569 Background: Taxane and platinum (TP) NAC regimens, e.g. Carboplatin and Docetaxel (CbD), in TNBC are currently of great interest, having good pathologic complete response (pCR) rates but with a significantly more manageable toxicity profile compared to anthracycline-based NAC regimens. Forkhead Box C1 (FOXC1), a transcriptional driver of cell plasticity/partial EMT/metastasis is an established mesenchymal marker diagnostic of basal-like breast cancer having proven prognostic value, but of uncertain predictive value. We sought to evaluate the potential of FOXC1 in predicting pCR to neoadjuvant TP regimens in patients diagnosed with TNBC. Methods: Pre-NAC tumor biopsy FOXC1 mRNA expression status was correlated with rate of pCR in a pooled, ambispective cohort (prospective cohort GEICAM/2006-03, NCT00432172 pooled with multi-institutional retrospective cohort, n = 119). A specific FOXC1 mRNA expression cutoff value was derived to maximize Negative Predictive Value (NPV) and Sensitivity for pCR prediction. The pCR-predictive ability of FOXC1 mRNA expression was then assessed in two validation cohorts of evaluable patients who had been enrolled in prospective clinical trials (UCONN/FIOCRUZ, n = 222, HGUGM, NCT01560663, n = 221). All evaluated patients had been diagnosed with TNBC and had received a Taxane plus Platinum-based NAC regimen. Results: FOXC1 mRNA expression was associated with pCR in CbD/TP treated TNBC patients with pCR rates of 43.48%, 47.89% and 52.73% observed in the discovery and two validation cohorts (two tailed T-test p-values of 0.0005, 0.002, 0.009, respectively). FOXC1 expression above the pre-determined cutoff value was associated with pCR to CbD/TP NAC in patients diagnosed with TNBC in both validation cohorts (OR 4.894, 1.504-15.924; p = 0.004 and OR 2.293, 1.208-4.352; p = 0.006). Conclusions: We report the retrospective validation of pre-NAC breast cancer biopsy FOXC1 mRNA expression for predicting efficacy of CbD/TP NAC in two independent, prospectively accrued TNBC patient cohorts. The described strategy may be acceptable for patient stratification to guide CbD/TP NAC recommendations in TNBC. FOXC1 mRNA or protein expression, assessed using qRT-PCR or routine immunohistochemistry (IHC), respectively, could potentially be utilized in future fixed-arm/adaptive clinical trials to further optimize NAC efficacy, in terms of achieved pCR rates, and to extend disease-free survival in patients diagnosed with TNBC.

Taxane

Carboplatin

Regimen

Triple-negative breast cancer

10.1200/jco.2022.40.16_suppl.569

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Supplemental Material from A PAM50-Based Chemoendocrine Score for Hormone Receptor–Positive Breast Cancer with an Intermediate Risk of Relapse

Aleix Prat Aña Lluch Arran Turnbull Anita K. Dunbier Lourdes Calvo

Supplemental Methods, Tables and Figures Tables Table S1. CES association with chemotherapy sensitivity (measured as pCR) in the MDACC-based dataset. Table S2. CES association with chemotherapy sensitivity (measured as Residual Cancer Burden [RCB]) in the MDACC-based dataset. Model A. Table S3. CES association with chemotherapy sensitivity (measured as Residual Cancer Burden [RCB]) in the MDACC-based dataset. Model B. Table S4. Univariate association of CES and various signatures with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S5. Association of CES and PAM50 Proliferation Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S6. Association of CES and CHEMOPRED Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S7. Association of CES and the proliferation component of the Genomic Health Index (GHI; OncotypeDX Recurrence Score) with chemotherapy sensitivity in HR+/HER2- negative disease from the MDACC-based dataset. Table S8. Association of CES and Genomic Grade Index (GGI) Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S9. Association of CES and SET index Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S10. Association of CES and RCBPRED Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S11. Association of CES and DLDA30 Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S12. Association of CES and ROR-P Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S13. Association of CES and Ki67 by IHC with chemotherapy sensitivity in HR+/HER2-negative disease of the Malaga cohort. 7 Table S14. Association of CES and PAM50 ROR with chemotherapy sensitivity in HR+/HER2-negative disease of the Malaga cohort. Table S15. CES association with endocrine sensitivity in the Marsden dataset (n=103). Table S16. CES association with endocrine sensitivity in the Marsden dataset within HER2-negative disease (n=89). Figures Fig. S1. Association of CES with Miller-Payne following chemotherapy in HR+/HER2- negative disease from the Malaga-based cohort. Fig. S2. CES association with endocrine sensitivity in the Edinburgh dataset (n=120). (A) Tumor volume changes of each patient and response classification. (B) Association of CES and other variables with response (defined as at least 70% reduction by 90 days) in the overall population. (C) Association of CES and other variables with response within HER2-negative disease. Fig. S3. Association of CES with pCR in the combined dataset from the MDACC- and Malaga-based cohorts.

