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This abstract was withdrawn by the authors. Citation Format: Rinkenbaugh AL, Sinha VC, Zhang X, Shao J, Piwnica-Worms H. Withdrawn [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-07-03.

Shifts in tumor cell phenotype in response to selective pressures (i.e. changing microenvironments, drug treatments) pose one of the biggest obstacles to successful breast cancer therapies. Phenotypically diverse breast tumor and stroma subpopulations, and interactions between them that alter tumor cell biology, represent unique and spatially distinct niches. We hypothesize that localized neighborhoods of breast tumor cells possess specialized phenotypes that mediate chemoresistance and represent novel therapeutic vulnerabilities. In order to assess these potential phenotypes, we utilized imaging mass cytometry (IMC), a highly multiplexed imaging modality that allows simultaneous measurement of 30-40 antigens while retaining the spatial architecture of the cancer tissue. We constructed an IMC antibody panel that combines markers for tissue architecture, tumor and stromal cell phenotyping, and signaling pathway activation. IMC was applied to patient-derived xenograft (PDX) models of triple negative breast cancer (TNBC).Our TNBC PDX collection was established from tumors obtained before and after neoadjuvant Adriamycin and cyclophosphamide (AC). IMC analysis of 18 PDX models representing eight patients revealed that stromal cell phenotypes were generally shared between all models, but tumor cell phenotypes were largely patient-specific. While every model was comprised primarily of a few major tumor cell phenotypes, we noted that each case also harbored several minor, unique populations, suggesting that specialized neighborhoods may exist within the tumor mass. Comparison of paired PDX models showed a wide range of phenotypic responses to chemotherapy, ranging from stable tumor composition to widespread changes in tumor phenotypes. These phenotypic changes arose despite relatively consistent genomic architecture. Vimentinhi fibroblasts were present more often in post-AC models, while SMAhi fibroblasts were unchanged after treatment. Comparison of pre-/post-AC PDX pairs revealed spatially constrained MAPK activation emerged after treatment. To capture acute changes in tumor phenotype, we treated treatment-naïve PDX models with AC and evaluated tumors by IMC. As tumors regressed and then regrew, we identified novel phenotypic shifts, again including increased MAPK signaling localized to discrete neighborhoods, suggesting this property may be a common feature of chemoresistant TNBC. Analysis of adjacent cells revealed seven distinct neighborhoods, and ongoing work is aimed at determining whether these neighborhoods are altered in response to chemotherapy treatment. Taken together, our findings suggest that distinct tumor phenotypes arise following treatment. Our goal is to determine whether these unique phenotypic niches functionally contribute to chemoresistance and if disruption of these niches enhances chemosensitivity. Citation Format: Amanda L. Rinkenbaugh, Vidya C. Sinha, Pankaj Singh, Yuan Qi, Jiansu Shao, Xiaomei Zhang, Gloria V. Echeverria, W. Fraser Symmans, Stacy L. Moulder, Helen Piwnica-Worms. Analysis of spatiotemporal phenotypic heterogeneity in chemoresistant triple negative breast cancer using imaging mass cytometry [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 1595.

Shifts in tumor phenotype in response to selective pressures (i.e. changing microenvironments, drug treatments) pose one of the biggest obstacles to successful cancer therapies. Phenotypically diverse tumor and stroma subpopulations, and interactions between them that alter tumor biology, represent unique signaling niches. We hypothesize that these localized neighborhoods of breast tumor cells possess specialized phenotypes that mediate chemoresistance and represent novel therapeutic vulnerabilities. In order to assess these potential phenotypes, we utilized imaging mass cytometry (IMC), a highly multiplexed imaging modality that allows simultaneous measurement of 30-40 antigens while retaining the spatial architecture of the cancer tissue. We have constructed an IMC antibody panel that combines markers for tissue architecture, tumor and stromal cell phenotyping, and signaling pathway activation. IMC was applied to a collection of patient-derived xenograft (PDX) models of triple negative breast cancer (TNBC). Our PDX collection was established from patient tumors obtained before and after neoadjuvant chemotherapy. IMC analysis of 18 PDX models representing eight patients revealed that stromal cell phenotypes were generally shared between all models, but tumor cell phenotypes were largely patient-specific. While every model was comprised primarily of a few major tumor cell phenotypes, we noted that each case also harbored several minor, unique populations, suggesting that specialized neighborhoods may exist within the tumor mass. Sequential PDX models showed a wide range of phenotypic responses after chemotherapy, ranging from stable tumor composition to widespread changes in tumor phenotypes. Importantly, comparison of multiple pre-/post-chemotherapy PDX pairs revealed spatially constrained MAPK activation emerging after treatment. To capture acute changes in tumor phenotype, we treated animals bearing PDX tumors with chemotherapy and evaluated tumors by IMC. As tumors regressed and then regrew, we identified novel phenotypic shifts, again including increased MAPK signaling localized to discrete neighborhoods, suggesting this phenomenon may be a common feature of chemoresistant TNBC. Taken together, our findings suggest that distinct tumor phenotypes arise following treatment. Ongoing work is examining the spatial arrangement of these cell types to determine their local niche compositions, and then correlating these findings with clinical features. Our goal is to determine whether these unique signaling niches functionally contribute to chemoresistance and if disruption of these niches enhances chemosensitivity. Citation Format: Amanda L. Rinkenbaugh, Vidya C. Sinha, Jiansu Shao, Xiaomei Zhang, Gloria V. Echeverria, W. Fraser Symmans, Stacy L. Moulder, Helen Piwnica-Worms. Analysis of spatiotemporal phenotypic heterogeneity in chemoresistant triple negative breast cancer using imaging mass cytometry [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PR01.

