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Chemotherapy, radiotherapy and adverse drug reaction mitigation using NGS

Chemotherapy is often aggressive and can provoke severe toxicity and adverse drug reactions (ADR). Noticeable differences also exist in the extent of ADRs between patients, even in those with similar types of cancer and disease stages who are treated with equal doses of chemotherapy. The reactions range from mild to severe or even life-threatening ADRs after as little as one dose of treatment, which can result in delays in treatment, the need for dose adjustments, or even discontinuation.

Along with chemotherapy, radiotherapy is used in many curative cancer treatments. Radiogenomics studies the influence of genetic variation on radiation responses in individuals, which can range from non-existent to severe reactions which may have a major negative impact on the patient’s health and quality of life. Therefore, predicting clinical radiosensitivity of individual patients (normal tissue toxicity, NTT) undergoing therapeutic irradiation is of crucial importance to evaluating possible short or long-term adverse effects (Vinnikov et al., 2020). Being able to predict which patients are at higher risk of developing ARDs, and adjust the dose or use the alternative treatment options available would serve to lower toxicity and improve patients; quality of life. In addition, evaluation of possible gene polymorphisms of an individual could prevent late-onset chemotherapy (and/or radiotherapy) toxicities (e.g. cardiomyopathy, pulmonary fibrosis, osteoporosis, etc.).

egSEQ library preparation and targeted sequencing solutions, including specific panels with maximised coverage on oncology-related targets and full bioinformatics solutions with reporting offer a customisable solution for cancer screening and genomic profiling to provide researchers working on effective cancer diagnosis, treatment, and prevention with invaluable genomic data that will lead to revolutionary new strategies in dealing with cancer.

Related Links:


Badam, T. V. S. (2021). Omic Network Modules in Complex diseases(Doctoral dissertation, Linköping University Electronic Press).

Vinnikov, V., Hande, M. P., Wilkins, R., Wojcik, A., Zubizarreta, E., & Belyakov, O. (2020). Prediction of the acute or late radiation toxicity effects in radiotherapy patients using ex vivo induced biodosimetric markers: A review. Journal of Personalized Medicine, 10(4), 285.


Image by Muhammad Syafi Al - adam


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