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Lee, A. V.

Publications and source records attributed to Lee, A. V..

At least 19 recordsLinked to original sources

Breast cancer ovarian metastases show increased activity of GPCR pathways

Treatment resistance and metastases occur in 10-20% of patients with invasive lobular carcinoma (ILC), the most common special histological subtype of breast cancer. ILC metastasizes to the ovary more frequently than no special type (NST) tumors, also known as invasive ductal carcinoma (IDC). To characterize the genomic landscape of breast cancer ovarian metastases, we analyzed 15,613 local breast cancers, 22,010 non-ovarian metastases, and 246 ovarian metastases sequenced using FoundationOne(R)CDx or FoundationOne(R) assays. Ovarian metastases had enriched CDH1, PIK3CA, and TBX3 mutations and depleted TP53 and MYC alterations relative to local breast cancers, with additional depletion of ESR1 mutations compared to non-ovarian metastases. CDH1 mutations were less frequent in ovarian metastases (47%) than local ILC (81.3%), with reduced 16q loss (64% vs 84%), indicating that ovarian metastases also arise from non-ILC tumors. We extended these findings to a UPMC cohort of 27 ovarian metastases (13 ILC, 8 IDC, 6 mixed ductal-lobular carcinoma) with patient-matched primary tumors in most cases. In both cohorts, patients with ovarian metastases were significantly younger than those with other metastatic sites. In the UPMC cohort, the most frequent mutations were in PIK3CA, CDH1, KMT2C, FOXA1, and RUNX1. Transcriptomic analysis identified upregulated G protein-coupled receptor (GPCR) pathways, including metabotropic glutamate receptor signaling. Functional studies showed that calcium-sensing receptor (CaSR), a GPCR overexpressed in ovarian metastases, drives MEK/ERK-dependent migration and F-actin reorganization in ILC cell lines, enhanced by estrogen and blocked by calcilytic, MEK, or anti- estrogen treatment. Our findings inform future therapeutic targeting of ovarian metastasis.

cancer biology↗

Novel transplantable mouse cell line model recapitulates invasive lobular breast carcinoma (ILC) phenotype and immune microenvironment.

Invasive lobular breast carcinoma (ILC) is the most common special histological subtype of breast cancer, which accounts for 10-15% of all cases. To study the phenotype characteristics, metastatic growth kinetic and immune microenvironment of ILC, we developed an orthotopically transplantable cell line model from the spontaneous mammary fat pad tumor of CDH1-PTEN dual knockout C57BL/6 mouse with Cre-loxP system, designated CPT6. CPT6 recapitulates single-file growth pattern of human ILC, with pleomorphic features and a high mitotic index. RNA sequencing together with whole exome sequencing reveals a luminal A subtype with targetable driver mutations such as Kras G12C. As a novel orthotopically transplantable ILC model in immune competent mice, CPT6 shows robust in vivo growth and metastatic rate, and has moderate immunogenicity which appears to be T-cell independent. We also profiled the immune microenvironment of CPT6, revealing a myeloid-rich environment with dominant M2-macrophage population, which is concordant with human ILC. In summary, this model recapitulates human ILC phenotype and represents a valuable preclinical platform for evaluating immunotherapy and other therapeutic strategies for invasive lobular breast carcinoma.

cancer biology↗

Restoration of E-cadherin Expression Alters Metastatic Organotropism in Invasive Lobular Breast Carcinoma Models

