Abstract 7609: Potential gene expression meta-signatures predict neoadjuvant chemotherapy response in invasive breast cancer

Abstract

Abstract Early prediction of Neoadjuvant Chemotherapy (NAC) response is crucial for women with locally advanced breast cancer (BC), given their low response rates. This study aims to identify gene expression patterns and tumor microenvironment (TME) characteristics associated with resistance to NAC, which could significantly impact tumor progression and treatment outcomes. The study encompassed differential gene expression comparing non-responders and responders, enrichment analysis, tumor microenvironment estimation, and cytokines identification from a female patient's cohort with distinct molecular subtypes and candidates to NAC at the Colombian National Cancer Institute. Candidate differentially expressed genes validated with RT-PCR in a larger validation cohort and corroborated in several publicly available databases, including associated treatment drugs. Distinct gene expression profiles were observed between responders and non-responders, emphasizing immune system-related pathways such as IL-17 signaling, B cell receptor signaling, complement and coagulation cascades, natural killer cell-mediated cytotoxicity, and NF-kB signaling. Immune-related genes (AGTR1, APOD, CCL19, CGA, ECEL1, NPY1R, NTNG1, PCSK1, PFDN2, S100B, TPRG1, WDR5B, ZNF385B) were identified as biomarkers correlated with non-response and worse prognosis. Responders showed increased B cell populations, CD4+ and CD8+ effector memory T-cells in lymphoid groups, while non-responders displayed elevated levels of CD8+ naive T-cells. Additionally, responders revealed upregulated myeloid cell populations like macrophages and dendritic cells. Several cytokines like IL1B, IL-2, IL-4, IL-12, IL-21, IL-22, IL-36, and TWEAK showed elevated expression in non-responders. Dexamethasone, Vinblastine, and Streptozocin were candidate drugs that interacted with AGTR1, CGA, and S100B, respectively and are associated with progression and metastasis. Logistic regression revealed that overexpression of CGA showed a higher probability (OR:1.83, p=0.03) while ECEL1 had a lower probability (OR=0.44, p=0.04) in non-responders compared to responders who lacked expression of these genes. Immune-related genes and various subtypes of immune cells within the TME exhibit correlations with response to NAC, and several cell fractions significantly changed before and after NAC. These results suggest meta-signatures that warrant further evaluation as concordance assessment between immunohistochemistry (IHC) and gene expression profiling, in addition to an extensive validation to triage patients before NAC and target personalized interventions. Detection and evaluation of TME components are essential to predict NAC efficacy and avoid disease relapse. Finally, these findings emphasize the importance of assessing admixed populations to facilitate novel findings and alleviate disparities. Citation Format: Hedda Michelle Guevara-Nieto, Rafael S. Parra-Medina, Jovanny Zabaleta, Liliana Lopez-Kleine, Alba L. Combita. Potential gene expression meta-signatures predict neoadjuvant chemotherapy response in invasive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7609.