Biology subjects

Oesterreich, S.

Publications and source records attributed to Oesterreich, S..

At least 19 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

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↗

bioRxiv2026

Dual HER2/HER3 Targeting with Antibody-Drug Conjugates Reveals a Novel Therapeutic Strategy for HER2-Mutant Lobular Breast Cancer

Activating HER2 mutations are significantly enriched in both primary and metastatic invasive lobular breast cancer (ILC), with large public datasets of primary breast tumors linking them to a worse prognosis in ILC. Despite their oncogenic role, no FDA-approved therapies currently target HER2-mutant breast cancers. While the HER2-directed antibody-drug conjugate (ADC) trastuzumab deruxtecan (T-DXd) has shown efficacy in HER2-mutant non-small cell lung cancer, its activity in HER2-mutant ILC remains unknown. Using the Caris real-world database, one of the largest cohorts with survival data in advanced breast cancers, we confirmed that HER2 mutations are more prevalent in advanced ILC than in invasive breast cancer of no special type (NST) tumors, are associated with worse survival in both histologies, yet predict improved response to T-DXd across subtypes, highlighting the need for mutation-directed, histology-informed therapies. Using endogenous HER2-mutant ILC cell lines (UACC3133-S310F, BCK4-L755S) and CRISPR-engineered isogenic ILC models with clinically relevant HER2 mutations (S310F, V777L), we found these mutations drive HER2/HER3 hyperactivation and downstream signaling, conferring increased sensitivity to HER2 tyrosine kinase inhibitors (TKIs) and T-DXd. Mechanistically, HER2 mutants showed enhanced receptor ubiquitination, internalization, and lysosomal degradation upon T-DXd treatment, explaining the observed drug sensitivity. While combining T-DXd with neratinib or the HSP90 inhibitor ganetespib yielded synergistic effects in long-term growth assays, accompanied by increased HER2 ubiquitination, the concurrent hyperactivation of HER3 in HER2-mutant cells suggested that co-targeting HER3 could provide an effective alternative strategy. Accordingly, HER2-mutant ILC exhibited enhanced sensitivity to the HER3-directed ADC patritumab deruxtecan (P-DXd) or LJM716, a HER3-targeting antibody. We further uncovered a previously unrecognized mechanism of P-DXd beyond HER3 ligand blockade and payload delivery: P-DXd promotes HER2/HER3 association, increases HER2 ubiquitination, and enhances T-DXd internalization, resulting in potent synergy with T-DXd. Mechanistically, we identified HER3 extracellular domains I and II as essential for P-DXd binding and for mediating P-DXd-induced HER2/HER3 association, establishing a structural basis for this activity. In vivo, both T-DXd and P-DXd suppressed UACC3133 and BCK4 xenograft growth, with combination therapy trending toward greater efficacy and prevented regrowth of tumors. Extending these findings beyond HER2-mutant ILC, combination treatment with T-DXd and P-DXd demonstrated synergistic activity across multiple breast cancer models, including (i) HER2-amplified NST patient-derived organoids (PDOs) harboring hotspot HER2 mutations, (ii) HER2-wild-type NST PDOs with clinically intrinsic or acquired T-DXd resistance, and (iii) isogenic HER2-mutant ILC PDOs with experimentally induced resistance after prolonged T-DXd exposure. Collectively, these findings support HER2 as an actionable target in HER2-mutant ILC and position T-DXd-based regimens, particularly in combination with HER3 inhibition, as a promising therapeutic strategy for this underserved patient population.

Cancer Biology↗

bioRxiv2026

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↗

bioRxiv2026

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↗

bioRxiv2026

Estrogen receptor-positive cell line xenograft models recapitulate metastatic dissemination and endocrine response of invasive lobular breast carcinoma

HighlightsO_LIER+, CDH1-deficient ILC xenografts recapitulate single-file histology in vivo C_LIO_LISpontaneous metastases faithfully mirror unique ILC clinical dissemination patterns C_LIO_LIER+ leptomeningeal metastases confirmed histologically in ILC xenograft models C_LIO_LIFulvestrant inhibits ILC tumor growth and metastatic burden, improving survival C_LIO_LIER signaling is enriched in ILC brain metastases, with upregulation of RET C_LI Invasive lobular breast carcinoma (ILC), the most common special histological subtype of breast cancer, is characterized by nearly universal expression of estrogen receptor alpha (ER) and unique sites of metastases, neither of which is fully recapitulated by genetically engineered mouse models. Using reporter-labeled ILC mouse xenografts, herein we used mammary fat pad, tail vein and intracardiac orthotopic growth to analyze spontaneous and experimental metastasis and gene expression. We observed ER-positive primary tumors with single-file histology and collagen deposition, and spontaneous metastasis from the mammary fat pad to bones, ovaries, and brain including the leptomeninges, thereby closely mirroring the growth and metastatic spread of human ILC. Brain metastases showed strong ER staining, confirmed by sequencing analyses which identified estrogen signaling as top activated pathway, and the lesions exhibited robust response to endocrine therapy. In summary, we report endocrine responsive mammary fat pad, tail vein and intracardiac xenografts that faithfully demonstrate unique ILC features and can serve as invaluable pre-clinical translational platforms for validating candidate ILC genetic drivers and testing novel therapeutics.

