Biology subjects

West, R. B.

Publications and source records attributed to West, R. B..

At least 19 recordsLinked to original sources

bioRxiv2026

Resolving the immune response across clonal cancer evolution in situ with whole transcriptome profiling

Single-cell spatial transcriptomics is now central to studying tumors in their native tissue context. Here we present the first comprehensive, independent evaluation of Atera, a new spatial whole-transcriptome platform, compared with Xenium in human ductal carcinoma in situ (DCIS). We show that Atera enables granular cell-state annotation and resolves rare cell populations, experimentally validated by multiplex immunofluorescence (IF). We further show that its transcriptome-wide coverage enables inference of copy-number alterations at single-cell resolution, allowing us to reconstruct the clonal evolution of DCIS. We orthogonally confirm the inferred copy-number alterations by whole-genome sequencing of 16 microdissected tumor regions from consecutive tissue sections. Finally, by mapping the immune microenvironment onto this clonal architecture, we demonstrate the feasibility of tracking the changes in immune response along the clonal tumor evolution in situ. Together, our results establish Atera as a validated platform for tracking clonal evolution and immune adaptation in clinical samples.

bioinformatics↗

bioRxiv2026

Extracellular Matrix Proteomic Signatures Associate with Disease-Free Survival in Later Events of Ductal Carcinoma In Situ or Invasive Breast Cancer

BackgroundDuctal carcinoma in situ (DCIS) is a noninvasive breast lesion with variable risk of progression to invasive breast cancer (IBC). Current transcription and cell marker investigations suggest ECM decreases in later events but are limited in details of ECM proteomic composition, including post-translational modifications. We investigated whether the extracellular matrix (ECM) proteome alters with later breast events of DCIS or IBC. MethodsECM-targeted mass spectrometry imaging and liquid chromatography-tandem mass spectrometry (LC-MS/MS) were applied to ten tissue microarrays from the Resource of Archival Human Breast Tissue cohort (RAHBT). Primary DCIS specimens (n=136) were analyzed in relation to later events of DCIS (n=40) or IBC(n=30), with a mean follow-up of 192.1 months 95% CI [179.1,205.1]. Statistical modeling, survival analyses, and exploratory machine learning approaches were used to identify ECM peptide signatures associated with later events. ResultsDistinct ECM peptide profiles were associated with later events of DCIS or IBC. Fifteen peptides derived from fibrillar collagens (COL1A1, COL1A2, COL3A1) and elastin, showed significantly reduced abundance in patients who developed IBC. Lower expression of specific collagen peptides associated with overall 19.9% 95% CI [17.92, 21.81] decreased disease-free survival for IBC. Lower expression of these peptides was significantly associated with reduced disease-free survival (age-adjusted hazard ratio [HR] = 2.45, 95% CI: 2.33-2.57; P < 0.05). Patient-matched samples of primary DCIS, later DCIS, and later invasive breast cancer further demonstrated reduction in ECM peptide detection. Exploratory predictive modeling from patient-matched samples achieved high performance (AUROC >0.98, accuracy >93%) in distinguishing primary from later events. Following prior work in the RAHBT cohort, reduction of certain collagen peptides was also observed in primary DCIS samples from higher risk patient groups. ConclusionsECM proteomic remodeling, particularly decreases of specific collagen domains, is strongly associated with later events of DCIS and IBC. These findings highlight ECM proteome as a critical regulator of breast cancer emergence with potential as a prognosticator of risk stratification to guide clinical management of DCIS.

pathology↗

bioRxiv2026

Multi-Scale Tri-Modal Histology Dataset Integrating Tumor Morphology, Immune Patterns, and Clinical Outcomes

Accurate prognostic assessment of prostate cancer (PCa) requires an integrated understanding of tissue morphology-encompassing cell structure, glandular architecture, and tissue organization-and the immune environment. We present Prostate-TriMod, a novel tri-modal histology dataset designed to integrate high-resolution visual morphology with spatial tissue maps, immune infiltration patterns, and clinical outcomes. This dataset, generated from the Cell DIVE multiplexed imaging platform, consists of three synchronized modalities: (1) multiscale virtual H&E tiles (224px, 256px, 512px, and 2040px) providing visual morphological context, (2) spatial tissue maps identifying cancerous/non-cancerous epithelial cells, stroma and immune cell populations (via TOPAZ and CAT models), and (3) text captions generated from single-cell data and patterns. The dataset includes comprehensive clinical annotations, including Grade Groups and biochemical recurrence (BCR) status. By providing high-fidelity alignment between visual features, spatial tissue maps, and textual descriptions, Prostate-TriMod empowers the development of advanced multimodal AI frameworks. We expect this resource to support reuse in multimodal representation learning, spatial analysis, and benchmarking studies that link histology morphology and immune context to clinical outcomes in prostate cancer.

