Biology subjects

Howitt, B. E.

Publications and source records attributed to Howitt, B. E..

7 recordsLinked to original sources

bioRxiv2026

SDHB deficiency silences ABCB1 expression and confers therapeutic vulnerability across multiple cancer types

Succinate dehydrogenase B (SDHB)-deficient cancers, including pheochromocytoma and paraganglioma (PPGL), renal cell carcinoma (RCC), and gastrointestinal stromal tumor (GIST), exhibit aggressive clinical behavior with limited treatment options. To identify novel therapeutic vulnerabilities, we performed high-throughput drug screening using co-cultured human SDHB-deficient and SDHB-reconstituted UOK269 human renal cell carcinoma cells with dual fluorescence labeling. Several compounds displaying preferential cytotoxicity toward SDHB-deficient cells were known substrates of the ATP-binding cassette B1 (ABCB1) transporter, also known as Multidrug Resistance Protein 1 (MDR1). Accordingly, SDHB-deficient cells demonstrated markedly reduced ABCB1 expression, a phenotype confirmed across human SDHB-deficient PPGL, RCC, and GIST samples, but absent in IDH- or FH-deficient tumors. Mechanistic investigation revealed that KDM4A histone demethylase is downregulated in SDHB-deficient tumors, and KDM4A loss (or inhibition) is sufficient to reduce ABCB1 expression, globally increase H3K9me3 levels, and sensitize cells to cytotoxic ABCB1 substrates. TCGA analysis confirmed correlated KDM4A-ABCB1 expression in SDHB-deficient cancers, with ABCB1 levels predicting drug sensitivity across cancer cell lines. Clinical analysis demonstrated that SDHB-mutant PPGL patients treated with vincristine-containing chemotherapy exhibited significantly longer progression-free survival compared to non-SDHB patients. These findings establish a novel metabolic-epigenetic pathway linking SDHB deficiency to ABCB1 silencing and provide rational basis for repurposing vincristine, and related ABCB1 substrate vinca alkaloids, across SDHB-deficient cancer types; offering an alternative precision treatment approach for these challenging malignancies.

cancer biology↗

bioRxiv2026

Mouse lymph node colonization models predict human tumor metastasis in melanoma

Aggressive tumor progression and distant metastases of cancers such as cutaneous melanoma are thought to be preceded by regional lymph node (LN) infiltration. Previous mouse studies have selectively enriched for tumor cells with enhanced LN migratory capacity but the mechanistic biology underpinning this proclivity has not been directly linked to human outcomes. Likewise, the exact role LN colonization plays in distant metastasis in humans remains unclear. To translate and conserve findings from mouse models to humans, we used a computational framework termed Translatable Components Regression (TransComp-R) to integrate mouse LN tumor samples with human primary and metastatic tumors. We identified transcriptional programs of early- and late-stage mouse tumor generations that stratified primary and metastatic tumors from patients with melanoma. These transcriptional programs associated with immune function, cell cycle checkpoints, and DNA-to-protein biosynthesis pathways. We then employed EcoTyper and identified six distinct melanoma-specific cellular communities (ecotypes) comprising co-occurring cell states. Of these six melanoma ecotypes, we identified a community strongly associated with primary tumor cells, while the other five represented a spectrum of metastatic tumor microenvironments with increased adverse outcomes. These ecotypes and their significantly expressed genes may contribute to the tumor-immune microenvironment that facilitates LN colonization in melanoma. We further validated the physical co-localization of these melanoma ecotypes using spatial transcriptomics. Our integration of pre-clinical models with human data reveals potential biological pathways and transcriptomic signatures for future investigation and supports the utility of mouse models in studying cancer metastasis.

systems biology↗

bioRxiv2026

Scalable genotyping in fixed transcriptomes resolves clonal heterogeneity via single-cell sequencing

Despite the promise of single-cell transcriptomics for understanding cell states in heterogeneous populations, widely used platforms have limited ability to link transcriptional states to somatic mutations within the same cells. Here, we introduce Genotyping in Fixed Transcriptomes (GIFT) for the simultaneous detection of large numbers of targeted genetic variants with whole transcriptome profiles in single cells. The core innovation of GIFT is a rationally designed gapfilling reaction between adjacent single-stranded DNA (ssDNA) probes that barcodes native transcript sequence to enable highly-specific targeted mutation detection. GIFT achieves greater than 99% genotyping accuracy and flexible capture of hundreds of mutations per cell, including in formalin-fixed, paraffin-embedded (FFPE) tissue, enabling clonal lineage tracing in heterogeneous settings. We demonstrate the unique scalability of GIFT by profiling more than 700,000 cells from 35 donors with myeloproliferative neoplasms (MPN), revealing mutation-dependent hematopoietic responses to systemic inflammation associated with the characteristic JAK2V617 mutation, including an allelic dose gradient of interferon-associated transcriptional programs and priming of hematopoietic stem cells that develop into divergent disease states. The technical advantages of GIFT enable direct resolution of genotype-to-phenotype relationships via clonal tracing with comprehensive cell-state measurements at single-cell resolution.