cancer biology↗

bioRxiv2026

Saturating hepatic clearance drives elevated cfDNA and fragment shortening in cancer

Liquid biopsy studies consistently report both elevated circulating cell-free DNA (cfDNA) concentrations and shortened fragment lengths in cancer. These features are often attributed to tumor-specific processes, despite tumor-derived cfDNA frequently constituting less than 1% of the total. Here, we consider an alternative explanation: Saturation of cfDNA clearance, which prolongs cfDNA circulation time, increases exposure to plasma nucleases and is expected to produce similar fragmentomic signatures independent of tumor burden. By combining a mechanistic model of cfDNA fragmentation with analyses of two independent cancer patient cohorts, and publicly available clearance-perturbation experiments, we demonstrate that elevated cfDNA levels are accompanied by a characteristic leftward shift in fragment length distributions consistent with impaired hepatic clearance. This fragmentation signature becomes more pronounced at higher cfDNA concentrations, is independent of circulating tumor DNA (ctDNA) fraction, is reproducible under experimentally reduced clearance, and is independently prognostic of patient survival. Together, these results identify saturating clearance as a central determinant of cfDNA abundance and fragment length, re-framing cancer-associated fragmentomic patterns as systemic consequences of clearance dynamics rather than tumor burden alone. More broadly, they highlight the value of mechanistic modeling of clearance processes in extracting clinically meaningful signals from cfDNA fragmentation data.

cancer biology↗

bioRxiv2025

Identification and Credentialing of Patient Derived Xenograft Models of Invasive Lobular Breast Carcinoma using Multi-omics and Histopathology assessment

Breast cancer is a heterogeneous disease with numerous histological subtypes. Invasive lobular cancer (ILC) is the most common special subtype, accounting for 10-15% of all breast cancers. The pathognomonic feature of ILC is the loss of E-cadherin (CDH1), which leads to a unique single-file growth pattern of discohesive cells. Although ILCs show better prognostic factors than the most common No Special Type (NST) of breast cancer, patients with ILC have worse long-term outcomes, which is not well understood. In this study, we aimed to identify and characterize Patient-Derived Xenograft (PDX) models of ILC based upon the presence of truncating CDH1 mutations and/or low CDH1 mRNA expression among 128 human breast cancer PDX models. We selected 8 PDX models for validation using Immunohistochemical (IHC) analysis for E-Cadherin, p120, ER, PR, and HER2. We confirmed that seven of these PDX models are indeed ILC while one was identified as mixed NST-ILC PDX. Molecular analysis of the confirmed ILC PDX models showed enrichment of truncating CDH1 mutations, significantly lower levels of CDH1 mRNA expression and predominantly luminal subtypes compared to NST PDX models, in line with the molecular characteristics of human ILC disease. The commonly altered genes in the ILC PDX models included PIK3CA (57%), CDH1 (57%) and TP53 (57%) among others. Our study confirms and characterizes new ILC PDX models, offering valuable tools to advance our understanding of human ILC biology and support the development of innovative treatment strategies.

cancer biology↗

bioRxiv2025

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↗

bioRxiv2025

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↗

bioRxiv2024

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↗

bioRxiv2024

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↗

bioRxiv2024

EstroGene2.0: A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities (https://estrogeneii.web.app/). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of genome-edited versus ectopic overexpression model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancers response to endocrine therapies and explore resistance mechanisms.

cancer biology↗

bioRxiv2024

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↗

bioRxiv2024

Cancer-cell derived S100A11 promotes macrophage recruitment in ER+ breast cancer

Macrophages are pivotal in driving breast tumor development, progression, and resistance to treatment, particularly in estrogen receptor-positive (ER+) tumors, where they infiltrate the tumor microenvironment (TME) influenced by cancer cell-secreted factors. By analyzing single-cell RNA-sequencing data from 25 ER+ tumors, we elucidated interactions between cancer cells and macrophages, correlating macrophage density with epithelial cancer cell density. We identified that S100A11, a previously unexplored factor in macrophage-cancer crosstalk, predicts high macrophage density and poor outcomes in ER+ tumors. We found that recombinant S100A11 enhances macrophage infiltration and migration in a dose-dependent manner. Additionally, in 3D models, we showed that S100A11 expression levels in ER+ cancer cells predict macrophage infiltration patterns. Neutralizing S100A11 decreased macrophage recruitment, both in cancer cell lines and in a clinically relevant patient-derived organoid model, underscoring its role as a paracrine regulator of cancer-macrophage interactions in the pro-tumorigenic TME. This study offers novel insights into the interplay between macrophages and cancer cells in ER+ breast tumors, highlighting S100A11 as a potential therapeutic target to modulate the macrophage-rich tumor microenvironment.

