Triple-negative Breast Cancer Cohort Research Articles

Extracellular matrix markerLAMC2 targets ZEB1 to promote TNBC malignancy via up-regulating CD44/STAT3 signaling pathway.

Triple negative breast cancer (TNBC) is a heterogeneous and aggressive disease characterized by a high risk of mortality and poor prognosis. It has been reported that Laminin γ2 (LAMC2) is highly expressed in a variety of tumors, and its high expression is correlated with cancer development and progression. However, the function and mechanism by which LAMC2 influences TNBC remain unclear. Kaplan-Meier survival analysis and Immunohistochemical (IHC) staining were used to examine the expression level of LAMC2 in TNBC. Subsequently, cell viability assay, wound healing and transwell assay were performed to detect the function of LAMC2 in cell proliferation and migration. A xenograft mouse model was used to assess tumorigenic function of LAMC2 in vivo. Luciferase reporter assay and western blot were performed to unravel the underlying mechanism. In this study, we found that higher expression of LAMC2 significantly correlated with poor survival in the TNBC cohort. Functional characterization showed that LAMC2 promoted cell proliferation and migration capacity of TNBC cell lines via up-regulating CD44. Moreover, LAMC2 exerted oncogenic roles in TNBC through modulating the expression of epithelial-mesenchymal transition (EMT) markers. Luciferasereporterassay verified that LAMC2 targeted ZEB1to promote its transcription.Interestingly, LAMC2 regulated cell migration in TNBC via STAT3 signaling pathway. LAMC2 targeted ZEB1 via activating CD44/STAT3 signaling pathway to promote TNBC proliferation and migration, suggesting that LAMC2 could be a potential therapeutic target in TNBC patients.

Immunohistochemical profile of triple negative breast cancers: SOX10 and AR dual negative tumors have worse outcomes.

Triple negative breast cancer (TNBC) refers to an estrogen receptor negative, progesterone receptor negative, and HER2-negative breast cancer. Although accepted as a clinically valid category, TNBCs are heterogeneous at the histologic, immunohistochemical, and molecular levels. Gene expression profiling studies have molecularly classified TNBCs into multiple groups, but the prognostic significance is unclear except for a relatively good prognosis for the luminal androgen receptor (LAR) subtype. Immunohistochemistry (IHC) has been used as a surrogate for basal and luminal subtypes within TNBC, but prognostication of TNBC using IHC is not routinely performed. We aimed to study immunophenotypic correlations in a well-annotated cohort of consecutive TNBCs, excluding post-neoadjuvant chemotherapy cases. Tissue microarrays were constructed from a total of 245 TNBC cases. IHC stains were performed and consisted of luminal (AR, INPP4B), basal (SOX10, Nestin, CK5, EGFR), and diagnostic (GCDFP15, mammaglobin, GATA3, TRPS1) markers. Survival analysis was performed to assess the significance of clinical pathologic variables including age, histology, grade, lymphovascular invasion [LVI], Nottingham prognostic index [NPI] category, AJCC stage, stromal tumor-infiltrating lymphocytes at 10% increment, CD8+ T-cell count, Ki-67 index, PD-L1 status, and chemotherapy along with the results of IHC markers. Apocrine tumors show prominent reactivity for luminal markers and GCDFP15 while no special type carcinomas are often positive for basal markers. TRPS1 is a sensitive marker of breast carcinoma but shows low or no expression in apocrine tumors. High AJCC stage, lack of chemotherapy, and dual SOX10/AR negativity are associated with worse outcomes on univariable as well as multivariable analysis. LVI and higher NPI category were associated with worse outcomes on univariable but not multivariable analysis. The staining for IHC markers varies based on tumor histology which may be considered in determining breast origin. Notably, we report that SOX10/AR dual negative status in TNBC is associated with a worse prognosis along with AJCC stage, and chemotherapy status.

Abstract PS05-02: PET Imaging of PARP Expression as a Biomarker of Response to Chemotherapy in Breast Cancer: A Nonrandomized Clinical Trial

Abstract Introduction: Poly–(adenosine diphosphate–ribose) polymerase (PARP) proteins are involved in double-stranded break repair, mediated through homologous recombination (HR) and non-homologous end joining (NHEJ). The majority of PARP activity in this context is attributed to PARP-1 (85-90%). PARP-1 binding to damaged DNA, catalytic activity, and subsequent release to allow access for other DNA repair proteins are necessary for efficient DNA repair. The critical function of PARP-1 in these processes makes this protein a unique potential biomarker of DNA repair capability. [18F]FluorThanatrace ([18F]FTT) is an 18F-labeled PARP inhibitor analog that binds to the same site as approved PARPi drugs. We hypothesized that the biologically relevant form of PARP in untreated breast cancer might provide an indication of functional tumor DNA repair capabilities and therefore predict chemotherapy response. Thus, this study aimed to determine whether a non-invasive quantitative measure of in vivo PARP expression correlated with response to chemotherapy in breast cancer. Methods: A single-arm prospective trial enriched for subjects with triple negative breast cancer (TNBC) was conducted at the University of Pennsylvania from May 2017 to March 2022 (NCT03083288 and NCT03846167). Inclusion criteria were primary breast cancer with tumor diameter of at least 1 cm on conventional imaging and willingness to undergo an [18F]FTT-PET scan prior to neoadjuvant chemotherapy. Participants provided written informed consent. [18F]FTT uptake in breast cancer was measured pre-therapy and tested for association with pathologic complete response (pCR). Subjects were scanned on an Ingenuity TF PET/CT (Philips Healthcare) following injection of [18F]FTT using a 20-minute static acquisition. Peak 1 cm3 average uptake (SUVpeak) were recorded from a spherical region-of-interest (ROI) covering the primary malignancy, guided by CT and prior imaging studies. All SUVs were partial volume corrected and normalized using muscle (NM). A Mann-Whitney test was used to determine if [18F]FTT uptake differed by pCR. Receiver operating characteristic (ROC) curves were constructed to test the performance of [18F]FTT uptake in predicting pCR. Statistical analyses utilized STATA v15.1 with significance based on a two-sided alpha level of ≤0.05. Participants: Twenty-six women with stage I-III breast cancer met inclusion criteria with age range of 29-74 years and self-reported race as Asian (1, 4%), Black (9, 37%) or White (16, 60%). One subject had bilateral tumors (ER+ stage IIA and HER2+ stage I) that were evaluated separately (27 total tumors). Breast tumors were pathologically confirmed and included 6 (22%) ER+/HER2-, 5 (19%) HER2+, and 16 (59%) TNBC. Germline sequencing was available for 21 participants. Results: Mean tumor diameter ranged from 15 to 91 mm (median 30 mm). A considerable range of [18F]FTT uptake was seen across subjects (SUVpeak/NM 0.66-6.5). [18F]FTT uptake was independent of subtype (ER+, HER2+, TN) (P=0.35), stage (P=0.39), and between mutations in genes associated with homologous recombination deficiency (i.e., BRCA1/2, PALB2) and wild-type (P=0.73). In the TNBC cohort, pre-treatment [18F]FTT uptake was higher in subjects who went on to have a pCR (n=16, P=0.05), while a trend toward higher uptake was seen when including all tumor types (n=27, P=0.11). ROC analysis of the value of [18F]FTT uptake for predicting pCR revealed an AUC of 0.79 and showed that a threshold SUV ratio < 2.47 predicted pCR in TNBC patients with a 100% specificity and 64% sensitivity. Conclusions: These early clinical results suggest a relationship between [18F]FTT uptake, a measure of PARP expression, and chemotherapy sensitivity in TNBC, warranting future studies to elucidate underlying mechanistic processes and potential clinical implications. Citation Format: Sarah Gitto, Anthony Young, Ira Bleiweiss, Amy Clark, Elizabeth McDonald. PET Imaging of PARP Expression as a Biomarker of Response to Chemotherapy in Breast Cancer: A Nonrandomized Clinical Trial [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 PS05-02.

