Biology subjects

Akutagawa, J.

Publications and source records attributed to Akutagawa, J..

4 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↗

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↗

bioRxiv2022

Identification of cancer drivers from tumor-only RNA-seq with RNA-VACAY

Detecting somatic mutations is a cornerstone of cancer genomics and clinical genotyping; however, there has been little systematic evaluation of the utility of RNA sequencing (RNA-seq) for somatic variant detection and driver mutation analysis. Variants found in RNA-Seq are also expressed, reducing the identification of passenger mutations and would not suffer from annotation bias observed in whole-exome sequencing (WES). We developed RNA-VACAY, a containerized pipeline that automates somatic variant calling from tumor RNA-seq data, alone, and evaluated its performance on simulated data and 1,349 RNA-seq samples with matched whole-genome sequencing (WGS). RNA-VACAY was able to detect at least 1 putative driver gene in 15 out of 16 cancer types and identified known driver mutations in 5 and 3 UTRs. The computational cost and time to generate and analyze RNA-seq data is lower than WGS or WES, which decreases the resources necessary for somatic variant detection. This study demonstrates the utility of RNA-seq to detect cancer drivers.

genomics↗