Biology subjects

Han, A. L.

Publications and source records attributed to Han, A. L..

5 recordsLinked to original sources

bioRxiv2026

Genome-scale perturbation signatures from primary human CD4+ T cells improve genetics-based prioritization of immune drug targets

While human genetic evidence improves drug program success, target selection largely relies on associational features. Even functional features are mainly observational, capturing disease associations rather than the consequence of perturbing genes in the disease-relevant human cell type. To move beyond association, we present IGNITE (Immune Genomics and fuNctional Integration for Target Enrichment), a framework that prioritizes immune drug targets by integrating human genetic priors with features from genome-scale perturb-seq in 22 million primary human CD4+ T cells and polarized T-helper subset differential expression. IGNITE is a semi-supervised machine learning model that applies positive-unlabeled learning to approved immune targets, then ranks 19,502 protein-coding genes to prioritize new candidates. In 727 in-trial genes held out from training, functional genomics increased target enrichment among the top 50 nominations from 2.7- to 4.8-fold for immune trial targets at any phase, and from 4.5- to 5.9-fold for targets in Phase III. These performance gains were immune-specific, as IGNITE outperformed genetic comparators on predicting immune-exclusive targets but not on cardiac-exclusive targets. Using temporal validation with labels frozen in 2014, IGNITE outperformed the genetics-only model in ranking 134 genes that subsequently entered immune trials. The functional genomics layer also surfaced two novel, pharmacologically tractable candidates, ELOVL6 and RUVBL1, elevating their rankings from outside the top 1,000 into the top 50. These findings highlight that perturbational signatures in the disease-relevant human cell type harbor target-relevant signals beyond human genetics, offering a generalizable route to indication-specific prioritization as perturbation atlases expand. Full IGNITE scores are publicly available at https://ignite.eecs.umich.edu/

bioinformatics↗

bioRxiv2024

Metabolic Switch in Endocrine Resistant Estrogen Receptor Positive Breast Cancer

PurposeThe development of endocrine resistance remains a significant challenge in the clinical management of estrogen receptor-positive (ER+) breast cancer. Metabolic reprogramming is a prominent component of endocrine resistance and a potential therapeutic intervention point. However, a limited understanding of which metabolic changes are conserved across the heterogeneous landscape of ER+ breast cancer or how metabolic changes factor into ER DNA binding patterns hinder our ability to target metabolic adaptation as a treatment strategy. This study uses dimethyl fumarate (DMF) to restore tamoxifen (Tam) and fulvestrant (Fulv) sensitivity in endocrine-resistant cell lines and investigates how metabolic changes influence ER DNA-binding patterns. Experimental DesignTo address the challenge of metabolic adaptation in anti-endocrine resistance, we generated Tam and Fulv resistance in six ER+ breast cancer (BC) cell lines, representing ductal (MCF7, T47D, ZR75-1, and UCD12), lobular (MDA-MB-134--VI), and HER2 amplified (BT474) BC molecular phenotypes. Metabolomic profiling, RNA sequencing, proteomics, and CUT&RUN assays were completed to characterize metabolic shifts, transcriptional and protein changes, and ER DNA-binding patterns in resistant cells. Dimethyl fumarate was assessed for its ability to reverse Tam and Fulv resistance, restore tricarboxylic acid cycle (TCA) cycle function, and restore parental cell (endocrine sensitive) ER DNA binding patterns. ResultsTamoxifen-resistant (TamR) and fulvestrant-resistant (FulvR) cells exhibited disrupted TCA cycle activity, reduced glutathione levels, and altered nucleotide and amino acid metabolism. DMF treatment replenished TCA cycle intermediates and reversed resistance in both TamR and FulvR cells. DMF also increased mevalonate pathway enzyme expression in both TamR and FulvR cells, with TamR cells upregulating enzymes in the cholesterol synthesis phase and FulvR enhancing enzymes in the early part of the pathway. DMF restored ER DNA-binding patterns in TamR cells to resemble parental cells, re-sensitizing them to Tam. In FulvR cells, DMF reversed resistance by modulating ER-cofactor interactions but did not restore parental ER DNA-binding signatures. ConclusionsOur findings provide new insights into how metabolic reprogramming affects ER DNA-binding activity in endocrine-resistant breast cancer. We demonstrate how altering metabolism can reprogram ER signaling and influence resistance mechanisms by targeting metabolic vulnerabilities, such as TCA cycle disruptions. Additionally, our data provide a comprehensive metabolomic, RNA-seq, and CUT&RUN data set relevant to tumor metabolic adaptation leading to acquired endocrine resistance in highly utilized ER+ breast cancer cell lines. This study improves our understanding of how metabolic states alter ER function in endocrine-resistant breast cancer.

