Biology subjects

Huang, F. W.

Publications and source records attributed to Huang, F. W..

12 recordsLinked to original sources

bioRxiv2026

Identification of TM4SF1 as a novel tumor-associated antigen in biliary tract cancers targetable by CAR-T cell therapy

Background & Aims: Biliary tract cancers (BTCs) are a rare set of genetically heterogenous and aggressive malignancies associated with delayed presentation and poor prognosis. Thus, there is an unmet clinical need for the development of novel therapeutic strategies. Identification of uniquely expressed cell-surface, tumor-associated antigens (TAAs) holds promise in epithelial tumors more generally, as they can serve as ligands for a variety of therapeutics, including CAR-T cell therapy. However, TAA identification in BTCs has been limited by expression in normal liver tissue. Here, we aim to characterize the cell-surface protein transmembrane 4 L six family member 1 (TM4SF1) as a potential BTC TAA targetable by CAR-T therapy. Methods: TM4SF1 expression in BTC relative to normal hepatic/biliary tissue was characterized at the mRNA level by analyzing TCGA datasets and at the protein level by immunohistochemistry of archival primary BTC tissue. Anti-TM4SF1 CAR-T cells were evaluated through in vitro coculture assays against human-derived BTC cell lines and in a cell line-derived xenograft (CDX) model. Results: We find TM4SF1 is significantly upregulated in BTC relative to normal hepatic/biliary tissue and across BTC anatomical subtypes at the mRNA and protein level. To validate TM4SF1 as a targetable TAA in BTC, we show anti-TM4SF1 CAR-T cells demonstrate robust growth inhibition of BTC cell lines in vitro and significant anti-tumor activity against a CDX in vivo. Conclusions: Together, our data provides support for TM4SF1 as a promising TAA in BTCs that can be used for the rational development of targeted therapeutic modalities, including CAR-T cells, in a patient population with significant unmet need.

cancer biology↗

bioRxiv2026

A single-cell and spatial atlas of prostate cancer reveals the combinatorial nature of gene modules underlying lineage plasticity and metastasis

Prostate cancer encompasses a spectrum of disease states driven by complex cellular heterogeneity. To delineate the transcriptional programs underlying lineage plasticity and metastasis, we constructed a comprehensive single-cell atlas of 128 patients, spanning localized, castration-resistant, and metastatic disease. Lineage plasticity was prevalent in localized disease, with subsets of tumor cells adopting distinct basal-like and club-like states. Luminal-like cancer cells also displayed extensive lineage infidelity, defined not by a binary loss of identity but by the combinatorial erosion of luminal gene modules associated with higher grade and stage. In the metastatic setting, gene program association analysis (GPAS) identified a broad induction of cell-cycle gene modules across organ sites as well as an induction of organ-specific gene modules, including osteomimetic signaling in bone, neuro-migratory genes in brain, and erythroid-like transitions in liver. Neuroendocrine prostate cancers (NEPCs) were not monolithic but defined by combinations of NE-associated gene modules including a novel HES6 program. Notably, these modules were detected at intermediate levels in localized samples, suggesting molecular plasticity precedes histological transformation. We also developed a refined NE signature that could distinguish NEPC tumors more accurately than previously published signatures. Within the tumor microenvironment (TME), we observed an elevation of pro-inflammatory Th17 T-cells in African American patients and identified a rare Schwann cell population. Finally, we present PCformer, a transformer-based foundation model trained on >500,000 cells to automate cell-state classification. Together, this comprehensive atlas demonstrates the complex nature of gene modules underlying lineage infidelity and plasticity in cancer cells and highlights distinct immune and stromal populations within the tumor ecosystem.

genomics↗

bioRxiv2024

Histologic variants in bladder cancer harbor aggressive molecular features including TM4SF1 expression and a CA125+ cell state

