Biology subjects

Chaisaingmongkol, J.

Publications and source records attributed to Chaisaingmongkol, J..

3 recordsLinked to original sources

bioRxiv2026

Cell type-centric interaction networks define spatial architecture of intrahepatic cholangiocarcinoma

Tumor spatial organization critically shapes disease progression and therapeutic response, yet remains poorly defined. Intrahepatic cholangiocarcinoma (iCCA), a rare and aggressive liver malignancy with extensive stromal and immune remodeling, provides a compelling model to study tumor architecture. We generated a single-cell spatial atlas of 1 million cells from 131 iCCA patients using 53-plex spatial proteomics. To systemically characterize tumor spatial organization, we developed a graph-based deep learning framework to define cell type-centric interaction networks, identifying 41 distinct multicellular spatial patterns. Integration of these networks revealed higher-order tumor- and immune-enriched microenvironments associated with patient outcomes. Notably, neutrophil-associated tumor-enriched and tumor-desert microenvironments delineated patient groups with opposing clinical outcomes and distinct neutrophil states. These findings were validated by single-cell spatial transcriptomic profiling of 6 million cells from 162 iCCA patients. Together, this study defines the spatial architecture of iCCA and provides a comprehensive resource for exploring tumor spatial organization.

cancer biology↗

bioRxiv2026

Enteroviral epitope mimicry enables NK cell-mediated targeting of ASPH in hepatocellular carcinoma

Cancer development is shaped by host-microbe interactions, including viral infections. While several viruses are established oncogenic drivers, their potential protective roles in cancer remain unclear. Here we identify a dominant antibody response to CE1, a consensus epitope of enterovirus and rhinovirus, that is associated with reduced hepatocellular carcinoma (HCC) incidence and mortality. Anti-CE1 antibodies selectively recognize HCC cells and mediate anti-tumor activity through NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC). Mechanistically, anti-CE1 antibodies cross-react with aspartate {beta}-hydroxylase (ASPH), with CE1-ASPH sequence homology underpinning tumor recognition and cytotoxicity. Clinically, ASPH is aberrantly upregulated in HCC and correlates with inferred NK cell-associated ADCC activity and improved survival in CE1-seropositive patients. Collectively, these findings reveal a mechanism by which antiviral humoral immunity confers cancer protection through molecular mimicry and highlight anti-CE1 immunity as a potential therapeutic strategy in HCC.

cancer biology↗

bioRxiv2019

Functional Genomic Complexity Defines Intratumor Heterogeneity and Tumor Aggressiveness in Liver Cancer

BackgroundChronic inflammation and chromosome aneuploidy are major traits of primary liver cancer (PLC), which represent the second most common cause of cancer related death worldwide. Increased cancer fitness and aggressiveness of PLC may be achieved by enhancing tumoral genomic complexity that alters tumor biology.\n\nMethodHere, we developed a scoring method, namely functional genomic complexity (FGC), to determine the degree of molecular heterogeneity among 580 liver tumors with diverse ethnicities and etiologies by assessing integrated genomic and transcriptomic data.\n\nResultsWe found that tumors with higher FGC scores are associated with chromosome instability and TP53 mutations, and a worse prognosis, while tumors with lower FGC scores have elevated infiltrating lymphocytes and a better prognosis. These results indicate that FGC scores may serve as a surrogate to define genomic heterogeneity of PLC linked to chromosomal instability and evasion of immune surveillance.\n\nConclusionOur findings demonstrate an ability to define genomic heterogeneity and corresponding tumor biology of liver cancer based only on bulk genomic and transcriptomic data. Our data also provide a rationale for applying this approach to survey liver tumor immunity and to stratify patients for immune-based therapy.\n\nSTATEMENT OF SIGNIFICANCEGenomic heterogeneity contributes to therapeutic failure and poor outcome in patients with liver cancer and poses a challenge in defining targeted therapy. Our findings demonstrate an ability to define genomic heterogeneity and corresponding tumor biology of liver cancer based only on bulk genomic and transcriptomic data. Our data also provide a rationale for applying this approach to survey liver tumor immunity and to stratify patients for immune-based therapy. \\body

genomics↗