Abstract PO1-06-07: EMSY enhances cancer stem cell self-renewal and tumorigenesis by reshaping methionine metabolism in triple-negative breast cancer

Abstract PO1-06-07: EMSY enhances cancer stem cell self-renewal and tumorigenesis by reshaping methionine metabolism in triple-negative breast cancer

Abstract PS03-03: The spatially resolved single-cell atlas of the tumor immune architecture revealed the central role of IFN-alpha and plasmacytoid dendritic cells in triple-negative breast cancer in the Mayo Clinic cohort and FinXX trial

Abstract Background: Multiple studies have confirmed the central role of preexisting immune response measured by stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC). Emerging studies showed that not only the number of TILs but also the location of TILs is important. There are 3 distinct immune architectures described based on the amount and locations of TILs, namely immune enriched (IN), immune excluded (IE), and immune desert (ID). Here we evaluated outcomes and characteristics associated with each immune landscape. Methods: NanoString Digital Spatial Profiling (DSP) and CosMx, a spatial multi-omics single-cell imaging platform, were performed in 75 samples from the Mayo Clinic (MC) TNBC cohort (Leon-Ferre BCRT 2018). NanoString IO360 was performed in 114 samples from the FinXX trial ( NCT00114816) . Firstly, tumors with sTIL quantified by H&E ≤ 30% were classified as ID. The rest of the tumors with high sTIL > 30% were categorized according to the intratumoral CD8 protein expression by DSP, with IE having intratumoral CD8 in the lower median and IN having intratumoral CD8 in the upper median. Chi-square test, gene set enrichment, Cox regression, and Kaplan-Meier analysis were used. Differential expression listed as log 2-fold change (FC) was estimated from the linear mixed model with significance defined as two-sided p< 0.05. Results: ID is associated with low Ki67 < 5% (23.3% vs. 9.6% ID, p 0.02) as well as apocrine (11/13, 84.6%) and metaplastic histology (10/12, 83%). In both univariate and multivariate analysis, patients with IN had significantly improved recurrence-free survival (RFS) compared to those with ID (HR 0.37, 95%CI 0.18-0.74, p 0.005). Despite having high sTILs, IE had poor outcomes similar to ID (HR 0.84, 95%CI 0.36-1.98). Strikingly, we identified that IE patients had significantly lower plasmacytoid dendritic cells (pDCs) compared to IN (mean 0 vs. 0.26/100 tumor cells, 95%CI 0.08-0.43 , p 0.01). Using Gene Set Enrichment Analysis to evaluate differential hallmarks between IN and IE, we identified IF Nɑ and IFNγ (FDR < 0.001) responses as significantly enriched in IN group, consistent wi th the function of pDCs, which are a subset of dendritic cells specialized in secreting high levels of type I interferon. To validate this finding, we further evaluated the 11 leading edge gene IFNɑ signature in the FinXX trial. A high IFNɑ signature score was associated with significantly improved outcomes in the FinXX trial (HR 0.21, 95%CI 0.09-0.51 , p < 0.001). Similar findings were observed using Kaplan-Meier analysis in the FinXX trial with significantly improved RFS (p 0.0006) and overall survival (p 0.0001) in patients with high IFNɑ signature scores. Furthermore, we evaluated the differential gene expression unique to IN tumors in the Mayo cohort. Expressions of MHC class I and class II in tumor cells, including HLA-A, HLA-B, HLA-C, HLA-DRA, HLA-DRB1, HLA-DPA1, and HLA-E, were associated with IN and significantly improved outcomes (p < 0.05) compared to ID and IE. Conclusions: Highlighting the importance of spatial context, we identified that patients with IE tumors had poor outcomes despite having high TILs. Moreover, u sing an in-depth analysis with spatially defined context, we identified the central role of pDC and the significance of IF Nɑ in TNBC. Support: Breast Cancer Research Foundation, Mayo Clinic Breast Cancer SPORE (P50CA116201-17) W81XWH-15-1-0292, P50CA015083, R35CA253187 Citation Format: Saranya Chumsri, Yi Liu, Yaohua Ma, Jodi Carter, Mark Gregory, Sarah Church, Jason Reeves, Heather Ann Brauer, Sarah Warren, Heikki Joensuu, Edith Perez, Roberto Leon-Ferre, David Hillman, Judy Boughey, James Ingle, Krishna Kalari, Fergus Couch, Matthew Goetz, Keith Knutson, E. Thompson. The spatially resolved single-cell atlas of the tumor immune architecture revealed the central role of IFN-alpha and plasmacytoid dendritic cells in triple-negative breast cancer in the Mayo Clinic cohort and FinXX trial [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 PS03-03.

