Cancer cytogenetics: methodology revisited

Molecular Methods: Clinical Utilization and Designing a Test Menu

Pre-analytical factors in molecular oncology diagnostics are reviewed. Issues around sample collection, storage, and transport that might affect the stability of nucleic acids and the ability to perform molecular testing are addressed. In addition, molecular methods used commonly in clinical diagnostic laboratories, including newer technologies such as next-generation sequencing and digital droplet polymerase chain reaction, as well as their applications, are reviewed. Finally, we discuss considerations in designing a molecular test menu to deliver accurate and timely results in an efficient and cost-effective manner.

Role of Interphase FISH Assay on Air-Dried Smears in Identifying Specific Structural Chromosomal Abnormalities among Pediatric Patients with Acute Leukemias

Leukemia-associated structural chromosomal abnormalities (SCA) can be identified either by karyotyping or interphase-fluorescence in-situ hybridization (i-FISH) assays. Both karyotyping and i-FISH on mononuclear cell suspension are time, resource, and manpower-consuming assays. In this study, we have compared the results of specific leukemia-associated SCAs identified by i-FISH on air-dried bone marrow (BM)/peripheral blood (PB) smears and BM karyotyping. The study was conducted among pediatric patients (age ≤ 18 years) diagnosed with acute leukemias between January 2018 to December 2022. The results of i-FISH on air-dried BM/PB smears and BM-karyotyping for our SCA of interest (BCR::ABL1, ETV6::RUNX1, TCF3::PBX1, KMT2A rearrangement, RUNX1::RUNX1T1, CBFB::MYH11, and PML::RARA) were entered in a contingency table and the agreement of results was calculated. The strength of agreement was assessed by Cramer's V test. Among 270 patients, SCA of interest was identified among 26% and 17% of patients by i-FISH on air-dried smears and karyotyping, respectively. Excluding 53 patients with metaphase failure, the remaining 217 patients had 92% agreement (Cramer's V of 0.931 with p < 0.000) between the results for specific SCAs identified by both techniques. On excluding samples with cryptic cytogenetic aberrancies, there was 99% agreement (Cramer's V of 0.953 with p < 0.000) for gross SCA identified by both techniques. In addition, i-FISH on air-dried smears identified SCA in 30% of patients with metaphase failure. I-FISH on air-dried PB/BMA smears is a less-labor and  resource-consuming assay. It can be considered an efficient alternative to conventional karyotyping for  identifying specific SCA of interest in under-resourced laboratories.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12288-023-01699-2.

The importance of protein domain mutations in cancer therapy

Cancer is a complex disease that is caused by multiple genetic factors. Researchers have been studying protein domain mutations to understand how they affect the progression and treatment of cancer. These mutations can significantly impact the development and spread of cancer by changing the protein structure, function, and signalling pathways. As a result, there is a growing interest in how these mutations can be used as prognostic indicators for cancer prognosis. Recent studies have shown that protein domain mutations can provide valuable information about the severity of the disease and the patient's response to treatment. They may also be used to predict the response and resistance to targeted therapy in cancer treatment. The clinical implications of protein domain mutations in cancer are significant, and they are regarded as essential biomarkers in oncology. However, additional techniques and approaches are required to characterize changes in protein domains and predict their functional effects. Machine learning and other computational tools offer promising solutions to this challenge, enabling the prediction of the impact of mutations on protein structure and function. Such predictions can aid in the clinical interpretation of genetic information. Furthermore, the development of genome editing tools like CRISPR/Cas9 has made it possible to validate the functional significance of mutants more efficiently and accurately. In conclusion, protein domain mutations hold great promise as prognostic and predictive biomarkers in cancer. Overall, considerable research is still needed to better define genetic and molecular heterogeneity and to resolve the challenges that remain, so that their full potential can be realized.