cancer biology↗

bioRxiv2024

The big tau splice isoform resists Alzheimer's-related pathological changes

In Alzheimers disease (AD), the microtubule-binding protein tau becomes abnormally hyperphosphorylated and aggregated in selective brain regions such as the cortex and hippocampus1-3. However, other brain regions like the cerebellum and brain stem remain largely intact despite the universal expression of tau throughout the brain. Here, we found that an understudied splice isoform of tau termed "big tau" is significantly more abundant in the brain regions less vulnerable to tau pathology compared to tau pathology-vulnerable regions. We used various cellular and animal models to demonstrate that big tau possesses multiple properties that can resist AD-related pathological changes. Importantly, human AD patients show a higher expression level of pathology-resisting big tau in the cerebellum, the brain region spared from tau pathology. Our study examines the unique properties of big tau, expanding our current understanding of tau pathophysiology. Altogether, our data suggest that alternative splicing to favor big tau is a viable strategy to modulate tau pathology.

neuroscience↗

bioRxiv2022

Estradiol (E2) concentration shapes the chromatin binding landscape of the estrogen receptor

How transcription factors (TF) selectively occupy a minute subset of their binding sites from a sizeable pool of putative sites in large mammalian genomes remains an important unanswered question. In part, nucleosomes help by creating formidable barriers to TF binding. TF concentration itself plays a crucial role in the competition between TFs and nucleosomes. In the case of nuclear receptors, the ligand adds another layer of complexity. Estrogen receptor alpha (ER) is a classic example where its main ligand estradiol (E2) can modulate ER binding on chromatin. Here we show a complete rewiring of ER binding as a function of E2 concentration. As E2 concentration increases by two orders of magnitude, ER levels decrease, and ER binding localizes to promoter-distal sites with strong ER motifs. At low E2 levels, abundant levels of ER are present in the nucleus, and ER binding occurs mostly at sites without an identifiable ER binding motif, potentially in cooperation with other TFs like STAT1. We propose that E2s effect on ER activity plays a major role in defining genome-wide ER binding profiles. Thus, variations in E2 concentrations in ER-positive breast tumors could be a significant factor driving heterogeneity in tumor phenotype, treatment response, and potentially drug resistance.

molecular biology↗

bioRxiv2021

Mapping Transcription Factor-Nucleosome Dynamics from Plasma cfDNA

Cell-free DNA (cfDNA) contains a composite map of the epigenomes of its cells-of-origin. Tissue-specific transcription factor (TF) binding inferred from cfDNA could enable us to track disease states in humans in a minimally invasive manner. Here, by enriching for short cfDNA fragments, we directly map TF footprints at single binding sites from plasma. We show that the enrichment of TF footprints in plasma reflects the binding strength of the TF in cfDNA tissue-of-origin. Based on this principle, we were able to identify the subset of genome-wide binding sites for selected TFs that leave TF-specific footprints in plasma. These footprints enabled us to not only identify the tissue-of-origin of cfDNA but also map the chromatin structure around the factor-bound sites in their cells-of-origin. To ask if we can use these plasma TF footprints to map cancer states, we first defined pure tumor TF signatures in plasma in vivo using estrogen receptor-positive (ER+) breast cancer xenografts. We found that the tumor-specific cfDNA protections of ER- could distinguish WT, ER-amplified, and ER-mutated xenografts. Further, tumor-specific cfDNA protections of ER- and FOXA1 reflect TF-specific accessibility across human breast tumors, demonstrating our ability to capture tumor TF binding in plasma. We then scored TF binding in human plasma samples and identified specific binding sites whose plasma TF protections can identify the presence of cancer and specifically breast cancer. Thus, plasma TF footprints enable minimally invasive mapping of the regulatory landscape of cancer in humans.

genomics↗