bioinformatics↗

bioRxiv2025

QUICHE reveals structural definitions of anti-tumor responses in triple negative breast cancer

While recent innovations in spatial biology have driven new insights into how tissue organization is altered in disease, interpreting these datasets in a generalized and scalable fashion remains a challenge. Computational workflows for discovering condition-specific differences in tissue organization typically rely on pairwise comparisons or unsupervised clustering. In many cases, these approaches are computationally expensive, lack statistical rigor, and are insensitive to low-prevalence cellular niches that are nevertheless highly discriminative and predictive of patient outcomes. Here, we present QUICHE - an automated, scalable, and statistically robust method that can be used to discover cellular niches differentially enriched in spatial regions, longitudinal samples, or clinical patient groups. In contrast to existing methods, QUICHE combines local niche detection with interpretable statistical modeling using graph neighborhoods to detect differentially enriched cellular niches, even at low prevalence. Using in silico models and spatial proteomic imaging of human tissues, we demonstrate that QUICHE can accurately detect condition-specific cellular niches occurring at a frequency of 0.5% in fewer than 20% of patient samples, outperforming the next best method which required a patient prevalence of 60% for detection. To validate our approach and understand how tumor structure influences recurrence risk in triple negative breast cancer (TNBC), we used QUICHE to comprehensively profile the tumor microenvironment in a multi-center, spatial proteomics cohort consisting of primary surgical resections, analyzing over 2 million cells from 314 patients across 5 medical centers. We discovered cellular niches that were consistently enriched in key regions of the tumor microenvironment, including the tumor-immune border and extracellular matrix remodeling regions, as well as niches statistically-associated with patient outcomes, including recurrence status and recurrence-free survival. The majority of differential niches (74.2%) were specific to patients that did not relapse and formed a robust interconnected network enriched in monocytes, macrophages, APCs, and CD8T cells with tumor and stroma cells. In contrast, the interaction network for patients that relapsed was notably sparse and enriched in B cells, CD68 macrophages and neutrophils. We validated these findings using two independent cohorts, observing similar cellular interactions and predictive power. Collectively, these results suggest that salient, generalized profiles of productive anti-tumor immune responses are defined by a network of structural engagement between innate and adaptive immunity with tumor and stromal cells, rather than by any single specific cell population. We have made QUICHE freely available as a user-friendly open-source Python package at https://github.com/jranek/quiche.

bioinformatics↗

bioRxiv2025

VISTA-induced tumor suppression by a four amino acid intracellular motif

VISTA is a key immune checkpoint receptor under investigation for cancer immunotherapy; however, its signaling mechanisms remain unclear. Here we identify a conserved four amino acid (NPGF) intracellular motif in VISTA that suppresses cell proliferation by constraining cell-intrinsic growth receptor signaling. The NPGF motif binds to the adapter protein NUMB and recruits Rab11 endosomal recycling machinery. We identify and characterize a class of triple-negative breast cancers with high VISTA expression and low proliferative index. In tumor cells with high VISTA levels, the NPGF motif sequesters NUMB at endosomes, which interferes with epidermal growth factor receptor (EGFR) trafficking and signaling to suppress tumor growth. These effects do not require canonical VISTA ligands, nor a functioning immune system. As a consequence of VISTA expression, EGFR receptor remains abnormally phosphorylated and cannot propagate ligand-induced signaling. Mutation of the VISTA NPGF domain reverts VISTA-induced growth suppression in multiple breast cancer mouse models. These results define a mechanism by which VISTA represses NUMB to control malignant epithelial cell growth and signaling. They also define distinct intracellular residues that are critical for VISTA-induced cell-intrinsic signaling that could be exploited to improve immunotherapy.

cancer biology↗

bioRxiv2024

TissueMap: A Web-Based Multiplexed Image Viewer

Datasets generated by spatial biology techniques such as multiplex immunofluorescence staining or spatial transcriptomics profiling of histologic sections carry a tremendous wealth of information. Several commercial platforms exist that can simultaneously acquire 1-1000 distinct marker signals (e.g., MIBI, CODEX, Orion, Nanostring CosMX SMI, Vizgen). However, due to the large size of these datasets, their viewing and sharing are slow, laborious, and require extensive computational resources. To overcome this, we developed TissueViewer, a web-based viewer designed to deliver high-resolution images over the internet with low bandwidth requirements and at high speed.

