Clinical Subtypes Of Breast Cancer Research Articles

Abstract B034: Characterization of MHC-I-mediated immune evasion in triple-negative breast cancer using human transcriptomic datasets and immunocompetent mouse models

Abstract In Triple-Negative Breast Cancer (TNBC) patients, adaptive immune system activity in the tumor microenvironment is associated with improved prognosis. However, tumors can evolve to evade immune detection, likely leading to worse patient outcomes. Multi-omic data of paired primary and metastatic breast tumors demonstrate that TNBC metastases frequently lose expression of genes involved in major histocompatibility complex class I (MHC-I) antigen presentation, a key pathway for adaptive immune activation (PMID: 36585450). Therefore, understanding and addressing MHC-I-mediated immune evasion may have profound clinical benefits for TNBC patients. We hypothesize that breast tumor MHC-I loss results in a unique immune-evasive phenotype, which we are characterizing using human clinical datasets and immunocompetent mouse models of breast cancer. First, using large transcriptomic datasets (i.e., SCAN-B and TCGA), we are characterizing molecular and clinical features of MHC-I-low human breast tumors using expression of the MHC-I gene human leukocyte antigen A (HLA-A) as a continuous variable. We found HLA-A expression varies significantly between PAM50 molecular and clinical subtypes of breast cancer and has differing impacts on patient survival based on clinical subtype. In TNBCs, low HLA-A expression is associated with worse outcomes, while in HR+/HER2- tumors, low HLA-A predicts improved outcomes. We also identified genes highly correlated with HLA-A regardless of molecular subtype. This list was functionally rich, related to antigen processing machinery, adaptive immune-mediated cytotoxicity, and T cell exhaustion features. To complement human genomic data, we are empirically testing the role of MHC-I in syngeneic mouse mammary tumor models by individually knocking out murine MHC-I genes–H2-K, H2-D, and B2m–through CRISPR/Cas9-mediated genome editing. We have generated and validated knockouts (KOs) of H2-K and B2m, as well as empty vector control clones from the “immune-hot” and immune checkpoint inhibitor (ICI) responsive mammary tumor cell lines KPB25L-UV and T11-APOBEC. RNA sequencing of KPB25L-UV H2-K and B2m KO versus wildtype cell lines in vitro identified lists of differentially expressed genes, many of which are related to proteolytic and peptide antigen processing. Next, these CRISPR-modified cell lines were injected into the mammary fat pad of syngeneic immunocompetent mice, and the resulting tumors were harvested for RNA sequencing. Differentially expressed genes in KPB25L-UV H2-K KO versus wildtype tumors were related to increased MHC Class II antigen presentation and dendritic cell activity. Preliminary data suggests that mice bearing KPB25L-UV H2-K KO tumors have shortened survival compared to H2-K wildtype tumors. Experiments are ongoing to further characterize the growth dynamics, metastatic potential, single-cell transcriptomic profiles, and ICI sensitivities of these KO tumors in vivo. Our long-term goal is to identify therapeutic means to overcome this common immune-evasive phenotype to improve TNBC patient outcomes. Citation Format: Constandina E O'Connell, Brooke M Felsheim, Aranzazu Fernandez-Martinez, Kevin R Mott, Charles M Perou. Characterization of MHC-I-mediated immune evasion in triple-negative breast cancer using human transcriptomic datasets and immunocompetent mouse models [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B034.

Comparison of Clinical Subtypes of Breast Cancer within the Claudin-Low Molecular Cluster Reveals Distinct Phenotypes

Background: Molecular subtyping of breast cancer has provided a new perspective on the pathogenesis of the disease and a foundation for building a clinical classification for this heterogeneous disease. The initial classification categorizing breast cancers into five groups, luminal A, luminal B, ERBB2-overexpressing, basal-like and normal-like, was later supplemented by an additional group, claudin-low tumors. However, the claudin-low group has been more difficult to align with clinically used immunohistochemical categories. The identity of this group among clinical cases remains ill defined. Methods: The METABRIC cohort comprising more than 1700 breast cancers and providing information for classifying them in both clinical groups and the genomic PAM50/claudin-low groups was analyzed to derive relationships and clarify potential pathogenic ramifications. Comparisons of the claudin-low cases bearing different clinical group classifications and of the respective cases with the same clinical non-claudin-low classifications were performed. Results: ER-negative/HER2-negative breast cancers are predominantly (88.4%) basal-like and claudin low. Conversely, most basal-like cancers (83.6%) are ER negative/HER2 negative. However, claudin-low breast cancers are only in 68.4% of cases ER negative/HER2 negative and the other clinical phenotypes, mostly ER positive/HER2 negative/low proliferation, are also represented in more than 30% of claudin-low cancers. These claudin-low non-ER-negative/HER2-negative breast cancers differ from claudin-low ER-negative/HER2-negative cases in grade, prevalence of integrative clusters, and prevalence of common mutations and common amplifications. Differences also exist between the two groups classified clinically as ER negative/HER2 negative, that are genomically basal-like or claudin-low, including in menopause status, grade, histology, prevalence of high tumor mutation burden, distribution of integrative clusters, prevalence of TP53 mutations and of amplifications in the MYC and MCL1 loci. Furthermore, distinct characteristics are observed between the luminal A and claudin-low groups within the clinical ER-positive/HER2-negative/low proliferation group. Conclusion: Within genomically claudin-low breast cancers, the ER-negative/HER2-negative group is distinct from the group with either ER or HER2 positivity. Conversely, within clinical phenotypes, claudin-low and non-claudin-low breast cancers differ in clinical characteristics and molecular attributes.

