Abstract
VISTA (V-domain Immunoglobulin Suppressor of T cell Activation), encoded by VSIR, functions as an inhibitory checkpoint predominantly expressed on myeloid cells. Despite its recognized role in solid tumors, systematic characterization of VSIR regulation and clinical implications in hematological malignancies remains limited. We performed integrative multi-omics analyses of diverse hematological malignancies (> 10,000 transcriptomes) to elucidate VSIR expression patterns, epigenetic regulation, and therapeutic potential. VSIR exhibited preferential upregulation in hematological malignancies, particularly myeloid leukemias. We identified dual epigenetic mechanisms driving VSIR overexpression: promoter hypomethylation progressively intensified from healthy controls through myelodysplastic syndromes (MDS) to acute myeloid leukemia (AML), validated by targeted bisulfite sequencing in 130 clinical samples; chromatin immunoprecipitation sequencing revealed direct transcriptional activation by KMT2A fusion proteins through enrichment of H3K4me3, H3K79me2, and H3K27ac activating marks at the VSIR promoter. Menin inhibitor treatment substantially reduced KMT2A occupancy and histone modifications, confirming Menin-dependent regulation. Similarly, NPM1 mutations promoted VSIR expression through stabilizing Menin-containing chromatin complexes. Functionally, VSIR-high tumors showed enrichment in immune regulatory pathways and predicted favorable immunotherapy responses. Prognostically, elevated VSIR expression conferred adverse outcomes in AML while predicting improved survival in DLBCL and MM. Computationally, VSIR-high patients showed increased likelihood of benefiting from immune checkpoint blockade, validated in real-world immunotherapy cohorts. The elucidated Menin-VSIR regulatory axis suggests potential for combining Menin inhibitors with VISTA checkpoint blockade in KMT2A-rearranged AML. Our findings suggest that VSIR expression is epigenetically dysregulated in hematological malignancies through dual mechanisms, which could inform biomarker-driven patient selection and rational design of combination immunotherapies.
Data availability
The datasets analyzed in this study are publicly available in Genotype-Tissue Expression (GTEx) database (https://gtexportal.org/), Cancer Cell Line Encyclopedia (CCLE) database (https://www.broadinstitute.org/ccle), The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/), UCSC Xena Browser (https://xenabrowser.net/), Genomic Data Commons (GDC) data portal (https://portal.gdc.cancer.gov/), cBioPortal for Cancer Genomics (http://www.cbioportal.org/), PREdiction of Clinical Outcomes from Genomic Profiles (PRECOG) database (https://precog.stanford.edu/), Hemap dataset (https://www.synapse.org; DOI: https://doi.org/10.7303/syn21991014), AML Proteomics Database ( [https://proteomics.leylab.org/](https:/proteomics.leylab.org) ), DiseaseMeth database (http://diseasemeth.edbc.org/), Tumor Immune Single-cell Hub 2 (TISCH2) database (http://tisch.comp-genomics.org/home/), Galen et al. AML cohort (GSE116256), FIMM AML cohort (https://www.s ynapse.org; DOI: https://doi.org/10.7303/syn21991014), Human Cell Atlas (HCA) ( [https://www.humancellatlas.org/](https:/www.humancellatlas.org) ), Tumor Immune Dysfunction and Exclusion (TIDE) platform (http://tide.dfci.harvard.edu/), and Molecular Signatures Database (MSigDB) (http://www.broad.mit.edu/gsea/msigdb). Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/): The publicly available GEO datasets used in this study included GSE103237, GSE10358, GSE107367, GSE10846, GSE11318, GSE1159, GSE117556, GSE12195, GSE122476, GSE12417.GPL96, GSE12417.GPL97, GSE12453, GSE13159, GSE132550, GSE145842, GSE14879, GSE15061, GSE181063, GSE186695, GSE19069, GSE19429, GSE196036, GSE197381, GSE19784, GSE21304, GSE21846, GSE23501, GSE24006, GSE24080, GSE2658, GSE26713, GSE2779, GSE28497, GSE29130, GSE30029, GSE32231, GSE32918, GSE33315, GSE33615, GSE34171.GPL570, GSE34861, GSE37642.GPL570, GSE38543, GSE43754, GSE45712, GSE4619, GSE4732, GSE47927, GSE48047, GSE50006, GSE51528, GSE51757, GSE53482, GSE53786, GSE54200, GSE54644, GSE56315, GSE58477, GSE58831, GSE61629, GSE63270, GSE6338, GSE63409, GSE6477, GSE68308, GSE6891, GSE69053.GPL14951, GSE69053.GPL8432, GSE71014, GSE79533, GSE87371, GSE89336, and