Chromosome Bandings and Recognition

Chromosome banding can be defined as the lengthwise variation in staining properties along a chromosome stained with a dye. Chromosome banding became more practical in the early 1970s and is an essential technique used in karyotyping to identify human chromosomes for both clinical and research purposes. Most importantly, karyotyping is now considered a mandatory investigation of all newly diagnosed leukemias. Some banding methods, such as Giemsa (G)-, reverse (R)-, and centromere (C)-banding, still contribute greatly by being used as a routine procedure in clinical cytogenetic laboratory nowadays. Each chromosome has a unique sequence of bar code-like stripes, allowing the identification of individual homologues and the recognition of structural abnormalities through analyzing the disruption of the normal banding pattern at specific landmarks, regions, and bands as described in the ideogram. Since the quality of metaphases obtained from malignant cells is generally inferior to normal constitutional cells for karyotyping, a practical and accurate chromosome identification training guide is indispensable for a trainee or newly employed cytogenetic technologist in a cancer cytogenetic laboratory. The most common and currently used banding methods and chromosome recognition guide for distinguishable bands of each chromosome are described in detail in this chapter with an aim to facilitate quick and accurate karyotyping in cancer cells.

Analytic Validation of Optical Genome Mapping in Hematological Malignancies

Structural variations (SVs) play a key role in the pathogenicity of hematological malignancies. Standard-of-care (SOC) methods such as karyotyping and fluorescence in situ hybridization (FISH), which have been employed globally for the past three decades, have significant limitations in terms of resolution and the number of recurrent aberrations that can be simultaneously assessed, respectively. Next-generation sequencing (NGS)-based technologies are now widely used to detect clinically significant sequence variants but are limited in their ability to accurately detect SVs. Optical genome mapping (OGM) is an emerging technology enabling the genome-wide detection of all classes of SVs at a significantly higher resolution than karyotyping and FISH. OGM requires neither cultured cells nor amplification of DNA, addressing the limitations of culture and amplification biases. This study reports the clinical validation of OGM as a laboratory-developed test (LDT) according to stringent regulatory (CAP/CLIA) guidelines for genome-wide SV detection in different hematological malignancies. In total, 60 cases with hematological malignancies (of various subtypes), 18 controls, and 2 cancer cell lines were used for this study. Ultra-high-molecular-weight DNA was extracted from the samples, fluorescently labeled, and run on the Bionano Saphyr system. A total of 215 datasets, Inc.luding replicates, were generated, and analyzed successfully. Sample data were then analyzed using either disease-specific or pan-cancer-specific BED files to prioritize calls that are known to be diagnostically or prognostically relevant. Sensitivity, specificity, and reproducibility were 100%, 100%, and 96%, respectively. Following the validation, 14 cases and 10 controls were run and analyzed using OGM at three outside laboratories showing reproducibility of 96.4%. OGM found more clinically relevant SVs compared to SOC testing due to its ability to detect all classes of SVs at higher resolution. The results of this validation study demonstrate the superiority of OGM over traditional SOC methods for the detection of SVs for the accurate diagnosis of various hematological malignancies.

PLPPR4 haploinsufficiency causes neurodevelopmental disorders by disrupting synaptic plasticity via mTOR signalling

Phospholipid phosphatase related 4 (PLPPR4), a neuron-specific membrane protein located at the postsynaptic density of glutamatergic synapses, is a putative regulator of neuronal plasticity. However, PLPPR4 dysfunction has not been linked to genetic disorders. In this study, we report three unrelated patients with intellectual disability (ID) or autism spectrum disorder (ASD) who harbour a de novo heterozygous copy number loss of PLPPR4 in 1p21.2p21.3, a heterozygous nonsense mutation in PLPPR4 (NM_014839, c.4C > T, p.Gln2*) and a homozygous splice mutation in PLPPR4 (NM_014839: c.408 + 2 T > C), respectively. Bionano single-molecule optical mapping confirmed PLPPR4 deletion contains no additional pathogenic genes. Our results suggested that the loss of function of PLPPR4 is associated with neurodevelopmental disorders. To test the pathogenesis of PLPPR4, peripheral blood mononuclear cells obtained from the patient with heterozygous deletion of PLPPR4 were induced to specific iPSCs (CHWi001-A) and then differentiated into neurons. The neurons carrying the deletion of PLPPR4 displayed the reduced density of dendritic protrusions, shorter neurites and reduced axon length, suggesting the causal role of PLPPR4 in neurodevelopmental disorders. As the mTOR signalling pathway was essential for regulating the axon maturation and function, we found that mTOR signalling was inhibited with a higher level of p-AKT, p-mTOR and p-ERK1/2, decreased p-PI3K in PLPPR4-iPSCs neurons. Additionally, we found silencing PLPPR4 disturbed the mTOR signalling pathway. Our results suggested PLPPR4 modulates neurodevelopment by affecting the plasticity of neurons via the mTOR signalling pathway.