Small Molecule Anticancer Compound Modulates Cell Cycle DNA Damage Response Pathway and Inhibit Tumorigenesis in Triple Negative Breast Cancer

ObjectiveTo investigate the mechanism of action and therapeutic benefits of NSC001, a small molecule anticancer compound, in the treatment of triple negative breast cancer (TNBC), a clinical subtype of breast cancer that is more aggressive, has poor prognosis. In TNBC, patients harbor tumors that lack expression of the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (Her2).HypothesisWe hypothesize that NSC001 will have a beneficial therapeutic effect on TNBC cells through the regulation of specific tumor associated signaling pathways in vitro.Material and methodsWe screened 1360 compounds from the National Cancer Institute (NCI) Diversity and Mechanistic Set library using the cell counting kit‐8 (CCK‐8) reagent from Dojindo Molecular Technologies, Inc. The screening was performed by applying 10µM of each candidate drug upon plates harboring the aggressive TNBC cell line, MDA‐MB‐231. Treatment time for all screening was fixed at 24 hours. The efficacy and potential mechanism of action of one of the potent drug candidates identified (NSC001) was further investigated on three TNBC cell lines (MDA‐MB‐231, MDA231‐LM2‐4175, and MDA‐MB‐468) using mass spectrometry and proteomic analysis. Afterwards, the results from the proteomic analysis were validated using molecular methods including cell viability assays, apoptosis assays, cell cycle assays, and western blotting.ResultsWe identified eight compounds that reduced the viability of MDA‐MB‐231 cells by up to 80% following a 24 hour treatment time point. Next, our in vitrodata show that NSC001 reduces the cell viability of TNBC cells in a dose‐and‐time dependent manner. Cell death data show that NSC001 induces potent apoptosis in a dose dependent manner in TNBC cells. Also, the results from colony formation assay show that 100nM [NSC001] is sufficient to inhibit the proliferative capacity of TNBC cells. Mass spectrometry and proteomic data reveals that NSC001 activates the cell cycle G2/M DNA damage checkpoint regulation in all the three TNBC cell lines used. Furthermore, we confirmed this finding in our cell cycle assay where we observed a clear G2/M cell cycle phase arrest. The arrest was potently induced at a dose significantly lower than the IC50 of NSC001. Lastly, we validated our proteomic results using western blotting, which confirmed that this low dose of NSC001 induces expression of p21, a cell cycle checkpoint regulator and tumor suppressor protein which is known to trigger cell cycle arrest in most cancer cell lines.ConclusionOverall, our data suggest that NSC001 may be a potent small molecule anticancer compound which should be further investigated for its potential to be used clinically in the treatment of TNBC patients.

HUNK Phosphorylates Rubicon to Support Autophagy, Promoting Tumorigenesis in HER2+ Breast Cancer

Human epidermal growth factor receptor 2‐positive (HER2+) breast cancer is one of the three clinical subtypes of breast cancer and is defined by having HER2 gene amplification that coincides with HER2 protein overexpression. HER2 is amplified in 15‐30% of breast cancers and overexpression of this gene is a predictor of survival in breast cancer patients. HER2‐targeted therapies have been successful in treating HER2+ breast cancer; however, over time, HER2+ breast cancer can develop resistance to these therapies. Therefore, there is an urgent need to establish novel targeted agents. One proposed method of resistance to these HER2 agents is dysregulation of autophagy where cancer cells can shift to a cytoprotective autophagy phenotype to avoid cell death. Previous work in our lab established that Hormonally Upregulated Neu‐associated kinase (HUNK) is a Serine/Threonine (S/T) protein kinase that is overexpressed in HER2+ breast cancer and is responsible for promoting autophagy, thereby leading to therapeutic resistance. Our previous work shows that HUNK phosphorylates an autophagy protein, Rubicon, in the N‐terminal domain at S92, promoting autophagy in 293T cells. However, we have yet to establish a role for this phosphorylation site within HER2+ breast cancer cells. Therefore, the objective of this study is to test whether Rubicon S92 phosphorylation plays a role in promoting tumorigenesis in HER2+ breast cancer. We generated multiple scientific tools: a phosphoserine antibody at S92 in Rubicon, a phospho‐mimetic (S92A) mutant, and a phospho‐deficient (S92D) mutant. We have established an autophagy phenotype within a HER2/neu model; mouse mammary tumor virus driven neu(rodent form of HER2) expressing mammary tumor cells (MMTV‐neu) genetically engineered to be HUNK wild type (WT) or HUNK knockout (KO). We performed an endogenous Rubicon immunoprecipitation (IP) and found that KO cells are deficient in S92 phosphorylation alongside with a lack of autophagy response, measured using LC3‐II western blot. These findings confirm that HUNK is required for Rubicon S92 phosphorylation in a genetically tractable model. Utilizing these cell lines alongside the phospho‐mimetic and phospho‐deficient Rubicon mutants will allow us to determine the role that HUNK plays in promoting tumorigenesis within HER2+ breast cancer in‐vitro and in‐vivo.

