Triple-negative Breast Cancer Molecular Subtypes Research Articles

Abstract PO1-15-04: Young Black Women With Triple-Negative Breast Cancer Molecular Subtypes: Population-Specific Patterns and Batch Effect Considerations

Abstract Introduction: While triple-negative breast cancer (TNBC) molecular subtypes have been associated with biological differences and clinical outcomes, studies have overwhelmingly been conducted in populations of European or Asian ancestry. Data collected across diverse populations is required to better leverage clinical directions from translational studies in TNBC. Through females recruited through the Black Women: Etiology and Survival of Triple-Negative Breast Cancers (BEST) study, we sought to characterize subtypes and explore associations. Methods: Our study included Black women diagnosed with early-stage (I-III) invasive TNBC at < = age 50 from 2005 to 2016, with recruitment from Florida and Tennessee state cancer registries. Germline DNA, tumor RNA, clinical outcomes, and risk factor data were collected. TNBC status in the BEST study was based on immunohistochemistry from pathology reports, cancer registry data, and self-reported data. Analyses on banked tumor samples, extracted at multiple time points, were conducted through PAM50 (Nanostring) and whole-transcriptome RNA-seq. TNBC subtype was assessed using TNBCtype-4 (Lehmann et al. 2016). Sources of batch effect were evaluated using PCA and corrected via limma. Genetic ancestry based on OncoArray or MEGA genotyping data was inferred using 1000Genomes continental reference samples. Immune cell characterization was performed via CIBERSORT and ESTIMATE. Statistical significance in comparing differences across subtypes was assessed via Chi-square test. Kaplan-Meier estimates and log-rank test were used for survival analysis. Results: RNA-seq from 114 self-reported Black females with TNBC was analyzed. TNBC subtype distribution in the BEST study cohort included 31.6% basal-like 1 (BL1), 28.9% basal-like 2 (BL2), 16.7% luminal androgen receptor (LAR), and 21.9% mesenchymal (M). While results were largely consistent with prior studies in patients of European or East Asian ancestry, a higher percentage of BL2 subtype was observed (28.9% vs. 21.0%, p=0.053). Based on PAM50 subtyping, 100% of tumors with BL1 and M were basal, whereas 68.8% of LAR and 86.7% of BL2 subtypes were basal. Tumors without subtype decreased from 9.8% to 1.1% after batch correcting for location at which RNA was extracted (Moffitt vs. Vanderbilt) and time between RNA banking and sequencing. All TNBC subtypes in this population demonstrated monocyte/activated dendritic cell predominance, with no significant subtype-specific associations with immune cell patterns. A lower relative proportion of M subtype was found in tumors from BRCA1/2 carriers, but this was not statistically significant due to the small number of carriers (8% vs. 18%; p=0.22). With a median follow-up time of 9 years, there was no significant difference in 10-year overall survival by TNBC subtype (p=0.18). However, patients with M subtype appeared to have worse survival relative to other subtypes combined (p=0.036). Conclusion: Our study is among the largest to date that interrogates TNBC subtypes and associated molecular/clinical data in self-reported Black females with invasive breast cancer. Our findings suggest that established TNBC subtyping can be applied in patients of African ancestry. Furthermore, data to correct for lab-based confounders remains critical; in this study, it enabled us to use many samples that could not be subtyped initially. Several population-specific patterns were observed, including no difference in 10-year overall survival across TNBC subtypes (consistent with prior data), but worse initial outcomes in M subtype; a preliminary association between BRCA1/2 carriers and non-M subtypes (in contrast to prior data); and no significant difference in immune cell distributions (in contrast to prior data mainly from patients of European ancestry). Studies of associations between TNBC subtypes, additional clinical data, and treatment data (type and response rates) are ongoing. Citation Format: Padma Rajagopal, Sonya Reid, Run Fan, Lindsay Venton, Anne Weidner, Mya Roberson, Susan Vadaparampil, Xuefeng Wang, Sean Yoder, Marilin Rosa, Jibril Hirbo, Jennifer Whisenant, Jennifer Pietenpol, Fei Ye, Tuya Pal, Brian Lehmann. Young Black Women With Triple-Negative Breast Cancer Molecular Subtypes: Population-Specific Patterns and Batch Effect Considerations [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 PO1-15-04.

Abstract PO2-15-05: Mesenchymal-like immune-activated: the 4th robust triple-negative breast cancer molecular subtype