Abstract PO5-03-06: Optimizing therapeutic regimens via digital twins to improve triple negative breast cancer response to neoadjuvant therapy

Abstract Introduction: Neoadjuvant systemic therapy (NAT) has been the standard-of-care of stage II-III, locally advanced triple-negative breast cancer (TNBC). However, about 50% of TNBC patients achieve a pathological complete response (pCR) to conventional neoadjuvant chemotherapy (NAC)1. Recently approved combination of NAC with the immunotherapy pembrolizumab, has improved the pCR rate by 7.5%2, although with a 44% risk of immune-related adverse reaction3. Aside from the need to develop new therapies with higher efficacy and lower toxicity, a critical barrier to improving TNBC response is the lack of rigorous ways to personally tailor therapeutic regimens. We seek to address this challenge by employing digital twins (i.e., mathematical models that provide virtual representation of individual patients and predict the changes at future time points) to systematically evaluate individual TNBC patient’s response to different NAT regimens, thereby patient-specifically optimizing treatments. Methods: A TNBC cohort (n = 139) from the ARTEMIS trial (NCT02276433)4 was used for this study. All patients received 4 cycles of Adriamycin/Cytoxan (A/C) every 2 weeks, followed by 12 cycles of weekly Taxol or experimental therapy in Phase II trials. All patients had surgery after NAT and post-surgical pathology to assess response status. For each patient, longitudinal MRIs were collected before, during, and after A/C. We have developed digital twins to integrate the longitudinal MRIs with a mechanism-based model to accurately predict TNBC response5. The model was based on a reaction-diffusion equation that describes the change in tumor cellularity due to migration, proliferation, and drug-induced death. With parameters personalized using MRIs, the patient-specific model (i.e., digital twin) significantly improved the accuracy to predict pCR5. We investigated patient-specific treatment optimization on 37 (19 pCR, 18 non-pCR) chemo-sensitive patients (≥ 70% volume decrease after A/C) who received only NAC. We evaluated the effect of altering the A/C/Taxol schedules on patient response. Specifically, each patient’s digital twin was used to predict the patient’s response to 128 clinically reasonable schedules of A/C/Taxol; i.e., 8 candidate A/C schedules combining with 16 candidate Taxol schedules (Table 1). The predicted response (pCR or non-pCR) from each alternative schedule was compared to the patient response from the actual treatment. Results: Without changing the total dose, shortening the duration of A/C/Taxol administration increased the treatment efficacy. The effectiveness of altering the schedules varied substantially in different patients. In particular, 8 patients who had non-pCR responses to their actual treatment were predicted to achieve pCR with the dense-dose Taxol (i.e., 4 cycles Taxol, 2 weeks per cycle), indicating a 21.62% improvement of pCR rate in the cohort. Discussion and conclusion: The preliminary results with our digital twin approach provided a unique opportunity of improving TNBC response to NAT through patient-specific optimization of therapeutic schedules. The ongoing effort focuses on accounting for toxicity and investigating the effects of altering therapy types and doses in combination with the schedules on the patient response. [1] Spring et al., Clin Cancer Res, 2020. [2] Schmid et al., NEJM, 2022. [3] Shah et al., Clin Cancer Res, 2022. [4] Yam et al., Clin Cancer Res, 2021. [5] Wu et al., Cancer Res, 2022. Table 1. Candidate therapeutic schedules Citation Format: Chengyue Wu, Ernesto Lima, Casey Stowers, Zhan Xu, Clinton Yam, Jong Bum Son, Jingfei Ma, Gaiane Rauch, Thomas Yankeelov. Optimizing therapeutic regimens via digital twins to improve triple negative breast cancer response to neoadjuvant therapy [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 PO5-03-06.

Abstract PO5-03-12: Genomic differences of primary triple negative breast cancer in patients younger than 45 years vs. patients older than 45 years of age

Abstract Background: Triple negative breast cancer (TNBC) is often associated with an aggressive clinical course, especially in younger women. We previously demonstrated that there are differences in the genomic spectrum of metastatic TNBC in patients who are ≤45 years and those who are >45 years of age (Vidula et al, SABCS, 2020). Here we explore genomic differences of primary TNBC in patients ≤45 years and patients >45 years to understand variations in the overall number of non-silent mutations and proportion of patients with specific gene mutations. Methods: We obtained filtered mutation calls generated by the Multi-Center Mutation Calling in Multiple Cancers (MC3) working group (Ellrott et al, Cell Syst, 2018), from whole exome sequencing data of 9079 The Cancer Genome Atlas (TCGA) samples across 33 cancer types that had been used for the comprehensive characterization of cancer driver genes and mutations (Bailey et al, Cell, 2018). Receptor subtype and age at diagnosis of 1247 TCGA breast cancer samples were obtained from the UCSC Xena browser (Goldman et al, Nat Biotechnol, 2020). These datasets were combined to identify 119 patients with primary TNBC with harmonized high confidence mutation calls for analysis. We compared the overall number of non-silent mutations between patients ≤45 years vs. >45 years using the Wilcoxon rank sum test. We also compared the proportion of patients with non-silent mutations in genes mutated at >10% frequency between age groups using the Fisher Exact test. Results: Altogether, 25 patients ≤45 years and 94 patients >45 years were identified with primary TNBC. No significant difference in the number of non-silent mutations among patients ≤45 years vs. >45 years was seen (median [range], ≤45 years: 65 [5-228] vs. >45 years: 74 [2-742], Wilcoxon rank sum p=0.57). In total, 35 unique genes were mutated at >10% frequency in either patients ≤45 years (30 genes) or >45 years (7 genes); notably, TP53 mutations were commonly seen in both age groups (≤45 years: 76%; >45 years: 79%, p=0.79) and TTN mutations were also frequently mutated in both cohorts (≤45 years: 20%; >45 years: 27%, p=0.61). Among the 35 genes identified, 12 genes were mutated at significantly different frequencies among patients ≤45 years vs. those >45 years, as depicted in Table 1. Conclusions: Relatively high frequencies of TP53 and TTN mutations were seen in both patients ≤45 years and those >45 years with primary TNBC. However, many genes associated with varying cellular functions including motility, signaling receptors, and growth were more frequently mutated in patients ≤45 years. These results suggest that there are genomic differences of primary TNBC in patients ≤45 years vs. those >45 years. Further research is needed to validate these findings in a larger cohort of primary TNBC since genomic differences may affect tumor biology and clinical behavior. Table 1. Significant Gene Mutation Differences in Primary TNBC Based on Age. Citation Format: Neelima Vidula, Leif Ellisen, Aditya Bardia, Christina Yau. Genomic differences of primary triple negative breast cancer in patients younger than 45 years vs. patients older than 45 years of age [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 PO5-03-12.