Abstract P2-09-01: Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes

Abstract Introduction: The risk of specific clinical subtype of breast cancer (defined by ER and HER2 status) among women in the general population who are carriers of germline pathogenic variants (PVs) in cancer predisposition genes is not well-defined. Methods: A total of 13,153 women with breast cancer (ER+/HER2-: 9381; ER+/HER2+: 1462; ER-/HER2+: 690; and ER-/HER2-: 1620) and 25,005 unaffected women (controls) from nine studies within the CAnceR RIsk Estimates Related to Susceptibility (CARRIERS) consortium that were not enriched for family history or early onset disease were included in the present analysis. A multiplex amplicon-based panel was used to perform germline sequencing for cancer predisposition genes. Case-control associations for each of the four clinical subtype of breast cancer was performed for PVs in 5 common breast cancer predisposition genes (ATM, BRCA1, BRCA2, CHEK2 and PALB2) utilizing a logistic regression model adjusting for study, age at diagnosis, race/ethnicity and family history of breast cancer. Results: The frequency of PVs in 5 genes was 3.8% for ER+/HER2-, 6.2% for ER+/HER2+, 4.2% for ER-/HER2+ and 9.3% for ER-/HER2- subtypes. PVs in BRCA1 and BRCA2 were associated with high risk (Odds Ratio (OR) >4) for all clinical subtypes of breast cancer, but the risk was highest (OR>8) for ER-/HER2- breast cancer. PVs in PALB2 were associated with high risk (OR>4) of ER-/HER2- and ER+/HER2+ subtypes and moderate risk (OR: 2-4) of ER+/HER2- breast cancer. Irrespective of the HER2 status, PVs in ATM were associated with a moderately increased risk (OR: 2-4) of ER+ breast cancer but the risk of ER- breast cancer was not elevated. In contrast, PVs in CHEK2 were associated with high risk (OR>4) of ER+/HER2+ breast cancer and moderate risk (OR: 2-4) of ER+/HER2- and ER-/HER2+ breast cancer, but the risk of ER-/HER2- breast cancer was not elevated. Conclusions: This study provides population-based estimates of risk of specific clinical subtypes of breast cancer which will be useful for genetic counseling and targeting appropriate screening strategies in PV carriers based on subtype specific risks of breast cancer. Citation Format: Siddhartha Yadav, Chunling Hu, Nicholas J. Boddicker, Eric Polley, Steven Hart, Rohan Gnanaolivu, Jie Na, Hongyan Huang, Song Yao, Celine M. Vachon, Lauren Teras, Jack A. Taylor, Dale P. Sandler, Julie R. Palmer, Janet E. Olson, Susan Neuhausen, Elena Martinez, Sara Lindstroem, Loic Le Marchand, Charles Kooperberg, Christopher Haiman, Mia M. Gaudet, James V. Lacey, Kimberly A. Bertrand, Leslie Bernstein, Paul W. Auer, Christine Ambrosone, Jeffrey N. Weitzel, Peter Kraft, David E. Goldgar, Katherine L. Nathanson, Susan M. Domchek, Fergus J. Couch, CARRIERS Consortium. Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-09-01.

Peripheral Blood Transcriptome in Breast Cancer Patients as a Source of Less Invasive Immune Biomarkers for Personalized Medicine, and Implications for Triple Negative Breast Cancer.