Chromosome classification via deep learning and its application to patients with structural abnormalities of chromosomes

BACKGROUND AND OBJECTIVE

Karyotyping is an important technique in cytogenetic practice for the early diagnosis of genetic diseases. Clinical karyotyping is tedious, time-consuming, and error-prone. The objective of our study was to develop a single-stage deep convolutional neural networks (DCNN)-based model to automatically classify normal and abnormal chromosomes in an end-to-end manner.

METHODS

We analyzed 2,424 normal chromosomes and 544 abnormal chromosomes. A preliminary support vector machine (SVM) model was developed to evaluate the basic recognition performance on the dataset. A DCNN-based model was then proposed to process the same dataset.

RESULTS

By utilizing the SVM model, the classification accuracy of 24 normal chromosomes was 86.01 %. The 32 types of normal and abnormal chromosomes got an accuracy of 85.37 %. The accuracy of the DCNN-based model performing the 24 normal chromosomal classification was 91.75 %. The accuracy of the 32 type classification was 87.76 %. To differentiate eight common structural abnormalities, we obtained accuracies that ranged from 90.84 % to 100 %, and the values of the AUC ranged from 91.81 % to 100 %.

CONCLUSIONS

Our proposed DCNN-based model effectively performed the karyotype classification in an end-to-end manner. It had the competence to be used as a prediction tool for abnormal karyotype detection and screening in genetic diagnosis without initial feature extraction. We believe our work is meaningful for genetic triage management to lower the cost in clinical practice.

Disruption of regulatory domains and novel transcripts as disease-causing mechanisms

Deletions, duplications, insertions, inversions, and translocations, collectively called structural variations (SVs), affect more base pairs of the genome than any other sequence variant. The recent technological advancements in genome sequencing have enabled the discovery of tens of thousands of SVs per human genome. These SVs primarily affect non-coding DNA sequences, but the difficulties in interpreting their impact limit our understanding of human disease etiology. The functional annotation of non-coding DNA sequences and methodologies to characterize their three-dimensional (3D) organization in the nucleus have greatly expanded our understanding of the basic mechanisms underlying gene regulation, thereby improving the interpretation of SVs for their pathogenic impact. Here, we discuss the various mechanisms by which SVs can result in altered gene regulation and how these mechanisms can result in rare genetic disorders. Beyond changing gene expression, SVs can produce novel gene-intergenic fusion transcripts at the SV breakpoints.

ChromoEnhancer: An Artificial-Intelligence-Based Tool to Enhance Neoplastic Karyograms as an Aid for Effective Analysis