Histologic variant (HV) subtypes of bladder cancer are clinically aggressive tumors that are more resistant to standard therapy compared to conventional urothelial carcinoma (UC). Little is known about the transcriptional programs that account for the morphological and biological differences in HV tumors. To investigate the tumor biology of HV bladder cancers, we generated a single cell RNA sequencing (scRNA- seq) atlas of nine HV tumors and three UC tumors. Our analyses revealed a tumor cell state specific to HVs that is characterized by expression of MUC16 (CA125), KRT24, and WISP2. This CA125+ cell state bears transcriptional hallmarks of epithelial-mesenchymal transition, is enriched in metastases, is predicted to be highly chemotherapy resistant, and is linked with poor survival, suggesting that this cell state plays an important role in the aggressive biology of HV tumors. Our analyses also provide novel evidence of transcriptional "mimicry" between HVs and histologically similar non-urothelial cell types. Lastly, we identified higher expression of TM4SF1, a cell surface protein associated with cancer metastasis, in HV tumor cells compared to UC tumor cells. Finally, CAR T cells engineered against TM4SF1 protein demonstrated in vitro and in vivo activity against bladder cancer cell lines in a TM4SF1 expression- dependent manner, highlighting its potential as a therapeutic target in bladder cancer. One sentence summarySingle cell RNA sequencing of primary bladder cancers identified a CA125+ cell state specific to histologic variants that is associated with aggressive biological features and TM4SF1 as a novel therapeutic target for histologic variant subtypes of bladder cancer which can be targeted by anti- TM4SF1 CAR T cells.

cancer biology↗

bioRxiv2023

RPL22 is a tumor suppressor in MSI-high cancers and a key splicing regulator of MDM4

Microsatellite instability high (MSI-H) tumors are malignant tumors that, despite harboring a high mutational burden, often have intact TP53. One of the most frequent mutations in MSI-H tumors is a frameshift mutation in RPL22, a ribosomal protein. Here, we identified RPL22 as a modulator of MDM4 splicing through an alternative splicing switch in exon 6. RPL22 loss increases MDM4 exon 6 inclusion, cell proliferation, and augments resistance to the MDM inhibitor Nutlin-3a. RPL22 represses expression of its paralog, RPL22L1, by mediating the splicing of a cryptic exon corresponding to a truncated transcript. Therefore, damaging mutations in RPL22 drive oncogenic MDM4 induction and reveal a common splicing circuit in MSI-H tumors that may inform therapeutic targeting of the MDM4-p53 axis and oncogenic RPL22L1 induction.

cancer biology↗

bioRxiv2023

Single cell transcriptional profiling of benign prostatic hyperplasia reveals a progenitor-like luminal epithelial cell state within an inflammatory microenvironment

Benign prostatic hyperplasia (BPH) is characterized by excessive cell proliferation and inflammation and affects most aging men. The development of new therapies for BPH requires a deeper understanding of the underlying pathophysiology and cellular components of BPH. Here, we characterize at single cell resolution the cellular states of BPH and identify cell populations enriched in BPH that contribute to cell proliferation and inflammation. Single-cell RNA-sequencing was performed on prostate tissue from 15 patients undergoing holmium laser enucleation of the prostate for treatment of BPH. Clustering and differential expression analysis on aligned single cell RNA-seq data was performed to annotate all cell types. Pseudotime, gene set enrichment, gene ontology, and ligand-receptor analyses were performed. 16,234 cells were analyzed and specific stromal, epithelial, and immune subgroups were found to be strongly associated with inflammation. A rare luminal subgroup was identified and pseudotime analysis indicated this luminal subgroup was more closely related to club and basal cells. Using a gene set derived from epithelial stem cells, we found that this luminal subgroup had a significantly higher stem cell signature score than all other epithelial subgroups, suggesting this subgroup is a luminal precursor state. Ligand-receptor interactions between stromal, epithelial, and immune cells were explored with CellPhoneDB. Unique interactions highlighting MIF, a pro-inflammatory cytokine that promotes epithelial cell growth and inflammation in the prostate, were found between fibroblasts and the progenitor luminal subgroup. This luminal subgroup also interacted with neutrophils and macrophages through MIF. Our single-cell profiling of BPH provides a roadmap for inflammation-linked cell subgroups and highlights a novel luminal progenitor subgroup interacting with other cell groups via MIF that may contribute to the inflammation and cell proliferation phenotype associated with BPH.