Simple SummaryTriple-negative breast cancer (TNBC) is an aggressive and heterogeneous breast cancer (BC) type which is difficult to treat and accompanied by disease recurrence. A better understanding of TNBC and the identification of novel biomarkers is needed to facilitate clinical decisions. Immune-related biomarkers are of particular interest, since immune responses play an important role in BC outcome. Transcriptome studies of peripheral blood cells can help us to understand the systemic immune responses to cancer cells and the mechanisms underlying cancer initiation and progression. They enable the identification of novel immune biomarkers for early cancer detection and personalized BC management and may bring forward new immunotherapy options. Recent transcriptome analyses of peripheral blood cells have delineated novel BC-patient immune subgroups. This categorization has implications for cancer prognosis, the identification of patients likely to benefit from immunotherapy, and treatment efficacy monitoring. Additionally, transcriptome studies have identified TNBC-enriched blood transcriptional signatures that can differentiate TNBC from other classical BC subtypes.Transcriptome studies of peripheral blood cells can advance our understanding of the systemic immune response to the presence of cancer and the mechanisms underlying cancer onset and progression. This enables the identification of novel minimally invasive immune biomarkers for early cancer detection and personalized cancer management and may bring forward new immunotherapy options. Recent blood gene expression analyses in breast cancer (BC) identified distinct patient subtypes that differed in the immune reaction to cancer and were distinct from the clinical BC subtypes, which are categorized based on expression of specific receptors on tumor cells. Introducing new BC subtypes based on peripheral blood gene expression profiles may be appropriate, since it may assist in BC prognosis, the identification of patients likely to benefit from immunotherapy, and treatment efficacy monitoring. Triple-negative breast cancer (TNBC) is an aggressive, heterogeneous, and difficult-to-treat disease, and identification of novel biomarkers for this BC is crucial for clinical decision-making. A few studies have reported TNBC-enriched blood transcriptional signatures, mostly related to strong inflammation and augmentation of altered immune signaling, that can differentiate TNBC from other classical BC subtypes and facilitate diagnosis. Future research is geared toward transitioning from expression signatures in unfractionated blood cells to those in immune cell subpopulations.

Mesoporous Silica Nanoparticle-Based Combination of Niclosamide and Doxorubicin: Effect of Treatment Regimens on Breast Cancer Subtypes.

Overexpressed Wnt/β-catenin signaling acts as a major cancer driver and plays an important role in the development of resistance against cancer chemotherapy. Therefore, the combinatorial approach of downregulating Wnt/β-catenin signaling along with using a chemotherapeutic agent may improve cancer therapy. However, systemic administration of free anticancer agents is nonspecific and poses serious side effects. Hence, the present study aimed at developing mesoporous silica nanoparticle (MSN)-based targeted combination therapy of a Wnt signaling inhibitor, niclosamide (Nic), and a conventional anticancer agent, doxorubicin (Dox). The results demonstrated the reproducible synthesis of highly stable and monodispersed sub-100 nm spherical shaped NPs. In vitro cytotoxicity studies demonstrated that the individual drug formulations caused concentration-dependent cytotoxicity to all of the three breast cancer subtypes, with higher concentrations being more cytotoxic. Further, sequential and concurrent combination of Nic-loaded MSNs with Dox-loaded MSNs was synergistic and caused significantly enhanced death in all breast cancer subtypes. Quantification of the combinatorial efficacy suggested that multiple combinatorial pairs were synergistic in all of the breast cancer types for both (sequential and concurrent) treatment regimens. However, the extent of synergism varied between the two treatment regimens in different clinical subtypes of breast cancer. Overall, the combination of Nic-loaded MSNs with Dox-loaded MSNs holds promise to be developed as an efficient therapeutic option for breast cancer irrespective of the clinical subtype in both sequential and concurrent treatment regimens.

A Synergistic Combination of Niclosamide and Doxorubicin as an Efficacious Therapy for All Clinical Subtypes of Breast Cancer.

Simple SummaryChemotherapy is the gold standard treatment option for metastatic cancers. However, the efficacy of chemotherapy is limited due to the development of resistance. The aberrantly expressed Wnt/β-catenin signaling pathway acts as one of the major cancer drivers that also causes the development of resistance. Therefore, in this study, we explored the combinatorial approach of downregulating the Wnt/β-catenin pathway along with using a chemotherapeutic agent as a strategy to overcome drug resistance and improve cancer therapy. We evaluated the combinatorial efficacy of Niclosamide (an antihelminthic repurposed as a Wnt signaling inhibitor) and Doxorubicin (first-line treatment for multiple cancers in the clinic) against breast cancer. The combination showed synergistically enhanced death of all three clinical subtypes of breast cancer cells in both the sequential and concurrent treatment regimens and holds the potential to be developed as an efficient therapeutic option for breast cancer irrespective of its clinical subtype.Drug resistance is one of the major hurdles in the success of cancer chemotherapy. Notably, aberrantly expressed Wnt/β-catenin signaling plays a major role in the initiation and maintenance of oncogenesis along with development of chemoresistance. Therefore, the combinatorial approach of targeting Wnt/β-catenin pathway along with using a chemotherapeutic agent seems to be a promising strategy to improve cancer therapy. In the present study, we evaluated the combination of niclosamide (Nic), an FDA-approved antihelminthic drug repurposed as a Wnt signaling inhibitor, and doxorubicin (Dox), a conventional anticancer agent, in all clinical subtypes of breast cancer viz. triple negative breast cancer, HER2 positive breast cancer, and hormone receptor positive breast cancer. The results demonstrated that the combination induced apoptosis and caused synergistically enhanced death of all breast cancer cell types at multiple combinatorial concentrations using both the sequential and concurrent treatment regimens. Mechanistically, downregulation of Wnt/β-catenin signaling and cell cycle arrest at G0/G1 phase by Nic and increase in reactive oxygen species by both Nic and Dox along with the inherent cytotoxicity of Dox mediated the synergism between the two drugs in both the treatment regimens. Overall, the combination of Nic and Dox holds promise to be developed as an efficient therapeutic option for breast cancer irrespective of its clinical subtype.