genomics↗

bioRxiv2026

scAmp analyzes focal gene amplifications at single-cell resolution

Oncogene amplification on extrachromosomal DNA (ecDNA) is a common driver of tumor progression and is associated with acquired drug resistance and poor patient survival. While whole genome sequencing (WGS) studies have revealed the landscape of genes amplified on ecDNA in tumors, it remains challenging to study the subclonal heterogeneity and functional (e.g., transcriptomic) consequences of ecDNA on tumors. To address this, we introduce scAmp: a probabilistic algorithm for detecting and analyzing ecDNA from single-cell datasets. We demonstrate scAmps improved accuracy over WGS approaches on well-characterized cell-lines and its applicability to clinical histopathology. We further showcase scAmp by analyzing 73 patient tumors profiled with single-cell ATAC-seq, where we analyze the subclonal evolution of ecDNA+ subclones and identify the effect of ecDNA amplifications on the chromatin accessibility landscape of cancer cells. Together, we anticipate that scAmp will broadly enable further studies - both retrospective and prospective - that dissect critical questions of how ecDNA affect cancer cells and the tumors in which they reside.

cancer biology↗

bioRxiv2025

Clonal lineage tracing of innate immune cells in human cancer

Innate immune cells constitute the majority of the tumor microenvironment (TME), where they mediate both natural anti-tumor immunity and immunotherapy responses. While single-cell T- and B-cell receptor sequencing has provided fundamental insights into the clonal dynamics of human adaptive immunity, the lack of appropriate tools has precluded similar analysis of innate immune cells. Here, we describe a method that leverages somatic mitochondrial DNA (mtDNA) mutations to reconstruct clonal lineage relationships between single cells across cell types in native human tissues. We jointly sequenced single-cell transposase-accessible chromatin and mtDNA to profile n=124,958 cells from matched tumor, non-involved lung tissue (NILT), and peripheral blood of early-stage non-small cell lung cancer (NSCLC) patients, as well as n=93,757 cells from matched tumor and peripheral blood of ovarian cancer patients. Single-cell concomitant profiling of lineage and cell states of thousands of immune cells resolved clonality across cell types, tissue sites, and malignancies. Clonal tracing of innate immune cells demonstrates that TME-resident myeloid subsets, including macrophages and type 3 dendritic cells (DC3), are clonally linked to both circulating and tissue-infiltrating monocytes. Further, we identify distinct DC-biased and macrophage-biased myeloid clones, enriched in the tumor and NILT, respectively, and find that their circulating monocyte precursors exhibit distinct epigenetic profiles, suggesting that myeloid differentiation fate may be predetermined before TME infiltration. These results delineate the clonal pathways of intratumoral myeloid cell recruitment and differentiation in human cancer and suggest that remodeling of the tumor myeloid compartment may be peripherally programmed.

genomics↗

bioRxiv2024

Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients.

Over the last decade, Hippo signaling has emerged as a major tumor-suppressing pathway. Its dysregulation is associated with abnormal expression of YAP1 and TEAD-family genes. Recent works have highlighted the role of YAP1/TEAD activity in several cancers and its potential therapeutic implications. Therefore, identifying patients with a dysregulated Hippo pathway is key to enhancing treatment impact. Although recent studies have derived RNAseq-based signatures, there remains a need for a reproducible and cost-effective method to measure the pathway activation. In recent years, deep learning applied to histology slides have emerged as an effective way to predict molecular information from a data modality available in clinical routine. Here, we trained models to predict YAP1/TEAD activity from H&E-stained histology slides in multiple cancers. The robustness of our approach was assessed in seven independent validation cohorts. Finally, we showed that histological markers of disease aggressiveness were associated with dysfunctional Hippo signaling.

bioinformatics↗

bioRxiv2023

Mapping ovarian cancer spatial organization uncovers immune evasion drivers at the genetic, cellular, and tissue level

Immune exclusion and evasion are central barriers to the success of immunotherapies and cell therapies in solid tumors. Here we applied single cell spatial and perturbational transcriptomics alongside clinical, histological, and genomic profiling to elucidate immune exclusion and evasion in high-grade serous tubo-ovarian cancer (HGSC). Using high-plex spatial transcriptomics we profiled more than 1.3 million cells from 95 tumors and 60 patients, revealing generalizable principles in HGSC tumor tissue organization. Our data demonstrates that effector T cells resist stroma-mediated trapping and sequestration. However, upon infiltration into the tumor, T cells, as well as Natural Killer (NK) cells, preferentially co-localize only with a subset of malignant cells that manifest a distinct transcriptional cell state. The latter consists of dozens of co-regulated genes and is repressed under various copy number alterations. Performing CRISPR Perturb-seq screens in ovarian cancer cells, we identified functionally diverse genetic perturbations - including knockout of the insulin sensing repressor PTPN1 and the epigenetic regulator ACTR8 - that de-repress the proposed immunogenic malignant cell state identified in patients and indeed sensitize ovarian cancer cells to T cell and NK cell cytotoxicity. Taken together, our study uncovered a profound connection between somatic genetic aberrations, malignant cell transcriptional dysregulation, and immune evasion at the cellular and tissue level, allowing us to identify targets that reprogram malignant cell states as an avenue to unleash anti-tumor immune responses.

cancer biology↗