Invasive lobular carcinoma (ILC) is the most frequently diagnosed special histological subtype of invasive breast cancer and accounts for 10 - 15% of all cases. The pathognomonic hallmark of ILC is the genetic loss of E-cadherin (CDH1) causing the disruption of adherens junctions and resulting in discohesive, linear growth. To better understand the role of E-cadherin in ILC metastasis, we generated three ILC cell lines, MDA-MB-134-VI, SUM44PE, and BCK4, with inducible E-cadherin expression, resulting in successful restoration of functional adherens junctions. E-cadherin expression reduced growth in 2D culture, and that effect was even greater in 3D ultra-low attachment (ULA) conditions where increased cell death was consistent with the previously described role of E-cadherin in anoikis. E-cadherin expression did not rescue the lack of migration and invasion of ILC cell line models; however, it decreased haptotaxis and increased adherence to Collagen I in SUM44 cells. There was no significant effect of E-cadherin expression on primary orthotopic tumor growth, but spontaneous metastasis to the reproductive tract, brain, and GI tract was reduced. Inhibition of metastasis to the reproductive tract and brain was also seen after tail vein injection of MDA-MB-134 E-cadherin-expressing cells. In summary, overexpression of functional E-cadherin in ILC models has some, but limited, effects on 2D growth in vitro and primary tumor growth in vivo, but there are pronounced effects on 3D ULA growth and metastases in vivo, with stronger effects on metastatic sites enriched in patients with ILC, especially the reproductive and GI tracts.

cancer biology↗

Benchmarking scRNA-seq Copy Number Inference: A Comprehensive Evaluation and Practitioner Guide

Accurately inferring copy number variation (CNV) from scRNA-seq data is critical for identifying malignant cells, reconstructing tumor subclonal architecture, and uncovering the genomic drivers that dictate cancer cell biology. However, the performance of existing tools varies significantly, and current benchmarks lack the breadth of datasets and methods necessary to provide definitive guidance. We present a comprehensive benchmark of 12 CNV inference methods across 28 real datasets (>100,000 cells) and diverse synthetic datasets. By evaluating methods based on malignant cell classification accuracy, CNV inference accuracy, scalability, and robustness, we establish a definitive practitioners guideline: allele-aware methods like Numbat excel when high-quality allelic inference can be achieved, whereas expression-centric tools such as Clonalscope, CopyKAT, inferCNV, and SCEVAN remain reliable when raw sequencing data are unavailable. Our study provides both a practical decision-making framework for researchers and a public repository of standardized CNV profiles to catalyze further methodological innovation.

cancer biology↗

Boost or Bust? The impact of supplementation on functional genetic diversity and selective processes in Tasmanian devils

Translocating individuals into existing populations of conspecifics can support threatened species by increasing population size, maintaining genetic diversity, and reducing the risk of inbreeding. However, for species whose adaptive potential is compromised due to ongoing threats, like disease, the outcome of such management interventions becomes more complex. The Tasmanian devil (Sarcophilus harrisii) is a prime example, where the emergence of Devil Facial Tumour Disease (DFTD) has led to significant population declines, raising concerns about their long-term survival. It is therefore critical to understand if the introduction of new functional genetic variants through supplementation actions enhances, or potentially hinders, their long-term persistence. We investigated changes in functional gene diversity at both the population- and individual-levels, pre and post supplementation, across multiple wild devil sites (four supplemented and four not supplemented). We found that functional diversity increased post supplementation. Though the magnitude of change was varied among sites, a similar site-specific pattern was also evident in genome-wide diversity. Importantly, we saw no evidence of swamping of local alleles or those putatively associated with DFTD regressions. This is likely due to the source population representing the broad wild genetic diversity and supplementations facilitating gene flow across the current fragmented landscape. Continued and long-term monitoring at multiple wild sites will be necessary to determine whether future generations retain this introduced genetic variation.

genomics↗

Integrating Artificial Intelligence-Driven Digital Pathology and Genomics to Establish Patient-Derived Organoids as a Novel Alternative Model for Drug Response in Head and Neck Cancer