Systemic Multi-Omics Analysis Reveals Amplified P4HA1 Gene Associated With Prognostic and Hypoxic Regulation in Breast Cancer.

Breast cancer (BC) is a common malignant tumor in females around the world. While multimodality therapies exist, the mortality rate remains high. The hypoxic condition was one of the potent determinants in BC progression. The molecular mechanisms underpinning hypoxia and their association with BC can contribute to a better understanding of tailored therapies. In this study, two hypoxic induced BC transcriptomic cohorts (GSE27813 and GSE47533) were assessed from the GEO database. The P4HA1 gene was identified as a putative candidate and significantly regulated in hypoxic BC cells compared to normal BC cells at different time intervals (6 h, 9 h, 16 h, 32 h, and 48 h). In patients with Luminal (p < 1E-12), triple-negative subclasses (p = 1.35059E-10), Stage 1 (p = 8.8817E-16), lymph node N1 (p = 1.62436E-12), and in the 40–80 age group (p = 1.62447E-12), the expression of P4HA1 was closely associated with the clinical subtypes of BC. Furthermore, at the 10q22.1 chromosomal band, the P4HA1 gene displayed a high copy number elevation and was associated with a poor clinical regimen with overall survival, relapse-free survival, and distant metastases-free survival in BC patients. In addition, using BioGRID, the protein–protein interaction (PPI) network was built and the cellular metabolic processes, and hedgehog pathways are functionally enriched with GO and KEGG terms. This tentative result provides insight into the molecular function of the P4HA1 gene, which is likely to promote hypoxic-mediated carcinogenesis, which may favor early detection of BC and therapeutic stratification.

Research advances and new challenges in overcoming triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a pathological term used to identify invasive breast cancers that lack expression of estrogen and progesterone receptors and do not have pathologic overexpression of the HER2 receptor or harbor ERBB2 gene amplification. TNBC includes a collection of multiple distinct disease entities based upon genomic, transcriptomic and phenotypic characterization. Despite improved clinical outcomes with the development of novel therapeutics, TNBC still yields the worst prognosis among all clinical subtypes of breast cancer. We will systematically review evidence of the genomic evolution of TNBC, as well as potential mechanisms of disease progression and treatment resistance, defined in part by advances in next-generation DNA sequencing technology (including single cell sequencing), providing a new perspective on treatment strategies, and promise to reveal new potential therapeutic targets. Moreover, we review novel therapies aimed at homologous recombination deficiency, PI3 kinase/AKT/PTEN pathway activation, androgen receptor blockade, immune checkpoint inhibition, as well as antibody-drug conjugates engaging novel cell surface targets, including recent progress in pre-clinical and clinical studies which further validate the role of targeted therapies in TNBC. Despite major advances in treatment for TNBC, including FDA approval of 2 PARP inhibitors for metastatic TNBC, the crossing of the superiority boundary in a phase 3, placebo-controlled study of adjuvant olaparib in early-stage patients with germline BRCA-mutated high-risk HER2-negative early breast cancer, the FDA approval of 2 PD-(L)1 checkpoint antibodies for metastatic TNBC, and the FDA approval of the first antibody drug conjugate for TNBC, significant challenges remain. For example, despite the dawn of immunotherapy in metastatic TNBC, durable responses are limited to a small subset of patients, definitive biomarkers for patient selection are lacking, and the Oncology Drug Advisory Committee to the FDA has recently voted against approval of an anti-PD-1 checkpoint antibody high risk early-stage TNBC in the neoadjuvant setting. Also, despite early positive randomized phase 2 studies of AKT inhibition in metastatic TNBC, a recent phase 3 registration trial failed to validate earlier phase 2 data. Finally, we note that level one evidence for clinical efficacy of androgen receptor blockade in TNBC is still lacking. To meet these and other challenges, we will catalogue the ongoing exponential increase in interest in basic, translational, and clinical research to develop new treatment paradigms for TNBC.

Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review.