bioinformatics↗

bioRxiv2023

Single Cell Expression Analysis of Ductal Carcinoma in Situ Identifies Alterations in Epithelial Integrity

To identify mechanisms underlying the growth of ductal carcinoma in situ (DCIS) and properties that lead to progression to invasive cancer, we performed single-cell RNA-sequencing (scRNA-seq) on DCIS lesions and matched synchronous normal breast tissue. Using inferred copy number variations (CNV), we identified neoplastic epithelial cells from the clinical specimens which contained a mixture of DCIS and normal ducts. Phylogenetic analysis based on the CNVs demonstrated intratumoral clonal heterogeneity was associated with significant gene expression differences. We also classified epithelial cells into mammary cell states and found that individual genetic clones contained a mixture of cell states suggesting an ongoing pattern of differentiation after neoplastic transformation. Cell state proportions were significantly different based on estrogen receptor (ER) expression with ER-DCIS more closely resembling the distribution in the normal breast, particularly with respect to cells with basal characteristics. Using deconvolution from bulk RNA-seq in archival DCIS specimens, we show that specific alterations in cell state proportions are associated with progression to invasive cancer. Loss of an intact basement membrane (BM) is the functional definition of invasive breast cancer (IBC) and scRNA-seq data demonstrated that ongoing transcription of key BM genes occurs in specific subsets of epithelial cell states. Examining BM in archival microinvasive breast cancers and an in vitro model of invasion, we found that passive loss of BM gene expression due to cell state proportion alterations is associated with loss of the structural integrity of the duct leading to an invasive phenotype. Our analyses provide detailed insight into DCIS biology. SIGNIFICANCESingle cell analysis reveals that preinvasive breast cancer is comprised of multiple genetic clones and there is substantial phenotypic diversity both within and between these clones. Ductal carcinoma in situ (DCIS) of the breast is a non-invasive condition commonly identified through mammographic screening. A primary diagnosis of DCIS carries little mortality risk on its own, but its presence is a risk factor for subsequent clonally related invasive breast cancer (IBC) (1-5).

cancer biology↗

bioRxiv2023

Analysis of ductal carcinoma in situ by self-reported race reveals molecular differences related to outcome.

Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated. We examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n=99) and White (n=191) women with DCIS in a large DCIS case-control cohort with longitudinal follow up. Gene expression and pathway analyses indicated that different genes and pathways are involved in ipsilateral breast outcome (DCIS or IBC) after DCIS treatment in White versus Black women. We identified differences in ER and HER2 expression, tumor microenvironment composition, and copy number variations by SRR and outcome groups. Our results suggest that different molecular mechanisms drive subsequent ipsilateral breast events in Black versus White women.

cancer biology↗

bioRxiv2023

Cholangiocytic differentiation drives cell proliferation in hepatoblastoma through Wnt-dependent FGF19 signaling

Cancers evolve not only through the acquisition and clonal transmission of somatic mutations but also by non-genetic mechanisms that modify cell phenotype. Here, we describe how transcriptional heterogeneity arises within human hepatoblastoma, one of the cancers with the lowest mutational burden, characterized by activating mutations in the Wnt pathway. Histology-guided RNA sequencing and evaluation of spatial gene expression in primary hepatoblastomas identified foci of tumor cells within the highly proliferative embryonal histology that express the growth factor FGF19, colocalizing with markedly increased expression of Wnt target genes and cholangiocyte markers. In patient-derived tumoroids, FGF19 provided a required growth signal for FGF19-negative cells, and its expression depended on both Wnt/-catenin and the biliary transcription factor SOX4. Our results reveal that a biliary lineage program induces FGF19 as a paracrine signal for tumor growth, thereby modulating the transcriptional outcome of constitutive Wnt activation and tumor cell proliferation.

