Dobrolecki, Lacey E.

ABSTRACT Advancements in transmission electron microscopy (TEM) have enabled in-depth studies of biological specimens, offering new avenues to large-scale imaging experiments with subcellular resolution. Mitochondrial structure is of growing interest in cancer biology due to its crucial role in regulating the multi-faceted functions of mitochondria. We and others have established the crucial role of mitochondria in triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer with limited therapeutic options. Building upon our previous work demonstrating the functional role of mitochondrial structure dynamics in the metabolic adaptations and survival of chemotherapy-refractory TNBC cells, we sought to extend those findings to a large-scale analysis of transmission electron micrographs. Here we present a novel U-Net artificial intelligence (AI) model for automatic annotation and assessment of mitochondrial morphology and feature quantification. Our model is trained on 11,039 manually annotated mitochondria across 125 micrographs derived from a variety of orthotopic patient-derived xenograft (PDX) mouse model tumors and adherent cell cultures. The model achieves an F1 score of 0.85 on test micrographs at the pixel level. To validate the ability of our model to detect expected mitochondrial structural changes, we utilized micrographs from mouse primary skeletal muscle cells genetically modified to lack Dynamin-related protein 1 (Drp1). We subjected in vitro and in vivo TNBC models to conventional chemotherapy treatments commonly used for clinical management of TNBC, including doxorubicin, carboplatin, paclitaxel, and docetaxel (DTX). We found substantial within-sample heterogeneity of mitochondrial structure in both in vitro and in vivo TNBC models. In four of five PDX models, in vivo treatment with DTX elicited significant alteration in mitochondrial elongation and/or area. We went on to compare mammary tumors and matched lung metastases in a highly metastatic PDX model of TNBC, uncovering significant increase in mitochondrial elongation in metastatic lesions compared to their matched primary mammary tumor. The successful application of our AI model to capture mitochondrial structure marks a step forward in high-throughput analysis of mitochondrial structures, enhancing our understanding of how morphological changes may relate to chemotherapy efficacy and mechanism of action. Our large, manually curated electron micrograph dataset - now publicly available - serves as a unique resource for developing, benchmarking, and applying computational models, while further advancing investigations into mitochondrial morphology and its impact on breast cancer biology. This study provides proof of concept that mitochondrial structural remodeling is an additional layer of cellular reprogramming accompanying therapeutic resistance TNBC that merits further investigation.

Abstract Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significance Integration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

Abstract Background: Amplification of chromosome 9p24.1 targeting PD-L1, PD-L2, and JAK2 (PDJ amplicon) is present in ~15% of TNBCs and is associated with activation of the JAK/STAT pathway and poor clinical outcomes. In preclinical studies, PD-L1 expression is markedly and rapidly inducible by low-dose IFN-γ in a PDJ amplicon copy-number dependent manner, mimicking an in situ inflammatory response. This suggests PDJ amplification could identify those TNBCs that would respond to ICIs and/or JAK2 targeted-therapies. The goals in this study were to determine the PDJ status of a well annotated cohort of TNBC PDXs with a 3 color FISH assay and to further define the genomes and transcriptomes of PDJ+ and PDJ- TNBCs. Methods: Tissue microarrays (TMAs) of 49 cores from 27 breast cancer PDX samples, including 21 TNBCs were obtained from the Baylor College of Medicine. The TMAs were interrogated with a 3 color FISH assay consisting of three probes that simultaneously target the PDJ amplicon, 9q22, and 9q34.1. The ratios of PDJ to 9q22 and PDJ to 9q34.1 were calculated to distinguish PDJ amplification from polyploidy. In each case, 50 cells were scored. Samples with PDJ signal >4.0, PDJ/9q22 ≥2 and/or PDJ/9q34.1 ≥2 were called positive by FISH. A subset of PDJ+ PDXs was then flow sorted by DNA content and interrogated with 400k whole genome CNV arrays. These results were integrated with existing clinical, exome, and transcriptome data for the TMAs (pdxportal.research.bcm.edu). Results: PDJ amplification was identified in 6/27 PDX samples including 3/21 (14%) TNBCs. Notably the number of PDJ+ cells in each sample ranged from 2-18. Single cells with ≥10 copies were observed in each PDJ+ sample as well as two PDJ- TNBCs. PDJ+ samples had increased expression of PD-L1 and JAK2 in their RNAseq data. Whole genome CNV analysis of flow sorted PDJ+ samples confirmed the presence of the PDJ amplicon and identified co-occurring amplifications and deletions. A similar pattern of PDJ amplicon heterogeneity was seen in a Mayo Clinic Arizona cohort of 70 surgically resected TNBCs. Previous whole genome CNV analysis of flow sorted samples identified 13/70 (18%) PDJ+ cases. FISH analysis of 14 TNBCs from this cohort (PDJ+ and PDJ- cases) validated these results and identified PDJ+ tumors with cells containing >20 copies of the amplicon. Conclusion: Our multicolor FISH assay of PDX and primary resected samples confirms a prevalence of ~15% PDJ+ TNBCs. Previous studies have reported an enrichment of JAK2 amplification in neoadjuvant treated TNBCs. Given the heterogeneous FISH patterns in both PDJ+ and PDJ- samples in our cohorts, we hypothesize that neoadjuvant therapy could enrich the presence of PDJ+ cells and thereby sensitize TNBCs to ICIs and JAK2 targeted therapies. Future work will explore the role of PDJ amplification and the presence of PDJ+ cells in TNBCs in response to neoadjuvant therapy. Citation Format: Alexander S. Roesler, Smriti Malasi, Elizabeth Lenkiewicz, Barbara A. Pockaj, Michael T. Lewis, Lacey E. Dobrolecki, Lori Koslosky, Peter Hartmayer, Karen S. Anderson, Michael T. Barrett. PDJ amplicon heterogeneity in triple negative breast cancers [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 1790.