Torres, Evanthia T. Roussos

Abstract Background: Hispanic/Latinx (HL) and African American (AA) breast cancer (BC) patients (pts) have increased prevalence of high-risk features such as incidence of BC at age <50 and estrogen receptor negativity. We previously showed that AA and HL had a lower fraction of neutrophils and M2 macrophages (Mɸ) despite higher percentage of PD-L1 positive cases. This study aims to further characterize differences in the tumor immune microenvironment between racial and ethnic groups, with a focus on how these differences vary by site of biopsy. Methods: We analyzed 19,459 BC samples tested by NGS (592, NextSeq; WES, NovaSeq) and WTS (NovaSeq; Caris Life Sciences). Race/ethnicity data were self-reported by pts. Immune cell proportions were estimated using WTS deconvolution (Quantiseq). Gene expression was analyzed for T-cell inflammed score (TIS), MAPK Activation Score (MPAS) and interferon-gamma (IFNy) score. Real-world overall survival (OS) data were derived from insurance claims, calculated from tissue collection or treatment initiation to last contact, and analyzed using Kaplan-Meier. Statistical significance was assessed by chi-square and Mann-Whitney U test with p-values adjusted for multiple comparisons (q<0.05). Results: There were 9674 Non-Hispanic Whites (NHW) (primary BC, defined as biopsy (bx) from breast) pBC: n=3,537, 36.6%; (metastatic BC, defined as biopsy outside of the breast) mBC: n=6,137 63.4%, 1800 AA (pBC: n=750, 42%, mBC: n=1,050, 58%), and 1795 HL (pBC: n=842, 47%; mBC n=953, 53%) samples. There were 2364 TNBC (66% NHW, 19% NHB, 15% HL), 4318 HR+/HER2- (76% NHW, 11.6% NHB, 12.4% HL), and 893 HER2+ (68% NHW, 15% NHB, 17% HL). In pBC overall, AA had lower median cell fraction (%) of B cells (4.8% vs 5.3%), M2 Mɸ (3.4% vs 4.4%), but higher median cell fraction of dendritic cells (DC) (2.8% vs 2.6%) compared to NHW while HL had lower median cell fraction of M2 Mɸ (3.9% vs 4.4%) and higher median cell fraction of CD8+ T cell (0.4% vs 0.2%), all q<0.05. In pBC, HL had higher IFNy score (-0.3 vs -0.34), while AA had lower MPAS (-1.2 vs -0.96), all q<0.05. In lymph node bx, AA had lower median % of M2 Mɸ (3.4% vs 4.4%, q<0.05). No significant differences were seen in the liver bx by race but notably there were lower median cell fractions of CD4+, CD8+, and regulatory T cells (0.0 across NHW, AA, HL) across all race/ethnicities vs. other biopsy sites. By subtype, TNBC primary bx yielded much of the significant changes with AA having lower median cell fraction of M2 Mɸ (2.49% vs 3.04%, q= 0.01) compared to NHW. In primary bx, AA (35.6 m vs 48.5 m, HR 1.4, 95% CI 1.2-1.5, p<0.001) and HL (42.4 m vs 48.5 m, HR 1.2, 95% CI 1.1-1.4, p<0.001) had worse median OS versus NHW. In lymph node bx, AA also had worse OS (29.2 m vs 37.2 m, HR 1.2, 95% CI 1-1.5, p=0.03) compared to NHW. In liver bx, there was worse mOS overall but no difference by race (NHW 18.65m, AA 18.79m, HL 20.6m, p =0.73). In HR+/HER2- liver bx AA had worse OS (14.2 m vs 20.9 m, HR 1.3, 95% CI 1-1.7, p=0.03) versus NHW. In HER2+ primary bx, HL had worse OS (43.2m vs 66.9m, HR 1.7, 95% CI 1.1-2.6, p=0.009). There was a trend towards worse mOS in TNBC AA patients receiving pembrolizumab (18.42m vs HL 23.69m vs NHW 35.30m; p=0.16) and HER2+ AA patients receiving trastuzumab deruxtecan (AA: 16.06m vs HL: 26.81m vs NHW: not reached; p = 0.05). Conclusions: We found race and biopsy site specific differences in the breast cancer