Abstract PO4-03-06: Body mass index and response to neoadjuvant chemo-immunotherapy among women with primary triple negative breast cancer

Abstract Background: Elevated body mass index (BMI) is associated with lower rates of pathologic complete response (pCR) after neoadjuvant chemotherapy in patients with breast cancer. The addition of PD-1 receptor inhibition with pembrolizumab to neoadjuvant chemotherapy is now considered the standard of care for patients with stage II or III triple negative breast cancer (TNBC) based on results from the KEYNOTE-522 (KN-522) trial. In other cancer types such as melanoma and lung cancer, patients with overweight/obesity have better survival outcomes following treatment with immunotherapy compared to patients with normal weight, despite a higher incidence of any-grade immune-related adverse events (irAEs). Whether BMI is associated with differential response and toxicity in patients with TNBC treated with neoadjuvant chemo-immunotherapy is unknown. Methods: Patients with stage II-III TNBC treated with neoadjuvant chemotherapy plus pembrolizumab per the KN-522 regimen from 8/2021 – 9/2022 at Memorial Sloan Kettering Cancer Center were included in this retrospective study. Patient characteristics, tumor characteristics, treatments, surgical pathology information, and irAEs were abstracted from medical records. pCR was defined as absence of invasive or in situ carcinoma in breast and axillary node tissue surgical specimens. BMI was categorized per standard definitions: underweight/normal weight < 25 kg/m2, overweight 25-29.9 kg/m2, and obese >=30 kg/m2. Wilcoxon rank sum tests, Pearson’s chi-squared tests, and Kendall rank correlation tests were used to test associations between variables. Results: 143 patients were included in this study. 57 patients (39.8%) were underweight/normal weight, 46 (32.2%) were overweight, and 40 (28.0%) were obese. Overall, 79/143 patients (55.2%) experienced a pCR. Among patients with a pCR, median BMI was 26.3 kg/m2 (interquartile range [IQR] 23.1-30.5 kg/m2); among patients without a pCR, median BMI was 26.1 kg/m2 (IQR 23.6-30.0 kg/m2; p >0.9). There was no significant association between BMI category and pCR (p=0.9). Overall, 63/143 (44%) of patients experienced an irAE; 42 (29.4%) required treatment for an irAE. There were no associations between BMI and the incidence (p=0.5) or frequency (p=0.7) of irAEs. Conclusions: In this TNBC cohort treated with neoadjuvant chemo-immunotherapy, BMI was not associated with rates of pCR or irAEs. These findings highlight the divergent impact of BMI on immunotherapy response across cancer types. Confirmatory studies in independent cohorts are needed. Citation Format: Sherry Shen, Sara Myers, Yuan Chen, Stephanie Downs-Canner, Nour Abuhadra, Tiffany Traina, Mark Robson, Neil Iyengar. Body mass index and response to neoadjuvant chemo-immunotherapy among women with primary 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 PO4-03-06.

Abstract PO5-13-07: Prediction of recurrence in triple negative breast cancer patients after receiving neoadjuvanttreatment using plasma metabolomics

Abstract Background Early-stage triple-negative breast cancer (TNBC) is usually treated with neoadjuvant chemotherapy (NADC), but prognosis remains poor compared with other BC subtypes. Unfortunately, less than 30% of BC patients achieve pathological complete response (pCR) to NADC and the overall survival of TNBC when cancer spreads is estimated at 10-13 months. Complete response is associated with improved progression-free and overall survival rates, but more accurate prognostic markers are needed. In this study, we assessed the prognostic value of blood circulating metabolites by using targeted-based metabolomics. Methods Patients received standard neoadjuvant chemotherapy with epirubicin plus cyclophosphamide followed by paclitaxel. Blood samples were obtained upon completion of chemotherapy and before surgery. Pathological response to treatment was recorded according to the Miller & Payne system, and categorized as partial (MP 1, 2, & 3) or complete response (MP 4 & 5). Blood samples were collected in EDTA tubes, centrifuged and plasma was stored at -80°C. After QC standard addition and methanol extraction of proteins, four fractions of the resulting extract were analysed: two by reverse-phase/UPLC-MS/MS methods with positive ion mode electrospray ionization (ESI), one by reverse phase/UPLC-MS/MS with negative ion mode ESI, and one by hydrophilic interaction liquid chromatography/UPLC-MS/MS) by Metabolon using a Thermo Scientific Q-Exactive mass spectrometer with a heated electrospray ionization source and an Orbitrap mass analyser. Using Metabolon's hardware and software, raw data were extracted, identified, QC processed and quantified using the area under the curve (AUC). Identified compounds were compared with library entries of purified standards or recurrent unknown entities. The prognostic capacity of each metabolite was assessed using BRB ArrayTools. Selected metabolites were validated using a targeted approach using compound standards as follows. Plasma samples were re-analysed by UPLC/MS using a Vanquish LC coupled to an Orbitrap Exploris 240 MS (Thermo Fisher Scientific) with positive and negative ionization mode ESI under polarity switching. Identification of compounds were performed by comparison of retention times (against in-house authentic standards), accurate mass (with an accepted deviation of 3ppm), and MS/MS spectra. These analyses were carried out by MS-Omics (Denmark). Results Twenty patients treated in the Medical Oncology Unit of the University Hospital of Jaén were recruited. Median age was 50 (31-76). Twelve patients obtained a pathological complete response. Median follow-up after surgery was 25 months. Seven patients eventually had distant metastases (2 in the lungs, 1 in the brain, 1 in the bones and 3 multi-site). Metabolon untargeted analysis identified and quantified 985 metabolites, 789 after xenobiotics exclusion. Survival analysis identified 16 metabolites related with distant relapse (p< 0.05). The ten metabolites with lower p-value were selected for targeted validation. Ms-Omics pipeline allowed absolute quantification of 5 metabolites, 3 of them showing high correlation (R >0.7) between both measurements (targeted and untargeted). Validation of the prognostic value of the candidate metabolites is ongoing in a larger TNBC cohort. Conclusions Metabolomics is a useful tool for the detection of simply assessable and cost-effective prognostic biomarkers in TNBC. Easily monitoring the presence of minimal residual disease is worth to be settled up in the clinical practice for the most aggressive molecular subtype of breast cancer. In this work we have defined a set of metabolites that could predict distant relapse events in TNBC patients treated with neoadjuvant chemotherapy. Further analyses are being carried out to validate the prognostic value of the proposed candidate metabolites. Citation Format: Pedro Sánchez-Rovira, Rocio Urbano-Cubero, Angelo Gamez Pozo, Carmen González-Olmedo, Alicia Cano-Jimenez, Andrea Zapater- Moros, Leticia Díaz-Beltrán, Lucia Trilla-Fuertes, Mariana Díaz-Almirón, Enrique Espinosa, Pilar Zamora, Juan Angel Fresno Vara. Prediction of recurrence in triple negative breast cancer patients after receiving neoadjuvanttreatment using plasma metabolomics [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 PO5-13-07.

Datopotamab Deruxtecan in Advanced or Metastatic HR+/HER2- and Triple-Negative Breast Cancer: Results From the Phase I TROPION-PanTumor01 Study.