Abstract Triple-negative breast cancer (TNBC) accounts for 15-20% of primary BC. This heterogeneous disease is the most aggressive BC subtype. TNBC is characterized by young age at onset, high-grade tumors, high risk of early recurrence and poor prognosis. Until recently, TNBC patients were considered as one group and all patients were treated with conventional chemotherapy. With the emergence of new therapies targeting distinct biological pathways, personalized medicine is now accessible by defining finer TNBC subtypes, e.g. molecular subtypes, and identifying their specific targetable pathways. Several studies based on transcriptomics have identified three to six TNBC molecular subtypes. Today, there is a clear consensus on three TNBC robust subtypes: luminal androgen receptor (LAR), basal-like immune-activated (BLIA) and basal-like immune-suppressed (BLIS). The debate about the robustness of other subtypes is still open, notably mesenchymal-like (M) and mesenchymal stem-like (MSL or MES). The goal of this study was to establish a robust molecular classification of TNBC that allow to determine the best treatment options. To optimize this process, we harvested as much transcriptomic data as possible. Available clinicopathological data linked to these data were also imported. To our knowledge, this is the largest study aimed at subtyping TNBC; it exploits a total of 1942 TNBC patient data collected from 19 datasets: 1243 samples from microarray technology (14 datasets) and 699 from RNAseq technology (five datasets including a new one from our institution [GSE225002]). We performed independent unsupervised analyses on these two large cohorts with consensus k-means clustering including selection of optimal number of clusters and optimal number of variables. Both consensus clustering analyses separated TNBC microarray and RNAseq TNBC cohorts into four optimal clusters. These clusters were then characterized using clinicopathological features, gene ontology enrichment analyses (GOEA), gene set enrichment analysis (GSEA), 70 gene expression signatures (GES) and expression of 47 immune checkpoint genes. We concluded that TNBC are composed of four robust subtypes: LAR, mesenchymal-like immune-activated (MLIA), BLIA and BLIS. Importantly, we propose that MLIA acronym should replace M or MSL, because it highlights the two main biological characteristics of this subtype, i.e. mesenchymal-like features and a high IR comparable to that of BLIA. Furthermore, we showed that each subtype shares common biological characteristics with another one: LAR and MLIA (androgen receptor pathway activation); MLIA and BLIA (immune activation, notably high levels of immune checkpoints); BLIA and BLIS (basal-like features); BLIS and LAR (immune suppression). As regards microarray cohort, LAR included 19.23% (n = 239) of TNBC, MLIA 17.38% (n = 216), BLIA 32.50% (n = 404) and BLIS 30.89% (n = 384). Concerning RNAseq cohort, LAR included 19.60% (n = 137) of TNBC, MLIA 17.31% (n = 121), BLIA 28.47% (n = 199) and BLIS 34.62% (n = 242). Distributions of patients among the four clusters in the two cohorts were similar (p = 0.3583). Distributions were also similar between studies for microarray cohort (p = 0.2479) and RNAseq cohort (p = 0.1775). Pooled data (n = 1942 patients) gave the following distribution: 19.36% for LAR; 17.35% for MLIA; 31.06% for BLIA; 32.23% for BLIS, confirming that TNBC are largely but not exclusively basal-like (63.29%). In brief, according to the TNBC subtype molecular characterisation, anti-androgen therapy could be prescribed for LAR, immune checkpoint inhibitors for MLIA and BLIA, alone or in combination, and TAM-focused and antineurogenic therapies for BLIS. As an extension of this work, TNBC transcriptomic data associated with their clinicopathological features and TNBC subtype annotations were included in bc-GenExMiner v5.0 web tool (http://bcgenex.ico.unicancer.fr). Citation Format: Mario Campone, Pascal Jézéquel, Fadoua Ben Azzouz, Wilfried Gouraud, Agnes Bassevile, Bertrand Michel, Hamza Lasla, Jean Sebastien FRENEL. Mesenchymal-like immune-activated: the 4th robust triple-negative breast cancer molecular subtype [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 PO2-15-05.

Abstract PO3-25-07: Characterization of tertiary lymphoid structures and its association with response to immune checkpoint inhibitors in triple negative breast cancer using spatial transcriptomics

Abstract Background Tertiary lymphoid structures (TLS) are ectopic lymphoid organs playing a role in adaptive antitumor immune response. They were shown to be associated with favorable outcome and appears to be a promising biomarker for response to immune checkpoint inhibitors (ICI). Yet, there is no consensus for their detection and quantification. Here we aimed to derive a specific TLS signature using high resolution spatial transcriptomics data from a large series of triple negative breast cancer (TNBC) samples and to assess its clinical relevance including response to ICI. Methods Spatial transcriptomics (ST) was performed on a series of 94 early-stage TNBC surgical samples with detailed clinicopathological and outcome data. TLS and tumor infiltrating lymphocytes (TILs) were scored using hematoxylin and eosin and double immunohistochemistry (CD3/CD20) stained slides by a dedicated breast pathologist. Regression based on morphological annotations and deconvolution methods estimated the fraction of gene expression related to TLS in each ST spot allowing to derive specific TLS signature. Its prognostic and predictive value of response to ICI was assessed using publicly available breast cancer (METABRIC, SCAN-B, and I-SPY2) and other tumor type datasets treated with ICI (Bareche et al. Ann Oncol, 2022) from bulk gene expression data. Results Deconvolution of the TLS compartments using the ST gene expression data showed that TLS are enriched in all B cell subsets, CD4+ (central) memory and naïve T cells, as well as mast cells. A functional analysis showed an enrichment of ‘vascular endothelial cell proliferation’, ‘mitotic G2/M transition checkpoint’, ‘V/D/J recombination’ and ‘regulation of cell chemotaxis to fibroblast growth factor’ suggesting that TLS aggregates are associated with angiogenesis, immune cell proliferation, adaptative humoral response and tissue remodeling. A comparison of gene expression data between TLS and non-aggregated TILs led to the development of a specific TLS gene signature comprising B and T cell-specific genes, immunoglobulin genes as well as genes associated with TLS initiation. Its projection on tumor slides overlapped with the regions annotated as TLS by the pathologist, demonstrating its specificity for TLS detection. As expected, the highest levels of the TLS signature were observed in the immunomodulatory TNBC molecular subtype and fully inflamed tumors, whereas the lowest levels were observed in the mesenchymal molecular subtype and immune desert tumors (p< 0.05). Of note, high levels of the TLS signature were associated with better prognosis in TNBC patients from METABRIC (p=6.5 10−5) and SCAN-B datasets (p=1.6 10−3) as well as with higher pathological complete response rates in all breast cancer patients treated with neoadjuvant pembrolizumab in the I-SPY2 study (p=0.026). Similar results were found in other tumor types treated with immunotherapy in the metastatic setting including metastatic melanoma, pancreatic and bladder cancers (PFS, p=6 10−6). Of interest, the TLS signature outperformed the predictive value of other immune-related signatures including TILs suggesting a key role of TLS in obtaining a sustainable, adaptive antitumor immune response in the vicinity of the tumor area. Conclusion By leveraging the potential of spatial transcriptomics, we have successfully developed a unique TLS gene signature that demonstrates a strong correlation with the response to ICI in breast cancer and various other tumor types. This TLS gene signature outperforms other immune biomarkers, underscoring the pivotal role of TLS in eliciting a robust antitumor immune response. The universality of this TLS signature makes it a potent biomarker capable of identifying patients who would benefit from immunotherapy, pending further validation. Citation Format: Xiaoxiao Wang, David Venet, Frédéric Lifrange, Denis Larsimont, Mattia Rediti, Linnea Stenbeck, Floriane Dupont, Ghizlane Rouas, Andrea Joaquin Garcia, David Gacquer, Ligia Craciun, Laurence Buisseret, Nayanika Bhalla, Yuvarani Masarapu, Kim Thrane, Eva Gracia Villacampa, Lovisa Franzén, Sami Saarenpää, Linda Kvastad, Joakim Lundeberg, Françoise Rothé, Christos Sotiriou. Characterization of tertiary lymphoid structures and its association with response to immune checkpoint inhibitors in triple negative breast cancer using spatial transcriptomics [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 PO3-25-07.