Breast cancer is a heterogeneous disease manifesting diversity at the molecular, histological and clinical level. The development of breast cancer classification was centered on informing clinical decisions. The current approach to the classification of breast cancer, which categorizes this disease into clinical subtypes based on the detection of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki67, is not ideal. This is manifested as a heterogeneity of therapeutic responses and outcomes within the clinical subtypes. The newer classification model, based on gene expression profiling (intrinsic subtyping) informs about transcriptional responses downstream from IHC single markers, revealing deeper appreciation for the disease heterogeneity and capturing tumor biology in a more comprehensive way than an expression of a single protein or gene alone. While accumulating evidences suggest that intrinsic subtypes provide clinically relevant information beyond clinical surrogates, it is imperative to establish whether the current conventional immunohistochemistry-based clinical subtyping approach could be improved by gene expression profiling and if this approach has a potential to translate into clinical practice.

111 Poster - Small molecule compound induces cell cycle arrest and subsequent apoptosis in an in-vitro model of triple negative breast cancer

Background: Triple negative breast cancer (TNBC) accounts for approximately 20% among clinical breast cancer subtypes found in patients. TNBC is very aggressive and has been associated with early and advanced-stages of the disease. TNBC patients harbor tumors that lack estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression; therefore, these patients cannot undergo hormonal therapy. The lack of targeted therapies for TNBC patients has intensified the need for more diagnostic modalities and treatment options.

Deep learned tissue \u201cfingerprints\u201d classify breast cancers by ER/PR/Her2 status from H&E images

Because histologic types are subjective and difficult to reproduce between pathologists, tissue morphology often takes a back seat to molecular testing for the selection of breast cancer treatments. This work explores whether a deep-learning algorithm can learn objective histologic H&E features that predict the clinical subtypes of breast cancer, as assessed by immunostaining for estrogen, progesterone, and Her2 receptors (ER/PR/Her2). Translating deep learning to this and related problems in histopathology presents a challenge due to the lack of large, well-annotated data sets, which are typically required for the algorithms to learn statistically significant discriminatory patterns. To overcome this limitation, we introduce the concept of “tissue fingerprints,” which leverages large, unannotated datasets in a label-free manner to learn H&E features that can distinguish one patient from another. The hypothesis is that training the algorithm to learn the morphological differences between patients will implicitly teach it about the biologic variation between them. Following this training internship, we used the features the network learned, which we call “fingerprints,” to predict ER, PR, and Her2 status in two datasets. Despite the discovery dataset being relatively small by the standards of the machine learning community (n = 939), fingerprints enabled the determination of ER, PR, and Her2 status from whole slide H&E images with 0.89 AUC (ER), 0.81 AUC (PR), and 0.79 AUC (Her2) on a large, independent test set (n = 2531). Tissue fingerprints are concise but meaningful histopathologic image representations that capture biological information and may enable machine learning algorithms that go beyond the traditional ER/PR/Her2 clinical groupings by directly predicting theragnosis.

The Contribution of Germline Predisposition Gene Mutations to Clinical Subtypes of Invasive Breast Cancer From a Clinical Genetic Testing Cohort.

BackgroundThe germline cancer predisposition genes associated with increased risk of each clinical subtype of breast cancer, defined by estrogen receptor (ER), progesterone receptor (PR), and HER2, are not well defined.MethodsA total of 54 555 invasive breast cancer patients with 56 480 breast tumors were subjected to clinical hereditary cancer multigene panel testing. Heterogeneity for predisposition genes across clinical breast cancer subtypes was assessed by comparing mutation frequencies by gene among tumor subtypes and by association studies between each tumor subtype and reference controls.ResultsMutations in 15 cancer predisposition genes were detected in 8.6% of patients with ER+/HER2-; 8.9% with ER+/HER2+; 7.7% with ER-/HER2+; and 14.4% of ER-/PR-/HER2- tumors. BRCA1, BRCA2, BARD1, and PALB2 mutations were enriched in ER- and HER2- tumors; RAD51C and RAD51D mutations were enriched in ER- tumors only; TP53 mutations were enriched in HER2+ tumors, and ATM and CHEK2 mutations were enriched in both ER+ and/or HER2+ tumors. All genes were associated with moderate (odds ratio > 2.00) or strong (odds ratio > 5.00) risks of at least one subtype of breast cancer in case-control analyses. Mutations in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53 had predicted lifetime absolute risks of at least 20.0% for breast cancer.ConclusionsGermline mutations in hereditary cancer panel genes confer subtype-specific risks of breast cancer. Combined tumor subtype, age at breast cancer diagnosis, and family history of breast and/or ovarian cancer information provides refined categorical estimates of mutation prevalence for women considering genetic testing.

