Biology subjects

Tanguay, S.

Publications and source records attributed to Tanguay, S..

3 recordsLinked to original sources

bioRxiv2026

Lysyl oxidase drives ccRCC progression by coordinating HIF-2α transcription program with tumor microenvironment

Clear cell renal cell carcinoma (ccRCC) is driven by persistent HIF-2 transcription program initiated by VHL loss, yet molecular mediators sustaining this program are poorly defined. Using single-cell transcriptomics, we identified lysyl oxidase (LOX) as a driver of ccRCC progression, selectively enriched in a hypoxia/epithelial-mesenchymal transition (EMT) gene program associated with poor outcome. While LOX oxidizes and stabilizes HIF-2 by antagonizing HUWE1-mediated ubiquitination and degradation, thereby sustaining HIF-2-driven transcription in cancer cells, it also remodels extracellular matrix (ECM) and promotes angiogenesis in the tumor microenvironment (TME). Genetic or pharmacological inhibition of LOX destabilizes HIF-2, disrupts ECM, inhibits angiogenesis, and suppresses tumor initiation, growth, and metastasis in vivo. LOX inhibition enhances anti-angiogenic therapy response and remains effective in belzutifan-resistant HIF-2 G323E-mutant tumors. Nuclear LOX protein correlates with nuclear HIF-2 in high-grade patient tumors. Together, LOX coordinates HIF-2 transcription program with TME and is a therapeutic target in ccRCC.

cancer biology↗

bioRxiv2026

Semantic fragment representations for coordinate-free analysis of genomics data

Many genomic assays begin with individual DNA fragments, but standard analysis quickly collapses those molecules into counts over genomic intervals. Rich information carried by each fragment, including its sequence, fragment body, cleavage boundaries, and local flanking context, is lost in this process. This loss is especially apparent in mixed-source and heterogeneous samples, where individual fragments originate from disparate cell types and can retain information about their cell of origin. To address this, we present LEAF-1, a fragment-level foundation model pre-trained on approximately 58 billion fragments spanning bulk ATAC-seq, single-cell ATAC-seq, and cell-free DNA profiles, representing each DNA molecule as a point in a learned semantic space defined by sequence context, assay modality, and explicit cleavage-boundary tokens. In sparse scATAC-seq datasets, mean-pooled LEAF-1 embeddings readily classify human cell types from as few as [~]1,000 fragments per cell, with high-scoring fragments linked to cell-type-associated transcription-factor programs. Similarly, in cell-free DNA profiling, LEAF-1 outperformed state-of-the-art coordinate-binning strategies and general-purpose DNA language model baselines across cancer detection tasks. Applying attention-based multiple-instance learning to LEAF-1 embeddings further improved cancer detection, reaching an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95. This pan-cancer model generalizes beyond cancer types it is trained on, as we show by profiling plasma samples from clear cell renal cell carcinoma patients and healthy volunteers and applying the frozen classifier without retraining, achieving an AUC of 0.83. These results show that semantic learning over individual DNA fragments preserves biochemical, cell-associated, and disease-associated signals that are otherwise lost during coordinate-based aggregation.

genomics↗

bioRxiv2023

Metagenomics for pathogen detection during a wildlife mortality event in songbirds

Mass mortality events in wildlife can be indications of an emerging infectious disease. During the spring and summer of 2021, hundreds of dead passerines were reported across the eastern US. Birds exhibited a range of clinical signs including swollen conjunctiva, ocular discharge, ataxia, and nystagmus. As part of the diagnostic investigation, high-throughput metagenomic next-generation sequencing was performed across three molecular laboratories on samples from affected birds. Many potentially pathogenic microbes were detected, with bacteria comprising the largest proportion; however, no singular agent was consistently identified, with many of the detected microbes also found in unaffected (control) birds, and thus considered to be subclinical infections. Congruent results across laboratories have helped drive further investigation into alternative causes including environmental contaminants and nutritional deficiencies. This work highlights the utility of metagenomic approaches in investigations of emerging diseases and provides a framework for future wildlife mortality events. Article Summary LineThe causative agent of a mass mortality event in passerines remains inconclusive after metagenomic high-throughput sequencing with results prompting further investigation into non-pathogenic causes.

genomics↗