Patient-derived organoids (PDOs) are emerging as advanced 3D ex vivo novel alternative method (NAM) preclinical models, offering significant advantages over traditional cell lines and monolayer cultures for therapeutic development. In this study, we established PDOs from surgically resected fresh tissues of human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) across anatomical sites, tumor T-categories, and sample types. These PDOs faithfully recapitulate the tumors pathology, mutational profile, and drug response. To enable rapid classification of PDO identity, we developed a new convolutional neural network (CNN) model, TransferNet-PDO, which accurately distinguished tumor versus normal PDOs in culture using digital histopathology images (AUC[≥]0.88). PDOs maintained stable cultures and were cryopreserved between passages 5 and 12. Immunohistochemistry (IHC) staining (PanCK, p63, Cytokeratin 13, Ki67) confirmed squamous phenotype and histologic aggression of the original tumor. For tumors harboring TP53 mutations by whole-exome sequencing (WES), PDOs retained the corresponding p53 functional status as confirmed by IHC (enhanced or loss of expression). Somatic mutational landscape revealed that PDOs preserved driver somatic mutations, copy number variations (CNVs), and clonal architecture including low-prevalence subclones. Drug sensitivity assessment of PDOs showed that cisplatin reduced cell viability, whereas cetuximab and lenvatinib had minimal effects. Chemoradiation led to greater tumor organoid killing compared to radiation or chemotherapy alone. This study presents an integrated HNSCC PDO platform combining tissue biobanking, organoid establishment, multi-omics characterization, functional drug screening, and AI-driven histopathologic classification, providing a comprehensive and scalable system for translational cancer research.

cancer biology↗

Targeting RET in Brain Metastases from Estrogen Receptor Positive Breast Cancer

Brain metastases (BrM) occur in 10-15% of patients with estrogen receptor (ER)-positive breast cancer, and remain a significant clinical challenge. While current therapeutic paradigms, including surgical resection and systemic therapy, have efficacy in the management of BrM from ER+BC, median overall survival following the diagnosis of BrM is approximately 18 months. The limited efficacy of current therapies, along with a relative paucity of therapeutic options, highlight the urgent clinical need to identify druggable targets for BrM from ER+BC. We previously identified recurrent overexpression of the receptor tyrosine kinase RET in breast cancer BrM relative to patient-matched primary tumors. The principal ligand for RET, Glial Cell-Derived Neurotrophic Factor (GDNF), is predominately expressed in the brain, where it functions in the maintenance of neurons and multiple glial cell types. Here, we show that increased RET expression and activation correlates with brain metastasis in breast cancer patients. Further, we confirm the role of RET signaling in the promotion of metastatic properties in vitro, including tumor spheroid formation, migration, invasion, and transformation. Using RET-overexpressing and RET-deficient models in four ER+BC cell lines, we demonstrate that RET overexpression enhances activation of RET downstream targets, such as ERK and AKT, and promotes metastatic phenotypes in in vitro, ex vivo and in vivo assays. Importantly, we demonstrate that the phenotypic effects of GDNF-mediated RET signaling can be abrogated by administration of Pralsetinib, a highly potent RET-selective kinase inhibitor. Using an ex vivo mouse brain slice co-culture model, we further demonstrate that RET overexpression in breast cancer cell lines potentiates their colonization and invasion into the brain tissues, which are reduced in RET-knockdown cell lines. RET overexpression facilitates brain colonization of breast cancer cells in vivo and is associated with reduced survival. Using proteomic analyses, we identify novel GDNF-mediated signaling pathways in breast cancer cell line models, including PLC{gamma}, P70S6K, STAT3 and CREB. RET-mediated activation of this range of downstream targets is sensitive to inhibition by Pralsetinib. In sum, this study identifies and characterizes RET as a targetable driver of breast cancer brain metastasis, and further describes the action of Pralsetinib in ER-positive breast cancer cell lines, providing insights to improve current targeted therapies for patients with breast cancer brain metastasis. Bullet pointsO_LIRET expression and activation are increased in breast cancer brain metastases. C_LIO_LIPralsetinib potently inhibits RET activation in RET overexpressing and in non-overexpressing breast cancer cell line models. C_LIO_LIRET overexpression and activation confers pro-metastatic properties including cell proliferation, colonization, migration and invasion in vitro and in ex vivo brain co-culture and enhances brain colonization of breast cancer cells in vivo. C_LIO_LIGDNF increases activation of ERK1/2, AKT, PCL{gamma}, P70S6K, STAT3, and CREB in RET overexpressing MCF-7 cells. C_LIO_LICREB or P70S6K knockdown attenuates GDNF stimulated activation of RET downstream targets and cell migration. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=193 HEIGHT=200 SRC="FIGDIR/small/647085v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@1628735org.highwire.dtl.DTLVardef@19ad565org.highwire.dtl.DTLVardef@2fdcc2org.highwire.dtl.DTLVardef@468233_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