Abstract 6620: PDX models of TNBC established from pre- and post-therapy tumors identify vulnerabilities of resistant disease

Abstract Chemotherapy, along with the PD1 inhibitor pembrolizumab, is the recommended standard of care for patients with primary triple negative breast cancer (TNBC). Nearly half of TNBC patients treated with standard neoadjuvant chemotherapy (NACT) have excellent responses. However, those patients with significant residual cancer burden (RCB) after NACT are at high risk of recurrence or metastatic relapse within two years. Due to the challenges posed by the inter- and intratumoral heterogeneity of TNBC, it is critical to develop appropriate models for predicting and overcoming therapy resistance. We established a collection of 92 orthotopic patient-derived xenograft (PDX) models of TNBC from 84 patients before, during, and after NACT while they were enrolled in the ARTEMIS trial (NCT02276443) at MD Anderson Cancer Center. Serial biopsies were obtained from patients prior to treatment (pre-NACT), from poorly responsive disease after four cycles of Adriamycin and cyclophosphamide (AC, mid-NACT), after a 3-month course of additional chemotherapy and/or different experimental therapies in cases of AC resistance (post-NACT), and from the metastatic lesions of two patients. The collection includes 12 longitudinal sets. Models were established from chemo-sensitive and -resistant tumors, but engraftment success was higher from those cancers that proved to be treatment resistant (RCB II/III). The PDX collection includes models encompassing a broad heterogeneity of chemotherapy responses, histologic features, and molecular TNBC subtypes. In addition, the majority of models develop spontaneous lung metastases. Whole exome sequencing demonstrated conservation of mutations between patient tumors and corresponding PDX models, with TP53 being the most commonly mutated gene. A similar comparison of patient and PDX transcriptomes revealed conservation of signaling pathway signatures, with those related to immune and stromal interactions being the most variable, as anticipated when adapting human tumors to growth in mice. The subclonal architecture of the tumors exhibited little overall change throughout NACT, suggesting that selection for resistant subclones is not likely to be a significant contributor to resistance. Tumor cells from the longitudinal PDX collections were subjected to high throughput drug susceptibility profiling to identify targetable vulnerabilities associated with resistance to NACT. We found that post-NACT tumors exhibited enhanced sensitivity to drugs targeting protein homeostasis pathways. Preclinical studies with pevonedistat validated the neddylation pathway as an effective target in chemoresistant TNBC. Citation Format: Amanda L. Rinkenbaugh, Yuan Qi, Reid T. Powell, Shirong Cai, Jiansu Shao, Faiza Baameur Hancock, Lei Guo, Xiaomei Zhang, Sabrina Jeter-Jones, Chunxiao Fu, Rebekah Gould, Jason B. White, Clifford Stephan, Gloria V. Echeverria, Peter J. Davies, Stacy Moulder, W. Fraser Symmans, Jeffrey T. Chang, Helen Piwnica-Worms. PDX models of TNBC established from pre- and post-therapy tumors identify vulnerabilities of resistant disease [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 6620.

176P Multiplex-immunoflourescence spatial patterns to predict triple-negative breast cancer molecular subtypes in the IMMUcan study

176P Multiplex-immunoflourescence spatial patterns to predict triple-negative breast cancer molecular subtypes in the IMMUcan study

Abstract B046: Analyzing heterogeneity of tumor microenvironment of TNBC patients by meta-analysis of 7 breast cancer scRNAseq studies

Abstract Breast cancer can be classified into several types. Among them, triple-negative breast cancer (TNBC) is breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Since targeted therapy for breast cancer relies on the three receptors, treatment outcomes have been worst in TNBCs. However, the clinical benefit of immune-checkpoint inhibitors (ICIs) with chemotherapy over chemotherapy alone was demonstrated in several trials, opening a new avenue for patients with metastatic PD-L1+ TNBC. After several studies with ICIs, researchers found that the tumor microenvironment affects the response rate of immunotherapies. Therefore, to unravel the heterogeneity of the tumor microenvironment of TNBC patients, we collected 7 public single-cell RNA sequencing breast cancer studies. From 141,068 cells populating tumors and tumor-microenvironment (TMEs), we first identified epithelial cells separately. Using whole cells including epithelial and immune-stromal cells, we identified the Baylor-proposed TNBC molecular subtype of each patient. This approach with epithelial cells revealed that 19 basal-like immune-activated (BLIA), 5 basal-like immune-suppressed (BLIS), 2 luminal-androgen receptor (LAR), 3 mesenchymal (MES), and 3 unclassified subtypes. By comparing cell number and cell-cell interactions, the heterogeneity of TME-consisting cell populations between the TNBC subtypes was analyzed. Analysis of tumor-infiltrating lymphocytes revealed their difference in activation, expansion, and exhaustion programs across patients. Among the subtypes, the BLIA subtype had a greater amount of exhausted CD8+ T cells and regulatory T cells. This finding was consistent with cell-cell interaction analysis. In the case of the BLIA subtype, the interaction between regulatory T cells and CD8 T cells was more active than in other subtypes. Also, the interaction between cytotoxic cells (T cells and NK cells) and regulatory T cells were more active in the BLIA subtype. Additionally, tumor cells in the BLIA subtype seem to inhibit cytotoxic cells to a greater extent. Among the interactions between epithelial cells and exhausted CD8+ T cells, MDK interaction was higher in the BLIA subtype. Additionally, the expression of the MDK gene in endothelial cells and macrophages leads to upregulation in immune infiltration which causes more T cells in TME. Also, we found that the progression-free survival of patients differs due to the expression of the MDK gene. In conclusion, the MDK gene causes a T cell-enriched environment in TME, which leads to different progression-free survival. Citation Format: Kyungsoo Kim, Jee Hung Kim, Soong June Bae, Sung Gwe Ahn, Joon Jeong. Analyzing heterogeneity of tumor microenvironment of TNBC patients by meta-analysis of 7 breast cancer scRNAseq studies [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B046.