Cytogenetics laboratory tests are among the most important procedures for the diagnosis of genetic diseases, especially in the area of hematological malignancies. Manual chromosomal karyotyping methods are time consuming and labor intensive and, hence, expensive. Therefore, to alleviate the process of analysis, several attempts have been made to enhance karyograms. The current chromosomal image enhancement is based on classical image processing. This approach has its limitations, one of which is that it has a mandatory application to all chromosomes, where customized application to each chromosome is ideal. Moreover, each chromosome needs a different level of enhancement, depending on whether a given area is from the chromosome itself or it is just an artifact from staining. The analysis of poor-quality karyograms, which is a difficulty faced often in preparations from cancer samples, is time consuming and might result in missing the abnormality or difficulty in reporting the exact breakpoint within the chromosome. We developed ChromoEnhancer, a novel artificial-intelligence-based method to enhance neoplastic karyogram images. The method is based on Generative Adversarial Networks (GANs) with a data-centric approach. GANs are known for the conversion of one image domain to another. We used GANs to convert poor-quality karyograms into good-quality images. Our method of karyogram enhancement led to robust routine cytogenetic analysis and, therefore, to accurate detection of cryptic chromosomal abnormalities. To evaluate ChromoEnahancer, we randomly assigned a subset of the enhanced images and their corresponding original (unenhanced) images to two independent cytogeneticists to measure the karyogram quality and the elapsed time to complete the analysis, using four rating criteria, each scaled from 1 to 5. Furthermore, we compared the enhanced images with our method to the original ones, using quantitative measures (PSNR and SSIM metrics).

EagleC: A deep-learning framework for detecting a full range of structural variations from bulk and single-cell contact maps

The Hi-C technique has been shown to be a promising method to detect structural variations (SVs) in human genomes. However, algorithms that can use Hi-C data for a full-range SV detection have been severely lacking. Current methods can only identify interchromosomal translocations and long-range intrachromosomal SVs (>1 Mb) at less-than-optimal resolution. Therefore, we develop EagleC, a framework that combines deep-learning and ensemble-learning strategies to predict a full range of SVs at high resolution. We show that EagleC can uniquely capture a set of fusion genes that are missed by whole-genome sequencing or nanopore. Furthermore, EagleC also effectively captures SVs in other chromatin interaction platforms, such as HiChIP, Chromatin interaction analysis with paired-end tag sequencing (ChIA-PET), and capture Hi-C. We apply EagleC in more than 100 cancer cell lines and primary tumors and identify a valuable set of high-quality SVs. Last, we demonstrate that EagleC can be applied to single-cell Hi-C and used to study the SV heterogeneity in primary tumors.

Analysis of Hi-C Data for Discovery of Structural Variations in Cancer

Structural variations (SVs) are large genomic rearrangements that can be challenging to identify with current short read sequencing technology due to various confounding factors such as existence of genomic repeats and complex SV structures. Hi-C breakfinder is the first computational tool that utilizes the technology of high-throughput chromatin conformation capture assay (Hi-C) to systematically identify SVs, without being interfered by regular confounding factors. SVs change the spatial distance of genomic regions and cause discontinuous signals in Hi-C, which are difficult to analyze by routine informatics practice. Here we provide step-by-step guidance for how to identify SVs using Hi-C data and how to reconstruct Hi-C maps in the presence of SVs.

The prognostic impact of Wilms tumor-1 polymorphism (rs16754) and human myeloid inhibitory C-type lectin-like receptor expression in cytogenetically normal-acute myeloid leukemia

Background

There are several genetic mutations that carry prognostic and predictive values in acute myeloid leukemia (AML). They are also implicated in disease pathogenesis and patient outcome. They can be a target of novel therapies for AML. The aim of the current study was to investigate prognostic value of Wilms’ tumor-1 (WT1) genotypes and human myeloid inhibitory C-type lectin-like (hMICL) receptor expression in normal-cytogenetic group of patients with AML. Genotyping of WT1 mutations was done by Rotor Gene real-time polymerase chain reaction (PCR) while hMICL expression was detected using phycoerythrin (PE)-conjugated mouse monoclonal anti-human (MoAbs) by flow cytometry.

Results

Sixty-three patients with cytogenetically normal AML (CN-AML) were included in the study. The alternate allele of WT1 single nucleotide polymorphism (SNP) rs16754 was found in 26.89%. At day 28 of therapy, complete remission was achieved in 100% of cases harboring mutant AG plus GG genotypes but only in 6.38% of cases harboring wild genotype (AA). After 6 months, 88.23% of patients harboring WT1 mutant genotype maintained complete remission, while only 23.40% of patients with wild type showed complete remission. The overall survival in patients harboring mutant WT1 genotypes was significantly longer than in those who carried the wild type gene (P-value, 0.001). Additionally, hMICL was overexpressed in approximately 87.3% of AML cases and inversely related to complete response. Similarly, overall survival was significantly shorter in patients with positive hMICL (P-value, 0.001).

