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Breast cancer-subtype and infiltrating macrophage signatures predict chemotherapy-response and survival

ABSTRACT: Triple-Negative Breast Cancer (TNBC) is a heterogeneous collection of cancers where personalized treatment is difficult and chemotherapy and immunotherapy combinations are the main treatment options. Many attempts to tackle patient heterogeneity have focused on defining cancer-intrinsic subtypes based on differential tumor mRNA-expression across patient cohorts. While these multi-gene diagnostics have shown success in hormone receptor- positive cancers (e.g. OncotypeDX), no TNBC classifiers have shown clinical utility in predicting patient survival or treatment response. We hypothesize that TNBC-infiltrating immune-cells both affect mRNA-based classification and contribute to treatment response variability. To evaluate this hypothesis, we benchmarked the performance of common TNBC-classification (TNBC-type) and infiltrating immune (CIBERSORT) algorithms on the same underlying datasets. Encouragingly, we found that – as with OncotypeDx– highly proliferative TNBC-subtypes (BL1) show the strongest evidence of response to cytotoxic chemotherapies. Interestingly, this cancer-proliferative signature (BL1) is strongly correlated with enrichment in tumor-infiltrating lymphocyte signatures (TIL) which show superior prognostic and predictive power. In addition, Tumor Associated Macrophage (TAM) signatures show independent predictive and prognostic power for both patient survival and response to anthracycline- and taxane-based chemotherapies. These gene signature-based correlations were validated in a new independent cohort of 67 TNBC-patients treated with neoadjuvant chemotherapy. Overall, these results argue for the independent contributions of both cancer-intrinsic and -extrinsic factors in predicting treatment response in the neoadjuvant setting.

ORGANISM(S): Homo sapiens

PROVIDER: GSE260693 | GEO | 2024/03/20

REPOSITORIES: GEO

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Project description:Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer, with approximately 50% of patients having residual disease after neoadjuvant chemotherapy (NACT) and worse prognosis with higher residual cancer burden (RCB). Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. There is a need for PDX models encompassing the heterogeneity of TNBC both pre- and post- therapy and for identifying clinical and molecular features of patient’s tumors that are associated with success in establishing these models. Using fine-needle aspirates (FNAs), we established orthotopic PDX models of TNBC from the primary breast tumors of patients prior to and following neoadjuvant systemic therapy while enrolled in the ARTEMIS trial (NCT02276443). ARTEMIS is a prospective neoadjuvant clinical trial for women with primary TNBC who are treated with four cycles of Adriamycin combined with cyclophosphamide (AC) followed by taxane +/- different experimental therapies. Serial biopsies were obtained from patients prior to treatment (pre-therapy), from poorly responsive disease after four cycles of AC (mid-NACT), and in cases of AC-resistance, after a three-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 FNA biopsies from 217 women, generating a total of 62 successful PDX models (overall success-rate = 23%). This cohort includes five serial pre- and mid-NACT PDX pairs, as well as one serial pre-, mid-, post-NACT triplet. Success of PDX engraftment was generally higher from cancers that proved to be treatment-resistant: whether poor response to AC determined by ultrasound measurements mid-NACT (p=0.063), RCB II/III status after NACT (p=0.046), or metastatic relapse within two years of surgery (p=0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumor revealed no significant association with PDX engraftment rate (p=0.877). Finally, we developed a statistical model predictive of PDX engraftment using percent Ki67 positive cells in the patient’s diagnostic biopsy, positive lymph node status at diagnosis, and low volumetric reduction of the patient’s tumor following AC treatment. This novel bank of 62 PDX models of TNBC provides a valuable resource for biomarker discovery and preclinical therapeutic trials aimed at improving neoadjuvant response rates for patients with TNBC.

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Breast cancer-subtype and infiltrating macrophage signatures predict chemotherapy-response and survival

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