Implications of the germline variants of DNA damage response genes detected by cancer precision medicine for radiological risk communication and cancer therapy decisions

Data Science Opportunities To Improve Radiotherapy Planning and Clinical Decision Making

Radiotherapy aims to achieve a high tumor control probability while minimizing damage to normal tissues. Personalizing radiotherapy treatments for individual patients, therefore, depends on integrating physical treatment planning with predictive models of tumor control and normal tissue complications. Predictive models could be improved using a wide range of rich data sources, including tumor and normal tissue genomics, radiomics, and dosiomics. Deep learning will drive improvements in classifying normal tissue tolerance, predicting intra-treatment tumor changes, tracking accumulated dose distributions, and quantifying the tumor response to radiotherapy based on imaging. Mechanistic patient-specific computer simulations ('digital twins') could also be used to guide adaptive radiotherapy. Overall, we are entering an era where improved modeling methods will allow the use of newly available data sources to better guide radiotherapy treatments.

Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors

PURPOSE

In this Pediatric Normal Tissue Effects in the Clinic (PENTEC) vision paper, challenges and opportunities in the assessment of subsequent neoplasms (SNs) from radiation therapy (RT) are presented and discussed in the context of technology advancement.

METHODS AND MATERIALS

The paper discusses the current knowledge of SN risks associated with historic, contemporary, and future RT technologies. Opportunities for research and SN mitigation strategies in pediatric patients with cancer are reviewed.

RESULTS

Present experience with radiation carcinogenesis is from populations exposed during widely different scenarios. Knowledge gaps exist within clinical cohorts and follow-up; dose-response and volume effects; dose-rate and fractionation effects; radiation quality and proton/particle therapy; age considerations; susceptibility of specific tissues; and risks related to genetic predisposition. The biological mechanisms associated with local and patient-level risks are largely unknown.

CONCLUSIONS

Future cancer care is expected to involve several available RT technologies, necessitating evidence and strategies to assess the performance of competing treatments. It is essential to maximize the utilization of existing follow-up while planning for prospective data collection, including standardized registration of individual treatment information with linkage across patient databases.

A genomic score to predict local control among patients with brain metastases managed with radiation

BACKGROUND

Clinical predictors of local recurrence following radiation among patients with brain metastases (BrM) provide limited explanatory power. We developed a DNA-based signature of radiotherapeutic efficacy among patients with BrM to better characterize recurrence risk.

METHODS

We identified 570 patients with 1487 BrM managed with whole-brain (WBRT) or stereotactic radiation therapy at Brigham and Women's Hospital/Dana-Farber Cancer Institute (2013-2020) for whom next-generation sequencing panel data (OncoPanel) were available. Fine/Gray's competing risks regression was utilized to compare local recurrence on a per-metastasis level among patients with versus without somatic alterations of likely biological significance across 84 genes. Genes with a q-value ≤ 0.10 were utilized to develop a "Brain-Radiation Prediction Score" ("Brain-RPS").

RESULTS

Genomic alterations in 11 (ATM, MYCL, PALB2, FAS, PRDM1, PAX5, CDKN1B, EZH2, NBN, DIS3, and MDM4) and 2 genes (FBXW7 and AURKA) were associated with decreased or increased risk of local recurrence, respectively (q-value ≤ 0.10). Weighted scores corresponding to the strength of association with local failure for each gene were summed to calculate a patient-level RPS. On multivariable Fine/Gray's competing risks regression, RPS [1.66 (1.44-1.91, P < .001)], metastasis-associated edema [1.60 (1.16-2.21), P = .004], baseline size [1.02 (1.01-1.03), P < .001] and receipt of WBRT without local therapy [4.04 (2.49-6.58), P < .001] were independent predictors of local failure.