Conclusion

Mutant WT1 genotypes (SNP rs16754) were conversely, associated with complete response, and hMICL overexpression had poor prognostic value in AML.

Molecular Methods: Clinical Utilization and Designing a Test Menu

Pre-analytical factors in molecular oncology diagnostics are reviewed. Issues around sample collection, storage, and transport that might affect the stability of nucleic acids and the ability to perform molecular testing are addressed. In addition, molecular methods used commonly in clinical diagnostic laboratories, including newer technologies such as next-generation sequencing and digital droplet polymerase chain reaction, as well as their applications, are reviewed. Finally, we discuss considerations in designing a molecular test menu to deliver accurate and timely results in an efficient and cost-effective manner.

Mosaicism in Human Health and Disease

Mosaicism refers to the occurrence of two or more genomes in an individual derived from a single zygote. Germline mosaicism is a mutation that is limited to the gonads and can be transmitted to offspring. Somatic mosaicism is a postzygotic mutation that occurs in the soma, and it may occur at any developmental stage or in adult tissues. Mosaic variation may be classified in six ways: (a) germline or somatic origin, (b) class of DNA mutation (ranging in scale from single base pairs to multiple chromosomes), (c) developmental context, (d) body location(s), (e) functional consequence (including deleterious, neutral, or advantageous), and (f) additional sources of mosaicism, including mitochondrial heteroplasmy, exogenous DNA sources such as vectors, and epigenetic changes such as imprinting and X-chromosome inactivation. Technological advances, including single-cell and other next-generation sequencing, have facilitated improved sensitivity and specificity to detect mosaicism in a variety of biological contexts.

A Practical Guide for Structural Variation Detection in the Human Genome

Profiling genetic variants-including single nucleotide variants, small insertions and deletions, copy number variations, and structural variations (SVs)-from both healthy individuals and individuals with disease is a key component of genetic and biomedical research. SVs are large-scale changes in the genome and involve breakage and rejoining of DNA fragments. They may affect thousands to millions of nucleotides and can lead to loss, gain, and reshuffling of genes and regulatory elements. SVs are known to impact gene expression and potentially result in altered phenotypes and diseases. Therefore, identifying SVs from the human genomes is particularly important. In this review, I describe advantages and disadvantages of the available high-throughput assays for the discovery of SVs, which are the most challenging genetic alterations to detect. A practical guide is offered to suggest the most suitable strategies for discovering different types of SVs including common germline, rare, somatic, and complex variants. I also discuss factors to be considered, such as cost and performance, for different strategies when designing experiments. Last, I present several approaches to identify potential SV artifacts caused by samples, experimental procedures, and computational analysis. © 2020 Wiley Periodicals LLC.

From Banding to BAM Files: Genomics Informs Diagnosis and Precision Medicine for Brain Tumors

Tumors of the central nervous system (CNS) have been historically classified according to their morphologic and immunohistochemical features. In 2016, updates to the classification of tumors of the CNS by the World Health Organization revolutionized this paradigm. For the first time, genomic findings, whether whole-arm chromosomal aberrations or single nucleotide variants, represent a necessary and critical component of diagnosis, contributing or superseding histologic findings. These updates stem from decades of technical innovation and genomic discovery. During this time, there has been a dramatic expansion and evolution in clinical genomic assays for these tumors, informing diagnosis and guiding therapeutic management.

Variability in Cytogenetic Testing for Multiple Myeloma: A Comprehensive Analysis From Across the United States

PURPOSE

Multiple myeloma (MM) treatment has changed tremendously, with significant improvement in patient out-comes. One group with a suboptimal benefit is patients with high-risk cytogenetics, as tested by conventional karyotyping or fluorescence in situ hybridization (FISH). Methodology for these tests has been published, but not necessarily standardized.

