Harnessing genome-wide association studies to minimize adverse radiation-induced side effects

Baseline DSB repair prediction of chronic rare Grade ≥ 3 toxicities induced by radiotherapy using classification algorithms

Small fractions of patients suffer from radiotherapy late severe adverse events (AEs Grade ≥ 3), which are usually irreversible and badly affect their quality of life. A novel functional DNA repair assay characterizing several steps of double-strand break (DSB) repair mechanisms was used. DNA repair activities of peripheral blood mononuclear cells were monitored for 1 week using NEXT-SPOT assay in 177 breast and prostate cancer patients. Only seven patients had Grade ≥ 3 AEs, 6 months after radiotherapy initiation. The machine learning method established the importance of variables among demographic, clinical and DNA repair data. The most relevant ones, all related to DNA repair, were employed to build a predictor. Predictors constructed with random forest and minimum bounding sphere predicted late Grade ≥ 3 AEs with a sensitivity of 100% and specificity of 77.17 and 86.22%, respectively. This multiplex functional approach strongly supports a dominant role for DSB repair in the development of chronic AEs. It also showed that affected patients share specific features related to functional aspects of DSB repair. This strategy may be suitable for routine clinical analysis and paves the way for modelling DSB repair associated with severe AEs induced by radiotherapy.

Targeting interleukin-17 in radiation-induced toxicity and cancer progression

Recent strategies to combine chemoradiation with immunotherapy to treat locally advanced lung cancer have improved five-year survival outcomes. However, collateral toxicity to healthy lungs, esophagus, cardiac, and vascular tissue continues to limit the effectiveness of curative-intent thoracic radiation (tRT). It is necessary to gain a deeper comprehension of the fundamental mechanisms underlying inflammation-mediated radiation-induced damage to normal cells. Several cells have been linked in published studies to the release of cytokines and chemokines after radiation therapy. Several inflammatory mediators, such as IL-1, IL-6, TNF-α, and TGF-β, also cause the production of Interleukin-17 (IL-17), a cytokine that is essential for maintaining immunological homeostasis and plays a role in the toxicity caused by radiation therapy. However, currently, the role of IL-17 in RT-induced toxicity in conjunction with cancer progression remains poorly understood. This review provides an overview of the most recent data from the literature implicating IL-17 in radiation-mediated tissue injuries and the efficacy of tRT in lung cancer, as well as its potential as a therapeutic target for interventions to reduce the side effects of tRT with curative intent and to boost an anti-tumor immune response to improve treatment outcomes. IL-17 may also act as a biomarker for predicting the effectiveness of a given treatment as well as the toxicity caused by tRT.

Molecular Biomarkers in Cancer

Molecular cancer biomarkers are any measurable molecular indicator of risk of cancer, occurrence of cancer, or patient outcome. They may include germline or somatic genetic variants, epigenetic signatures, transcriptional changes, and proteomic signatures. These indicators are based on biomolecules, such as nucleic acids and proteins, that can be detected in samples obtained from tissues through tumor biopsy or, more easily and non-invasively, from blood (or serum or plasma), saliva, buccal swabs, stool, urine, etc. Detection technologies have advanced tremendously over the last decades, including techniques such as next-generation sequencing, nanotechnology, or methods to study circulating tumor DNA/RNA or exosomes. Clinical applications of biomarkers are extensive. They can be used as tools for cancer risk assessment, screening and early detection of cancer, accurate diagnosis, patient prognosis, prediction of response to therapy, and cancer surveillance and monitoring response. Therefore, they can help to optimize making decisions in clinical practice. Moreover, precision oncology is needed for newly developed targeted therapies, as they are functional only in patients with specific cancer genetic mutations, and biomarkers are the tools used for the identification of these subsets of patients. Improvement in the field of cancer biomarkers is, however, needed to overcome the scientific challenge of developing new biomarkers with greater sensitivity, specificity, and positive predictive value.

Proton beam therapy with concurrent chemotherapy is feasible in children with newly diagnosed rhabdomyosarcoma

Background

The optimal treatment for rhabdomyosarcoma (RMS) requires multidisciplinary treatment with chemotherapy, surgery, and radiotherapy. Surgery and radiotherapy are integral to the local control (LC) of RMS. However, postsurgical and radiotherapy-related complications could develop according to the local therapy and tumor location. In this study, we conducted a single-center analysis of the outcomes and toxicity of multidisciplinary treatment using proton beam therapy (PBT) for pediatric RMS.

Materials and methods

RMS patients aged younger than 20 years whose RMS was newly diagnosed and who underwent PBT at University of Tsukuba Hospital (UTH) during the period from 2009 to 2019 were enrolled in this study. The patients' clinical information was collected by retrospective medical record review.

Results

Forty-eight patients were included. The 3-year progression-free survival (PFS) and overall survival (OS) rates of all the patients were 68.8% and 94.2%, respectively. The 3-year PFS rates achieved with radical resection, conservative resection, and biopsy only were 65.3%, 83.3%, and 67.6%, respectively (p = 0.721). The 3-year LC rates achieved with radical resection, conservative resection, and biopsy only were 90.9%, 83.3%, and 72.9%, respectively (p = 0.548). Grade 3 or higher mucositis/dermatitis occurred in 14 patients. Although the days of opioid use due to mucositis/dermatitis during the chemotherapy with PBT were longer than those during the chemotherapy without PBT [6.1 and 1.6 (mean), respectively, p = 0.001], the frequencies of fever and elevation of C-reactive protein were equivalent.

Conclusions

Multidisciplinary therapy containing PBT was feasible and provided a relatively fair 3-year PFS, even in children with newly diagnosed RMS without severe toxicity.

Artificial Intelligence and Precision Medicine: A Perspective

This article aims to present how the advanced solutions of artificial intelligence and precision medicine work together to refine medical management. Multi-omics seems the most suitable approach for biological analysis of data on precision medicine and artificial intelligence. We searched PubMed and Google Scholar databases to collect pertinent articles appearing up to 5 March 2021. Genetics, oncology, radiology, and the recent coronavirus disease (COVID-19) pandemic were chosen as representative fields addressing the cross-compliance of artificial intelligence (AI) and precision medicine based on the highest number of articles, topicality, and interconnectedness of the issue. Overall, we identified and perused 1572 articles. AI is a breakthrough that takes part in shaping the Fourth Industrial Revolution in medicine and health care, changing the long-time accepted diagnostic and treatment regimens and approaches. AI-based link prediction models may be outstandingly helpful in the literature search for drug repurposing or finding new therapeutical modalities in rapidly erupting wide-scale diseases such as the recent COVID-19.