CONCLUSIONS

We developed a genomic score to quantify local recurrence risk following brain-directed radiation. To the best of our knowledge, this represents the first study to systematically correlate DNA-based alterations with radiotherapeutic outcomes in BrM. If validated, Brain-RPS has potential to facilitate clinical trials aimed at genome-based personalization of radiation in BrM.

Targeted delivery of Dbait by an artificial extracellular vesicle for improved radiotherapy sensitivity of esophageal cancer

Intensification of radiotherapy has been shown to be an effective way for improving the therapeutic efficacy of radiation sensitive malignancies such as esophageal cancer (EC). The application of DNA Bait (Dbait), a type of DNA repair inhibitor, is an emerging strategy for radiosensitization. In this study, a Eca-109 cancerous cytomembrane-cloaked biomimetic drug delivery system (DDS), CMEC-Dbait, was designed and successfully fabricated, for targeted delivery of Dbait. Our systematic evaluation demonstrated that the ingenious artificial gastrointestinal extracellular vesicle owns neat spherical structure, proper particle size (154.6±5.5 nm) and surface charge (2.6±0.3 mV), favourable biocompatibility and immunocompatibility, being conducive to in vivo drug delivery. Besides, Eca-109 cytomembrane coating endowed CMEC-Dbait with effective targeting ability to homologous EC cells. Owing to these advantages, the biomimetic DDS was proved to be a potent radiosensitizer in vitro, indicated by remarkably reduced cell viability and enhanced cellular apoptosis by the combination therapy of radiation and CMEC-Dbait. The result was validated in vivo using mouse xenograft models of EC, the results illustrated that radiotherapy plus CMEC-Dbait significantly suppressed tumor growth and prolonged survival of tumor bearing mice. Western blotting results showed that CMEC-Dbait can significantly inhibit DNA damage repair signaling pathways by simulating DNA double-strand breaks both in and ex vivo. In conclusion, the versatile biomimetic CMEC-Dbait was characterized of low toxicity, excellent biocompatibility and satisfactory drug delivery efficiency, which is confirmed to be an ideal radiosensitizer for homologous cancer and merits further investigation in both pre-clinical and clinical studies.

Meiotic chromosome organization and its role in recombination and cancer

Chromosomes adopt specific conformations to regulate various cellular processes. A well-documented chromosome configuration is the highly compacted chromosome structure during metaphase. More regional chromatin conformations have also been reported, including topologically associated domains encompassing mega-bases of DNA and local chromatin loops formed by kilo-bases of DNA. In this review, we discuss the changes in chromatin conformation taking place between somatic and meiotic cells, with a special focus on the establishment of a proteinaceous structure, called the chromosome axis, at the beginning of meiosis. The chromosome axis is essential to support key meiotic processes such as chromosome pairing, homologous recombination, and balanced chromosome segregation to transition from a diploid to a haploid stage. We review the role of the chromosome axis in meiotic chromatin organization and provide a detailed description of its protein composition. We also review the conserved and distinct roles between species of axis proteins in meiotic recombination, which is a major factor contributing to the creation of genetic diversity and genome evolution. Finally, we discuss situations where the chromosome axis is deregulated and evaluate the effects on genome integrity and the consequences from protein deregulation in meiocytes exposed to heat stress, and aberrant expression of genes encoding axis proteins in mammalian somatic cells associated with certain types of cancers.

Revisiting Secondary Information Related to Pharmacogenetic Testing

Incidental or secondary findings have been a major part of the discussion of genomic medicine research and clinical applications. For pharmacogenetic (PGx) testing, secondary findings arise due to the pleiotropic effects of pharmacogenes, often related to their endogenous functions. Unlike the guidelines that have been developed for whole exome or genome sequencing applications for management of secondary findings (though slightly different from PGx testing in that these refer to detection of variants in multiple genes, some with clinical significance and actionability), no corresponding guidelines have been developed for PGx clinical laboratories. Nonetheless, patient and provider education will remain key components of any PGx testing program to minimize adverse responses related to secondary findings.