Datopotamab deruxtecan (Dato-DXd) is an antibody-drug conjugate consisting of a humanized antitrophoblast cell-surface antigen 2 (TROP2) monoclonal antibody linked to a potent, exatecan-derived topoisomerase I inhibitor payload via a plasma-stable, selectively cleavable linker. TROPION-PanTumor01 (ClinicalTrials.gov identifier: NCT03401385) is a phase I, dose-escalation, and dose-expansion study evaluating Dato-DXd in patients with previously treated solid tumors. The primary study objective was to assess the safety and tolerability of Dato-DXd. Secondary objectives included evaluation of antitumor activity and pharmacokinetics. Results from patients with advanced/metastatic hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer (BC) or triple-negative BC (TNBC) are reported. At data cutoff (July 22, 2022), 85 patients (HR+/HER2- BC = 41, and TNBC = 44) had received Dato-DXd. The objective response rate by blinded independent central review was 26.8% (95% CI, 14.2 to 42.9) and 31.8% (95% CI, 18.6 to 47.6) for patients with HR+/HER2- BC and TNBC, respectively. The median duration of response was not evaluable in the HR+/HER2- BC cohort and 16.8 months in the TNBC cohort. The median progression-free survival in patients with HR+/HER2- BC and TNBC was 8.3 and 4.4 months, respectively. All-cause treatment-emergent adverse events (TEAEs; any grade, grade ≥3) were observed in 100% and 41.5% of patients with HR+/HER2- BC and 100% and 52.3% of patients with TNBC. Stomatitis was the most common TEAE (any grade, grade ≥3) in both HR+/HER2- BC (82.9%, 9.8%) and TNBC (72.7%, 11.4%) cohorts. In patients with heavily pretreated advanced HR+/HER2- BC and TNBC, Dato-DXd demonstrated promising clinical activity and a manageable safety profile. Dato-DXd is currently being evaluated in phase III studies.

Abstract LB006: Cell marker-based classification of TNBC subtypes and patient outcomes

Abstract Background: Triple-negative breast cancer (TNBC) is an aggressive BC subtype characterized by significant molecular and clinical heterogeneity, influenced by genetic, phenotypic, and environmental factors, as well as interactions of the tumor with its surrounding milieu. In the recent past, gene expression-based subtyping methods have provided a functional understanding for the observed molecular diversity/heterogeneity. In this study, we propose an approach to reclassifying TNBC while considering the cellular heterogeneity of the tumor as well as the tumor milieu. Methods: RNA-Sequencing data for TNBC cohort of 250 diverse women [European (EA, self-reported race, SRR): 114 and African (AA, SRR): 136)], was obtained from our collaborators at LSUHSC. 38/250 were labeled ERhi via IHC but histologically confirmed to be TNBC patients. We utilized 261 breast specific cell type markers to classify our cohort via hierarchical (HC) and consensus (CC) clustering. Differentially expressed genes (DEGs) were identified at p-adj ≤ 0.05. Endotype specific networks were generated using protein-protein interactions, DEGs, and genes regulated by transcription factor. Survival was assessed via log-rank tests. Genetic admixture was performed on 227/250 patients using method described by Pakstis, A. J. et al. Results: We identified three distinct mechanistic subtypes (endotype, CC1-3) containing nine distinct groups (HC1-9), revealing substantial heterogeneity in cell-type and tissue-state within TNBC. Each subtype exhibited unique biomarkers, reflecting diverse immune, extracellular matrix, adipogenesis, and inflammatory signatures. Endotype specific networks revealed patients in CC1 exhibited upregulation of CD8 T cell activation, interferon and interleukin markers, while CC2 showed upregulation of extracellular matrix genes, and CC3, the subtype containing ERhi patients, showed upregulation of fatty acid regulation, hormone sensitivity, and pro-inflammatory genes. Survival analysis demonstrated favorable outcomes for CC1 and less favorable outcomes for CC2. Additionally, SRR-inferred survival differences highlighted poorer outcomes for CC2 groups. We found SRR-inferred prognostic biomarkers such as TTC6, ANKRD30A, and KRT86 associated with distinct prognostic profiles in CC2. Genetic admixture showed a comparable distribution of SRR and genetic ancestry across subtypes. We developed a user-friendly Shiny App for our subtyping method and validated it using TCGA TNBC data. Conclusion: TNBC subtyping using cellular heterogeneity of biopsied samples provides a mechanistic approach to patient classification. Subtype-specific mechanisms suggest tailored therapeutic strategies and provide survival outcomes specific to each subtype. Our method can be applied to other cohorts using the application developed in this work. Citation Format: Zahra Mesrizadeh, Kavitha Mukund, Fokrul Hossain, Jovanny Zabaleta, Denise Danos, Luis Del Valle, Xiao-Cheng Wu, Chindo Hicks, Yuan Chun Ding, Augusto Ochoa, Lucio Miele, Victoria L. Seewaldt, Shankar Subramaniam. Cell marker-based classification of TNBC subtypes and patient outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB006.

Identification of immune-related prognostic biomarkers in triple-negative breast cancer.

Triple-negative breast cancer (TNBC), a type of breast cancer, lacks immune-related markers that can be used for prognosis or prediction. Therefore, we created a predictive framework for TNBC using a risk assessment. Our previous study group consisted of 360 individuals who were diagnosed with TNBC through pathology using RNA sequencing and had clinical data from Fudan University Shanghai Cancer Center (FUSCC). A risk scoring model was constructed using the Cox regression method with the least absolute shrinkage and selection operator (LASSO). A multivariate Cox regression analysis was utilized to develop the prediction model, which was then assessed using the consistency index and calibration plots. The validation cohort of The Cancer Genome Atlas (TCGA) TNBC confirmed the strength of the signatures' predictive value. The prognostic risk score model included 12 genes: TDO2, CHIT1, CARML2, HLA-C, ADIRF, C19orf33, CA8, AHNAK2, RHOV, OPLAH, THEM6, and NEBL. The receiver operator characteristic (ROC) curves for survivability values at 1, 3, and 5 years in the FUSCC TNBC cohort demonstrated area under the curve (AUC) values of 0.78, 0.83, and 0.75, respectively. These results indicated a high level of accuracy in predicting outcomes, which was further confirmed through validation using TCGA database. The patients in the high-risk group showed worse prognoses and lower levels of immune cell infiltration, specifically CD8+ T cells, than those in the low-risk group. Furthermore, the low-risk group exhibited a significant upregulation of genes that encode immune checkpoints, including CD274 and CTLA4, suggesting that immunotherapy may yield enhanced efficacy within this particular group. In conclusion, the prognostic signature consisting of 12 genes can assist in the choice of immunotherapy for TNBC.

