ReviewImmuno-oncology technology2019
Germline genetic host factors as predictive biomarkers in immuno-oncology.
Review in Immuno-oncology technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- First-in-Human Study of 23ME-00610, an Antagonistic Antibody for Genetically Validated CD200R1 Immune Checkpoint, in Participants with Advanced Solid Malignancies.Cancer research communications · 2025Trial
- PCCA variant rs16957301 is a novel AKI risk genotype-specific for patients who receive ICI treatment: Real-world evidence from all of us cohort.European journal of cancer (Oxford, England : 1990) · 2024Article
- Getting visible with exciting IO tech!Immuno-oncology technology · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In immuno-oncology (IO), the baseline host factors attract significant clinical interest as promising predictive biomarker candidates. Growing evidence from experimental or population-based studies suggests that the host genetic factors contribute to the immunological status of a patient as it plays out at the multiple rate-limiting steps of the cancer immunity cycle. Recent observations suggest that germline genetics may be associated with tumor microenvironment phenotypes, autoimmune toxicities and/or efficacy of immunotherapy regimens and overall cancer survival. Despite these highly intriguing indications, the potential of germline genetic factors as personalized biomarkers of immune-checkpoint inhibition (ICI) remains vastly unexplored. Here, we review the rationale for exploring the germline genetic factors as novel biomarkers predictive of IO outcomes, including ICI efficacy, toxicity and survival, and discuss the comprehensive approaches for the identification of such germline genetic indicators. In addressing the current limitations, we highlight a need for large collaborative consortia in these efforts. We also outline possible avenues for incorporating germline genetic factors into emerging multifactorial tools for a more personalized prediction of ICI outcomes.
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