrinsic subtypes and residual cancer burden (RCB) index. Results: TNBC subtype and pCR status were significantly associated ( P = 0.04379). The basal-like 1 (BL1) subtype had the highest pCR rate (52%); basal-like 2 (BL2) and luminal androgen receptor had the lowest (0% and 10%, respectively). TNBC subtype was an independent predictor of pCR status ( P = 0.022) by a likelihood ratio test. The subtypes better predicted pCR status than did the PAM50 intrinsic subtypes (basal-like vs. non basal-like). Conclusions: Classifying TNBC by 7 subtypes predicts high versus low pCR rate. We confirm the clinical relevancy of the 7 subtypes of TNBC. We need to prospectively validate whether the pCR rate differences translate into long-term outcome differences. The 7-subtype classification may spur innovative personalized medicine strategies for patients with TNBC. Clin Cancer Res; 19(19); 5533–40. ©2013 AACR .

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Journal ArticleDOI

Molecular-biological characteristics of triple negative breast cancer

TL;DR: A review of the literature on the molecular-biological characteristics of triple negative breast cancer and the main approaches to targeted therapies for each subtype are described.
Journal ArticleDOI

Update on triple‐negative breast cancers – highlighting subtyping update and treatment implication

Julia Y S Tsang, +1 more
- 05 Dec 2022 - 
TL;DR: In this article , the authors provide an overview of the recent findings on TNBC heterogeneity at different levels and corresponding subtyping and discuss the characteristic of subtypes and the implication of these subtypes in therapeutic approaches.
Journal ArticleDOI

Expression of GHRH-R, a Potentially Targetable Biomarker, in Triple-negative Breast Cancer.

TL;DR: A considerable number of TNBCs are positive for GHRH-R as a predictor of potential response to anti-GHRh-R treatment, however, this expression however, varies considerably between histologic subtypes of triple-negative breast cancers.
References
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Journal ArticleDOI

Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications

TL;DR: Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
Journal ArticleDOI

Summaries of Affymetrix GeneChip probe level data

TL;DR: It is found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models.
Journal ArticleDOI

Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies

TL;DR: Gen expression profiles from 21 breast cancer data sets and identified 587 TNBC cases may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.
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