immune microenvironment. AA pts had lower M2 Mɸ in primary and lymph node bx while NHW pts showed higher CD8+ T cell in primary tumors. Liver biopsies exhibited low T cell infiltration across all groups. AA pts had worse mOS in primary and lymph node bx compared to NHW but not in liver bx of which we saw worse mOS in all races. These results highlight the need to consider both race and bx site in treatment decisions. Citation Format: R. Hsu, S. Deshmukh, N. Gyabaah-Kessie, E. Rallos, B. Al-Zubeidy, E. Gonzalez, A. G. Baugh, S. Carrel, M. Li, D. Zavala, A. Martynova, P. Jayachandran, D. Stewart, D. Spicer, S. Wu, J. Xiu, G. W. Sledge Jr., R. L. Mahtani, A. C. Sandoval Leon, S. Gandhi, S. Chumsri, M. Lustberg, M. C. Stern, E. T. Roussos Torres. Immune microenvironment and survival differences among Hispanic and African American breast cancer cases by biopsy site [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-12-06.

1051 Background: Hispanics or Latinos (HL) and African Americans or Black (AA) have a higher prevalence of advanced-stage breast cancer (BC) at diagnosis compared to Non-Hispanic Whites (NHW). To understand the role of immune system, we evaluated the tumor immune microenvironment (TIME) by race/ethnicity among HL, AA, and NHW BC patients. Methods: 15544BC samples were tested by NGS (592, NextSeq; WES, NovaSeq) and WTS (NovaSeq; Caris Life Sciences, Phoenix, AZ). Race/ethnicity data is self-reported. Immune cell were estimated using WTS deconvolution (Quantiseq). Gene expression profiles were analyzed for T-cell inflammation score (TIS) and interferon-gamma (IFN-gamma) score. Real-world overall survival (OS) was obtained from insurance claims and calculated from date of tumor biopsy to last contact using Kaplan-Meier estimates. Statistical significance was determined by chi-square and Mann-Whitney U test with p -values adjusted for multiple comparisons (q < .05). Results: 7170 NHW (35.3%, N = 2528) biopsied (bx) from primary breast cancer (pBC), 64.7% (N = 4642) metastatic bx (mBC), 1,508 AA (pBC 39.3% N = 592, mBC 60.7% N = 916), and 1,754 HL (pBC 44.1% N = 774, mBC 55.9% N = 980) cases were included. By subtype, there were 1,956 (60.4% NHW, 20.7% NHB, 18.9% HL) TNBC, 3425 HR+/HER2- (72.6% NHW, 11.9% NHB, 15.6% HL), and 694 HER2+ (64.6% NHW, 15.7% NHB, 19.7% HL). Across all cases, AA (20.5%) and HL (20.4%) had greater incidence (%) of PD-L1+ cases versus (vs) NHW (17.4%), all q < .05. TMB-High (³10 mut/Mb) was similar in NHW (11.5%), AA (10.8%), and HL (10.9%). AA tumors had lower median % cell infiltration of M2-like macrophages (M2 Mφ), B cells, and neutrophils vs NHW (Table). HL had a lower fraction of M2 Mφ and higher CD8+ T cells (Table). AA had lower TIS (-8 vs 1, p = .02) while HL had lower IFN-gamma (-0.38 vs. -0.35, q < .05) vs NHW. By subtype, AA had lower neutrophils (4% vs 4.3%) and increased DC fractions (3.1% vs 2.8%) in TNBC vs NHW, all q < .05; no significant changes seen in HL vs NHW. AA had worse mOS than NHW overall (31.8 vs 36.8 months (mo)), HR 1.1, 95% CI 1 – 1.2, p = < .01), in pBC (40.3 vs 49.9 mo, HR 1.3, 95% CI 1.1 – 1.5, p = < .01), but not mBC (27.4 vs 29.1 mo, HR 1, p = 0.2). HL had similar mOS vs NHW overall (37.4 vs 36.8 mo, HR 0.9, p = 0.9) and in mBC (29.1 vs 31 mo, HR 0.96, p = 0.4), but worse mOS in pBC (44.7 vs 50.0 mo, HR 1.1, 95% CI 1 – 1.3, p = .01). Conclusions: Our study shows worse mOS in AA and HL pBC cases vs NHW, possibly from a less inflamed TIME in AA and