genomics↗

bioRxiv2023

Motifs in SARS-CoV-2 evolution

We present a novel framework enhancing the prediction of whether novel lineage poses the threat of eventually dominating the viral population. The framework is based purely on genomic sequence data, without requiring prior established biological analysis. Its building blocks are sets of co-evolving sites in the alignment (motifs), identified via co-evolutionary signals. The collection of such motifs forms a relational structure over the polymorphic sites. Motifs are constructed using distances quantifying the co-evolutionary coupling of pairs and manifest as co-evolving clusters of sites. We present an approach to genomic surveillance based on this notion of relational structure. Our system will issue an alert regarding a lineage, based on its contribution to drastic changes in the relational structure. We then conduct a comprehensive retrospective analysis of the COVID-19 pandemic based on SARS-CoV-2 genomic sequence data in GISAID from October 2020 to September 2022, across 21 lineages and 27 countries with weekly resolution. We investigate the performance of this surveillance system in terms of its accuracy, timeliness and robustness. Lastly, we study how well each lineage is classified by such a system.

bioinformatics↗

bioRxiv2022

Profile of the somatic mutational landscape in breast tumors from Hispanic/Latina women

Breast cancer causes the most cancer deaths among Hispanic/Latinas (H/L). However, limited tumor-sequencing data from H/L are available to guide treatment. To address this gap, we performed whole-exome sequencing of DNA from 140 HL germline and 146 matched breast tumors and RNA-seq for the tumors. We generated somatic-mutation profiles, identified copy-number alterations (CNAs), and compared results to non-Hispanic White (White) women in The Cancer Genome Atlas. Similar to Whites, PIK3CA and TP53 were the most commonly mutated genes in breast tumors from H/L. We found 4 common COSMIC mutation signatures (1, 2, 3, 13) and signature 16 not previously reported in other breast-cancer datasets. We observed recurrent amplifications in breast-cancer drivers including MYC, FGFR1, CCND1, and ERBB2, and a recurrent amplification on 17q11.2 associated with high KIAA0100 gene expression, implicated in breast-cancer aggressiveness. Expanded research is required to determine how these characteristics of H/L tumors impact treatment response and survival.

cancer biology↗

bioRxiv2022

Buying time: detecting VOCs in SARS-CoV-2 via co-evolutionary signals

We present a novel framework facilitating the rapid detection of variants of interest (VOI) and concern (VOC) in a viral multiple sequence alignment (MSA). The framework is purely based on the genomic sequence data, without requiring prior established biological analysis. The frameworks building blocks are sets of co-evolving sites (motifs), identified via co-evolutionary signals within the MSA. Motifs form a weighted simplicial complex, whose vertices are sites that satisfy a certain nucleotide diversity. Higher dimensional simplices are constructed using distances quantifying the co-evolutionary coupling of pairs and in the context of our method maximal motifs manifest as clusters. The framework triggers an alert via a cluster with a significant fraction of newly emerging polymorphic sites. We apply our method to SARS-CoV-2, analyzing all alerts issued from November 2020 through August 2021 with weekly resolution for England, USA, India and South America. Within a week at most a handful of alerts, each of which involving on the order of 10 sites are triggered. Cross referencing alerts with a posteriori knowledge of VOI/VOC-designations and lineages, motif-induced alerts detect VOIs/VOCs rapidly, typically weeks earlier than current methods. We show how motifs provide insight into the organization of the characteristic mutations of a VOI/VOC, organizing them as co-evolving blocks. Finally we study the dependency of the motif reconstruction on metric and clustering method and provide the receiver operating characteristic (ROC) of our alert criterion.

bioinformatics↗

bioRxiv2022

The CIC-ERF co-deletion underlies fusion independent activation of ETS family member, ETV1, to drive prostate cancer progression