Automated mitotic spindle hotspot counts are highly associated with clinical outcomes in systemically untreated early-stage triple-negative breast cancer

Operable triple-negative breast cancer (TNBC) has a higher risk of recurrence and death compared to other subtypes. Tumor size and nodal status are the primary clinical factors used to guide systemic treatment, while biomarkers of proliferation have not demonstrated value. Recent studies suggest that subsets of TNBC have a favorable prognosis, even without systemic therapy. We evaluated the association of fully automated mitotic spindle hotspot (AMSH) counts with recurrence-free (RFS) and overall survival (OS) in two separate cohorts of patients with early-stage TNBC who did not receive systemic therapy. AMSH counts were obtained from areas with the highest mitotic density in digitized whole slide images processed with a convolutional neural network trained to detect mitoses. In 140 patients from the Mayo Clinic TNBC cohort, AMSH counts were significantly associated with RFS and OS in a multivariable model controlling for nodal status, tumor size, and tumor-infiltrating lymphocytes (TILs) (p < 0.0001). For every 10-point increase in AMSH counts, there was a 16% increase in the risk of an RFS event (HR 1.16, 95% CI 1.08–1.25), and a 7% increase in the risk of death (HR 1.07, 95% CI 1.00–1.14). We corroborated these findings in a separate cohort of systemically untreated TNBC patients from Radboud UMC in the Netherlands. Our findings suggest that AMSH counts offer valuable prognostic information in patients with early-stage TNBC who did not receive systemic therapy, independent of tumor size, nodal status, and TILs. If further validated, AMSH counts could help inform future systemic therapy de-escalation strategies.

Abstract 2948: Unveiling hidden genomic diversity: Exploring epigenetic potential and gene expression in African Pan Genome contig sequences

Abstract An important consideration when studying cancer in diverse populations is the representativeness of the reference genome. Cancer genomics findings are largely based upon alignments to GRCh37 and GRCh38 references, and with the recent release of the telomere-to-telomere (T2T) and the Human Pangenome Reference Consortium references, analyses of sequences distinct from previous references in the cancer context provide exciting opportunities to identify novel targets that may be linked to cancer outcomes. Because GRCh38 and T2T are overwhelmingly Eurocentric, the question remains if these references have applicability outside the ancestral populations that comprise them. Prior to T2T and pangenome, whole genome sequencing of 910 individuals of African descent revealed 296.5 million distinct base pairs, which were assembled into 125,715 African Pan Genome (APG) contigs. These unique sequences represent African ancestry novel genomic sequences whose function was unclear. Here we present provisional efforts to determine the function of APG contigs, and whether they are represented in newer references. To determine the epigenetic potential of the 125,715 APG contigs, we used Emboss Cpgplot to predict CpG islands. We identified 8,353 potential CpG islands, where 6,352 contigs had at least 1 predicted CpG island, and 1 contig had 9. There was weak correlation between contig length, GC content and number of predicted CpG islands suggesting that these sequences represented potentially functional regions. Using unmapped transcriptomic reads from our published African ancestry triple negative breast cancer cohort, we sought to determine the expression potential of these contigs. Unmapped reads mapped to ~9% of the contigs, where ~1100 APG contigs had both predicted CpG islands and alignment of the unmapped transcriptomic reads. This strongly suggests that these APG contigs contain African ancestry-specific regulatory regions and functional gene coding sequences. Preliminary BLASTn queries of contigs with regulatory potential revealed that these sequences may be present in T2T. Mapping to T2T and visualization of expression and CpG islands showed that our predictions matched novel T2T sequences. We anticipated some contigs would map to T2T given one- or two-end placement in GRCh38 and wanted to determine if any of the ~1100 contigs mapped to T2T. Initial analysis of this contig subset shows ~15% fail to map to T2T, indicating that T2T may still fail to capture diversity across ancestry groups. These sequences represent previously unstudied expression and epigenetic potential not captured in the reference genome, and we are working to evaluate all 125,715 sequences. Capturing the diversity across the genome remains extremely important to contextualize these findings and build resources to continue moving precision medicine approaches forward across diverse ancestry groups. Citation Format: Rachel Martini, Kyriaki Founta, Sebastian Maurice, Jason White, Onyinye Balogun, Nyasha Chambwe, Melissa Davis. Unveiling hidden genomic diversity: Exploring epigenetic potential and gene expression in African Pan Genome contig sequences [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 2948.

Abstract 1162: Tumor-immune microenvironment associated with obesity in triple-negative breast cancer in the Mayo Clinic cohort

Abstract Background: Previous studies demonstrated that obesity is associated with poor outcomes and significantly worse pathological complete response (pCR) in triple-negative breast cancer (TNBC) treated with conventional chemotherapy. Emerging studies described a phenomenon termed the obesity paradox, which referred to improved outcomes observed in obese patients treated with immune checkpoint inhibitors (ICIs). Our study aimed to determine distinct immune features in TNBC across body mass index (BMI). Methods: Characteristics and outcomes of TNBC patients treated with neoadjuvant pembrolizumab-based chemotherapy at Mayo Clinic were collected. Normal BMI was defined as 18-25 kg/m2, overweight 25-30, and obese BMI ≥ 30. NanoString CosMx, a spatial multi-omics single-cell imaging (SMI), was performed in 75 samples from the Mayo Clinic TNBC cohort (Leon-Ferre BCRT 2018). Differential expression as log 2-fold change (FC) was estimated from the linear mixed model with significance defined as two-sided p&amp;lt; 0.05. Results: Between 2021-2023, there were 108 TNBC patients treated with neoadjuvant pembrolizumab. 25.9% were obese, 32.4% were overweight, and 41.7% had normal BMI. In contrast to previous studies with conventional chemotherapy, obese patients numerically had a higher pCR rate of 71.4% with pembrolizumab-based chemotherapy compared to 55.6% in normal and 62.9% in overweight patients. However, this difference did not reach statistical significance (obese vs. normal weight, OR 2.26, 95%CI 0.89-6.06, p 0.094). We further evaluated spatially-resolved immune features associated with obesity using CosMx SMI in 75 samples from the MC TNBC cohort. Obese patients had significantly higher intratumoral B cells (log2FC 1.88, p 0.017), stromal B cells (log2FC 2.79, p 0.001), stromal plasmablasts (log2FC 1.94, p 0.047), and stromal macrophages (log2FC 1.80, p 0.017) compared to patients with normal BMI. Obese patients also had significantly lower intratumoral myeloid dendritic cells (mDC) (log2FC -1.27, p 0.037). Similar trends were observed after standardizing cell counts per 100 tumor or stromal cells, including higher intratumoral B cells (log2FC 3.00, p 0.001), intratumoral plasmablasts (log2FC 2.00, p 0.006), intratumoral natural killer (NK) cells (log2FC 1.66, p 0.044), and stromal B cells (log2FC 1.50, p 0.008). Differential gene analyses for intratumoral B cells revealed that genes (CD74, HLA-C, HLA-DRB1, HLA-DRA, HLA-DRB) associated with the positive regulation of type 2 immune or chemokine response were upregulated. Conclusions: Using in-depth analysis with spatially defined context, our study showed that obese TNBC patients had significantly higher B cell infiltration, which is associated with improved outcomes with ICIs. Future research on how obesity alters the immune microenvironment is needed to identify potential pathways to improve outcomes with ICIs in TNBC. Citation Format: Songhan Pang, Yi Liu, Yaohua Ma, Zhuo Li, Roberto A. Leon-Ferre, David Zahrieh, David W. Hillman, Judy C. Boughey, James N. Ingle, Krishna R. Kalari, Fergus J. Couch, Matthew P. Goetz, Keith L. Knutson, Saranya Chumsri, E. Aubrey Thompson. Tumor-immune microenvironment associated with obesity in triple-negative breast cancer in the Mayo Clinic cohort [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 1162.