HL and lower fraction of neutrophils and M2 Mφ despite higher % of PD-L1+. Targeting Mφ and CD8+ T cells and converting cold to hot TIME may lessen race/ethnic disparities, especially in early-stage BC. Immune cell fraction of NHW, AA and HL BC. NHW (median %) AA (median %) HL (median %) q-valueNHW vs AA q-value NHW vs HL B cell 5.2 4.8 5.0 <.05 0.7 DC 2.6 2.7 2.6 0.08 0.4 M1 Mφ 2.5 2.4 2.4 0.4 0.9 M2 Mφ 4.6 3.7 4.2 <.05 <.05 Neutrophils 3.7 3.5 3.4 <.05 <.05 NK cell 2.9 2.9 2.9 0.7 0.6 CD8+ T cell 0.1 0.15 0.26 0.8 <.05 Treg 1.5 1.5 1.6 0.6 <.05

569 Background: Several studies established the prognostic role of both the amount and locations of tumor-infiltrating lymphocytes (TILs) in TNBC. Three distinct immunotypes were described based on the amount and locations of TILs: immune enriched (IN), immune excluded, and immune desert. Using single-cell spatial transcriptomic analysis in the Mayo Clinic TNBC cohort, our previous studies showed the central role of interferon (IFN) signaling in IN phenotype. Herein, we evaluated the association between IFN and outcomes in TNBC in 3 independent datasets. Methods: NanoString IO360 was performed in 114 samples from FinXX (NCT00114816) to generate 22-gene IFNα and 33-gene IFNγ signatures. RNA sequencing was performed in 388 samples from CALGB 40603 (NCT00861705). 3038 TNBC samples were tested by WTS (NovaSeq; Caris Life Sciences, Phoenix, AZ). Median values were used as cut-offs for high vs low IFNγ RNA expression and 18-gene IFNγ signature scores. Caris Life Science CODEai was used to evaluate real-world overall survival (OS) obtained from insurance claims and calculated from tissue collection to last contact using Kaplan-Meier estimates. Chi-square, Mann-Whitney U, ANOVA, and Cox regression were used. Results: A high 22-gene IFNα signature score was associated with significantly improved recurrence-free survival (RFS) in FinXX (hazard ratio [HR] 0.32, 95% confidence interval [CI] 0.14-0.74, p 0.007) and OS (HR 0.28, 95%CI 0.12-0.66, p 0.003). Similar findings were observed with 33-gene IFNγ signature with significant improvement in RFS (HR 0.21, 95%CI 0.09-0.51, p < 0.001) and OS (HR 0.18, 95%CI 0.08-0.44, p < 0.001). Furthermore, in CALGB 40603, both IFNα and IFNγ scores were positively associated with pathologic complete response (pCR: IFNα p 0.019 and IFNγ p 0.007) and residual cancer burden (RCB: IFNα p 0.044 and IFNγ p 0.013). Using the Caris data platform to further validate, we identified 2899 TNBC patients (pts) with genomic and clinical outcome data. High IFNγ expression was associated with significant improvement in OS (25.95 vs 17.43 months; HR 0.65, 95% CI 0.59 – 0.72, p < 0.001). Similarly, pts with high IFNγ signature scores had significant improvement in median OS (25.79 vs 16.22 months; HR 0.66, 95% CI 0.6 – 0.73, p < 0.001). Conclusions: This study underscores the pivotal role of IFN signaling in TNBC. High IFNα and IFNγ signatures were consistently associated with improved RFS, OS, higher pCR rates, and lower RCB across clinical trial cohorts and real-world data. These findings signify IFN signaling as a potential key biomarker and therapeutic target in TNBC. Support: U10CA180821, U10CA180882, U24CA196171; Breast Cancer Research Foundation, Mayo Clinic Breast Cancer SPORE (P50CA116201-17), Bankhead Coley, W81XWH-15-1-0292, P50CA015083, R35CA253187; https://acknowledgments.alliancefound.org . Genentech. Clinical trial information: NCT00114816 and NCT00861705 .