CITEgeist: Cellular Indexing of Transcriptomes and Epitopes for Guided Exploration of Intrinsic Spatial Trends

BackgroundDysplastic tissue architecture in estrogen receptor-positive (ER+) breast cancer across therapy-naive and therapy-exposed cancer tissues presents unique challenges in the analysis of spatial transcriptomics. Many tools for deconvolution are developed on well-structured tissue architectures such as the 10x Genomics mouse hippocampus dataset. Spatial transcriptomics analysis could offer valuable insights into treatment response, but faces limitations in cellular resolution. MethodsTo address this problem, we developed CITEgeist, a computational tool for spatial transcriptomic deconvolution using integrated proteomics data from the same slide. Visium Antibody Capture technology was applied alongside our novel algorithm to analyze the tumor microenvironment. We demonstrate the reliability of our method using pre- and post-treatment samples from six breast cancer cases. ResultsOur approach revealed previously undetectable cellular interactions within the tumor microenvironment. By taking an interoperable approach to software development and grounding our algorithm in interpretable variables, we demonstrate how CITEgeist deconvolution is not only accurate but robust enough to be directly used as input in external analytical tools developed by other research teams. We then applied this approach to a set of specimens from a prospective trial our group ran and further validated the findings in a series of in vitro experiments as a demonstrated use case of the utility, necessity, and flexibility of CITEgeist; and the potential of our method to rapidly translate novel clinical samples to new biological insights. ConclusionsCITEgeist addresses a critical technical gap in spatial multi-omics analysis through an integrated, multi-disciplinary approach. This work demonstrates the value of combining clinical, translational, and computational expertise to identify novel mechanisms of treatment resistance, potentially transforming therapeutic strategies for resistant disease.

cancer biology↗

Hope for Others: Research Results from the University of Pittsburgh Rapid Autopsy Program for Breast Cancer

Breast cancer affects 1/8 of women throughout their lifetimes, with over 90% of cancer deaths being caused by metastasis. However, metastasis poses unique challenges to research, as complex changes in the microenvironment in different metastatic sites and difficulty obtaining tissue for study hinder the ability to examine in depth the changes that occur during metastasis. Rapid autopsy programs thus fill a unique need in advancing metastasis research. Here, we describe our protocol and processes for establishing and improving the US-based Hope for OTHERS (Our Tissue Helping Enhance Research and Science) program for organ donation in metastatic breast cancer. As of August 2024, we consented 114 patients and performed 37 autopsies, from which we collected 551 unique metastatic frozen tumor samples, 1244 FFPE blocks, 90 longitudinal liquid biopsy samples and developed 14 patient-derived organoid and 8 patient-derived xenograft models. We report in-depth clinical and histopathological information and discuss extensive new research and novel findings in patient outcomes, metastatic phylogeny, and factors in successful living model development. Our results reveal key logistical and protocol improvements that are uniquely beneficial to certain programs based on identifiable features, such as working closely with patient advocates, methods to rescue RNA quality in cases where tissue quality may degrade due to time delays, as well as guidelines and future expansions of our program. Statement of SignificanceRapid autopsy programs are unique research settings with huge potential for studying metastatic cancer, however, they have complex research challenges. Our work provides a valuable resource in advancing this field of research.

cancer biology↗

Systemic and local chronic inflammation and hormone disposition promote a tumor-permissive environment for breast cancer in older women