Abstract 3510: A radiogenomic approach for triple-negative breast cancer risk stratification

Abstract Background: Triple-negative breast cancer (TNBC) is an aggressive disease that accounts for 15-20% of all breast cancers. Expressions of ER, PR and HER2 receptors are lacking in this disease, and thus targeted therapies are not effective. TNBC has a shorter relapse-free survival, higher metastasis rate and decreased overall survival compared with other breast cancers. However, when undergoing standard treatment, some patients respond well, while others have poor outcome, suggesting TNBC heterogeneity. Early stratification of patients with long versus short survival could identify the subgroup of patients who would not benefit from exposure to toxicity of chemotherapy treatment. Here, we developed a non-invasive radiogenomic approach for TNBC risk stratification. Methods: A transcriptomic-based prognostic gene signature was previously developed using the TCGA-BRCA cohort (n=860). Briefly, LASSO Cox regression model analysis with the ‘glmnet’ R package was used to identify the transcriptomic signature gene-set consisting of 50 genes. We tested this signature to prognosticate overall survival in a Stanford cohort (n=63) and a previously published SCANB cohort (n=604). The patients were stratified into high- and low-risk groups based on the median risk-score. Next, we developed a machine learning model that identified a radiomic feature set to predict the prognostic transcriptomic risk-groups. Radiomic features were extracted from pre-treatment breast MRI. Radiomics features were extracted using PyRadiomics. The model utilized Decision Tree Classifier and LeaveOneOut method was used for cross-validation. Results: The transcriptomic signature low-risk group was significantly associated with improved overall survival in the two TNBC cohorts, with hazard ratios of 0.11 [95% CI: 0.01-0.88] for the Stanford cohort and 0.71 [95% CI: 0.52-0.97] for the SCANB cohort (log-rank p-values p=0.012 and p=0.032, respectively). Including this transcriptomic signature in a multivariate analysis, which adjusted for clinical features (patient age, grade, stage and Ki67%), the transcriptomic prognostic signature remained a significant prognostic factor (p&amp;lt;0.05). The radiomic feature set (consisting of 20 features) predicted the high- and low-risk transcriptomic groups with a mean accuracy of 72.2% and a mean AUROC of 71%. The precision, F1 and recall scores were 67%, 74% and 82%, respectively. In an independent dataset consisting of 116 Stanford TNBC patients, we used this model to predict risk groups based on the MRI radiomics features, and evaluated the prognostic effects of predicted risk groups. The overall survival of the predicted high-risk group was significantly poorer than the predicted low-risk group (p=0.013). Conclusions: We present a prognostic model that can non-invasively stratify TNBC patients for low versus high mortality risk using radiomic features derived from pre-treatment patient MRI data. Citation Format: Humaira Noor, Yuanning Zheng, Adam Mantz, Ryle Zhou, Andrew Kozlov, Wendy B. DeMartini, Shu-tian Chen, Satoko Okamoto, Debra Ikeda, Sarah Mattonen, Sandy Napel, Melinda L. Telli, George Sledge, Allison Kurian, Mina Satoyoshi, Olivier Gevaert, Haruka Itakura. A radiogenomic approach for triple-negative breast cancer risk stratification [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 3510.

Impact of HER2-low status for patients with early-stage breast cancer and non-pCR after neoadjuvant chemotherapy: a National Cancer Database Analysis.

To investigate potential differences in pathological complete response (pCR) rates and overall survival (OS) between HER2-low and HER2-zero patients with early-stage hormone receptor (HR)-positive and triple-negative breast cancer (TNBC), in the neoadjuvant chemotherapy setting. We identified early-stage invasive HER2-negative BC patients who received neoadjuvant chemotherapy diagnosed between 2010 and 2018 in the National Cancer Database. HER2-low was defined by immunohistochemistry (IHC) 1+ or 2+ with negative in situ hybridization, and HER2-zero by IHC0. All the methods were applied separately in the HR-positive and TNBC cohorts. Logistic regression was used to estimate the association of HER2 status with pCR (i.e. ypT0/Tis and ypN0). Kaplan-Meier method and Cox proportional hazards model were applied to estimate the association of HER2 status with OS. Inverse probability weighting and/or multivariable regression were applied to all analyses. For HR-positive patients, 70.9% (n = 17,934) were HER2-low, whereas 51.1% (n = 10,238) of TNBC patients were HER2-low. For both HR-positive and TNBC cohorts, HER2-low status was significantly associated with lower pCR rates [HR-positive: 5.0% vs. 6.7%; weighted odds ratio (OR) = 0.81 (95% CI: 0.72-0.91), p < 0.001; TNBC: 21.6% vs. 24.4%; weighted OR = 0.91 (95% CI: 0.85-0.98), p = 0.007] and improved OS [HR-positive: weighted hazard ratio = 0.85 (95% CI: 0.79-0.91), p < 0.001; TNBC: weighted hazard ratio = 0.91 (95% CI: 0.86-0.96), p < 0.001]. HER2-low status was associated with favorable OS among patients not achieving pCR [HR-positive: adjusted hazard ratio = 0.83 (95% CI: 0.77-0.89), p < 0.001; TNBC: adjusted hazard ratio = 0.88 (95% CI 0.83-0.94), p < 0.001], while no significant difference in OS was observed in patients who achieved pCR [HR-positive: adjusted hazard ratio = 1.00 (95% CI: 0.61-1.63), p > 0.99; TNBC: adjusted hazard ratio = 1.11 (95% CI: 0.85-1.45), p = 0.44]. In both early-stage HR-positive and TNBC patients, HER2-low status was associated with lower pCR rates. HER2-zero status might be considered an adverse prognostic factor for OS in patients not achieving pCR.