Abstract Background: Metaplastic Breast Cancer (MBC) is rare (0.2-5%), aggressive form of BC characterized by chemotherapy resistance and has worse outcomes in comparison to other BC subtypes. Resistance to chemotherapeutic agents is related to defects in intact intrinsic apoptosis pathway and the BCL2 family of proteins are the central regulators of this pathway. Majority of MBC have triple-negative receptor status and have no standard therapeutic approach and validated prognostic markers. Here, we examine the association of BCL2 family pro-apoptotic and anti-apoptotic genes expression with metaplastic TNBC (MTNBC) patient survival. Methods: 13,036 BC samples (MTNBC, n=102; metaplastic non-TNBC, n=20) were analyzed by next-generation sequencing (592, NextSeq; WES, NovaSeq), Whole Transcriptome Sequencing (WTS; NovaSeq) (Caris Life Sciences, Phoenix, AZ). A total of 10 pro-apoptotic (BAX, BAK1, BID, BAD, BIK, BCL2L11, BMF, HRK, PMAIP1, BBC3) and 6 anti-apoptotic (BCL2, BCL2L1, BCL2L2, MCL1, BCL2A1, BCL2L10) BCL2 family genes were analyzed. MTNBC with PMAIP1-high(H) and -low(L) expression was classified by top and bottom quartile, respectively. Pathway enrichment was determined by GSEA (Broad Inst). Real world overall survival (OS) was extracted from insurance claims and calculated from tissue collection to last contact using Kaplan-Meier estimates. Statistical significance was determined using chi-square and Mann-Whitney U test with p-values adjusted for multiple comparisons (q &lt; 0.05). Results: MTNBC had enrichment of apoptosis (NES: 1.4, FDR: 0.05), glycolysis (NES: 1.48, FDR: 0.03), PI3K/AKT/mTOR signaling (NES: 1.43, FDR: 0.05), P53 (NES: 1.51, FDR: 0.06), NOTCH signaling (NES: 1.39, FDR: 0.05), TGFβ signaling (NES: 1.41, FDR: 0.05), WNTβ catenin signaling (NES: 1.41, FDR: 0.05) and IL2/STAT5 signaling (NES: 1.33, FDR: 0.09) pathways compared to metaplastic non-TNBC. MTNBC had higher expression of BCL2 pro-apoptotic genes BAX (Fold Change (FC): 1.6), BAK1 (FC: 1.3), BID (FC: 2), BAD (FC: 1.6), BCL2L11 (FC: 2.5) and BBC3 (FC: 1.5), and anti-apoptotic genes BCL2L1 (FC: 1.6) and BCL2L2 (FC: 1.3) (all p &lt; 0.05) compared to metaplastic non-TNBC. Higher PMAIP1 gene expression was associated with worse MTNBC patient survival (mOS: 14.3 month; HR: 0.37; 95% CI 0.19-1.41; p=0.002) (Table 1), but not in metaplastic non-TNBC (mOS: Inf; HR: 1.96; 95% CI 0.64-6.02; p=0.23). PMAIP1-H MTNBC had higher expression of immune checkpoint genes CD274 (FC: 2.8), PDCD1 (FC: 2.2), TIM3 (FC: 1.8), LAG3 (FC: 2.1) and IDO1 (FC: 5.7) (all p &lt; 0.05), compared to PMAIP1-L MTNBC. PMAIP1-H MTNBC had higher frequency of IHC-PD-L1 positivity (68.4% vs 14.3%, p &lt; 0.05). PMAIP1-H MTNBC had higher expression of stem cell related genes CD44 (FC: 1.7), ALDH1A2 (FC: 2.2), ALDH1A3 (FC: 2.6), SOX2 (FC: 5.21) and NANOG (FC: 2.13) (all p &lt; 0.05) compared to PMAIP1-L MTNBC. Conclusion: This is the first comprehensive analysis of expression and prognostic role of