Selective inhibition of CDK9 in triple negative breast cancer

Targeted therapy for triple-negative breast cancers (TNBC) remains a clinical challenge due to tumour heterogeneity. Since TNBC have key features of transcriptionally addicted cancers, targeting transcription via regulators such as cyclin-dependent kinase 9 (CDK9) has potential as a therapeutic strategy. Herein, we preclinically tested a new selective CDK9 inhibitor (CDDD11-8) in TNBC using cell line, patient-derived organoid, and patient-derived explant models. In vitro, CDDD11-8 dose-dependently inhibited proliferation (IC50 range: 281–734 nM), induced cell cycle arrest, and increased apoptosis of cell lines, which encompassed the three major molecular subtypes of TNBC. On target inhibition of CDK9 activity was demonstrated by reduced RNAPII phosphorylation at a CDK9 target peptide and down-regulation of the MYC and MCL1 oncogenes at the mRNA and protein levels in all cell line models. Drug induced RNAPII pausing was evident at gene promoters, with strongest pausing at MYC target genes. Growth of five distinct patient-derived organoid models was dose-dependently inhibited by CDDD11-8 (IC50 range: 272–771 nM), including three derived from MYC amplified, chemo-resistant TNBC metastatic lesions. Orally administered CDDD11-8 also inhibited growth of mammary intraductal TNBC xenograft tumours with no overt toxicity in vivo (mice) or ex vivo (human breast tissues). In conclusion, our studies indicate that CDK9 is a viable therapeutic target in TNBC and that CDDD11-8, a novel selective CDK9 inhibitor, has efficacy in TNBC without apparent toxicity to normal tissues.

Development of an ubiquitin-proteasome system signature for predicting prognosis and providing therapeutic guidance for patients with triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a pathological subtype with a high mortality, and the development of inhibitors in the ubiquitin-proteasome system (UPS) component could be a novel therapeutic tool. Triple-negative breast cancer data were obtained from The Cancer Genome Atlas (TCGA), and subtype analysis was performed by consistent clustering analysis to identify molecular subtypes of TNBC according to UPS characteristics. Differential analysis, COX and least absolute shrinkage and selection operator (LASSO) COX regression analyses were performed to select genes associated with overall survival in TNBC. The final prognostic model (UPS score) was determined using the LASSO COX model. The model performance was assessed using receiver operating characteristic (ROC) curves and survival curves. In addition, the results of the UPS score on analyzing the abundance of immune cell infiltration and immunotherapy were explored. Finally, we developed a nomogram for TNBC survival prediction. Two UPS subtypes (UPSMS1 and UPSMS2) showing significant survival differences were classified. COX regression analysis on differentially expressed genes in UPSMS1 and UPSMS2 filtered five genes that affected overall survival. Based on the regression coefficients and expression data of the five genes, we built a prognostic assessment system (UPS score). The UPS score showed consistent prognostic and therapeutic guidance values. Finally, the ROC curve of the nomogram and UPS score showed the highest predictive efficacy compared with traditional clinical prognostic indicators. The UPS score represented a promising prognostic tool to predict overall survival and immune status and guide personalized treatment selection in TNBC patients, and this study may provide a more practical alternative for clinical monitoring and management of TNBC.

Research Progress on Molecular Subtyping and Modern Treatment of Triple-Negative Breast Cancer.

Breast cancer has become the most common malignant tumor worldwide. Triple-negative breast cancer (TNBC) is a type of breast cancer that is negative for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Compared with other molecular subtypes of breast cancer, TNBC is the most aggressive and highly heterogeneous. TNBC is insensitive to endocrine and anti-HER2 therapy, and chemotherapy is currently the main systemic treatment. With the continuous development of detection techniques and deepening research on TNBC molecular subtypes, drugs targeting immune checkpoints and different targets have emerged, such as atezolizumab, pembrolizumab, poly (ADP-ribose) polymerase (PARP) inhibitors, trophoblast cell-surface antigen 2 (TROP-2), and antibody-drug conjugates. These therapies provide new hope for TNBC treatment. Based on the analysis and classification of TNBC, this article summarizes the immunotherapy, targeted therapy, and new treatment combinations, providing references for the precise treatment of TNBC in the future.

Targeting DCLK1 attenuates tumor stemness and evokes antitumor immunity in triple-negative breast cancer by inhibiting IL-6/STAT3 signaling

Triple-negative breast cancer (TNBC) exhibits the poorest outcomes among breast cancer subtypes due to the high heterogeneity and a lasting scarcity of effectual treatments. Targeted therapies based on molecular subtypes of TNBC are critical step toward tailoring treatments to improve clinical outcomes. Gastrointestinal cancer stem cell (CSC) marker DCLK1 was reported to be highly expressed in stem cell-rich subtype of TNBC. Here, we firstly explored the impacts of DCLK1 on tumor cells as well as their immune microenvironment in TNBC and potential therapeutic strategies for TNBC patients with high DCLK1 expression. Our results disclosed that DCLK1 overexpression promoted, while knockout of DCLK1 suppressed the CSC-like traits of TNBC cells and resistance to chemotherapeutics. Besides, DCLK1 supported immune escape by inhibiting intratumoral cytotoxic T cell infiltration in TNBC and hence limited immune checkpoint inhibitors efficacy. Mechanistically, bioinformatics analysis revealed that IL-6/STAT3 signaling was significantly enriched in high DCLK1-expressing patients, and our results further revealed that DCLK1 enhanced IL-6 expression and STAT3 activation in TNBC cells, which finally gave rise to upregulated CSC traits and suppressed CD8+ T-cell activity. Inhibiting IL-6/STAT3 pathway by IL-6R antagonist, Tocilizumab or STAT3 inhibitor, S31-201 could abolish DCLK1-promoted malignant phenotypes of TNBC cells. Finally, DCLK1 was identified to be specifically and highly expressed in the mesenchymal-like subtype of TNBC and targeting DCLK1 could improve chemotherapy efficacy and activate antitumor immunity. Overall, our study revealed the potential clinical benefits of targeting DCLK1 in TNBC treatment.

