Genetics of Cancer Immunology

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 981

Special Issue Editor

Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
Interests: bioinformatics; computational biology; system biology; genomic analysis; integrative bioinformatics; network bioinformatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

  • Background & history of this topic:

The genetic basis of cancer immunology is central to understanding tumor–immune interactions, immune evasion, and the development of immunotherapies. Various genetic alterations in both tumor cells and immune cells shape the immune response to cancer, influencing tumor progression, metastasis, and response to treatment. The concept of immune surveillance was introduced in the mid-20th century, proposing that the immune system can recognize and eliminate cancerous cells. This model, proposed in the early 2000s, describes how the immune system interacts with tumors in three phases—elimination, equilibrium, and escape. With advancements in genomics, researchers have identified key mutations, neoantigens, and immune checkpoints that regulate the tumor microenvironment. Genetic studies have contributed to the development of checkpoint inhibitors (e.g., anti-PD-1/PD-L1, anti-CTLA-4) and personalized cancer vaccines. High-throughput sequencing, single-cell omics, CRISPR-based gene editing, and spatial multiomic profiling have propelled our understanding of tumor–immune interactions and resistance mechanisms.

  • Aim and scope of the special issue:

This Special Issue aims to cover all areas of the genetic and molecular mechanisms underlying cancer immunology, highlighting recent breakthroughs and their translational potential. Its scope includes, but is not limited to, the genomic and transcriptomic profiling of tumor–immune interactions, the identification of tumor neoantigens and their role in immunotherapy, the genetics of immune evasion and resistance mechanisms to immunotherapy, germline and somatic mutations influencing immune response in cancer, CRISPR and gene-editing technologies for modulating immune responses, the tumor microenvironment (TME) in the genetic regulation role of non-coding RNAs, epigenetics, and chromatin remodeling in immune regulation, machine learning and computational approaches in immunogenetics, and translational and clinical studies focusing on genetic biomarkers of immunotherapy response.

  • Cutting-edge research:

Some of the most exciting areas in the field include the following: single-cell genomics and spatial transcriptomics—understanding how the immune system interacts with tumors at the single-cell level, tumor mutational burden and neoantigen prediction—linking genetic alterations to immunotherapy response, microbiome and immune system interactions—investigating how gut microbiota influences genetic predisposition to immune-based therapies, synthetic immunology and genetic engineering—engineering T cells (e.g., CAR-T, TCR-T) and other immune components to improve therapeutic outcomes, the genomic basis of immunotherapy resistance—unraveling mutations and epigenetic changes that drive resistance and AI-driven biomarker discovery—and using artificial intelligence to discover new genetic signatures predictive of immune response.

  • What kind of papers we are soliciting:

We welcome submissions of the following types of articles: novel findings on the genetics of cancer immunology, comprehensive overviews of recent advancements, emerging findings with high impact potential, innovations in genetic analysis, sequencing, or computational approaches, and research with direct implications for patient care.

Dr. Jing Yang
Guest Editor

Manuscript Submission Information

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Keywords

  • tumor–immune interaction
  • immunotherapy
  • immune regulation
  • immune evasion

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Published Papers (1 paper)

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Research

17 pages, 2313 KiB  
Article
Mapping Inherited Genetic Variation with Opposite Effects on Autoimmune Disease and Four Cancer Types Identifies Candidate Drug Targets Associated with the Anti-Tumor Immune Response
by Junyu Chen, Michael P. Epstein, Joellen M. Schildkraut and Siddhartha P. Kar
Genes 2025, 16(5), 575; https://doi.org/10.3390/genes16050575 - 14 May 2025
Viewed by 804
Abstract
Background: Germline alleles near genes encoding certain immune checkpoints (CTLA4, CD200) are associated with autoimmune/autoinflammatory disease and cancer, but in opposite ways. This motivates a systematic search for additional germline alleles with this pattern with the aim of identifying [...] Read more.
Background: Germline alleles near genes encoding certain immune checkpoints (CTLA4, CD200) are associated with autoimmune/autoinflammatory disease and cancer, but in opposite ways. This motivates a systematic search for additional germline alleles with this pattern with the aim of identifying potential cancer immunotherapeutic targets using human genetics. Methods: Pairwise fixed effect cross-disorder meta-analyses combining genome-wide association studies (GWAS) for breast, prostate, ovarian and endometrial cancers (240,540 cases/317,000 controls) and seven autoimmune/autoinflammatory diseases (112,631 cases/895,386 controls) coupled with in silico follow-up. Results: Meta-analyses followed by linkage disequilibrium clumping identified 312 unique, independent lead variants with p < 5 × 10−8 associated with at least one of the cancer types at p < 10−3 and one of the autoimmune/autoinflammatory diseases at p < 10−3. At each lead variant, the allele that conferred autoimmune/autoinflammatory disease risk was protective for cancer. Mapping led variants to nearest genes as putative functional targets and focusing on immune-related genes implicated 32 genes. Tumor bulk RNA-Seq data highlighted that the tumor expression of 5/32 genes (IRF1, IKZF1, SPI1, SH2B3, LAT) was each strongly correlated (Spearman’s ρ > 0.5) with at least one intra-tumor T/myeloid cell infiltration marker (CD4, CD8A, CD11B, CD45) in every one of the cancer types. Tumor single-cell RNA-Seq data from all cancer types showed that the five genes were more likely to be expressed in intra-tumor immune versus malignant cells. The five lead SNPs corresponding to these genes were linked to them via the expression of quantitative trait locus mechanisms and at least one additional line of functional evidence. Proteins encoded by the genes were predicted to be druggable. Conclusions: We provide population-scale germline genetic and functional genomic evidence to support further evaluation of the proteins encoded by IRF1, IKZF1, SPI1, SH2B3 and LAT as possible targets for cancer immunotherapy. Full article
(This article belongs to the Special Issue Genetics of Cancer Immunology)
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