Introduction: Ductal carcinoma in situ is a non-invasive lesion of the breast that comprises ~20% of newly diagnosed breast cancers in the United States. Prospectively distinguishing indolent from aggressive lesions has been a major clinical challenge. To begin addressing these challenges, we use an experimentally tractable mouse model of breast cancer in which invasive (but rarely in situ) lesions display architectural and morphological abnormalities while also being heavily immune-infiltrated. Methods: To explore the tumor-stroma niches that evolve as breast cancer progresses, we are undertaking single cell RNA sequencing and imaging mass cytometry to identify tumor and immune cells present within in situ (early) versus invasive (advanced) lesions, and to characterize shifts in phenotype and tumor-stroma niches that may occur as breast cancer transitions from in situ to invasive disease. Results: Single cell analyses revealed major cell populations within the tumor compartment of both early and advanced disease, including luminal- and basal-like populations, as well as an additional minor population that appears to represent a unique intermediate between luminal and basal states. Early stage lesions were comprised primarily of the major luminal population, whereas advanced lesions exhibited a significant expansion of intermediate and basal populations, suggesting that breast cancer cells may undergo a transition from luminal-like to basal-like phenotype during progression to invasive disease. Analysis of the immune compartments of early versus advanced disease also revealed that the relative neutrophil/MDSC/S100A8+ population increased as lesions advanced, while B cells, NK cells, and some T cells decreased. Furthermore, the immune populations of advanced lesions exhibited widespread upregulation of IL-17 targets, suggesting that the IL-17 pathway may drive shifts in the immune microenvironmental to support disease progression, particularly the increase in neutrophils/MDSCs. Additionally, given a previously reported role of IL-17 to alter epithelial stemness, increased IL-17 signaling in advanced lesions may also be driving the potential luminal-to-basal transition of malignant cells. Conclusion: Taken together, these findings suggest that a subset of malignant epithelial cells may transition from luminal-like to basal-like cells, and that this transition may be driven and/or maintained by a commensurate increase in IL-17 signaling that both directly impacts tumor cells and also establishes a tumor-supportive microenvironment. Citation Format: Vidya C. Sinha, Mingchu Xu, Amanda L. Rinkenbaugh, Xinhui Zhou, Xiaomei Zhang, Helen Piwnica-Worms. Single-cell evaluation to identify tumor-stroma niches driving the transition from in situ to invasive breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2822.

