Biology subjects

Carleton, N.

Publications and source records attributed to Carleton, N..

5 recordsLinked to original sources

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

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↗

bioRxiv2020

Single cell transcriptomic heterogeneity in invasive ductal and lobular breast cancer cells

Invasive lobular breast carcinoma (ILC), one of the major breast cancer histological subtypes, exhibits unique clinical and molecular features compared to the other well-studied ductal cancer subtype (IDC). The pathognomonic feature of ILC is loss of E-cadherin, mainly caused by inactivating mutations within the CDH1 gene, but the extent of contribution of this genetic alteration to ILC-specific molecular characteristics remains largely understudied. To profile these features transcriptionally, we conducted single cell RNA sequencing on a panel of IDC and ILC cell lines, as well as an IDC cell line (T47D) with CRISPR-Cas9-mediated knock out (KO) of CDH1. Inspection of intra-cell line heterogeneity illustrated genetically and transcriptionally distinct subpopulations in multiple cell lines and highlighted rare populations of MCF7 cells highly expressing an apoptosis-related signature, positively correlated with a pre-adaptation signature to estrogen deprivation. Investigation of CDH1 KO-induced alterations showed transcriptomic membranous systems remodeling, elevated resemblance to ILCs in regulon activation, and suggests IRF1 as a potential mediator of reduced proliferation and increased cytokine-mediated immune-reactivity in ILCs.

cancer biology↗