METHODS

We address variability in the testing and reporting methodology for MM cytogenetics in the United States using the ongoing African American Multiple Myeloma Study (AAMMS). We evaluated clinical and cytogenetic data from 1,221 patients (1,161 with conventional karyotyping and 976 with FISH) tested between 1998 and 2016 across 58 laboratories nationwide.

RESULTS

Interlab and intralab variability was noted for the number of cells analyzed for karyotyping, with a significantly higher number of cells analyzed in patients in whom cytogenetics were normal (P 5.0025). For FISH testing, CD138-positive cell enrichment was used in 29.7% of patients and no enrichment in 50% of patients, whereas the remainder had unknown status. A significantly smaller number of cells was analyzed for patients in which CD138 cell enrichment was used compared with those without such enrichment (median, 50 v 200; P, .0001). A median of 7 loci probes (range, 1-16) were used for FISH testing across all laboratories, with variability in the loci probed even within a given laboratory. Chromosome 13-related abnormalities were the most frequently tested abnormality (n5956; 97.9%), and t(14;16) was the least frequently tested abnormality (n 5 119; 12.2%).

CONCLUSIONS

We report significant variability in cytogenetic testing across the United States for MM, potentially leading to variability in risk stratification, with possible clinical implications and personalized treatment approaches.

Use of Fluorescence In Situ Hybridization (FISH) in Diagnosis and Tailored Therapies in Solid Tumors

Fluorescence in situ hybridization (FISH) is a standard technique used in routine diagnostics of genetic aberrations. Thanks to simple FISH procedure is possible to recognize tumor-specific abnormality. Its applications are limited to designed probe type. Gene rearrangements e.g., ALK, ROS1 reflecting numerous translocational partners, deletions of critical regions e.g., 1p and 19q, gene fusions e.g., COL1A1-PDGFB, genomic imbalances e.g., 6p, 6q, 11q and amplifications e.g., HER2 are targets in personalized oncology. Confirmation of genetic marker is frequently a direct indication to start specific, targeted treatment. In other cases, detected aberration helps pathologists to better distinguish soft tissue sarcomas, or to state a final diagnosis. Our main goal is to show that applying FISH to formalin-fixed paraffin-embedded tissue sample (FFPE) enables assessing genomic status in the population of cells deriving from a primary tumor or metastasis. Although many more sophisticated techniques are available, like Real-Time PCR or new generation sequencing, FISH remains a commonly used method in many genetic laboratories.

Evaluation of Cytogenetic Abnormalities in Patients with Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) accounts for 20% of all adult leukemias and is the most common leukemia during childhood (80%). We present data on cytogenetics of ALL from a tertiary centre in India correlating it with clinical factors. Karyotyping of bone marrow samples of 204 patients with newly diagnosed ALL was performed with standard G-banding technique. Clinical data of patients was obtained from case records. Survival was estimated using Kaplan-Meir curves and compared by the log-rank test. Univariate and multivariate analysis was done for survival with age, sex, immunophenotype, hyperleukocytosis, risk type, remission status and cytogenetics. The most common karyotypes observed were normal in 39.7% (N = 81), hyperdiploidy in 12.7% (N = 26), t(9;22) in 4.4% (N = 9), t(1;19) in 3.9% (N = 8). Adults with ALL had worse survival compared with pediatric patients (HR 3.62; 2.03-6.45 95% CI, p < 0.001). Patients not in morphologic remission after induction chemotherapy fared poorly (HR 4.86; 2.67-8.84 95% CI, p < 0.001). Patients with favourable cytogenetics had better overall survival (HR 0.36; 0.12-1.05 95% CI, p < 0.05). On multivariate analysis, achievement of morphologic remission emerged as single most significant predictor of survival (p < 0.001). MLL gene rearrangement and t(12;21) were seen less commonly as compared to Western data. However, incidence rates of various cytogenetic abnormalities were similar to that reported from other centres from India. Age, morphologic remission at end of induction chemotherapy and favourable cytogenetics correlated significantly with survival.