Estrogen receptor positive (ER+) breast cancer is the most common subtype of breast cancer and is an age-related disease. The peak incidence of diagnosis occurs around age 70, even though these post-menopausal patients have low circulating levels of estradiol (E2). Despite the hormone sensitivity of age-related tumors, we have a limited understanding of the interplay between systemic and local hormones, chronic inflammation, and immune changes that contribute to the growth and development of these tumors. Here, we show that aged F344 rats treated with the dimethylbenz(a)anthracene / medroxyprogestrone acetate (DMBA/MPA) carcinogen develop more tumors at faster rates than their younger counterparts, suggesting that the aged environment promotes tumor initiation and impacts growth. Single-nuclei RNA-seq (snRNA-seq) of the tumors showed broad local immune dysfunction that was associated with circulating chronic inflammation. Across a broad cohort of specimens from patients with ER+ breast cancer and age-matched donors of normal breast tissue, we observe that even with an estrone (E1)-predominant estrogen disposition in the systemic circulation, tumors in older patients increase HSD17B7 expression to convert E1 to E2 in the tumor microenvironment (TME) and have local E2 levels similar to pre-menopausal patients. Concurrently, trackable increases in several chemokines, defined most notably by CCL2, promote a chronically inflamed but immune dysfunctional TME. This unique milieu in the aged TME, characterized by high local E2 and chemokine-enriched chronic inflammation, promotes both accumulation of tumor-associated macrophages (TAMs), which serve as signaling hubs, as well as polarization of TAMs towards a CD206+/PD-L1+, immunosuppressive phenotype. Pharmacologic targeting of estrogen signaling (either by HSD17B7 inhibition or with fulvestrant) and chemokine inflammation both decrease local E2 and prevent macrophage polarization. Overall, these findings suggest that chronic inflammation and hormonal disposition are critical contributors to the age-related nature of ER+ breast cancer development and growth and offer potential therapeutic insight to treat these patients. Translational SummaryWe uncover the unique underpinnings establishing how the systemic host environment contributes to the aged breast tumor microenvironment, characterized by high local estradiol and chronic inflammation with immune dysregulation, and show that targeting avenues of estrogen conversion and chronic inflammation work to restore anti-tumor immunity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/616978v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1ecd90borg.highwire.dtl.DTLVardef@9d7ac8org.highwire.dtl.DTLVardef@e7fb74org.highwire.dtl.DTLVardef@2da524_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Mutual information for detecting multi-class biomarkers when integrating multiple bulk or single-cell transcriptomic studies

MotivationBiomarker detection plays a pivotal role in biomedical research. Integrating omics studies from multiple cohorts can enhance statistical power, accuracy and robustness of the detection results. However, existing methods for horizontally combining omics studies are mostly designed for two-class scenarios (e.g., cases versus controls) and are not directly applicable for studies with multi-class design (e.g., samples from multiple disease subtypes, treatments, tissues, or cell types). ResultsWe propose a statistical framework, namely Mutual Information Concordance Analysis (MICA), to detect biomarkers with concordant multi-class expression pattern across multiple omics studies from an information theoretic perspective. Our approach first detects biomarkers with con-cordant multi-class patterns across partial or all of the omics studies using a global test by mutual information. A post hoc analysis is then performed for each detected biomarkers and identify studies with concordant pattern. Extensive simulations demonstrate improved accuracy and successful false discovery rate control of MICA compared to an existing MCC method. The method is then applied to two practical scenarios: four tissues of mouse metabolism-related transcriptomic studies, and three sources of estrogen treatment expression profiles. Detected biomarkers by MICA show intriguing biological insights and functional annotations. Additionally, we implemented MICA for single-cell RNA-Seq data for tumor progression biomarkers, highlighting critical roles of ribosomal function in the tumor microenvironment of triple-negative breast cancer and underscoring the potential of MICA for detecting novel therapeutic targets. Availabilityhttps://github.com/jianzou75/MICA

bioinformatics↗

The invasive lobular cancer cell line encyclopedia (ICLE) for studying potential biomarkers and exploring therapeutic opportunities

