History and evolution of cytogenetic techniques: Current and future applications in basic and clinical research

A DAPI-Based Modified C-banding Technique for a Rapid Achieving High Photographic Contrast of Centromeres on Chromosomes

Many chromosome assays rely on the quantification of chromosome abnormalities in cells, and one important abnormality is the existence of more than one centromere for each chromosome. The quantification of such abnormalities has been studied before. However, this process is labor-intensive and time consuming. Thus, this assay is challenging for ex-laboratory applications, where speed is required. We present a visualization method that uses a cheap stain-DAPI, long (e.g., high-resolution) chromosomes and our modified C-banding method for labeling chromosomes. The labeled chromosomes can then be easily seen with a conventional and readily available fluorescence microscopy system. This method achieves an acceleration of the detection of the presence of constitutive heterochromatin in chromosomal centromeres by more than 10 times, to ~2 h, in Human lymphocyte cells and in cells of the human Jurkat line. This new procedure will ultimately provide an easier and cheaper alternative to FISH/PNA probes, or the classic Giemsa staining method. Simplification and reduction in time of the overall procedure will enable the utilization of centromere-counting assays in laboratory and ex-laboratory applications, including in emergency response.

Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions

Deep learning (DL) is a branch of machine learning and artificial intelligence that has been applied to many areas in different domains such as health care and drug design. Cancer prognosis estimates the ultimate fate of a cancer subject and provides survival estimation of the subjects. An accurate and timely diagnostic and prognostic decision will greatly benefit cancer subjects. DL has emerged as a technology of choice due to the availability of high computational resources. The main components in a standard computer-aided design (CAD) system are preprocessing, feature recognition, extraction and selection, categorization, and performance assessment. Reduction of costs associated with sequencing systems offers a myriad of opportunities for building precise models for cancer diagnosis and prognosis prediction. In this survey, we provided a summary of current works where DL has helped to determine the best models for the cancer diagnosis and prognosis prediction tasks. DL is a generic model requiring minimal data manipulations and achieves better results while working with enormous volumes of data. Aims are to scrutinize the influence of DL systems using histopathology images, present a summary of state-of-the-art DL methods, and give directions to future researchers to refine the existing methods.

The future of biological dosimetry in mass casualty radiation emergency response, personalized radiation risk estimation and space radiation protection

PURPOSE

The aim of this brief personal, high level review is to consider the state of the art for biological dosimetry for radiation routine and emergency response, and the potential future progress in this fascinating and active field. Four areas in which biomarkers may contribute to scientific advancement through improved dose and exposure characterization, as well as potential contributions to personalized risk estimation, are considered: emergency dosimetry, molecular epidemiology, personalized medical dosimetry, and space travel.

CONCLUSION

Ionizing radiation biodosimetry is an exciting field which will continue to benefit from active networking and collaboration with the wider fields of radiation research and radiation emergency response to ensure effective, joined up approaches to triage; radiation epidemiology to assess long term, low dose, radiation risk; radiation protection of workers, optimization and justification of radiation for diagnosis or treatment of patients in clinical uses, and protection of individuals traveling to space.

Chromothripsis-Explosion in Genetic Science

Chromothripsis has been defined as complex patterns of alternating genes copy number changes (normal, gain or loss) along the length of a chromosome or chromosome segment (International System for Human Cytogenomic Nomenclature 2020). The phenomenon of chromothripsis was discovered in 2011 and changed the concept of genome variability, mechanisms of oncogenic transformation, and hereditary diseases. This review describes the phenomenon of chromothripsis, its prevalence in genomes, the mechanisms underlying this phenomenon, and methods of its detection. Due to the fact that most often the phenomenon of chromothripsis occurs in cancer cells, in this review, we will separately discuss the issue of the contribution of chromothripsis to the process of oncogenesis.