Integrative detection and analysis of structural variation in cancer genomes

Structural variants (SVs) can contribute to oncogenesis through a variety of mechanisms. Despite their importance, the identification of SVs in cancer genomes remains challenging. Here, we present a framework that integrates optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole-genome sequencing to systematically detect SVs in a variety of normal or cancer samples and cell lines. We identify the unique strengths of each method and demonstrate that only integrative approaches can comprehensively identify SVs in the genome. By combining Hi-C and optical mapping, we resolve complex SVs and phase multiple SV events to a single haplotype. Furthermore, we observe widespread structural variation events affecting the functions of noncoding sequences, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel three-dimensional chromatin structural domains. Our results indicate that noncoding SVs may be underappreciated mutational drivers in cancer genomes.

Potential Clinical Application of Genomics in Multiple Myeloma

Multiple myeloma is a heterogeneous disease with different characteristics, and genetic aberrations play important roles in this heterogeneity. Studies have shown that these genetic aberrations are crucial in prognostication and response assessment; recent efforts have focused on their possible therapeutic implications. Despite many emerging studies being published, the best way to incorporate these results into clinical practice remains unclear. In this review paper we describe the different genomic techniques available, including the latest advancements, and discuss the potential clinical application of genomics in multiple myeloma.

A new ETV6-NTRK3 cell line model reveals MALAT1 as a novel therapeutic target - a short report

BACKGROUND

Previously, the chromosomal translocation t(12;15)(p13;q25) has been found to recurrently occur in both solid tumors and leukemias. This translocation leads to ETV6-NTRK3 (EN) gene fusions resulting in ectopic expression of the NTRK3 neurotropic tyrosine receptor kinase moiety as well as oligomerization through the donated ETV6-sterile alpha motif domain. As yet, no in vitro cell line model carrying this anomaly is available. Here we genetically characterized the acute promyelocytic leukemia (APL) cell line AP-1060 and, by doing so, revealed the presence of a t(12;15)(p13;q25). Subsequently, we evaluated its suitability as a model for this important clinical entity.

METHODS

Spectral karyotyping, fluorescence in situ hybridization (FISH), and genomic and transcriptomic microarray-based profiling were used to screen for the presence of EN fusions. qRT-PCR was used for quantitative expression analyses. Responses to AZ-23 (NTRK) and wortmannin (PI3K) inhibitors, as well as to arsenic trioxide (ATO), were assessed using colorimetric assays. An AZ-23 microarray screen was used to define the EN targetome, which was parsed bioinformatically. MAPK1 and MALAT1 activation were assayed using Western blotting and RNA-FISH, respectively, whereas an AML patient cohort was used to assess the clinical occurrence of MALAT1 activation.

RESULTS

An EN fusion was detected in AP1060 cells which, accordingly, turned out to be hypersensitive to AZ-23. We also found that AZ-23 can potentiate the effect of ATO and inhibit the phosphorylation of its canonical target MAPK1. The AZ-23 microarray screen highlighted a novel EN target, MALAT1, which also proved sensitive to wortmannin. Finally, we found that MALAT1 was massively up-regulated in a subset of AML patients.

CONCLUSIONS

From our data we conclude that AP-1060 may serve as a first publicly available preclinical model for EN. In addition, we conclude that these EN-positive cells are sensitive to the NTRK inhibitor AZ-23 and that this inhibitor may potentiate the therapeutic efficacy of ATO. Our data also highlight a novel AML EN target, MALAT1, which was so far only conspicuous in solid tumors.