Abstract LB_A02: Predicting breast cancer patients’ response to neoadjuvant chemotherapy from the deconvolved transcriptome of different cell types in the tumor microenvironment

Abstract Introduction: The tumor microenvironment (TME) constitutes a multifaceted ecosystem that influences tumor growth and clinical response via dynamic interactions between diverse cell types. Considerable attention has been devoted in recent years in exploring the TME’s impact on clinical response following immunotherapy, warranting further investigation into its impact in the context of chemotherapy. To address this, we present a novel computational framework called DECODEM (DEcoupling Cell-type-specific Outcomes using DEconvolution and Machine learning). Through DECODEM, we investigate the association of cell-type-specific transcriptomic profiles within the TME with response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). Methods: DECODEM leverages cellular deconvolution of bulk transcriptomics data to extract cell-type-specific transcriptomics profiles for different cell types present in the TME, and further utilizes machine learning to build cell-type-specific predictors of clinical response. Using DECODEM, we analyzed the bulk transcriptomics data across three publicly available cohorts of HER2-negative BC patients who underwent NAC. We compared the predictive powers of these cell types, both individually and in concert with each other, against a state-of-the-art predictor employing clinical and transcriptomic features. We then validated our findings in a single-cell chemotherapy cohort of triple-negative breast cancer. Furthermore, we extended DECODEM to DECODEMi that can incorporate the cell-cell interactions (CCIs) among the prominent cell types to predict clinical response, hinting at the underlying mechanism at play. Results: Our analysis revealed that the diverse cell types within the TME significantly contribute to the prediction of chemotherapy response in HER2-negative BC, thus extending beyond the impact of malignant tumor cells alone. Notably, our key findings are: 1. We demonstrated the superior predictive powers of immune cells (myeloid, plasmablasts, B-cells) and stromal cells (endothelial, normal epithelial, cancer-associated fibroblasts), as compared to the bulk mixture and the state-of-the-art predictor. 2. We illustrated the complementary impacts of the prominent cell types via building highly accurate multi-cell-ensembles, where, remarkably, a three-cell-ensemble of endothelial, myeloid, and plasmablasts displayed the best predictive capability across cohorts. 3. We displayed that DECODEMi can capture the regulatory roles of CCIs and identified new CCIs likely to mediate chemotherapy response in HER2-negative BC. Conclusion: We provide an unprecedented computational approach to objectively delineate the cell-type-specific impacts of the TME in clinical response. Our analysis provides comprehensive insights into the intricate interplay of the cells in TME and their associations with chemotherapy response in HER2-negative BC, contributing to a deeper understanding of BC treatment efficacy. Citation Format: Saugato Rahman Dhruba, Sahil Sahni, Binbin Wang, Di Wu, Yael Schmidt, Eldad Shulman, Sanju Sinha, Stephen-John Sammut, Carlos Caldas, Kun Wang, Eytan Ruppin. Predicting breast cancer patients’ response to neoadjuvant chemotherapy from the deconvolved transcriptome of different cell types in the tumor microenvironment [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr LB_A02.

Identification of a targetable JAK-STAT enriched androgen receptor and androgen receptor splice variant positive triple-negative breast cancer subtype

Triple-negative breast cancer (TNBC) is an aggressive subtype with no targeted therapeutics. The luminal androgen receptor (LAR) subtype constitutes 15% of TNBC and is enriched for androgen receptor (AR) and AR target genes. Here, we show that a cohort of TNBC not only expresses AR at a much higher rate (∼80%) but also expresses AR splice variants (AR-SVs) (∼20%), further subclassifying LAR-TNBC. Higher AR and AR-SV expression and corresponding aggressive phenotypes are observed predominantly in specimens obtained from African American women. LAR TNBC specimens are enriched for interferon, Janus kinase (JAK)-signal activator and transducer (STAT), and androgen signaling pathways, which are exclusive to AR-expressing epithelial cancer cells. AR- and AR-SV-expressing TNBC cell proliferation and xenograft and patient-tumor explant growth are inhibited by AR N-terminal domain-binding selective AR degrader or by a JAK inhibitor. Biochemical analysis suggests that STAT1 is an AR coactivator. Collectively, our work identifies pharmacologically targetable TNBC subtypes and identifies growth-promoting interaction between AR and JAK-STAT signaling.

Clinical activity of nivolumab in combination with eribulin in HER2-negative metastatic breast cancer: A phase IB/II study (KCSG BR18-16)

AimWe evaluated the efficacy and safety of nivolumab and eribulin combination therapy for metastatic breast cancer (BC) in Asian populations. MethodsIn this parallel phase II study, adult patients with histologically confirmed recurrent/metastatic hormone receptor-positive/HER2-negative (HR+HER2-) or triple-negative BC (TNBC) were prospectively enroled from 10 academic hospitals in Korea (ClinicalTrials.gov Identifier: NCT04061863). They received nivolumab (360 mg) on day 1 plus eribulin (1.4 mg/m2) on days 1 and 8 every 3 weeks until disease progression or intolerable toxicity. The primary endpoint was the investigator-assessed 6-month progression-free survival (PFS) rate in each subtype. Secondary endpoints included investigator-assessed objective response rate (ORR) as per Response Evaluation Criteria in Advanced Solid Tumors version 1.1, disease control rate, overall survival, and treatment toxicity. The association between PD-L1 expression and efficacy was investigated. ResultsForty-five patients with HR+HER2- BC and 45 with TNBC were enroled. Their median age was 51 (range, 31–71) years, and 74 (82.2%) received one or two prior treatments before enrolment. Six-month PFS was 47.2% and 25.1% in the HR+HER2- and TNBC cohorts, respectively. Median PFS was 5.6 (95% confidence interval [CI]: 5.3–7.4) and 3.0 (95% CI: 2.1–5.2) months in the HR+HER2- and TNBC groups, respectively. ORRs were 53.3% (complete response [CR]: 0, partial response [PR]: 24) and 28.9% (CR: 1, PR: 12). Patients with PD-L1+ tumours (PD-L1 expression ≥1%) and PD-L1- tumours (ORR 50% versus 53.8% in HR+HER2-, 30.8% versus 29.0% in TNBC) had similar ORRs. Neutropenia was the most common grade 3/4 adverse event; the most common immune-related adverse events (AEs) were grades 1/2 hypothyroidism and pruritus. Five patients discontinued therapy because of immune-related AEs. ConclusionNivolumab plus eribulin showed promising efficacy and tolerable safety in previously treated HER2- metastatic BC. Trial registrationNCT04061863