Abstract
Purpose: Little is known about the efficacy of HER2-targeted therapy in patients with breast cancer showing different HER2pathway dependence and immune phenotypes. Herein, we report a NeoALTTO exploratory analysis evaluating the clinical value of 22 types of tumor-infiltrating immune cells by CIBERSORT and 5 immune-related metagenes in the overall patient population, and in subgroups defined by the TRAR classifier as HER2-addicted (TRAR-low) or not (TRAR-high). Patients and Methods: Association of baseline TRAR, immune related metagenes, and CIBERSORT data with pathologic complete response (pCR) and event-free survival (EFS) were assessed using logistic and Cox regression models. Corrections for multiple testing were performed by the Bonferroni method. Results: A total of 226 patients were analyzed: 80 (35%) achieved a pCR, and 64 (28%) experienced a relapse with a median follow-up of 6.7 (interquartile range 6.1-6.8) years;108 cases were classified as TRAR-low, and 118 TRAR-high. Overall, gamma(8) T-cell fraction [OR = 2.69;95% confidence interval (CI), 1.40-5.18], and no immune-related metagenes were predictive of pCR. Notably, lymphocyte-specific kinase (LCK) predicted pCR to combination (OR = 2.53;95% CI, 1.12-5.69), but not to single-agent trastuzumab or lapatinib [OR = 0.74;95% CI, 0.45- 1.22 (P-interaction = 0.01)]. Integrating LCK with gamma(8) T cells in a multivariate model added to the discriminatory capability of clinical and molecular variables with a shift in AUC from 0.80 (95% CI, 0.74-0.86) to 0.83 (95% CI, 0.78-0.89). In TRAR-low cases, activated mast cells, IFN and MHCII were reduced, and STAT1, HCK1, and y8 T cells were associated with pCR. STAT1 was broadly associated with improved EFS regardless of pCR, and nodal status in overall (HR = 0.68;95% CI, 0.49-0.94) and in TRAR-low cases (HR = 0.50;95% CI, 0.30-0.86). Conclusions: Immuno-phenotyping holds the promise to complement current predictive models in HER2-positive breast cancer and to assist in new therapeutic development.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 1078-0432 |
Sprache: | Englisch |
Dokumenten ID: | 101159 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023, 15:36 |
Letzte Änderungen: | 17. Okt. 2023, 15:07 |