Biology subjects

Spanheimer, P. M.

Publications and source records attributed to Spanheimer, P. M..

5 recordsLinked to original sources

bioRxiv2024

Quantitative proteomic mass spectrometry of protein kinases to determine dynamic heterogeneity of the human kinome

The kinome is a dynamic system of kinases regulating signaling networks in cells and dysfunction of protein kinases contributes to many diseases. Regulation of the protein expression of kinases alters cellular responses to environmental changes and perturbations. We configured a library of 672 proteotypic peptides to quantify >300 kinases in a single LC-MS experiment using ten micrograms protein from human tissues including biopsies. This enables absolute quantitation of kinase protein abundance at attomole-femtomole expression levels, requiring no kinase enrichment and less than ten micrograms of starting protein from flash-frozen and formalin fixed paraffin embedded tissues. Breast cancer biopsies, organoids, and cell lines were analyzed using the SureQuant method, demonstrating the heterogeneity of kinase protein expression across and within breast cancer clinical subtypes. Kinome quantitation was coupled with nanoscale phosphoproteomics, providing a feasible method for novel clinical diagnosis and understanding of patient kinome responses to treatment.

biochemistry↗

bioRxiv2024

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling

Annotation of the cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to improving our understanding of tumor biology. Herein, we present a compendium of matched chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell-of-origin for luminal breast tumors and basal breast tumors and then introduce a novel methodology that implements linear mixed-effects models to systematically quantify associations between regions of chromatin accessibility (i.e. regulatory elements) and gene expression in malignant cells versus normal mammary epithelial cells. These data unveil regulatory elements with that switch from silencers of gene expression in normal cells to enhancers of gene expression in cancer cells, leading to the upregulation of clinically relevant oncogenes. To translate the utility of this dataset into tractable models, we generated matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing, for each subtype, a conserved oncogenic gene expression program between in vitro and in vivo cells. Together, this work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of BC cells at single-cell resolution.

genomics↗

bioRxiv2023

Cell cycle plasticity underlies fractional resistance to palbociclib in ER+/HER2- breast tumor cells

The CDK4/6 inhibitor palbociclib blocks cell cycle progression in ER+/HER2- breast tumor cells. Although these drugs have significantly improved patient outcomes in metastatic breast cancers, a small percentage of tumor cells continues to divide in the presence of palbociclib--a phenomenon we refer to as fractional resistance. It is critical to understand the cellular mechanisms underlying fractional resistance because the precise percentage of resistant cells in patient tissue is a strong predictor of clinical outcome. Here, we hypothesize that fractional resistance arises from cell-to-cell differences in core cell cycle regulators that allow a subset of cells to escape CDK4/6 inhibitor therapy. We used multiplex, single-cell imaging to identify fractionally resistant tumor cells both in a cell culture model of ER+/HER2- breast cancer as well as live primary tumor cells resected from a patient. We found that tumor cells capable of proliferating in the presence of palbociclib showed both expected (e.g., CDK2, E2F1) and unexpected (e.g., Cdt1, p21, cyclin B1) shifts in core cell cycle regulators. Notably, resistant cells in both tumor models showed premature enrichment of the G1 regulators E2F1 and CDK2 protein and, unexpectedly, the G2/M regulator cyclin B1 just before cell cycle entry, suggesting that resistant cells may use noncanonical mechanisms to overcome CDK4/6 inhibition. Using computational data integration and trajectory inference approaches, we show how plasticity in cell cycle regulators gives rise to alternate cell cycle "paths" that allow individual ER+/HER2- tumor cells to escape palbociclib treatment. Understanding drivers of cell cycle plasticity, and how to eliminate resistant cell cycle paths, could lead to improved cancer therapies targeting fractionally resistant cells to improve patient outcomes.

cancer biology↗

bioRxiv2023

Tamoxifen Response at Single Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors

In ER+/HER2- breast cancer, multiple measures of intra-tumor heterogeneity are associated with worse response to endocrine therapy. To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live human tumors and normal breast specimens immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from 3 distinct resistant subpopulations are prognostic in large cohorts of ER+ breast cancer patients and enriched in endocrine therapy resistant tumors. This novel ex vivo model system now provides a foundation to define responsive and resistant sub-populations within heterogeneous tumors, to develop precise single cell-based predictors of response to therapy, and to identify genes and pathways driving resistance to therapy.

cancer biology↗

bioRxiv2022

Single-Cell Transcriptional and Epigenetic Profiles of Male Breast Cancer Nominate Salient Cancer-Specific Enhancers

Male breast cancer represents about 1% of all breast cancer diagnoses and, although there are some similarities between male and female breast cancer, the paucity of data available on male breast cancer makes it difficult to establish targeted therapies. To date, most male breast cancers (MBC) are treated according to protocols established for female breast cancer (FBC). Thus, defining the transcriptional and epigenetic landscape of MBC with improved resolution is critical for developing better avenues for therapeutic intervention. In this study, we present matched transcriptional (scRNA-seq) and epigenetic (scATAC-seq) profiles at single-cell resolution of two treatment naive MBC tumors processed immediately after surgical resection. These data enable the detection of differentially expressed genes between male and female breast tumors across immune, stromal, and malignant cell types, to highlight several genes that may have therapeutic implications. Notably, MYC target genes and mTORC1 signaling genes were significantly upregulated in the malignant cells of MBC compared to the female counterparts. To understand how the regulatory landscape of MBC give rise to these male-specific gene expression patterns, we leveraged the scATAC-seq data to systematically link changes in chromatin accessibility to changes in gene expression within each cell type. We observed cancer-specific rewiring of several salient enhancers and posit that these enhancers have a higher regulatory load than lineage specific enhancers. We highlight two examples of previously unannotated cancer-cell specific enhancers of ANXA2 and PRDX4 gene expression and show evidence for super-enhancer regulation of LAMB3 and CD47 in male breast cancer cells. Overall, this dataset annotates clinically relevant regulatory networks in male breast tumors, providing a useful resource that expands our current understanding of the gene expression programs that underlie the biology of MBC.

genomics↗