Cancer Cytogenetics: An Introduction

Evaluation of Acute Myeloid Leukemia Genomes using Genomic Proximity Mapping

Background

Cytogenetic analysis encompasses a suite of standard-of-care diagnostic testing methods that is routinely applied in cases of acute myeloid leukemia (AML) to assess chromosomal changes that are clinically relevant for risk classification and treatment decisions.

Objective

In this study, we assess the use of Genomic Proximity Mapping (GPM) for cytogenomic analysis of AML diagnostic specimens for detection of cytogenetic risk variants included in the European Leukemia Network (ELN) risk stratification guidelines.

Methods

Archival patient samples (N=48) from the Fred Hutchinson Cancer Center leukemia bank with historical clinical cytogenetic data were processed for GPM and analyzed with the CytoTerra® cloud-based analysis platform.

Results

GPM showed 100% concordance for all specific variants that have associated impacts on risk stratification as defined by ELN 2022 criteria, and a 72% concordance rate when considering all variants reported by the FH cytogenetic lab. GPM identified 39 additional variants, including variants of known clinical impact, not observed by cytogenetics.

Conclusions

GPM is an effective solution for the evaluation of known AML-associated risk variants and a source for biomarker discovery.

Prospective Identification of Prognostic Hot-Spot Mutant Gene Signatures for Leukemia: A Computational Study Based on Integrative Analysis of TCGA and cBioPortal Data

The advantage of an increasing amount of bioinformatics data on leukemias intrigued us to explore the hot-spot mutation profiles and investigate the implications of those hot-spot mutations in patient survival. We retrieved somatic mutations and their distribution in protein domains through data analysis of The Cancer Genome Atlas and cBioPortal databases. After determining differentially expressed mutant genes related to leukemia, we further conducted principal component analysis and single-factor Cox regression analyses. Moreover, survival analysis was performed for the obtained candidate genes, followed by a multi-factor Cox proportional hazard model method for the impacts of the candidate genes on the survival and prognosis of patients with leukemia. At last, the signaling pathways involved in leukemia were investigated by gene set enrichment analysis. There were 223 somatic missense mutation hot-spots identified with pertinence to leukemia, which were distributed in 41 genes. Differential expression in leukemia was witnessed in 39 genes. We found a close correlation between seven genes and the prognosis of leukemia patients, among which, three genes could significantly influence the survival rate. In addition, among these three genes, CD74 and P2RY8 were highlighted due to close pertinence with survival conditions of leukemia patients. Finally, data suggested that B cell receptor, Hedgehog, and TGF-beta signaling pathways were enriched in low-hazard patients. In conclusion, these data underline the involvement of hot-spot mutations of CD74 and P2RY8 genes in survival status of leukemia patients, highlighting their as novel therapeutic targets or prognostic indicators for leukemia patients. Summary of Graphical Abstract: We identified 223 leukemia-associated somatic missense mutation hotspots concentrated in 41 different genes from 2297 leukemia patients in the TCGA database. Differential analysis of leukemic and normal samples from the TCGA and GTEx databases revealed that 39 of these 41 genes showed significant differential expression in leukemia. These 39 genes were subjected to PCA analysis, univariate Cox analysis, survival analysis, multivariate Cox regression analysis, GSEA pathway enrichment analysis, and then the association with leukemia survival prognosis and related pathways were investigated.

A comprehensive molecular characterization of the 8q22.2 region reveals the prognostic relevance of OSR2 mRNA in muscle invasive bladder cancer

Technological advances in molecular profiling have enabled the comprehensive identification of common regions of gene amplification on chromosomes (amplicons) in muscle invasive bladder cancer (MIBC). One such region is 8q22.2, which is largely unexplored in MIBC and could harbor genes with potential for outcome prediction or targeted therapy. To investigate the prognostic role of 8q22.2 and to compare different amplicon definitions, an in-silico analysis of 357 patients from The Cancer Genome Atlas, who underwent radical cystectomy for MIBC, was performed. Amplicons were generated using the GISTIC2.0 algorithm for copy number alterations (DNA_Amplicon) and z-score normalization for mRNA gene overexpression (RNA_Amplicon). Kaplan-Meier survival analysis, univariable, and multivariable Cox proportional hazard ratios were used to relate amplicons, genes, and clinical parameters to overall (OS) and disease-free survival (DFS). Analyses of the biological functions of 8q22.2 genes and genomic events in MIBC were performed to identify potential targets. Genes with prognostic significance from the in silico analysis were validated using RT-qPCR of MIBC tumor samples (n = 46). High 8q22.2 mRNA expression (RNA-AMP) was associated with lymph node metastases. Furthermore, 8q22.2 DNA and RNA amplified patients were more likely to show a luminal subtype (DNA_Amplicon_core: p = 0.029; RNA_Amplicon_core: p = 0.01). Overexpression of the 8q22.2 gene OSR2 predicted shortened DFS in univariable (HR [CI] 1.97 [1.2; 3.22]; p = 0.01) and multivariable in silico analysis (HR [CI] 1.91 [1.15; 3.16]; p = 0.01) and decreased OS (HR [CI] 6.25 [1.37; 28.38]; p = 0.0177) in RT-qPCR data analysis. Alterations in different levels of the 8q22.2 region are associated with manifestation of different clinical characteristics in MIBC. An in-depth comprehensive molecular characterization of genomic regions involved in cancer should include multiple genetic levels, such as DNA copy number alterations and mRNA gene expression, and could lead to a better molecular understanding. In this study, OSR2 is identified as a potential biomarker for survival prognosis.