cancer biology↗

bioRxiv2023

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity

Cancer represents a broad spectrum of molecularly and morphologically diverse diseases. Individuals with the same clinical diagnosis can have tumors with drastically different molecular profiles and clinical response to treatment. It remains unclear when these differences arise during disease course and why some tumors are addicted to one oncogenic pathway over another. Somatic genomic aberrations occur within the context of an individuals germline genome, which can vary across millions of polymorphic sites. An open question is whether germline differences influence somatic tumor evolution. Interrogating 3,855 breast cancer lesions, spanning pre-invasive to metastatic disease, we demonstrate that germline variants in highly expressed and amplified genes influence somatic evolution by modulating immunoediting at early stages of tumor development. Specifically, we show that the burden of germline-derived epitopes in recurrently amplified genes selects against somatic gene amplification in breast cancer. For example, individuals with a high burden of germline-derived epitopes in ERBB2, encoding human epidermal growth factor receptor 2 (HER2), are significantly less likely to develop HER2-positive breast cancer compared to other subtypes. The same holds true for recurrent amplicons that define four subgroups of ER-positive breast cancers at high risk of distant relapse. High epitope burden in these recurrently amplified regions is associated with decreased likelihood of developing high risk ER-positive cancer. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show the germline genome plays a previously unappreciated role in dictating somatic evolution. Exploiting germline-mediated immunoediting may inform the development of biomarkers that refine risk stratification within breast cancer subtypes.

cancer biology↗

bioRxiv2023

Cost-effective DNA methylation profiling by FML-seq

Current methods for profiling DNA methylation require costly reagents, sequencing, or labor time. We introduce FML-seq, a sequencing library protocol that greatly reduces all these costs. Relative to other techniques tested on the same human cell lines, FML-seq produces similar measurements of absolute and differential cytosine methylation at a fraction of the price. FML-seq enables inexpensive, high-throughput experimental designs for large-scale epigenetics research projects.

genomics↗

bioRxiv2022

Synthetic whole-slide image tile generation with gene expression profiles infused deep generative models

The acquisition of multi-modal biological data for the same sample, such as RNA sequencing and whole slide imaging (WSI), has increased in recent years, enabling studying human biology from multiple angles. However, despite these emerging multi-modal efforts, for the majority of studies only one modality is typically available, mostly due to financial or logistical constraints. Given these difficulties, multi-modal data imputation and multi-modal synthetic data generation are appealing as a solution for the multi-modal data scarcity problem. Currently, most studies focus on generating a single modality (e.g. WSI), without leveraging the information provided by additional data modalities (e.g. gene expression profiles). In this work, we propose an approach to generate WSI tiles by using deep generative models infused with matched gene expression profiles. First, we train a variational autoencoder (VAE) that learns a latent, lower dimensional representation of multi-tissue gene expression profiles. Then, we use this representation to infuse generative adversarial networks (GAN) that generate lung and brain cortex tissue tiles, resulting in a new model that we call RNA-GAN. Tiles generated by RNA-GAN were preferred by expert pathologists in comparison to tiles generated using traditional GANs and in addition, RNA-GAN needs fewer training epochs to generate high-quality tiles. Finally, RNA-GAN was able to generalize to gene expression profiles outside of the training set, showing imputation capabilities. A web-based quiz is available for users to play a game distinguishing real and synthetic tiles: https://rna-gan.stanford.edu/ and the code for RNA-GAN is available here: https://github.com/gevaertlab/RNA-GAN.

bioinformatics↗

bioRxiv2022

A spatial map of human macrophage niches links tissue location with function

Macrophages are the most abundant immune cell type in the tumor microenvironment (TME). Yet the spatial distribution and cell interactions that shape macrophage function are incompletely understood. Here we use single-cell RNA sequencing data and multiplex imaging to discriminate and spatially resolve macrophage niches within benign and malignant breast and colon tissue. We discover four distinct tissue-resident macrophage (TRM) layers within benign bowel, two TRM niches within benign breast, and three tumor-associated macrophage (TAM) populations within breast and colon cancer. We demonstrate that IL4I1 marks phagocytosing macrophages, SPP1 TAMs are enriched in hypoxic and necrotic tumor regions, and a novel subset of FOLR2 TRMs localizes within the plasma cell niche. Furthermore, NLRP3 TAMs that colocalize with neutrophils activate an inflammasome in the TME and in Crohns disease and are associated with poor outcomes in breast cancer patients. This work suggests novel macrophage therapy targets and provides a framework to study human macrophage function in clinical samples.

cancer biology↗

bioRxiv2022

Collective invasion of the basement membrane in breast cancer driven by forces from cell volume expansion and local contractility

Breast cancer becomes invasive when carcinoma cells collectively invade through the basement membrane (BM), a nanoporous layer of matrix that physically separates the primary tumor from the stroma, in a first step towards metastasis. Single cells can invade through nanoporous three-dimensional (3D) matrices via protease-mediated degradation or, when the matrix exhibits sufficient mechanical plasticity, force-mediated widening of pores. However, how cells invade collectively through physiological BM layers in cancer remains unclear. Here, we developed a 3D in vitro model of collective invasion of the BM during breast cancer. We show that cells utilize both proteases and forces to breach the BM. Forces are generated from a combination of global cell volume expansion that stretch the BM with local contractile forces that act in the plane of the BM to breach it, allowing invasion. These results uncover a mechanism by which cells collectively interact to overcome a critical barrier to metastasis.