Clinical subtypes of breast cancer in Thai women: a population-based study of Chiang Mai province

Abstract Background The change over time of distribution of breast cancer subtypes using population-based data has not been reported. Objective To describe the change over time of the distribution of female breast cancer by clinical subtype among the population in Chiang Mai, Thailand. Methods Data of breast cancer patients from Chiang Mai Cancer Registry, diagnosed from 2004 to 2013 were combined with immunohistochemical status from medical record, and used to describe the proportions of clinical breast cancer subtypes: (1) luminal A-like (ER+/PR+ and HER2-), (2) luminal B-like (ER+/PR+ and HER2+), (3) HER2 (ER- and PR- and HER2+), (4) triple-negative (ER- and PR- and HER2-). The distribution of breast cancer subtypes by age group was also described. Results Among 3,228 female breast cancer cases diagnosed during 2004–2013, the median age was 52 years and most patients presented at the regional stage. The unknown tumor subtype was lower than 25% in the periods 2008– 2009, 2010–2011, and 2012–2013. In those periods, the proportions of luminal A-like were 33%, 36%, and 48%; the proportions of luminal B-like were 14%, 20%, and 16%, the proportions of HER2 were 15%, 14%, and 13%; and the proportions of triple-negative were 16%, 14%, and 13%, respectively. In comparison with other groups, women aged ≥60 years had a significantly higher proportion of luminal A-like (P = 0.001), while women aged &lt;40 years tended to have a higher proportion of triple-negative (P = 0.10). Conclusions The proportion of breast cancer with luminal subtypes is increasing. Thus, in the future, treatment protocols with a variety of hormone therapies should be provided in order to improve efficacy and coverage of treatment for this population.

Breast Cancer Molecular Subtypes as a Predictor of Radiotherapy Fractionation Sensitivity

Breast cancer molecular subtypes have been shown to be predictive for certain systemic therapies; yet, there is a paucity of data regarding their use as a predictor of radiotherapy fractionation sensitivity. The hypothesis of this analysis is that the impact of hypofractionation (HF) in comparison to conventional fractionation (CF), does not differ across breast cancer subtypes in a population of women with invasive breast cancer treated with modern systemic therapy. Patients diagnosed with stage I - III breast cancer between 2005-2009 and referred to a population-based cancer care program were identified. Descriptive statistics were used to report clinico-pathologic and treatment parameters. Molecular subtype was determined using the American Joint Committee on Cancer (AJCC) classification system: Luminal A (ER+ AND PR+ AND HER2- AND Grade 1) OR (ER2-3+ AND PR2-3+ AND HER2- AND Grade 2); Luminal B (All other (ER+ OR PR+) AND HER2-); HER2+ (All Her2+); Triple Negative (ER- AND PR- AND Her2-). Radiotherapy fractionation was categorized as HF (16 fractions) versus CF (25-30 fractions). Multivariable Cox Regression modelling was used to identify predictors of local recurrence (LR). LR-free survival (LRFS) was determined using the Kaplan-Meier method and compared using the log-rank test. A total of 5,868 cases were identified. The median age was 58 years (range: 23 – 91). Patients with Luminal A subtype comprised 45% of the cohort (N=2,628), compared to 30% Luminal B (N=1,734), 15% HER2+ (N=903), and 10% Triple Negative (N=603). There was no difference between those that received HF versus CF in terms of margin status (p=0.67), presence of extensive ductal carcinoma in situ (p=0.30) or receipt of radiotherapy boost (p=0.54). On multivariable analysis, tumor grade (p=0.003), presence of LVI (p=0.006), use of systemic therapy (p=0.01) and receipt of endocrine therapy (p=0.001) were associated with the risk of LR. The overall 10-year LRFS was 97.1% (95 CI: 96.6-97.6) for the whole cohort. The 10-year LRFS based on molecular subtypes was 98.3% (95 CI: 97.6 – 98.7) Luminal A, 96.6% (95 CI: 95.5 – 97.4) Luminal B, 97.0% (95 CI: 95.5 – 98.0) HER2+, and 93.5% (95 CI: 91.1 – 95.3) Triple Negative (p <0.001). There was no difference in the 10-year LRFS between patients treated with HF versus CF in those with Luminal A (98.2% versus 98.4%; p=.42); Luminal B (96.6% versus 96.8%; p=.90); HER2+ (97.5% versus 95.8%; p=.12) or Triple Negative subtype (93.9% versus 92.2%; p=0.47). There was no significant interaction between breast cancer subtype and fractionation regimen. Within the AJCC’s four commonly recognized clinical subtypes of breast cancer, local recurrence-free survival was not affected by breast radiotherapy fractionation. This data supports the routine use of hypofractionated regimens across all breast cancer subtypes.