Detection of deletions in 1q25, 1p36 and 1pTEL and chromosome 17 aneuploidy in oral epithelial dysplasia and oral squamous cell carcinoma by fluorescence in situ hybridization (FISH)

OBJECTIVE

To identify chromosome deletions in 1q25, 1p36 and 1pTEL, and chromosome 17 ploidy status in oral epithelial dysplasia (OED) and oral squamous cell carcinoma (OSCC).

MATERIAL AND METHODS

Samples from 57 OED and 63 OSCC were selected. FISH was performed using centromeric probes 17 and n LSIR 1p36/LSI 1q25 Dual Color Probe.

RESULTS

In OED, deletions were found only in 1pTEL region (29.8%). In OSCC, there was a higher frequency of deletion in 1pTEL (79.4%), followed by 1p36 (73.0%), and 1q25 (20.6%). Advanced TNM clinical stages (III/IV) showed all the deletions studied; at early clinical stages (I/II) of OSCC, deletions were observed only in 1pTEL. The frequency of deletion in 1p36 was 17.0 times higher in OSCC at advanced clinical stages (PR: 17.00). The median number of cell nuclei with chromosome 17 aneuploidy was higher in OSCC than in OED (P < 0.001). Early clinical stages of OSCC showed lower median number nuclei with aneuploidy when compared to advanced tumors (P < 0.05). Tumors harboring deletions in 1p36, 1q25 and 1pTEL revealed higher median numbers of trisomic/polysomic nuclei when compared to lesions exhibiting no abnormalities in chromosome 1 (P < 0.05).

CONCLUSION

A higher prevalence of chromosomal abnormalities was found in OSCC than in OED, while in OSCC, higher abnormalities were present in lesions with higher TNM staging. 1pTEL deletion and monosomy of chromosome 17 are possible markers for progression of OED to OSCC. 1p36 deletion and trisomy/polysomy of chromosome 17 could be markers of worse prognosis of OSCC.

The Assessment of Radon Emissions as Results of the Soil Technogenic Disturbance

222Rn is a specific indoor-type pollutant that represents a primary radiological hazard as a main source of ionizing radiation (IR) for humans. Coal mining creates new sources of gas that are formed over mines. This process can significantly increase the density of radon flux. Therefore, the concentration of radon in a room can increase. We investigated the territory of the Leninsk-Kuznetsky district of the Kemerovo region, which is subject to underground mining. Two groups of residential locations and measuring points of radon flux density were selected to identify the higher emanation relationship of radon and mining-affected areas. The first group (Case group) included subjects located within the territory of the underground mine; the other (Control group) included subjects in an area without mining. Radon flux density in coal mining areas was significantly higher than in the rest of the territory; moreover, the percentage of values in the Case group that had a radon flux density above 80 mBq·m-2·s-1 was 64.53%. For the Case group, 20.62% of residential buildings had a radon concentration above 200 Bq/m3. For the studied area, the radon flux density correlates positively (r = 0.79, p = 0.002) with indoor radon. Additional clastogenic/aneugenic effects are also found in dwellings with increased volume activity of radon (VAR) within the territories of underground mines. Ring chromosomes are positively correlated with radon levels in smoker groups but not in non-smokers. An increased frequency of binucleated (BN) cells with micronuclei (MN) is also positively correlated with VAR regardless of smoking status. It has been concluded that reducing the total exposure level of a population to radon can be achieved by monitoring areas with underground mines where radon is emitted heavily.

Cytogenetics and Cytogenomics Evaluation in Cancer

The availability of cytogenetics and cytogenomics technologies improved the detection and identification of tumor molecular signatures as well as the understanding of cancer initiation and progression. The use of large-scale and high-throughput cytogenomics technologies has led to a fast identification of several cancer candidate biomarkers associated with diagnosis, prognosis, and therapeutics. The advent of array comparative genomic hybridization and next-generation sequencing technologies has significantly improved the knowledge about cancer biology, underlining driver genes to guide targeted therapy development, drug-resistance prediction, and pharmacogenetics. However, few of these candidate biomarkers have made the transition to the clinic with a clear benefit for the patients. Technological progress helped to demonstrate that cellular heterogeneity plays a significant role in tumor progression and resistance/sensitivity to cancer therapies, representing the major challenge of precision cancer therapy. A paradigm shift has been introduced in cancer genomics with the recent advent of single-cell sequencing, since it presents a lot of applications with a clear benefit to oncological patients, namely, detection of intra-tumoral heterogeneity, mapping clonal evolution, monitoring the development of therapy resistance, and detection of rare tumor cell populations. It seems now evident that no single biomarker could provide the whole information necessary to early detect and predict the behavior and prognosis of tumors. The promise of precision medicine is based on the molecular profiling of tumors being vital the continuous progress of high-throughput technologies and the multidisciplinary efforts to catalogue chromosomal rearrangements and genomic alterations of human cancers and to do a good interpretation of the relation genotype-phenotype.

Calling Variants in the Clinic: Informed Variant Calling Decisions Based on Biological, Clinical, and Laboratory Variables

Deep sequencing genomic analysis is becoming increasingly common in clinical research and practice, enabling accurate identification of diagnostic, prognostic, and predictive determinants. Variant calling, distinguishing between true mutations and experimental errors, is a central task of genomic analysis and often requires sophisticated statistical, computational, and/or heuristic techniques. Although variant callers seek to overcome noise inherent in biological experiments, variant calling can be significantly affected by outside factors including those used to prepare, store, and analyze samples. The goal of this review is to discuss known experimental features, such as sample preparation, library preparation, and sequencing, alongside diverse biological and clinical variables, and evaluate their effect on variant caller selection and optimization.