Invasive lobular carcinoma (ILC), the most common histological "special type", accounts for [~]10-15% of all BC diagnoses, is characterized by unique features such as E-cadherin loss/deficiency, lower grade, hormone receptor positivity, larger diffuse tumors, and specific metastatic patterns. Despite ILC being acknowledged as a disease with distinct biology that necessitates specialized and precision medicine treatments, the further exploration of its molecular alterations with the goal of discovering new treatments has been hindered due to the scarcity of well-characterized cell line models for studying this disease. To address this, we generated the ILC Cell Line Encyclopedia (ICLE), providing a comprehensive multi-omic characterization of ILC and ILC-like cell lines. Using consensus multi-omic subtyping, we confirmed luminal status of previously established ILC cell lines and uncovered additional ILC/ILC-like cell lines with luminal features for modeling ILC disease. Furthermore, most of these luminal ILC/ILC-like cell lines also showed RNA and copy number similarity to ILC patient tumors. Similarly, ILC/ILC-like cell lines also retained molecular alterations in key ILC genes at similar frequency to both primary and metastatic ILC tumors. Importantly, ILC/ILC-like cell lines recapitulated the CDH1 alteration landscape of ILC patient tumors including enrichment of truncating mutations in and biallelic inactivation of CDH1 gene. Using whole-genome optical mapping, we uncovered novel genomic-rearrangements including novel structural variations in CDH1 and functional gene fusions and characterized breast cancer specific patterns of chromothripsis in chromosomes 8, 11 and 17. In addition, we systematically analyzed aberrant DNAm events and integrative analysis with RNA expression revealed epigenetic activation of TFAP2B - an emerging biomarker of lobular disease that is preferentially expressed in lobular disease. Finally, towards the goal of identifying novel druggable vulnerabilities in ILC, we analyzed publicly available RNAi loss of function breast cancer cell line datasets and revealed numerous putative vulnerabilities cytoskeletal components, focal adhesion and PI3K/AKT pathway in ILC/ILC-like vs NST cell lines. In summary, we addressed the lack of suitable models to study E-cadherin deficient breast cancers by first collecting both established and putative ILC models, then characterizing them comprehensively to show their molecular similarity to patient tumors along with uncovering their novel multi-omic features as well as highlighting putative novel druggable vulnerabilities. Not only we expand the array of suitable E-cadherin deficient cell lines available for modelling human-ILC disease but also employ them for studying epigenetic activation of a putative lobular biomarker as well as identifying potential druggable vulnerabilities for this disease towards enabling precision medicine research for human-ILC.

cancer biology↗

ESR1 fusion proteins invoke breast cancer subtype-dependent enrichment of ligand independent pro-oncogenic signatures and phenotypes

Breast cancer is a leading cause of female mortality and despite advancements in diagnostics and personalized therapeutics, metastatic disease largely remains incurable due to drug resistance. Fortunately, identification of mechanisms of therapeutic resistance have rapidly transformed our understanding of cancer evasion and is enabling targeted treatment regimens. When the druggable estrogen receptor (ER, ESR1), expressed in two-thirds of all breast cancer, is exposed to endocrine therapy, there is risk of somatic mutation development in approximately 30% of cases and subsequent treatment resistance. A more recently discovered mechanism of ER mediated endocrine resistance is the expression of ER fusion proteins. ER fusions, which retain the proteins DNA binding domain, harbor ESR1 exons 1-6 fused to an in-frame gene partner resulting in loss of the 3 ER ligand binding domain (LBD). In this report we demonstrate that in no-special type (NST) and invasive lobular carcinoma (ILC) cell line models, ER fusion proteins exhibit robust hyperactivation of canonical ER signaling pathways independent of the ligand estradiol or anti-endocrine therapies such as Fulvestrant and Tamoxifen. We employ cell line models stably overexpressing ER fusion proteins with concurrent endogenous ER knockdown to minimize the influence of endogenous wildtype ER. Cell lines exhibited shared transcriptomic enrichment in pathways known to be drivers of metastatic disease, notably the MYC pathway. The heterogeneous 3 fusion partners, particularly transcription factors SOX9 and YAP1, evoked varying degrees of transcriptomic and cistromic activity that translated into unique phenotypic readouts. Herein we report that cell line activity is subtype-, fusion-, and assay-specific suggesting that the loss of the LBD, the 3 fusion partner, and the cellular landscape all influence fusion activity. Therefore, it will be critical to generate additional data on frequency of the ER fusions, in the context of the clinicopathological features of the tumor. SignificanceER fusion proteins exhibit diverse mechanisms of endocrine resistance in breast cancer cell lines representing the no special type (NST) and invasive lobular cancer (ILC) subtypes. Our emphasize upon both the shared and unique cellular adaptations imparted by ER fusions offers the foundation for further translational research and clinical decision making.