Introduction: Imaging mass cytometry (IMC) enables highly multiplexed assessment of more than 30 proteins at a time for the quantification of cell phenotypes within the tumor microenvironment of formaldehyde fixed-paraffin embedded (FFPE) tumor tissue. This methodology provides a deep understanding of the immune-contexture while preserving their spatial information in regards to malignant cells. We report a detailed workflow for optimization of a 27-plex immune-oncology (IO) panel, immune-phenotyping, and spatial analysis of tumor tissue. Methods: IO-panel includes 27 antibodies targeting lymphoid (CD3e, CD4, CD8a, CD19, CD45RO, LAG3, ICOS, Granzyme-B), myeloid (CD11b, CD14, CD33, CD68, CSF1R, IDO-1), immune-regulatory (HLA-DR, OX-40, VISTA, TIM-3, CD73, B7-H3), epithelial (Cytokeratin), proliferative (Ki-67), and constitutive (GAPDH, NaKATPase, Vimentin, aSMA, Histone H3) markers that were selected by singlet automated chromogenic immunohistochemistry (IHC) staining. BSA-free formulation from the same clones of antibodies were isotope-metal conjugated and manual indirect immunofluorescence (IF) staining was used to confirm the stability of metal-tagged antibodies. The optimization by singlet-IF and multiplexed-IMC staining was performed with normal and malignant tissues (4mm core TMA with tonsil, placenta, prostate, breast carcinoma, ovarian carcinoma, and endometrioid carcinoma tissues). All images from IHC (HALO software), indirect IF (InForm software), and IMC (MCD viewer software) slides were evaluated by two pathologists. Cell densities and spatial analysis of a breast carcinoma core was performed using HALO software. Results: All antibodies included in the panel were individually optimized by IHC under the same protocol conditions. A significant correlation of optimal antibody concentrations where observed across the different staining techniques (IHC vs IF, r=0.51; IHC vs IMC, r= 0.54; IF vs IMC, r=0.992; all p values Conclusions: IMC is a powerful platform for highly multiplexed detection of protein and cell phenotypes quantification in FFPE samples. Our developed IMC panel and digital image analysis of tissues allow the quantification of immune cells and spatial analysis of the tumor tissue microenvironment. Citation Format: Pedro Rocha, Luisa Solis, Edwin Parra, Ou Shi, Barbara Mino, Vidya C. Sinha, Amanda Rinkenbaugh, Auriole Tamegnon, Mak Duncan, Wei Lu, Mei Jiang, Lakshimi Kakarala, Jared K. Burks, Helen Piwnica-Worms, Cara Haymacker, Michael Teztlaff, Ignacio Wistuba, Alejandro Francisco-Cruz. Immuno-oncology panel optimization for imaging mass cytometry and digital image analysis of tumor tissues [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2679.

Tumors are increasingly appreciated as complex ecosystems, wherein functional interactions between tumor subclones, as well as components of the microenvironment, contribute to progression and drug resistance. While some studies have focused on soluble factors that mediate these interactions, little is known about the communication between physically neighboring tumor subclones (and their microenvironment). To investigate the nature and impact of such localized interactions, we are assessing the activation status of key cancer signaling pathways in neighboring tumor cells; importantly, we are characterizing these features at the single cell level within physically intact tumors. Triple negative breast cancer (TNBC) exhibits a high degree of intratumor heterogeneity, which has contributed to a lack of effective targeted therapy options. Chemotherapy remains the standard of care; however approximately half of patients have substantial residual disease following chemotherapy, which is associated with a high risk of recurrence. Our objective is to spatially define signaling heterogeneity using patient-derived xenograft (PDX) models before and after chemotherapy treatment, to determine if spatially-defined signaling niches drive chemoresistance in TNBC. We hypothesize that neighborhoods of cells possess specialized phenotypes that mediate chemoresistance, and when disrupted, will inhibit the growth of chemoresistant tumors. We are employing imaging mass cytometry (IMC),a next-generation immunostaining approach that allows for simultaneous measurement of 30-40 biomarkers while retaining the spatial organization of the sample.Wehave constructed an IMC panel of antibodies that combines markers for tissue architecture, tumor and immune cell phenotyping, and signaling pathway activation. Our PDX collection features sequential pairs derived from biopsies taken before and after chemotherapy treatment. IMC of the pre-/post-chemotherapy pairs revealed spatial patterns of pathway activation that emerged following treatment, including increases in PI3K/mTOR and localized MAPK signaling. To complement these studies, we treated PDX models with chemotherapy and analyzed tumors via IMC throughout the course of treatment. Again, we observed the emergence of increased MAPK signaling, localized to discrete neighborhoods within the tumor. Taken together, our findings suggest that unique signaling niches arise following treatment. Our goal is to now determine whether these signaling niches functionally contribute to chemoresistance and if disruption of these niches can inhibit the growth of chemoresistant disease. Citation Format: Amanda L. Rinkenbaugh, Vidya C. Sinha, Gloria V. Echeverria, Xiaomei Zhang, Jiansu Shao, W. Fraser Symmans, Stacy L. Moulder, Helen Piwnica-Worms. Analysis of spatiotemporal phenotypic heterogeneity in chemoresistant triple negative breast cancer using imaging mass cytometry [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1513.

