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<p>The protein encoded by the Disco-interacting protein 2 homolog B (DIP2B) gene contains DNA methyltransferase and adenosine monophosphate (AMP) binding sites. Although DIP2B has been implicated in tumorigenesis, its diagnostic and prognostic significance across various cancers remains unclear. A comprehensive data analysis was performed using multiple bioinformatics platforms and tools, including the TCGA and GTEx databases, the R programming language, STRING, Cytoscape, TISIDB, cBioPortal, GSCALite, HPA, NetworkAnalyst, and CancerSEA. DIP2B expression was elevated in multiple cancer types, with variations observed across different immune and molecular subtypes. DIP2B was implicated in numerous cancer-related signaling pathways and showed enhanced diagnostic and prognostic significance across malignancies. Transcription factor analysis identified specificity protein 1 (SP1), specificity protein 3 (SP3), and histone deacetylase 1 (HDAC1) as potential regulators of DIP2B expression.In addition, a positive correlation was found between DIP2B and central memory CD8 T cells in cancers, suggesting a potential role in immune modulation. DIP2B shows promise as a prognostic biomarker and may represent anovel target for immunotherapy.</p> Graphical Abstract <p>Step 1: A pan-cancer transcriptomic atlas of the target gene was constructed from TCGA and GTEx data using R/ggplot2, and validated at the protein level via The Human Protein Atlas. Step 2: Clinical relevance and prognostic significance were systematically assessed using R/ggplot2 and Kaplan–Meier analyses across pan-cancer cohorts. Step 3: Integrated multi-omics profiling utilized cBioPortal, STRING–Cytoscape, and GSCALite to outline genetic alterations, DNA methylation landscapes, protein–protein interactomes, and functional enrichments. Step 4: Immuno-oncologic analyses employed TISIDB, CancerSEA, and NetworkAnalyst to link gene expression with immune cell infiltration, tumor microenvironment remodeling, and master regulatory network architecture.</p> <p></p>

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DIP2B as a Prognostic Biomarker and Immunotherapy Target: Insights from Pan-Cancer Analysis

  • 期刊论文

  • 发表日期：

    2026年1月4日

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  • Hai Bai,
  • Yue Cao,
  • Guozheng Wei,
  • Wanqing Xu,
  • Richard Mprah,
  • Cui Li,
  • Mingming Wang

摘要

The protein encoded by the Disco-interacting protein 2 homolog B (DIP2B) gene contains DNA methyltransferase and adenosine monophosphate (AMP) binding sites. Although DIP2B has been implicated in tumorigenesis, its diagnostic and prognostic significance across various cancers remains unclear. A comprehensive data analysis was performed using multiple bioinformatics platforms and tools, including the TCGA and GTEx databases, the R programming language, STRING, Cytoscape, TISIDB, cBioPortal, GSCALite, HPA, NetworkAnalyst, and CancerSEA. DIP2B expression was elevated in multiple cancer types, with variations observed across different immune and molecular subtypes. DIP2B was implicated in numerous cancer-related signaling pathways and showed enhanced diagnostic and prognostic significance across malignancies. Transcription factor analysis identified specificity protein 1 (SP1), specificity protein 3 (SP3), and histone deacetylase 1 (HDAC1) as potential regulators of DIP2B expression.In addition, a positive correlation was found between DIP2B and central memory CD8 T cells in cancers, suggesting a potential role in immune modulation. DIP2B shows promise as a prognostic biomarker and may represent anovel target for immunotherapy.

Graphical Abstract

Step 1: A pan-cancer transcriptomic atlas of the target gene was constructed from TCGA and GTEx data using R/ggplot2, and validated at the protein level via The Human Protein Atlas. Step 2: Clinical relevance and prognostic significance were systematically assessed using R/ggplot2 and Kaplan–Meier analyses across pan-cancer cohorts. Step 3: Integrated multi-omics profiling utilized cBioPortal, STRING–Cytoscape, and GSCALite to outline genetic alterations, DNA methylation landscapes, protein–protein interactomes, and functional enrichments. Step 4: Immuno-oncologic analyses employed TISIDB, CancerSEA, and NetworkAnalyst to link gene expression with immune cell infiltration, tumor microenvironment remodeling, and master regulatory network architecture.