Abstract 1648: Deep learning tissue "fingerprints" to identify patients and predict clinical subtypes of breast cancer from digital pathology images

Abstract Inspired by facial recognition, we define an analogous problem in digital pathology called tissue matching. The objective is to match histology image patches to the patient. Unlike many classification problems in pathology, tissue matching comes with its own ground truth, and does not require subjective annotation. Using tissue-matching via deep neural networks, we developed strategies to overcome common sources of noise in histology data, including H&amp;E and slide scanner variability. We demonstrate that the typical approach of increasing the training set size, in the current study up to 12,000 tissue cores, yields only moderate gains in test accuracy, while including a loss term promoting style-invariance cooperatively improves the impact of scaling training set size. Our best neural network learned features that matched patients from the test set of H&amp;E image patches with 93% accuracy (n=104 patients, baseline accuracy &amp;lt;1%). Leveraging this network’s identification ability, we applied its internal representation as a feature vector (tissue fingerprint) to apply to other problems in pathology. We found that a fingerprint-based classifier could predict estrogen receptor status from breast cancer whole-slides on two separate cohorts with high accuracy (AUCROC=0.89), a sizeable improvement over previous approaches. This work presents a novel, scalable, and transparent approach to train neural networks to identify distinctive features of pathology images. These features have demonstrated utility in classifying biomarkers from morphology and have the potential to assist in a number of difficult tasks in pathology, including tissue subtype classification and patient tumor similarity assessments based on morphometry. Citation Format: Rishi Rawat, Fei Sha, Darryl Shibata, Daniel Ruderman, David Agus. Deep learning tissue "fingerprints" to identify patients and predict clinical subtypes of breast cancer from digital pathology images [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 1648.

Correction: Manganese-porphyrin-enhanced MRI for the detection of cancer cells: A quantitative in vitro investigation with multiple clinical subtypes of breast cancer.

[This corrects the article DOI: 10.1371/journal.pone.0196998.].

Therapeutically Active RIG-I Agonist Induces Immunogenic Tumor Cell Killing in Breast Cancers.

Cancer immunotherapies that remove checkpoint restraints on adaptive immunity are gaining clinical momentum but have not achieved widespread success in breast cancers, a tumor type considered poorly immunogenic and which harbors a decreased presence of tumor-infiltrating lymphocytes. Approaches that activate innate immunity in breast cancer cells and the tumor microenvironment are of increasing interest, based on their ability to induce immunogenic tumor cell death, type I IFNs, and lymphocyte-recruiting chemokines. In agreement with reports in other cancers, we observe loss, downregulation, or mutation of the innate viral nucleotide sensor retinoic acid-inducible gene I (RIG-I/DDX58) in only 1% of clinical breast cancers, suggesting potentially widespread applicability for therapeutic RIG-I agonists that activate innate immunity. This was tested using an engineered RIG-I agonist in a breast cancer cell panel representing each of three major clinical breast cancer subtypes. Treatment with RIG-I agonist resulted in upregulation and mitochondrial localization of RIG-I and activation of proinflammatory transcription factors STAT1 and NF-κB. RIG-I agonist triggered the extrinsic apoptosis pathway and pyroptosis, a highly immunogenic form of cell death in breast cancer cells. RIG-I agonist also induced expression of lymphocyte-recruiting chemokines and type I IFN, confirming that cell death and cytokine modulation occur in a tumor cell-intrinsic manner. Importantly, RIG-I activation in breast tumors increased tumor lymphocytes and decreased tumor growth and metastasis. Overall, these findings demonstrate successful therapeutic delivery of a synthetic RIG-I agonist to induce tumor cell killing and to modulate the tumor microenvironment in vivo Significance: These findings describe the first in vivo delivery of RIG-I mimetics to tumors, demonstrating a potent immunogenic and therapeutic effect in the context of otherwise poorly immunogenic breast cancers. Cancer Res; 78(21); 6183-95. ©2018 AACR.

Stable Isotope-Resolved Metabolomic Differences between Hormone-Responsive and Triple-Negative Breast Cancer Cell Lines.

Purpose To conduct an exploratory study to identify mechanisms that differentiate Luminal A (BT474 and MCF-7) and triple-negative (MDA-MB-231 and MDA-MB-468) breast cancer (BCa) cell lines to potentially provide novel therapeutic targets based on differences in energy utilization. Methods Cells were cultured in media containing either [U-13C]-glucose or [U-13C]-glutamine for 48 hours. Conditioned media and cellular extracts were analyzed by 1H and 13C NMR spectroscopy. Results MCF-7 cells consumed the most glucose, producing the most lactate, demonstrating the greatest Warburg effect-associated energy utilization. BT474 cells had the highest tricarboxylic acid cycle (TCA) activity. The majority of energy utilization patterns in MCF-7 cells were more similar to MDA-MB-468 cells, while the patterns for BT474 cells were more similar to MDA-MB-231 cells. Compared to the Luminal A cell lines, TNBC cell lines consumed more glutamine and less glucose. BT474 and MDA-MB-468 cells produced high amounts of 13C-glycine from media [U-13C]-glucose which was integrated into glutathione, indicating de novo synthesis. Conclusions Stable isotopic resolved metabolomics using 13C substrates provided mechanistic information about energy utilization that was difficult to interpret using 1H data alone. Overall, cell lines that have different hormone receptor status have different energy utilization requirements, even if they are classified by the same clinical BCa subtype; and these differences offer clues about optimizing treatment strategies.