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Updated: Jul 16, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Non-coding RNAs in cancer immunotherapy: Predictive biomarkers and targets
Murad Alahdal1,2, Eyad Elkord3,4
1Johns Hopkins All Children's Hospital, St, Petersburg, Florida, USA.
Background:
To date, standardising clinical predictive biomarkers for assessing the response to immunotherapy remains challenging due to variations in personal genetic signatures, tumour microenvironment complexities and epigenetic onco-mechanisms.
Main Body:
Early monitoring of key non-coding RNA (ncRNA) biomarkers may help in predicting the clinical efficacy of cancer immunotherapy and come up with standard predictive ncRNA biomarkers. For instance, reduced miR-125b-5p level in the plasma of non-small cell lung cancer patients treated with anti-PD-1 predicts a positive outcome. The level of miR-153 in the plasma of colorectal cancer patients treated with chimeric antigen receptor T lymphocyte (CAR-T) cell therapy may indicate the activation of T-cell killing activity. miR-148a-3p and miR-375 levels may forecast favourable responses to CAR-T-cell therapy in B-cell acute lymphoblastic leukaemia. In cancer patients treated with the GPC3 peptide vaccine, serum levels of miR-1228-5p, miR-193a-5p and miR-375-3p were reported as predictive biomarkers of good response and improved overall survival. Therefore, there is a critical need for further studies to elaborate on the key ncRNA biomarkers that have the potential to predict early clinical responses to immunotherapy.
Conclusion:
This review summarises important predictive ncRNA biomarkers that were reported in cancer patients treated with different immunotherapeutic modalities, including monoclonal antibodies, small molecule inhibitors, cancer vaccines and CAR-T cells. In addition, a concise discussion on forthcoming perspectives is provided, outlining technical approaches for the optimal utilisation of immunomodulatory ncRNA biomarkers as predictive tools and therapeutic targets.
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