GSE97562. These datasets were used for differential expression analysis across 22 hematologic cancer types (Pan-Hem-Diff cohort), prognostic evaluation in AML, DLBCL, and MM (survival meta-analysis), DNA methylation profiling, and ChIP-seq analysis of KMT2A fusion and Menin regulatory mechanisms. Additional survival data were obtained from BeatAML cohort, Bullinger AML cohort, CoMMpass trial, and Reddy DLBCL cohort as referenced in the manuscript. Immunotherapy cohort data were obtained from published studies as referenced in the manuscript. The reduced representation bisulfite sequencing (RRBS) dataset generated in our previous study is available in NCBI Sequence Read Archive (SRA) database (accession number: PRJNA670308). The targeted bisulfite sequencing data generated in this study, comprising methylation levels at four VSIR promoter CpG sites across 168 clinical samples, are provided in Table S3. The original contributions presented in the study are included in the article and its Supplementary Materials (Table S1, Table S2, and Table S3). Further inquiries can be directed to the corresponding author.
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Acknowledgements
We sincerely thank the researchers who collected and curated the Hemap resource. Their pioneering work in establishing this comprehensive blood cancer genomics atlas provided invaluable foundation for our multi-cancer investigation and greatly facilitated our exploration of VSIR across diverse hematological malignancies. We extend our gratitude to the teams maintaining GTEx, CCLE, TCGA, and GEO repositories, whose sustained efforts in data curation and accessibility have been instrumental to this study. We also acknowledge the developers of computational tools including ESTIMATE, xCell, CIBERSORT, MCP-counter, and the TIDE platform, which enabled comprehensive immune microenvironment characterization and immunotherapy response prediction. We are grateful to all patients who contributed clinical samples and consented to participate in this research. Finally, we thank all researchers who collected, managed, and maintained the publicly available resources that made this integrative analysis possible.
Funding
This study was supported by National Natural Science Foundation of China (81970118, 82270179, 81900166), Zhenjiang Clinical Research Center of Hematology (SS2018009), Natural Science Foundation of Jiangsu Province (BK20251849, BK20221287), Research Project of Jiangsu Commission of Health (M2022123), Social Development Foundation of Zhenjiang (SH2025073, SH2024001, SH2023022, SH2024029), Medical Education Collaborative Innovation Fund of Jiangsu University (JDY2023008, JDYY2023021), and Horizontal Project from Jichuan Pharmaceutical Group Co., Ltd. (JC-2023-002).
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JL, and JQ supervised the study and commented on the manuscript; JL, JQ, and Z-JX conceived and designed the study; Z-JX, XM Wu, and RC collected and assembled data; Z-JX performed bioinformatics analysis with assistance from XM Wu and RC; H-YC and FW contributed to the collection of clinical samples and performed Menin inhibitor treatment and RT-qPCR validation experiments; XM Wen performed targeted bisulfite sequencing experiments; JQ and J-DZ provided technical support to RRBS experiments and processed the RRBS data; Z-JX drafted the manuscript. All authors read and approved the final manuscript.
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This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of the Affiliated People’s Hospital of Jiangsu University (Approval No. K-20230212-Y). Written informed consent was obtained from all participants or their legal guardians prior to sample collection.
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Xu, Zj., Wu, Xm., Chang, R. et al. Comprehensive characterization of VSIR reveals dual epigenetic regulation and immune landscape across hematological malignancies. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41978-2
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DOI: https://doi.org/10.1038/s41598-026-41978-2