Table (database)

10.1158/1078-0432.22463336.v1

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Supplementary Data from Genetic Polymorphisms and Correlation with Treatment-Induced Cardiotoxicity and Prognosis in Patients with Breast Cancer

Parvin F. Peddi Peter A. Fasching Duan Liu Emmanuel Quinaux Nicholas J. Robert

Supplementary Data from Genetic Polymorphisms and Correlation with Treatment-Induced Cardiotoxicity and Prognosis in Patients with Breast Cancer

Cardiotoxicity

10.1158/1078-0432.22483668.v1

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Supplementary Figure S4 from Triple-Negative PAM50 Non-Basal Breast Cancer Subtype Predicts Benefit from Extended Adjuvant Capecitabine

Karama Asleh Aña Lluch Angela Goytain Carlos H. Barrios Xue Q. Wang

Supplementary Figure S4 shows a forest plot of the exploratory categorical analysis of selected (meta)gene expression and their association with disease free survival on the capecitabine arm vs. observation.

Triple-negative breast cancer

Basal (medicine)

Categorical variable

Exploratory analysis

10.1158/1078-0432.22488650.v1

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Data from Analysis of Fcγ Receptor IIIa and IIa Polymorphisms: Lack of Correlation with Outcome in Trastuzumab-Treated Breast Cancer Patients

Sara A. Hurvitz David J. Betting Howard M. Stern Emmanuel Quinaux Jeremy Stinson

<div>AbstractPurpose: The mechanisms by which trastuzumab imparts clinical benefit remain incompletely understood. Antibody-dependent cellular cytotoxicity via interactions with Fcγ receptors (FcγR) on leukocytes may contribute to its antitumor effects. Single-nucleotide polymorphisms (SNP) in FCGR3A and FCGR2A genes lead to amino acid substitutions at positions 158 and 131, respectively, and affect binding of antibodies to FcγR such that 158V/V and 131H/H bind with highest affinity. This study aimed to determine whether high-affinity SNPs are associated with disease-free survival (DFS) among patients with HER2-positive nonmetastatic breast cancer.Experimental Design: Genomic DNA was isolated from 1,286 patients enrolled in a trial of adjuvant trastuzumab-based chemotherapy. Genotyping was conducted using Sanger sequencing and Sequenom mass spectrometry.Results: Patient samples (N = 1,189) were successfully genotyped for FCGR3A and 1,218 for FCGR2A. Compared with the overall results of the BCIRG006 study, in the subset of patients genotyped in this analysis, a less robust improvement in DFS was observed for the trastuzumab arms than control arm (HR, 0.842; P = 0.1925). When stratified for prognostic features, the HR in favor of trastuzumab was consistent with that of the overall study (HR, 0.74; P = 0.036). No correlation between DFS and FCGR3A/2A genotypes was seen for trastuzumab-treated patients (158V/V vs. V/F vs. F/F, P = 0.98; 131H/H vs. H/R vs. R/R, P = 0.76; 158V/V and/or 131H/H vs. others, P = 0.67).Conclusion: This analysis evaluating the association between FCGR3A/2A genotypes and trastuzumab efficacy in HER2-positive breast cancer did not show a correlation between FCGR3A-V/F and FCGR2A-H/R SNPs and DFS in patients treated with trastuzumab. Clin Cancer Res; 18(12); 3478–86. ©2012 AACR.</div>

10.1158/1078-0432.c.6519876

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Supplementary Figure from Determinants of Response to Talazoparib in Patients with HER2-Negative, Germline BRCA1/2-Mutated Breast Cancer

Joanne L. Blum A. Douglas Laird Jennifer K. Litton Hope S. Rugo Johannes Ettl

Supplementary Figure from Determinants of Response to Talazoparib in Patients with HER2-Negative, Germline BRCA1/2-Mutated Breast Cancer

HER2 negative

10.1158/1078-0432.22482984

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Supplementary Table S1 from Baseline mutations and ctDNA dynamics as prognostic and predictive factors in ER-positive/HER2-negative metastatic breast cancer patients

Javier Pascual Miguel Gil‐Gil Paula Proszek Christoph Zielinski Alistair Reay

Supplementary Table 1. List of the 21 genes included in the breast cancer panel used for sequencing, and the targeted coding regions in each case.

HER2 negative

Baseline (sea)

10.1158/1078-0432.27033649.v1

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Supplementary Figure S1 from Baseline mutations and ctDNA dynamics as prognostic and predictive factors in ER-positive/HER2-negative metastatic breast cancer patients

Javier Pascual Miguel Gil‐Gil Paula Proszek Christoph Zielinski Alistair Reay

Supplementary Figure 1. Survival analysis in baseline population (C1D1).

Baseline (sea)

HER2 negative

10.1158/1078-0432.27033664.v1

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Supplementary Table S12 from Baseline mutations and ctDNA dynamics as prognostic and predictive factors in ER-positive/HER2-negative metastatic breast cancer patients

Javier Pascual Miguel Gil‐Gil Paula Proszek Christoph Zielinski Alistair Reay

Supplementary Table 12. Baseline genomic landscape of mutations distribution for the CDR population (n=120), by number of mutations or presence/absence, across treatment arms.

HER2 negative

Baseline (sea)

10.1158/1078-0432.27033640.v1

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Role of Stromal Myofibroblasts Infiltrating Colon Cancer in Tumor Invasion

Pathology - Research and Practice (1996)

Miguel Martín Philippe Pujuguet Florian Martin

Myofibroblast

10.1016/s0344-0338(96)80093-8

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