cancer biology↗

bioRxiv2022

Interactions in CSF1-driven Tenosynovial Giant Cell Tumors

The majority of cells in Tenosynovial Giant Cell Tumor (TGCT) are macrophages responding to CSF1 that is overproduced by a small number of neoplastic cells with a chromosomal translocation involving the CSF1 gene. Treatment with inhibitors of the CSF1 pathway has been clinically effective. An autocrine loop was postulated where the neoplastic cells are stimulated through the CSF1 receptor (CSF1R) expressed on their surface. Here we show that the neoplastic cells themselves do not express CSF1R and therefore may be unaffected by current therapies. We identified a new marker for synoviocytes, GFPT2, that highlights the tumor cells in TCGT and is associated with activation of the YAP1/TAZ pathway. The neoplastic cells in TGCT are highly similar non-neoplastic synoviocytes. Finally, we provide molecular support for the osteoclast-like features of the giant cells in TGCT that correlate with the destructive effects of TGCT on bone.

cancer biology↗

bioRxiv2021

Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma

Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand how the tumor microenvironment (TME) changes with transition to IBC, we used Multiplexed Ion Beam Imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to analyze 140 clinically annotated surgical resections covering the full spectrum of breast cancer progression. We compared normal, DCIS, and IBC tissues using machine learning tools for multiplexed cell segmentation, pixel-based clustering, and object morphometrics. Transition from DCIS to IBC was found to occur along a trajectory marked by coordinated shifts in location and function of myoepithelium, fibroblasts, and infiltrating immune cells in the surrounding stroma. Taken together, this comprehensive study within the HTAN Breast PreCancer Atlas offers insight into the etiologies of DCIS, its transition to IBC, and emphasizes the importance of the TME stroma in promoting these processes.

cancer biology↗

bioRxiv2019

Unmasking the tissue microecology of ductal carcinoma in situ with deep learning

Despite increasing evidence supporting the clinical relevance of tumour infiltrating lymphocytes (TILs) in invasive breast cancer, TIL spatial distribution pattern surrounding ductal carcinoma in situ (DCIS) and its association with progression is not well understood. To characterize the tissue microecology of DCIS, we designed and tested a new deep learning pipeline, UNMaSk (UNet-IM-Net-SCCNN), for the automated detection and simultaneous segmentation of DCIS ducts. This new method achieved the highest sensitivity and recall over cutting-edge deep learning networks in three patient cohorts, as well as the highest concordance with DCIS identification based on CK5 staining. Following automated DCIS detection, spatial tessellation centred at each DCIS duct created the boundary in which local ecology can be studied. Single cell identification and classification was performed with an existing deep learning method to map the distribution of TILs. In a dataset comprising grade 2-3 pure DCIS and DCIS adjacent to invasive cancer (adjacent DCIS), we found that pure DCIS cases had more TILs compared to adjacent DCIS. However, TILs co-localise significantly less with DCIS ducts in pure DCIS compared with adjacent DCIS, suggesting a more inflamed tissue ecology local to adjacent DCIS cases. Our experiments demonstrate that technological developments in deep convolutional neural networks and digital pathology can enable us to automate the identification of DCIS as well as to quantify the spatial relationship with TILs, providing a new way to study immune response and identify new markers of progression, thereby improving clinical management.

pathology↗

bioRxiv2018

YAP-independent mechanotransduction drives breast cancer progression

Increased tissue stiffness is a driver of breast cancer progression. The transcriptional regulator YAP is considered a universal mechanotransducer, based largely on 2D culture studies. However, the role of YAP during in vivo breast cancer remains unclear. Here, we find that mechanotransduction occurs independently of YAP in breast cancer patient samples and mechanically tunable 3D cultures. Mechanistically, the lack of YAP activity in 3D culture and in vivo is associated with the absence of stress fibers and an order of magnitude decrease in nuclear cross-sectional area relative to 2D culture. This work highlights the context-dependent role of YAP in mechanotransduction, and establishes that YAP does not mediate mechanotransduction in breast cancer.\n\nOne Sentence SummaryBreast cancer mechanotransduction occurs independently of YAP, due to compact nuclear morphologies in vivo.

cancer biology↗