The dysregulation of ETS family transcription factors drives human prostate cancer. The majority of prostate cancer is the result of chromosomal rearrangements that lead to aberrant ETS gene expression. The mechanisms that lead to fusion independent ETS factor upregulation and prostate oncogenesis remain unknown. Here, we show that two neighboring transcription factors, Capicua (CIC) and ETS2 repressor factor (ERF), which are co-deleted in human prostate tumors can drive prostate oncogenesis. Concurrent CIC and ERF loss commonly occurs through focal genomic deletions at chromosome 19q13.2. Mechanistically, CIC and ERF co-bind the proximal regulatory element and mutually repress the ETS transcription factor, ETV1. Targeting ETV1 in CIC and ERF deficient prostate cancer limits tumor growth. Thus, we have uncovered a fusion independent mode of ETS transcriptional activation defined by concurrent loss of CIC and ERF.

cancer biology↗

bioRxiv2021

Single-cell analysis of hepatoblastoma identifies distinct tumor cell signatures that predict susceptibility to chemotherapy using patient-specific tumor spheroids

Pediatric hepatoblastoma (HB) is the most common primary liver cancer in infants and children. Studies of HB that focus exclusively on tumor cells demonstrate sparse somatic mutations and a common cell of origin, the hepatoblast, across patients. In contrast to the homogeneity these studies would suggest, HB tumors have a high degree of heterogeneity that can portend poor prognosis. In this study, we used single-cell genomic techniques to analyze resected human pediatric HB specimens. This study establishes that tumor heterogeneity can be defined by the relative proportions of five distinct subtypes of tumor cells. Notably, patient-derived HB spheroid cultures predict differential responses to treatment based on the transcriptomic signature of each tumor, suggesting a path forward for precision oncology for these tumors. Collectively, these results define HB tumor heterogeneity with single-cell resolution and demonstrate that patient-derived spheroids can be used to evaluate responses to chemotherapy.

cancer biology↗

bioRxiv2020

Single-cell analysis of human primary prostate cancer reveals the heterogeneity of tumor-associated epithelial cell states

Prostate cancer is the second most common malignancy in men worldwide and consists of a mixture of tumor and non-tumor cell types. To characterize the prostate cancer tumor microenvironment, we performed single-cell RNA-sequencing on prostate biopsies, prostatectomy specimens, and patient-derived organoids from localized prostate cancer patients. We identify a population of tumor-associated club cells that may act as progenitor cells and uncover heterogeneous cellular states in prostate epithelial cells marked by high androgen signaling states that are enriched in prostate cancer. ERG- tumor cells, compared to ERG+ cells, demonstrate shared heterogeneity with surrounding luminal epithelial cells and appear to give rise to common tumor microenvironment responses. Finally, we show that prostate epithelial organoids recapitulate tumor-associated epithelial cell states and are enriched with distinct cell types and states from their parent tissues. Our results provide diagnostically relevant insights and advance our understanding of the cellular states associated with prostate carcinogenesis.

cancer biology↗

bioRxiv2020

Expression of ACE2 and TMPRSS2, the SARS2-CoV-2 receptor and co-receptor, in prostate epithelial cells

The COVID-19 pandemic has spread across more than 200 countries and resulted in over 170,000 deaths. For unclear reasons, higher mortality rates from COVID-19 have been reported in men compared to women. While the SARS-CoV-2 receptor ACE2 and serine protease TMPRSS2 have been detected in lung and other tissues, it is not clear what sex differences may exist. We analyzed a publicly-available normal human prostate single-cell RNA sequencing dataset and found TMPRSS2 and ACE2 co-expressing cells in epithelial cells, with a higher proportion in club and hillock cells. Then we investigated datasets of lung epithelial cells and also found club cells co-expressing TMPRSS2 and ACE2. A comparison of ACE2 expression in lung tissue between males and females showed higher expression in males and a larger proportion of ACE2+ cells in male type II pneumocytes, with preliminary evidence that type II pneumocytes of all lung epithelial cell types showed the highest expression of ACE2. These results raise the possibility that sex differences in ACE2 expression and the presence of double-positive cells in the prostate may contribute to the observed disparities of COVID-19.

genomics↗