BCL2 family proteins in MBC. Our data suggest a strong association of higher expression of PMAIP1 with worse MTNBC patient survival, potentially attributed to higher immune checkpoint, stem cell-related genes expression, and higher frequency of PD-L1 positivity in PMAIP1-H tumors. These findings indicate PMAIP1 as a potential prognostic biomarker candidate in MTNBC but needs further validation in large prospective studies Table 1. Overall survival of metaplastic TNBC patient based on BCL2 family gene expression. Citation Format: Pooja Advani, Sachin Deshmukh, Sharon Wu, Jacob Andring, Joanne Xiu, Alex Farrell, Milan Radovich, George Sledge Jr, Dario Trapani, Evanthia Roussos Torres, Stephanie Graff, Asher Chanan-Khan. Comprehensive Characterization of BCL2 Family Genes in Metaplastic Triple Negative Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-24-02.

Background The C-C motif chemokine receptor 5 (CCR5)/C-C motif chemokine ligand 5 (CCL5) axis plays a major role in colorectal cancer (CRC). We aimed to characterize the molecular features associated with CCR5 / CCL5 expression in CRC and to determine whether CCR5 / CCL5 levels could impact treatment outcomes. Methods 7604 CRCs tested with NextGen Sequencing on DNA and RNA were analyzed. Molecular features were evaluated according to CCR5 and CCL5 tumor gene expression quartiles. The impact on treatment outcomes was assessed in two cohorts, including 6341 real-world patients and 429 patients from the Cancer and Leukemia Group B (CALGB)/SWOG 80405 trial. Results CCR5 / CCL5 expression was higher in right-sided versus left-sided tumors, and positively associated with consensus molecular subtypes 1 and 4. Higher CCR5 / CCL5 expression was associated with higher tumor mutational burden, deficiency in mismatch repair and programmed cell death ligand 1 (PD-L1) levels. Additionally, high CCR5 / CCL5 were associated with higher immune cell infiltration in the tumor microenvironment (TME) of MMR proficient tumors. Ingenuity pathway analysis revealed upregulation of the programmed cell death protein 1 (PD-1)/PD-L1 cancer immunotherapy pathway, phosphatase and tensin homolog (PTEN) and peroxisome proliferator-activated receptors (PPAR) signaling, and cytotoxic T-lymphocyte antigen 4 (CTLA-4) signaling in cytotoxic T lymphocytes, whereas several inflammation-related pathways were downregulated. Low CCR5 / CCL5 expression was associated with increased benefit from cetuximab-FOLFOX treatment in the CALGB/SWOG 80405 trial, where significant treatment interaction was observed with biologic agents and chemotherapy backbone. Conclusions Our data show a strong association between CCR5/CCL5 gene expression and distinct molecular features, gene expression profiles, TME cell infiltration, and treatment benefit in CRC. Targeting the CCR5/CCL5 axis may have clinical applications in selected CRC subgroups and may play a key role in developing and deploying strategies to modulate the immune TME for CRC treatment.