Dose and Dose-Rate Effects in a Mouse Model of Internal Exposure from 137Cs. Part 2: Integration of Gamma-H2AX and Gene Expression Biomarkers for Retrospective Radiation Biodosimetry

Inhalation and ingestion of 137Cs and other long-lived radionuclides can occur after large-scale accidental or malicious radioactive contamination incidents, resulting in a complex temporal pattern of radiation dose/dose rate, influenced by radionuclide pharmacokinetics and chemical properties. High-throughput radiation biodosimetry techniques for such internal exposure are needed to assess potential risks of short-term toxicity and delayed effects (e.g., carcinogenesis) for exposed individuals. Previously, we used γ-H2AX to reconstruct injected 137Cs activity in experimentally-exposed mice, and converted activity values into radiation doses based on time since injection and 137Cs-elimination kinetics. In the current study, we sought to assess the feasibility and possible advantages of combining γ-H2AX with transcriptomics to improve 137Cs activity reconstructions. We selected five genes (Atf5, Hist2h2aa2, Olfr358, Psrc1, Hist2h2ac) with strong statistically-significant Spearman's correlations with injected activity and stable expression over time after 137Cs injection. The geometric mean of log-transformed signals of these five genes, combined with γ-H2AX fluorescence, were used as predictors in a nonlinear model for reconstructing injected 137Cs activity. The coefficient of determination (R2) comparing actual and reconstructed activities was 0.91 and root mean squared error (RMSE) was 0.95 MBq. These metrics remained stable when the model was fitted to a randomly-selected half of the data and tested on the other half, repeated 100 times. Model performance was significantly better when compared to our previous analysis using γ-H2AX alone, and when compared to an analysis where genes are used without γ-H2AX, suggesting that integrating γ-H2AX with gene expression provides an important advantage. Our findings show a proof of principle that integration of radiation-responsive biomarkers from different fields is promising for radiation biodosimetry of internal emitters.

Radiation Exposure Biomarkers in the Practice of Medical Radiology: Cooperative Research and the Role of the International Atomic Energy Agency (IAEA) Biodosimetry/Radiobiology Laboratory

The strategy toward personalized medicine in radiation oncology, nuclear medicine, and diagnostic and interventional radiology demands a specific set of assays for individualized estimation of radiation load for safety concerns and prognosis of normal tissue reactions caused by ionizing radiation. Apparently, it seems reasonable to use validated radiation dosimetric biomarkers for these purposes. However, a number of gaps in knowledge and methodological limitations still have to be resolved until dosimetric biomarkers will start to play a valuable role in clinical practice beyond radiation protection and radiation medicine. An extensive international multicenter research is necessary to improve the methodology of clinical applications of biodosimetry. That became a rationale for launching the IAEA Coordinated Research Project E35010 MEDBIODOSE: "Applications of Biological Dosimetry Methods in Radiation Oncology, Nuclear Medicine, and Diagnostic and Interventional Radiology." At the 2 Coordination Meeting on MEDBIODOSE (18-22 February 2019, Recife, Brazil), participants reported progress in the usage of biological dosimetry for genotoxicity assessment and/or individualization of radiotherapy treatment plans. Another avenue of research was the prognosis of normal tissue toxicity and cancer risk prediction using biomarkers' yield measured in vivo or after ex vivo irradiation of patients' cells. Other important areas are mechanisms of cytogenetic radiation response, validation of new radiation biomarkers, development of innovative techniques, automated and high-throughput assays for biodosimetry, and the overall improvement of biodosimetry service. An important aspect of clinical application of biodosimetry is standardization of techniques and unification of approaches to data interpretation. The new IAEA Biodosimetry/Radiobiology Laboratory, which is being established, will provide support for this activity. The declared lab's mission includes, among other tasks, a harmonization of the biodosimetry applications with relevant international standards, guidelines on good laboratory practice, and the IAEA EPR-Biodosimetry manual.