Abstract P6-01-05: Platelet-derived growth factor-CC expression in primary triple-negative breast cancer is associated with the basal-like molecular subtype and increased immune infiltrate

Abstract Around 10-15% of all breast cancers are categorized clinically as triple-negative breast cancer (TNBC). TNBC is defined by lack of protein expression or over expression of treatment targets such as the Estrogen Receptor α (ER) and Human Epidermal Growth Factor Receptor-2 (HER2), and the prognostic factor PR (Progesterone Receptor). The negative definition of TNBC results in a heterogeneous mix of tumors with variable molecular characteristics and prognosis. Defining TNBC molecular subtypes in detail is of importance to improve prognostication and find new treatment options. Expression of Platelet-derived growth factor-CC (PDGF-CC) has previously been correlated with the TNBC subtype, and paracrine PDGF-CC signaling has been reported to be of importance for maintaining TNBC tumor cell phenotype. We aimed to characterize PDGF-CC expression within the TNBC patient population by combining studies of PDGF-CC in tissue microarrays (TMAs) with matching RNAseq data and clinical follow-up; all variables originating from the SCAN-B (Sweden Cancerome Analysis Network – Breast) clinical study (ClinicalTrials.gov: NCT02306096). TMAs constructed of primary TNBC patient samples were stained for PDGF-CC using the Dako PT Autostainer system. Tumor cell-specific expression of PDGF-CC intensity was scored as either absent (N=11), weak (N=86), intermediate (N=81) or strong (N=70), and the scores were used to create corresponding TNBC PDGF-CC subgroups. We then explored associations of these subgroups with clinicopathological variables and time-to-event outcomes. Intermediate and strong PDGF-CC scores were associated with Nottingham Histological Grade 3 (p=0.001), increased proliferation (p< 0.001) and younger patient age at diagnosis (p=0.002). RNAseq data corresponding to tumors included in the TMAs was then retrieved, and differentially expressed genes were identified and used to perform Gene Set Enrichment Analysis (GSEA) comparing the TMA-derived PDGF-CC subgroups. Immune-related signatures were found to be enriched in the strong PDGF-CC subgroup vs. intermediate. Interestingly, strong PDGF-CC intensity was associated with a decreased risk of recurrence in the chemotherapy treated patient group (HR 0.28, 95% CI 0.10-0.80, p=0.017). Finally, patient samples were assigned a PAM50 subtype and a TNBC molecular subtype by the TNBCtype algorithm. Ninety-four percent of tumors in the strong PDGF-CC subgroup were classified as basal-like, whereas the corresponding number in the weak and intermediate PDGF-CC subgroups were 51% and 84%, respectively. The TNBC molecular subtype termed ‘Immunomodulatory’ was more frequently represented in the strong PDGF-CC subgroup compared to weak and intermediate (33% vs. 13% and 16%, respectively). In conclusion, strong PDGF-CC protein expression identified basal-like TNBCs, with an increase in immune cell infiltrate shown by RNAseq analysis. Whether or not PDGF-CC has a direct effect on influx of immune cells into tumors remains to be investigated. Analyses are currently ongoing to better understand the improved outcome associated with strong PDGF-CC intensity and on the contrary, the worse outcome associated with weak and intermediate PDGF-CC intensity, and if paracrine PDGF-CC signaling may explain the discrepancy observed. Citation Format: Sophie Lehn, Gyula Pekar, Paulina Bolivar Balbas, Johan Staaf, Christina Möller, Kristina Lövgren, Anna Ehinger, Ana Bosch Campos, Åke Borg, Kristian Pietras. Platelet-derived growth factor-CC expression in primary triple-negative breast cancer is associated with the basal-like molecular subtype and increased immune infiltrate [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-01-05.

Abstract PD4-01: PD4-01 Spatial transcriptomics reveals a substantial heterogeneity in TNBC tumor and stroma compartments with potential clinical implications