Abstract Background: Data supporting high tumor mutational burden (TMB-H) as a lone biomarker for an immune responsive tumor microenvironment (TME) or of response to immune checkpoint inhibition (ICI) in metastatic breast cancer (MBC) is weak; yet the tumor agnostic approval in TMB-H advanced tumors makes ICI an option in the clinic. PDL-1 positivity (PDL-1+) is the only consistent biomarker for ICI benefit in metastatic triple-negative BC (mTNBC). We sought to further evaluate concurrent predictors of an immune responsive or non-responsive TME within TMB-H MBC. Methods: Tumor samples (N=5621) obtained from patients with MBC were analyzed by next-generation sequencing (NGS) of DNA (592-gene panel or whole exome sequencing) and RNA (whole transcriptome sequencing) at Caris Life Sciences (Phoenix, AZ). Friends of Cancer Research TMB Harmonization Project (Merino et al., 2020) recommendations, with the TMB-H threshold set to ≥ 10 muts/Mb, were used. PDL-1+ (≥1% immune cells stained) assessed by IHC (Ventana SP142). Deficient-mismatch repair (dMMR) and high microsatellite instability (MSI-H) were determined by IHC and NGS, respectively. Gene expression profiling assessed 21 immune-related signatures and TMEs using MCP-counter (Betch et al., 2016) and quanTIseq (Finotello et al., 2019). Immune cell types were classified as immune-responsive (CD8+ and CD4+ T cells, B cells, myeloid dendritic cells, M1 macrophages, NK cells, and neutrophils) or non-responsive (Tregs, M2 macrophages, and monocytes). P-values adjusted by the Benjamini-Hochberg procedure. Exploratory p-values reported for sub-analyses of TMB-H responsive vs nonresponsive TME and PDL1+ vs PDL1- subgroups. Results: TMB-H was identified in 461/5621 (8.2%) MBC samples. TMB-H tumors exhibit significant enrichment of dMMR/MSI-H (7 vs 0%, p&lt;0.0001) and IHC-PDL1+ (36 vs 28%, p&lt;0.05) compared to TMB-L. TMB-H was not associated with increased abundance or proportion of immune responsive cell types or immune response gene signatures (e.g. antigen presentation), yet positive trends were observed. To identify predictive biomarkers of immune responsive (hot) or non-responsive (cold) TME profiles within TMB-H MBC, we generated a composite TME score representing the overall proportion of hot vs cold immune cell types. APOBEC mutagenesis was common in TMB-H tumors (72%) and was more frequently associated with an immune cold TME (77 vs 66% in hot TME subgroup, p=0.068). Within TMB-H tumors, cold TMEs were enriched with mutations (muts) in PIK3CA (61 vs 47%), CHEK2 (5 vs 0%), CBFB (4 vs 0%), amplifications (amp) of CCND1 (13 vs 4%), FGF19 (16 vs 5%), FGF4 (11 vs 4%), and MMLT6 (6 vs 0%), and expression of IHC-AR (75 vs 58%) compared to hot TMEs (all p&lt;0.05). Hot TMEs had increased frequency of MSI-H (12 vs 5%) and KMT2D muts (12 vs 3%) compared to cold TMEs (all p&lt;0.05). Amongst TMB-H and TMB-L tumors, PDL1+ was significantly associated with increased proportion of immune responsive cell types (ie CD8+) compared to PDL1- tumors (0.14 vs -0.08 TME score, p&lt;0.0001). Comparison of TMB-H tumors by PDL1 status revealed enrichment of TP53 (67 vs 53%) and B2M (8 vs 0%) muts in PDL1+ tumors, while IHC-ER positivity (68 vs 54%) and CDH1 muts (32 vs 16%) were increased in PDL1- tumors (all p&lt;0.05). Conclusions: High TMB alone does not strongly correlate with immune infiltrate or immune response gene signatures in MBC. Within TMB-H MBC, concurrent mutations in MSI-H and KMT2D are associated with an immune responsive TME while mutations in PIK3CA, CHEK2, CBFB, amplifications of CCND1, FGF19, FGF4, and MMLT6, and expression of IHC-AR are associated with an immune non-responsive TME. Co-occurring biomarkers within TMB-H breast cancer warrant evaluation in prospective cohorts for response or resistance to ICI to help develop composite biomarkers in breast cancer. Citation Format: Sarah Sammons, Andrew Elliott, Jeremy Force, Saranya Chumsri, Carey Anders, Antoinette R Tan, Daniel Magee, Jia Zeng, W. Michael Korn, Mustafa Kahsraw, Evanthia T Roussos Torres. Concurrent predictors of an immune responsive tumor microenvironment within tumor mutational burden-high breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-08-08.