Tumors are highly heterogeneous populations of cells, and measures of intratumoral heterogeneity (ITH) and diversity correlate with worse prognosis in many cancers, including breast cancer. Emerging studies are highlighting functional interactions between subclones, as well as among subclones and components of the tumor microenvironment. However, these studies have largely focused on soluble factors without interrogating the spatial distribution of subclones defined by activated signaling pathways. Previous work in this area has been severely limited by technical restrictions - existing techniques allowing measurement of many biomarkers simultaneously lose all information about the tissue architecture, while those that do retain spatial information can only assay a handful of markers at once. We will circumvent these limitations by undertaking imaging mass cytometry (IMC), which allows for simultaneous measurement of 30-40 antigens while retaining the spatial organization of the sample. Our objective is to dissect the signaling heterogeneity in tumors from patients and patient-derived xenograft (PDX) models of triple negative breast cancer (TNBC), through two main approaches: (1) characterization of signaling heterogeneity in tissue microarrays of human tumors and PDX models of TNBC with IMC and (2) modeling cell signaling heterogeneity in cell line-based models to determine mechanisms of cell-cell interaction and communication. We have constructed an IMC panel of antibodies that combines markers for tissue architecture, tumor and immune cell phenotyping, and signaling pathway activation. Profiling of a diverse panel of TNBC PDX models captures the heterogeneity of human TNBC. Analysis of distinct regions within individual PDX tumors demonstrate unique compositions of cell phenotypes between the edge and core of the tumor. Our PDX collection also includes sequential pairs derived from biopsies taken before and after chemotherapy treatment. Comparison of the pre-/post-chemotherapy pairs indicates emerging patterns of pathway activation. Interestingly, while the tumor cells from these models exhibit distinct phenotypes, the stromal cells are largely indistinguishable from one another, suggesting that these models are capturing tumor cell-intrinsic changes associated with chemotherapy response. Ultimately, we plan to use these results to identify novel vulnerabilities in subclonal interactions that can be targeted therapeutically in TNBC. Citation Format: Amanda L. Rinkenbaugh, Vidya C. Sinha, Xiaomei Zhang, Jiansu Shao, Helen Piwnica-Worms. Investigating triple negative breast cancer phenotypic heterogeneity of human and patient-derived xenograft samples using imaging mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4708.

Tumors are highly heterogeneous populations of cells, and measures of intratumoral heterogeneity (ITH) and diversity correlate with worse prognosis in many cancers, including breast cancer. Emerging studies are highlighting functional interactions between subclones, as well as among subclones and components of the tumor microenvironment. However, these studies have largely focused on soluble factors without interrogating the spatial distribution of subclones defined by activated signaling pathways. Previous work in this area has been severely limited by technical restrictions – existing techniques allowing measurement of many biomarkers simultaneously lose all information about the tissue architecture, while those that do retain spatial information can only assay a handful of markers at once. We will circumvent these limitations by undertaking imaging mass cytometry (IMC), which allows for simultaneous measurement of 30-40 antigens while retaining the spatial organization of the sample. Our objective is to dissect the signaling heterogeneity in tumors from patients and patient-derived xenograft (PDX) models of triple negative breast cancer (TNBC), through two main approaches: (1) characterization of signaling heterogeneity in human tumors and PDX models of TNBC through the use of imaging mass cytometry (IMC) and (2) modeling cell signaling heterogeneity in cell line-based models to determine mechanisms of cell-cell interaction and communication. We have constructed an IMC panel of antibodies that combines markers for tissue architecture, cell phenotyping, and signaling pathway activation. Profiling of a panel of TNBC PDX models, including matched sets of pre- and post-chemotherapy treatment, indicates emerging patterns of pathway activation. We will utilize these results to inform functional studies in our isogenic cell line models. As it is becoming more clear that tumors are composed of heterogeneous subclones, it is crucial that we understand the communication between subclones and with components of the microenvironment. Ultimately, we plan to use these results to identify novel vulnerabilities in subclonal interactions that can be targeted therapeutically in TNBC. Citation Format: Amanda L. Rinkenbaugh, Vidya C. Sinha, Xiaomei Zhang, Helen Piwnica-Worms. Functionalizing intratumoral signaling heterogeneity in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2181.