Abstract Background Triple negative breast cancer (TNBC) is a heterogeneous disease characterized by at least five molecular subtypes, namely basal like (BL), immunomodulatory (IM), luminal androgen receptor (LAR), mesenchymal (M) and mesenchymal stem like (MSL), associated with distinct gene expression, genomic and tumor microenvironment (TME) profiles. Recent technological advances allow to investigate intratumor geographic heterogeneity ignored by bulk tumor analyses. Here, we deployed spatial transcriptomics (ST) to interrogate tumor and stroma compartments heterogeneity and assess its association with clinical outcome. Methods Spatial transcriptomics (Visium® Spatial Gene Expression, 10X Genomics) was performed on a retrospective series of 94 case-control TNBC samples matched for known clinic-pathological parameters with available long term outcome. Detailed morphological annotations spanning 11 histomorphological categories were performed by a breast dedicated pathologist assisted by the automated QuPath digital pathology software. Bioinformatic analyses were performed using in house pipelines. Results We investigated the distribution of each morphological category across the five TNBC molecular subtypes. We found that LAR, M and MSL, even though they had less tumor cells, had more patches of very small size (p< 0.0001). On the other hand, BL and IM had few large and dense patches. Stroma had an opposite distribution compared to tumor, with LAR and MSL being enriched with stroma (p< 00001). Tumor infiltrating lymphocytes were specific of the IM (p< 0.0001) and to a lesser extent the BL subtype. Normal structures, like fat tissue (p< 0.008), lactiferous ducts (p< 0.03) and vessels (p< 0.02), were more present in MSL and LAR. The differences between the molecular subtypes are mirrored at the level of their cell composition and tumor organization, suggesting the possibility to assess TNBC molecular subtypes from imaging data alone. At the gene expression level, spatial deconvolution analyses revealed the co-existence of tumor and stroma compartments from different TNBC subtypes within a tumor sample of a given subtype as defined by bulk tumor analysis. Interestingly, these different tumor-stroma combinations were associated with prognosis. For example, M tumors associated with MSL stroma seem to have a better prognosis than M tumors with an M stroma (p=0.001). Furthermore, spatial resolution of the gene expression identified 418 individual clusters (median 4 clusters per sample) associated with specific molecular and cellular features highlighting a substantial intra-patient heterogeneity. These clusters were further grouped into 11 ecotypes associated with distinct hallmarks and pathways, including EMT, angiogenesis, DNA repair and immune profiles revealing an important inter-patient heterogeneity beyond TNBC classification. Interestingly, 2 ecotypes were identified within the IM subtype associated with distinct clinical outcome, with ecotype 6 characterized by high EMT, mesenchymal stroma and worse prognosis (p = 0,021). Conclusion To our knowledge, this is the largest study demonstrating the substantial intra- and inter-patient heterogeneity characterizing TNBC at an unprecedented level, with differences both in tumor and stroma composition as well as spatial organization and clinical outcome. Our results hightlight the need to consider TNBC heterogeneity for patient care and future clinical development including immunotherapy. Citation Format: Xiaoxiao Wang, David Venet, Frédéric Lifrange, Denis Larsimont, Mattia Rediti, Linnea Stenbeck, David Gacquer, Floriane Dupont, Ghizlane Rouas, Matteo Serra, Joakim Lundeberg, Françoise Rothé, Christos Sotiriou. PD4-01 Spatial transcriptomics reveals a substantial heterogeneity in TNBC tumor and stroma compartments with potential clinical implications [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD4-01.

Abstract PD9-07: Role of immunosuppressive JNK pathway in the tumor microenvironment among Triple Negative Breast Cancer subtypes in IBCSG Trial 22-00

Abstract BACKGROUND: Although the triple-negative breast cancer (TNBC) tumor microenvironment (TME) has been deeply characterized, much remains unknown about pathways attributing to an immunosuppressive TME in this disease. The phosphorylation of JNK (c-Jun N-terminal kinase) pathway has been associated with promoting an immunosuppressive phenotype, enhancing TNBC aggressiveness. Here, we aimed to explore the role of the JNK pathway in TNBC using a gene signature inferring the level of JNK phosphorylation. For this purpose, we used the TNBC cohort from the phase III adjuvant IBCSG 22-00 trial, which evaluated low-dose cyclophosphamide and methotrexate (CM) chemotherapy showing no clinical benefit in the overall population. METHODS: JNK gene signature was developed in TNBC samples by integrating RNA-seq gene expression data and phospho-JNK-targeted proteomic data in The Cancer Genome Atlas. Stochastic subsampling was performed to select the candidate markers. LASSO regression was performed to determine the final transcriptional signature to reflect JNK phosphorylation. The signature was then applied in a cohort composed of 498 TNBCs selected using stratified 1:3 relapse cases and non-relapse subcohort ratio from the IBCSG 22-00 trial. RNA-seq data from FFPE tumor samples were available for 347 patients. The JNK signature was calculated as the mean of the products between gene expression and signature coefficients, defining high and low levels using the median cut-off. Immune hot tumors were defined according to TNBC molecular subtypes or tumor-infiltrating lymphocytes (TILs) levels higher than 30%. Multivariable Cox models were used for disease-free survival (DFS) analysis. Wilcoxon test was used to evaluate the association between gene signatures and the levels of JNK. RESULTS: Tumors with either immunomodulatory (IM) phenotype or high TILs showed better DFS when presenting low levels of JNK compared to high levels (HR = 0.75, 95% CI, 0.57 to 0.99; P-value = 0.024 and HR = 0.62, 95% CI, 0.43 to 0.89, P-value = 0.0013). No significant differences in DFS were observed in other TNBC subtypes or tumors with low TILs, further highlighting the relevance of JNK signaling pathway in tumors presenting immune infiltration. Moreover, immune hot tumors with high levels of JNK were enriched for angiogenesis and eosinophils signatures and linked to immunosuppression. The immune targets B7-H3, CSF1R, GITR, and GARP were significantly associated with high levels of JNK. Of note, these genes are involved in the immune escape, activation of macrophages, and regulation of Tregs population. On the other hand, low levels of JNK were associated with higher levels of activated CD8+ T cells, pointing to an anti-tumor immune response, as well as with higher levels of the immune targets PDL-1, CTLA4, CD47, DCIR, and TIGIT. Of interest, a significant DFS benefit was found in IM tumors with high levels of JNK when treated with low-dose CM, compared to those who were not (HR = 0.52, 95% CI, 0.28 to 0.99; P interaction = 0.045). CONCLUSIONS: We developed a JNK gene signature to estimate the phosphorylation level of JNK from gene expression data in TNBC, and validated the associated biological and prognostic value in the IBCSG 22-00 trial. Our results are in line with the immunosuppressive effect described by the JNK gene signature and highlight the heterogeneity of immune response in immune hot TNBCs. Of note, high levels of JNK were associated with worse DFS, as well as with a benefit from low-dose CM potentially related to the immunomodulatory effect described for metronomic regimens. Overall, our findings suggest a potential role of the JNK signature in identifying TNBCs with an immunosuppressive TME and provide the rationale to explore its role as a biomarker for immunotherapy. Further validation of these findings is required. Citation Format: Andrea Joaquin Garcia, Takashi Semba, Mattia Rediti, Daniel J. McGrail, Xuemei Xie, Xiaoping Wang, Dileep R. Rampa, David Venet, Samira Majjaj, Roswitha Kammler, Marco Colleoni, Sherene Loi, Giuseppe Viale, Meredith Regan, Françoise Rothé, Christos Sotiriou, Naoto T. Ueno. Role of immunosuppressive JNK pathway in the tumor microenvironment among Triple Negative Breast Cancer subtypes in IBCSG Trial 22-00 [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD9-07.

Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer

Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. We established orthotopic PDX models of triple negative breast cancer (TNBC) from the primary breast tumors of patients prior to and following neoadjuvant chemotherapy (NACT) while they were enrolled in the ARTEMIS trial (NCT02276443). Serial biopsies were obtained from patients prior to treatment (pre-NACT), from poorly responsive disease after four cycles of Adriamycin and cyclophosphamide (AC, mid-NACT), and in cases of AC-resistance, after a 3-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 fine needle aspirates (FNAs) from 217 women, generating a total of 62 PDX models (overall success-rate = 23%). Success of PDX engraftment was generally higher from those cancers that proved to be treatment-resistant, whether poorly responsive to AC as determined by ultrasound measurements mid-NACT (p = 0.063), RCB II/III status after NACT (p = 0.046), or metastatic relapse within 2 years of surgery (p = 0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumors 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.

Characterization of triple negative breast cancer gene expression profiles in Mexican patients.

Triple negative breast cancer (TNBC) is an aggressive type of cancer that accounts for ~23% of breast tumors in Mexico. In an attempt to understand in an improved way the behavior of TNBC, throughout the years, gene expression in these tumors has been studied. Lehman et al identified 6 subtypes of gene expression in TNBC with distinct characteristics. In the present study, it was aimed to assess clinical, pathological and prognostic characteristics of TNBC in a Mexican-based cohort. A total of 55 patients diagnosed with TNBC at Mexico's National Institute of Cancer (INCan) were included. Tumor needle biopsy samples were obtained and subjected to microarray analysis. Patients were thus classified into one of the 6 TNBC molecular subtypes. The prognostic, clinical and pathological information of patients was obtained, and differences across molecular subtypes were sought. Out of the 55 included patients, the following subtypes were identified: 9 basal-like-1, 11 basal-like-2 (BSL2), 16 immunomodulatory (IM), 12 mesenchymal, 6 androgen receptor-like and 1 mesenchymal stem-like. Mean follow-up time was 47.1 months. The IM molecular subtype had the best overall survival (OS) (median OS was not reached). BSL2 had the worst OS (15 months). A complete pathologic response to neoadjuvant chemotherapy was obtained more often in the IM subtype (P=0.032). No significant associations were found between any of the clinical or pathological characteristics and the TNBC molecular subtypes. The results obtained from the present study should be considered when seeking to implement a clinical-molecular model for TNBC patient care, particularly in Hispanic-based populations, as they have been frequently underrepresented in clinical studies assessing TNBC molecular subtypes.

Predictive and prognostic values of tumor infiltrating lymphocytes in breast cancers treated with neoadjuvant chemotherapy: A meta-analysis

BackgroundThis meta-analysis assessed the predictive and prognostic value of tumor infiltrating lymphocytes (TILs) in neoadjuvant chemotherapy (NACT) treated breast cancer and an optimal threshold for predicting pathologic complete response (pCR). MethodsA systematic search of PubMed, EMBASE and Web of Science electronic databases was conducted to identify eligible studies published before April 2022. Either a fixed or random effects model was applied to estimate the pooled hazard ratio (HR) and odds ratio (OR) for prognosis and predictive values of TILs in breast cancer patients treated with NACT. The study is registered with PROSPERO (CRD42020221521). ResultsA total of 29 published studies were eligible. Increased levels of TILs predicted response to NACT in HER2 positive breast cancer (OR = 2.54 95%CI, 1.50–4.29) and triple negative breast cancer (TNBC) (OR = 3.67, 95%CI, 1.93–6.97), but not for hormone receptor (HR) positive breast cancer (OR = 1.68, 95 %CI, 0.67–4.25). A threshold of 20% of H & E-stained TILs was associated with prediction of pCR in both HER2 positive breast cancer (P = 0.035) and TNBC (P = 0.001). Moreover, increased levels of TILs (either iTILs or sTILs) were associated with survival benefit in HER2-positive breast cancer and TNBC. However, an increased level of TILs was not a prognostic factor for survival in HR positive breast cancer (pooled HR = 0.64, 95%CI: 0.03–14.1, P = 0.78). ConclusionsIncreased levels of TILs were associated with increased rates of response to NACT and improved prognosis for the molecular subtypes of TNBC and HER2-positive breast cancer, but not for patients with HR positive breast cancer. A threshold of 20% TILs was the most powerful outcome prognosticator of pCR.

Leveraging diverse cell-death patterns to predict the prognosis and drug sensitivity of triple-negative breast cancer patients after surgery

BackgroundPostoperative progression and chemotherapy resistance is the major cause of treatment failure in patients with triple-negative breast cancer (TNBC). Currently, there is a lack of an ideal predictive model for the progression and drug sensitivity of postoperative TNBC patients. Diverse programmed cell death (PCD) patterns play an important role in tumor progression, which has the potential to be a prognostic and drug sensitivity indicator for TNBC after surgery. Materials and methodsTwelve PCD patterns (apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis) were analyzed for model construction. Bulk transcriptome, single-cell transcriptome, genomics, and clinical information were collected from TCGA-BRCA, METABRIC, GSE58812, GSE21653, GSE176078, GSE75688, and KM-plotter cohorts to validate the model. ResultsThe machine learning algorithm established a cell death index (CDI) with a 12-gene signature. Validated in five independent datasets, TNBC patients with high CDI had a worse prognosis after surgery. Two molecular subtypes of TNBC with distinct vital biological processes were identified by an unsupervised clustering model. A nomogram with high predictive performance was constructed by incorporating CDI with clinical features. Furthermore, CDI was associated with immune checkpoint genes and key tumor microenvironment components by integrated analysis of bulk and single-cell transcriptome. TNBC patients with high CDI are resistant to standard adjuvant chemotherapy regimens (docetaxel, oxaliplatin, etc.); however, they might be sensitive to palbociclib (an FDA-approved drug for luminal breast cancer). ConclusionGenerally, we established a novel CDI model by comprehensively analyzing diverse cell death patterns, which can accurately predict clinical prognosis and drug sensitivity of TNBC after surgery. A user-friendly website was created to facilitate the application of this prediction model (https://tnbc.shinyapps.io/CDI_Model/).