cancer biology↗

WCRC-25: A novel luminal Invasive Lobular Carcinoma cell line model

Breast cancer is categorized by the molecular and histologic presentation of the tumor, with the major histologic subtypes being No Special Type (NST) and Invasive Lobular Carcinoma (ILC). ILC are characterized by growth in a single file discohesive manner with stromal infiltration attributed to their hallmark pathognomonic loss of E-cadherin (CDH1). Few ILC cell line models are available to researchers. Here we report the successful establishment and characterization of a novel ILC cell line, WCRC-25, from a metastatic pleural effusion from a postmenopausal Caucasian woman with metastatic ILC. WCRC-25 is an ER-negative luminal epithelial ILC cell line with both luminal and Her2-like features. It exhibits anchorage independent growth and haptotactic migration towards Collagen I. Sequencing revealed a CDH1 Q706* truncating mutation, together with mutations in FOXA1, CTCF, BRCA2 and TP53, which were also seen in a series of metastatic lesions from the patient. Copy number analyses revealed amplification and deletion of genes frequently altered in ILC while optical genome mapping revealed novel structural rearrangements. RNA-seq analysis comparing the primary tumor, metastases and the cell line revealed signatures for cell cycle progression and receptor tyrosine kinase signaling. To assess targetability, we treated WCRC-25 with AZD5363 and Alpelisib confirming WCRC-25 as susceptible to PI3K/AKT signaling inhibition as predicted by our RNA sequencing analysis. In conclusion, we report WCRC-25 as a novel ILC cell line with promise as a valuable research tool to advance our understanding of ILC and its therapeutic vulnerabilities. Financial supportThe work was in part supported by a Susan G Komen Leadership Grant to SO (SAC160073) and NCI R01 CA252378 (SO/AVL). AVL and SO are Komen Scholars, Hillman Foundation Fellows and supported by BCRF. This project used the UPMC Hillman Cancer Center and Tissue and Research Pathology/Pitt Biospecimen Core shared resource which is supported in part by award P30CA047904. This research was also supported in part by the University of Pittsburgh Center for Research Computing, RRID:SCR_022735, through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483. Finally, partial support was provided by the Magee-Womens Research Institute and Foundation, The Shear Family Foundation, and The Metastatic Breast Cancer Network.

cancer biology↗

Spatial molecular profiling of mixed invasive ductal-lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures and actionable driver mutations

Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially-resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity (e.g., MDLC with TNBC/basal ductal and ER+/luminal lobular regions), distinct enrichment of senescence/dormancy and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular, but not ductal regions, and single-cell ductal and lobular sub-populations with unique oncogenic signatures further highlighting intra-regional heterogeneity. Altogether, we demonstrated that the intra-tumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma. SignificanceMDLC displays both ductal and lobular tumor regions. Our multi-omic profiling approach revealed that these morphologically distinct tumor regions harbor distinct intrinsic subtypes and oncogenic features that may cause prognostic uncertainty and therapeutic dilemma. Thus histopathological/molecular profiling of individual tumor regions may guide clinical decision making and benefit patients with MDLC, particularly in the advanced setting where there is increased reliance on next generation sequencing.

cancer biology↗

Hrq1/RECQL4 regulation is critical for preventing aberrant recombination during DNA intrastrand crosslink repair and is upregulated in breast cancer.