A High Throughput Approach to Reconstruct Partial-Body and Neutron Radiation Exposures on an Individual Basis

Biodosimetry-based individualized reconstruction of complex irradiation scenarios (partial-body shielding and/or neutron + photon mixtures) can improve treatment decisions after mass-casualty radiation-related incidents. We used a high-throughput micronucleus assay with automated scanning and imaging software on ex-vivo irradiated human lymphocytes to: a) reconstruct partial-body and/or neutron exposure, and b) estimate separately the photon and neutron doses in a mixed exposure. The mechanistic background is that, compared with total-body photon irradiations, neutrons produce more heavily-damaged lymphocytes with multiple micronuclei/binucleated cell, whereas partial-body exposures produce fewer such lymphocytes. To utilize these differences for biodosimetry, we developed metrics that describe micronuclei distributions in binucleated cells and serve as predictors in machine learning or parametric analyses of the following scenarios: (A) Homogeneous gamma-irradiation, mimicking total-body exposures, vs. mixtures of irradiated blood with unirradiated blood, mimicking partial-body exposures. (B) X rays vs. various neutron + photon mixtures. The results showed high accuracies of scenario and dose reconstructions. Specifically, receiver operating characteristic curve areas (AUC) for sample classification by exposure type reached 0.931 and 0.916 in scenarios A and B, respectively. R² for actual vs. reconstructed doses in these scenarios reached 0.87 and 0.77, respectively. These encouraging findings demonstrate a proof-of-principle for the proposed approach of high-throughput reconstruction of clinically-relevant complex radiation exposure scenarios.

Challenges in identifying large germline structural variants for clinical use by long read sequencing

Genomic structural variations, previously considered rare events, are widely recognized as a major source of inter-individual variability and hence, a major hurdle in optimum patient stratification and disease management. Herein, we focus on large complex germline structural variations and present challenges towards target treatment via the synergy of state-of-the-art approaches and information technology tools. A complex structural variation detection remains challenging, as there is no gold standard for identifying such genomic variations with long reads, especially when the chromosomal rearrangement in question is a few Mb in length. A clinical case with a large complex chromosomal rearrangement serves as a paradigm. We feel that functional validation and data interpretation are of outmost importance for information growth to be translated into knowledge growth and hence, new working practices are highlighted.

Hi-C detects novel structural variants in HL-60 and HL-60/S4 cell lines

Cancer cell lines often have large structural variants (SVs) that evolve over time. There are many reported differences in large scale SVs between HL-60 and HL-60/S4, two cell lines derived from the same acute myeloid leukemia sample. However, the stability and variability of inter- and intra-chromosomal structural variants between different sources of the same cell line is unknown. Here, we used Hi-C and RNA-seq to identify and compare large SVs in HL-60 and HL-60/S4 cell lines. Comparisons with previously published karyotypes identified novel SVs in both cell lines. Hi-C was used to characterize the known expansion centered on the MYC locus. The MYC expansion was integrated into known locations in HL-60/S4, and a novel location (chr4) in HL-60. The HL-60 cell line has more within-line structural variation than the HL-60/S4 derivative cell line. Collectively we demonstrate the usefulness of Hi-C and with RNA-seq data for the identification and characterization of SVs.

On the Complexity of Mechanisms and Consequences of Chromothripsis: An Update

In the present review, we focus on the phenomenon of chromothripsis, a new type of complex chromosomal rearrangements. We discuss the challenges of chromothripsis detection and its distinction from other chromoanagenesis events. Along with already known causes and mechanisms, we introduce aberrant epigenetic regulation as a possible pathway to chromothripsis. We address the issue of chromothripsis characteristics in cancers and benign tumours, as well as chromothripsis inheritance in cases of its occurrence in germ cells, zygotes and early embryos. Summarising the presented data on different phenotypic effect of chromothripsis, we assume that its consequences are most likely determined not by the chromosome shattering and reassembly themselves, but by the genome regions involved in the rearrangement.