136MO Differential benefit of low-dose cyclophosphamide and methotrexate maintenance chemotherapy among TNBC subtypes in the context of the IBCSG 22-00 study

Triple-negative breast cancer (TNBC) is a heterogeneous disease with at least five molecular subtypes characterized by distinct gene expression, genomic and tumor microenvironment (TME) profiles. The phase III adjuvant IBCSG 22-00 trial evaluating low-dose cyclophosphamide and methotrexate (CM) chemotherapy did not show a clinical benefit in unselected TNBC patients. Here, we aimed to explore whether specific TNBC molecular subtypes and TME features could predict benefit to low-dose CM maintenance chemotherapy in the IBCSG 22-00 study.

Intra- and Peritumoral Radiomics Model Based on Early DCE-MRI for Preoperative Prediction of Molecular Subtypes in Invasive Ductal Breast Carcinoma: A Multitask Machine Learning Study.

PurposeThe aim of this study is to investigate radiomics features extracted from the optimal peritumoral region and the intratumoral area on the early phase of dynamic contrast-enhanced MRI (DCE-MRI) for predicting molecular subtypes of invasive ductal breast carcinoma (IDBC).MethodsA total of 422 IDBC patients with immunohistochemical and fluorescence in situ hybridization results from two hospitals (Center 1: 327 cases, Center 2: 95 cases) who underwent preoperative DCE-MRI were retrospectively enrolled. After image preprocessing, radiomic features were extracted from the intratumoral area and four peritumoral regions on DCE-MRI from two centers, and selected the optimal peritumoral region. Based on the intratumoral, peritumoral radiomics features, and clinical–radiological characteristics, five radiomics models were constructed through support vector machine (SVM) in multiple classification tasks related to molecular subtypes and visualized by nomogram. The performance of radiomics models was evaluated by receiver operating characteristic curves, confusion matrix, calibration curves, and decision curve analysis.ResultsA 6-mm peritumoral size was defined the optimal peritumoral region in classification tasks of hormone receptor (HR)-positive vs others, triple-negative breast cancer (TNBC) vs others, and HR-positive vs human epidermal growth factor receptor 2 (HER2)-enriched vs TNBC, and 8 mm was applied in HER2-enriched vs others. The combined clinical–radiological and radiomics models in three binary classification tasks (HR-positive vs others, HER2-enriched vs others, TNBC vs others) obtained optimal performance with AUCs of 0.838, 0.848, and 0.930 in the training cohort, respectively; 0.827, 0.813, and 0.879 in the internal test cohort, respectively; and 0.791, 0.707, and 0.852 in the external test cohort, respectively.ConclusionRadiomics features in the intratumoral and peritumoral regions of IDBC on DCE-MRI had a potential to predict the HR-positive, HER2-enriched, and TNBC molecular subtypes preoperatively.

Abstract 2542: Unraveling heterogeneity of tumor microenvironment of TNBC patients by meta-analysis of 6 breast cancer scRNAseq studies

Abstract Breast cancer can be classified into several types. Among them, triple-negative breast cancer (TNBC) is breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Since targeted therapy for breast cancer relies on the three receptors, treatment outcomes have been worst in TNBCs. However, clinical benefit of immune-checkpoint inhibitors (ICIs) with chemotherapy over chemotherapy alone was demonstrated in the KEYNOTE-355 and IMPASSION-130 trials in terms of overall survival, opening new avenue for patients with metastatic PD-L1+ TNBC. After several studies with ICIs, researchers found that the tumor microenvironment affects the response rate of immunotherapies. Therefore, to unravel the heterogeneity of tumor microenvironment of TNBC patients, we collected 28 TNBC samples from 6 public single cell RNA sequencing breast cancer studies. Results: From 124,301 cells populating tumors and tumor-microenvironment (TMEs), we first identified epithelial cells separately. Using epithelial cells alone, we identified the Baylor-proposed TNBC molecular subtype of each patient. This approach with epithelial cells revealed that 3 basal-like immune-activated (BLIA), 11 basal-like immune-suppressed (BLIS), 5 luminal- androgen receptor (LAR), and 9 unclassified subtypes. By comparing cell number and cell-cell interactions, the heterogeneity of TME-consisting cell populations between the TNBC subtypes was analyzed. Analysis of tumor-infiltrating lymphocytes revealed their difference in activation, expansion, and exhaustion programs across patients. Among the subtypes, the LAR subtype had less amount of exhausted CD8+ T cells and regulatory T cells. This finding was consistent with cell-cell interaction analysis. In the case of the LAR subtype, the interaction between regulatory T cells and CD8 T cells was less active than other subtypes. Also, the interaction between cytotoxic cells (T cells and NK cells) and regulatory T cells was less active in the LAR subtype. Additionally, tumor cells in the LAR subtype seem to inhibit cytotoxic cells to a lesser extent. When we repeated our analyses using whole cells including epithelial and immune-stromal cells, the molecular subtypes of each subject were changed (7 of 19, 36.8%). 4 of 11 BLIS were changed to BLIA, 1 of 11 BLIS were changed to mesenchymal (MES), and 2 of 5 LAR were changed to MES. Characteristics of immune cells in the epithelial-based LAR subtype were conserved in the whole cells-based MES. Conclusions:This extensive meta-analysis of public single cell RNA sequencing analysis enhances our knowledge about the heterogeneity and dynamics of the tumor microenvironment. These results offer insights about potential diagnostic and therapeutic targets for TNBC depending on their subtypes. Citation Format: Kyungsoo Kim, Sung Gwe Ahn, Soong June Bae, Chihhao Chu, Jung Hwan Ji, Jee Hung Kim, Joon Jeong. Unraveling heterogeneity of tumor microenvironment of TNBC patients by meta-analysis of 6 breast cancer scRNAseq studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2542.