systems biology↗

bioRxiv2024

Estrogen regulation and functional role of FGFR4 in estrogen receptor positive breast cancer

BackgroundResistance to endocrine therapy is a major challenge of managing estrogen receptor positive (ER+) breast cancer. We previously reported frequent overexpression of FGFR4 in endocrine resistant cell lines and breast cancers that recurred and metastasized following endocrine therapy, suggesting FGFR4 as a potential driver of endocrine resistance. In this study, we investigated the role of FGFR4 in mediating endocrine resistance and explored the therapeutic potential of targeting FGFR4 in advanced breast cancer. MethodsA gene expression signature of FGFR4 activity was examined in ER+ breast cancer pre- and post-neoadjuvant endocrine therapy and the association between FGFR4 expression and patient survival was examined. A correlation analysis was used to uncover potential regulators of FGFR4 overexpression. To investigate if FGFR4 is necessary to drive endocrine resistance, we tested response to FGFR4 inhibition in long term estrogen deprived (LTED) cells and their paired parental cells. Doxycycline inducible FGFR4 overexpression and knockdown cell models were generated to examine if FGFR4 was sufficient to confer endocrine resistance. Finally, we examined response to FGFR4 monotherapy or combination therapy with fulvestrant in breast cancer cell lines to explore the potential of FGFR4 targeted therapy for advanced breast cancer and assessed the importance of PAM50 subtype in response to FGFR4 inhibition. ResultsA FGFR4 activity gene signature was significantly upregulated post neoadjuvant aromatase inhibitor treatment, and high FGFR4 expression predicted poorer survival in patients with ER+ breast cancer. Gene expression association analysis using TCGA, METABRIC and SCAN-B datasets uncovered ER as the most significant gene negatively correlated with FGFR4 expression. ER negatively regulates FGFR4 expression at both the mRNA and protein level across multiple ER+ breast cancer cell lines. Despite robust overexpression of FGFR4, LTED cells did not show enhanced responses to FGFR4 inhibition compared to parental cells. Similarly, FGFR4 overexpression, knockdown or hotspot mutations did not significantly alter response to endocrine treatment in ER+ cell lines, nor did FGFR4 and fulvestrant combination treatment show synergistic effects. The HER2-like subtype of breast cancer showed elevated expression of FGFR4 and an increased response to FGFR4 inhibition relative to other breast cancer subtypes. ConclusionsDespite ER-mediated upregulation of FGFR4 post endocrine therapy, our study does not support a general role of FGFR4 in mediating endocrine resistance in ER+ breast cancer. Our data suggests that specific genomic backgrounds such as HER2 expression may be required for FGFR4 function in breast cancer and should be further explored.

cancer biology↗

bioRxiv2023

Paracrine effects of the senescence-associated secretory phenotype decrease cancer cell adhesion

Cellular senescence, characterized by a stable cell cycle arrest, is a well-documented consequence of several widely used chemotherapeutics that has context-dependent roles in cancer. Although senescent cells are non-proliferative, they remain biologically active and secrete a complex and diverse array of factors collectively known as the se-nescence-associated secretome (SAS), which exerts pro-tumorigenic effects. Here, we aimed to mechanistically investigate how the SAS contributes to metastatic dissemination of high grade serous ovarian cancer (HGSOC) using standard-of-care cisplatin as a se-nescence inducer. Our findings demonstrate that the cisplatin-induced SAS enhances the dissemination of HGSOC in vivo without affecting cell proliferation or viability. We found that the SAS facilitates cell detachment, an effect that is mediated by a metabolic com-ponent. Using a metabolically focused CRISPR knockout screen, we identified complex I as the key driver of SAS-mediated cell detachment in bystander cells and validated that inhibition of complex I activity decreases HGSOC dissemination in vivo. Mechanistically, this effect was driven by SAS-mediated inhibition of an NAD+-SIRT-SREBP axis, leading to decreased plasma membrane cholesterol that increased cell detachment. Excitingly, we found that fructose is the key SAS component upstream of the NAD+-SIRT-SREBP-cholesterol axis mediating increased detachment of bystander cells, and a high fructose diet increases HGSOC dissemination in vivo. These findings reveal that the cisplatin-induced SAS reprograms the metabolic microenvironment in HGSOC, driving cancer cell detachment and promoting metastatic dissemination in a paracrine fashion. They also point to a previously unrecognized pro-tumorigenic effect of the SAS that may contribute to the high recurrence rate of HGSOC patients.

cancer biology↗

bioRxiv2023

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↗