Characterization of immortalized human mammary epithelial cell line HMEC 2.6

Primary human mammary epithelial cells have a limited life span which makes it difficult to study them in vitro for most purposes. To overcome this problem, we have developed a cell line that was immortalized using defined genetic elements, and we have characterized this immortalized non-tumorigenic human mammary epithelial cell line to establish it as a potential model system. human mammary epithelial cells were obtained from a healthy individual undergoing reduction mammoplasty at SIU School of Medicine. The cells were transduced with CDK4R24C followed by transduction with human telomerase reverse transcriptase. Post all manipulation, the cells displayed a normal cell cycle phase distribution and were near diploid in nature, which was confirmed by flow cytometry and karyotyping. In vitro studies showed that the cells were anchorage dependent and were non-invasive in nature. The cell line expressed basal epithelial markers such as cytokeratin 7, CD10, and p63 and was negative for the expression of estrogen receptor and progesterone receptor. Upon G-band karyotyping, the cell line displayed the presence of a few cytogenic abnormalities, including trisomy 20 and trisomy 7, which are also commonly present in other immortalized mammary cell lines. Furthermore, the benign nature of these cells was confirmed by multiple in vitro and in vivo experiments. Therefore, we think that this cell line could serve as a good model to understand the molecular mechanisms involved in the development and progression of breast cancer and to also assess the effect of novel therapeutics on human mammary epithelial cells.

Genome stability of programmed stem cell products

Inherited and acquired genomic abnormalities are known to cause genetic diseases and contribute to cancer formation. Recent studies demonstrated a substantial mutational load in mouse and human embryonic and induced pluripotent stem cells (ESCs and iPSCs). Single nucleotide variants, copy number variations, and larger chromosomal abnormalities may influence the differentiation capacity of pluripotent stem cells and the functionality of their derivatives in disease modeling and drug screening, and are considered a serious risk for cellular therapies based on ESC or iPSC derivatives. This review discusses the types and origins of different genetic abnormalities in pluripotent stem cells, methods for their detection, and the mechanisms of development and enrichment during reprogramming and culture expansion.

Cancer Cytogenetics: An Introduction

The Philadelphia chromosome was the first chromosomal abnormality discovered in cancer using the cytogenetics technique in 1960, and was consistently associated with chronic myeloid leukemia. Over the past five decades, innovative technical advances in the field of cancer cytogenetics have greatly enhanced the detection ability of chromosomal alterations, and have facilitated the research and diagnostic potential of chromosomal studies in neoplasms. These developments notwithstanding, chromosome analysis of a single cell is still the easiest way to delineate and understand the relationship between clonal evolution and disease progression of cancer cells. The use of advanced fluorescence in situ hybridization (FISH) techniques allows for the further identification of chromosomal alterations that are unresolved by the karyotyping method. It overcame many of the drawbacks of assessing the genetic alterations in cancer cells by karyotyping. Subsequently, the development of DNA microarray technologies provides a high-resolution view of the whole genome, which may add massive amounts of new information and opens the field of cancer cytogenomics. Strikingly, cancer cytogenetics does not only provide key information to improve the care of patients with malignancies, but also acts as a guide to identify the genes responsible for the development of these neoplastic states and has led to the emergence of molecularly targeted therapies in the field of personalized medicine.

Chromosome Bandings

Chromosome banding is an essential technique used in chromosome karyotyping to identify normal and abnormal chromosomes for clinical and research purposes. Giemsa (G)-, reverse (R)-, and centromere (C)-banding are the most commonly dye-based chromosome-banding techniques. G-banding involves the staining of trypsin-treated chromosomes and R-banding involves denaturing in hot acidic saline followed by Giemsa staining. C-banding is specifically used for identifying heterochromatin by denaturing chromosomes in a saturated alkaline solution followed by Giemsa staining. Different banding techniques may be selected for the identification of chromosomes.

The current state of molecular cytogenetics in cancer diagnosis

Cytogenetics and molecular cytogenetics are and will continue to be indispensable tools in cancer diagnostics. Leukemia and lymphoma diagnostics are still emphases of routine (molecular) cytogenetics and corresponding studies of solid tumors gain more and more prominence. Here, first a historical perspective of molecular tumor cytogenetics is provided, which is followed by the basic principles of the fluorescence in situ hybridization (FISH) approach. Finally the current state of molecular cytogenetics in cancer diagnostics is discussed. Nowadays routine diagnostics includes basic FISH approaches rather than multicolor-FISH. The latter together with modern high-throughput methods have their impact on research to identify new tumor-associated genomic regions.