Human RECQL4 is a member of the RecQ family of DNA helicases and functions during DNA replication and repair. RECQL4 mutations are associated with developmental defects and cancer. Although RECQL4 mutations lead to disease, RECQL4 overexpression is also observed in cancer, including breast and prostate. Thus, tight regulation of RECQL4 protein levels is crucial for genome stability. Because mammalian RECQL4 is essential, how cells regulate RECQL4 protein levels is largely unknown. Utilizing budding yeast, we investigated the RECQL4 homolog, HRQ1, during DNA crosslink repair. We find that Hrq1 functions in the error-free template switching pathway to mediate DNA intrastrand crosslink repair. Although Hrq1 repairs cisplatin-induced lesions, it is paradoxically degraded by the proteasome following cisplatin treatment. By identifying the targeted lysine residues, we show that preventing Hrq1 degradation results in increased recombination and mutagenesis. Like yeast, human RECQL4 is similarly degraded upon exposure to crosslinking agents. Furthermore, over-expression of RECQL4 results in increased RAD51 foci, which is dependent on its helicase activity. Using bioinformatic analysis, we observe that RECQL4 overexpression correlates with increased recombination and mutations. Overall, our study uncovers a role for Hrq1/RECQL4 in DNA intrastrand crosslink repair and provides further insight how misregulation of RECQL4 can promote genomic instability, a cancer hallmark.

genetics↗

Loss of E-cadherin Induces IGF1R Activation Revealing a Targetable Pathway in Invasive Lobular Breast Carcinoma

No Special Type breast cancer (NST; commonly known as Invasive Ductal Carcinoma (IDC)) and Invasive Lobular Carcinoma (ILC) are the two major histological subtypes of breast cancer with significant differences in clinicopathological and molecular characteristics. The defining pathognomonic feature of ILC is loss of cellular adhesion protein, E-cadherin (CDH1). We have previously shown that E-cadherin functions as a negative regulator of the Insulin-like Growth Factor 1 Receptor (IGF1R) and propose that E-cadherin loss in ILC sensitizes cells to growth factor signaling which thus alters their sensitivity to growth factor signaling inhibitors and their downstream activators. To investigate this potential therapeutic vulnerability, we generated CRISPR-mediated CDH1 knockout (CDH1 KO) IDC cell lines (MCF7, T47D, ZR75.1) to uncover the mechanism by which loss of E-cadherin results in IGF pathway activation. CDH1 KO cells demonstrated enhanced invasion and migration that was further elevated in response to IGF1, serum and Collagen I. CDH1 KO cells exhibited increased sensitivity to IGF resulting in elevated downstream signaling. Despite minimal differences in membranous IGF1R levels between wildtype (WT) and CDH1 KO cells, significantly higher ligand-receptor interaction was observed in the CDH1 KO cells, potentially conferring enhanced downstream signaling activation. Critically, increased sensitivity to IGF1R, PI3K, Akt and MEK inhibitors was observed in CDH1 KO cells and ILC patient-derived organoids, suggesting that these targets require further exploration in ILC treatment and that CDH1 loss may be exploited as a biomarker of response for patient stratification.

cancer biology↗

Hotspot ESR1 mutations are multimodal and contextual drivers of breast cancer metastasis

Constitutively active estrogen receptor- (ER/ESR1) mutations have been identified in approximately one third of ER+ metastatic breast cancer. Although these mutations are known mediators of endocrine resistance, their potential role in promoting metastatic disease has not yet been mechanistically addressed. In this study, we show the presence of ESR1 mutations exclusively in distant, but not local recurrences. In concordance with transcriptomic profiling of ESR1 mutant tumors, genome-edited Y537S and D538G cell models have a reprogrammed cell adhesive gene network via alterations in desmosome/gap junction genes and the TIMP3/MMP axis, which functionally confers enhanced cell-cell contacts while decreased cell-ECM adhesion. Context-dependent migratory phenotypes revealed co-targeting of Wnt and ER as vulnerability. Mutant ESR1 exhibits non-canonical regulation of several metastatic pathways including secondary transactivation and de novo FOXA1-driven chromatin remodeling. Collectively, our data supports evidence for ESR1 mutation-driven metastases and provides insight for future preclinical therapeutic strategies. SignificanceContext and allele-dependent transcriptome and cistrome reprogramming in genome-edited ESR1 mutation cell models elicit diverse metastatic phenotypes, including but not limited to alterations in cell adhesion and migration. The gain-of-function mutations can be pharmacologically targeted, and thus may be key components of novel therapeutic treatment strategies for ER-mutant metastatic breast cancer.

cancer biology↗