Cancers (Jun 2023)
Predictive Roles of Baseline Stromal Tumor-Infiltrating Lymphocytes and Ki-67 in Pathologic Complete Response in an Early-Stage Triple-Negative Breast Cancer Prospective Trial
- Nour Abuhadra,
- Ryan Sun,
- Clinton Yam,
- Gaiane M. Rauch,
- Qingqing Ding,
- Bora Lim,
- Alastair M. Thompson,
- Elizabeth A. Mittendorf,
- Beatriz E. Adrada,
- Senthil Damodaran,
- Kiran Virani,
- Jason White,
- Elizabeth Ravenberg,
- Jia Sun,
- Jaihee Choi,
- Rosalind Candelaria,
- Banu Arun,
- Naoto T. Ueno,
- Lumarie Santiago,
- Sadia Saleem,
- Sausan Abouharb,
- Rashmi K. Murthy,
- Nuhad Ibrahim,
- Aysegul Sahin,
- Vicente Valero,
- William Fraser Symmans,
- Jennifer K. Litton,
- Debu Tripathy,
- Stacy Moulder,
- Lei Huo
Affiliations
- Nour Abuhadra
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Ryan Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Gaiane M. Rauch
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Qingqing Ding
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Bora Lim
- Department of Oncology, Baylor College of Medicine, Houston, TX 77030, USA
- Alastair M. Thompson
- Division of Surgical Oncology, Section of Breast Surgery, Baylor College of Medicine, Houston, TX 77030, USA
- Elizabeth A. Mittendorf
- Division of Breast Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Beatriz E. Adrada
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Senthil Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Kiran Virani
- Division of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Jason White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Elizabeth Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Jia Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Jaihee Choi
- Department of Statistics, Rice University, Houston, TX 77005, USA
- Rosalind Candelaria
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Banu Arun
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Naoto T. Ueno
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Lumarie Santiago
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Sadia Saleem
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Sausan Abouharb
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Rashmi K. Murthy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Nuhad Ibrahim
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Aysegul Sahin
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- William Fraser Symmans
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Jennifer K. Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Stacy Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- DOI
- https://doi.org/10.3390/cancers15133275
- Journal volume & issue
-
Vol. 15,
no. 13
p. 3275
Abstract
High stromal tumor-infiltrating lymphocytes (sTILs) are associated with improved pathologic complete response (pCR) in triple-negative breast cancer (TNBC). We hypothesize that integrating high sTILs and additional clinicopathologic features associated with pCR could enhance our ability to predict the group of patients on whom treatment de-escalation strategies could be tested. In this prospective early-stage TNBC neoadjuvant chemotherapy study, pretreatment biopsies from 408 patients were evaluated for their clinical and demographic features, as well as biomarkers including sTILs, Ki-67, PD-L1 and androgen receptor. Multivariate logistic regression models were developed to generate a computed response score to predict pCR. The pCR rate for the entire cohort was 41%. Recursive partitioning analysis identified ≥20% as the optimal cutoff for sTILs to denote 35% (143/408) of patients as having high sTILs, with a pCR rate of 59%, and 65% (265/408) of patients as having low sTILs, with a pCR rate of 31%. High Ki-67 (cutoff > 35%) was identified as the only predictor of pCR in addition to sTILs in the training set. This finding was verified in the testing set, where the highest computed response score encompassing both high sTILa and high Ki-67 predicted a pCR rate of 65%. Integrating Ki67 and sTIL may refine the selection of early stage TNBC patients for neoadjuvant clinical trials evaluating de-escalation strategies.
Keywords
- triple-negative breast cancer
- Ki-67
- tumor-infiltrating lymphocytes
- neoadjuvant chemotherapy
- pathologic complete response
- predictor