Clinical Relevance of the Systematic Analysis of Copy Number Variants in the Genetic Study of Cardiomyopathies.

Cardiomyopathies (CMs), one of the main causes of sudden death among the young population, are a heterogeneous group of myocardial diseases, usually with a genetic cause. Next-Generation Sequencing (NGS) has expanded the genes studied for CMs; however, the yield is still around 50%. The systematic study of Copy Number Variants (CNVs) could contribute to improving our diagnostic capacity. These alterations have already been described as responsible for cardiomyopathies in some cases; however, their impact has been rarely assessed. We analyzed the clinical significance of CNVs in cardiomyopathies by studying 11,647 affected patients, many more than those considered in previously published studies. We evaluated the yield of the systematic study of CNVs in a production context using NGS and a novel CNV detection software tool v2.0 that has demonstrated great efficacy, maximizing sensitivity and avoiding false positives. We obtained a CNV analysis yield of 0.8% that fluctuated depending on the type of cardiomyopathy studied (0.29% HCM, 1.41% DCM, 1.88% ARVC, 1.8% LVNC, 1.45% RCM), and we present the frequency of occurrence for 18 genes that agglutinate the 95 pathogenic/likely pathogenic CNVs detected. We conclude the importance of including in diagnostic tests a systematic study of these genetic alterations for the different cardiomyopathies.

Germline Co-deletion of CDKN2A and CDKN2B Genes in Pleomorphic Xanthoastrocytoma: Case Report.

BACKGROUND/AIM: Gliomas are highly heterogeneous malignancies originating from diverse cell types within the brain. Although their precise etiology is frequently unknown, risk factors, such as chemical exposure, radiation, and specific uncommon genetic disorders have been identified. Diagnosis typically entails imaging tests, such as magnetic resonance imaging and computed tomography, complemented by a biopsy for confirmation, which may be further validated through genetic testing. CASE REPORT: Next-generation sequencing technology revealed germline co-deletion deletion of cyclin-dependent kinase inhibitor 2 A and B genes (CDKN2A and CDKN2B) in a patient diagnosed with pleomorphic xanthoastrocytoma based on the tumor's molecular characteristics. Following this result, we performed focused genetic analysis with use of multiplex ligation-dependent probe amplification technology for the mother that revealed the same co-deletion. Moreover, due to the father's neuroendocrine pancreatic cancer, application of the NGS technology detected a pathogenic variant in the BRCA1-interacting helicase 1 (BRIP1) gene. Comprehensive multi-gene testing conducted within the familial context, marked by a varied spectrum of cancer type, revealed a constellation of genetic predispositions. CONCLUSION: This case study underscores the critical importance of molecular testing for tumor characterization and highlights the pivotal role of genetic testing in facilitating early intervention and screening for at-risk family members. Furthermore, the identification of germline co-deletions in cancer lays the foundation for the development of targeted therapeutic strategies aimed at restoring normal cellular regulation and improving patient management.

Impact of STAT5A-CNVs on growth traits in Chinese beef cattle breeds.

CNVs, which are a type of structural variation, make a substantial impact on diverse characteristics in multiple species. Q-PCR and data association analysis were used for STAT5A gene copy in this study. This study aimed to investigate the copy number variation (CNV) of the STAT5A gene in seven Chinese cattle breeds, namely Qinchuan cattle, Xianan cattle, Yunling cattle, Ji'an cattle, Jiaxian Red cattle, Qaidam cattle, and Guyuan yellow cattle. Blood samples were collected for CNV typing, and the correlation between CNV type and growth traits was analyzed using SPSS 23.0 software and ANOVA. The findings revealed variations in the distribution of different copy number types among the different cattle breeds. Furthermore, association analysis demonstrated a positive impact of CNV in the STAT5A gene on cattle growth: in the JX, individuals with duplication types exhibited superior performance in terms of rump length (P < 0.05). Conversely, normal GY cattle demonstrated better body height and abdomen circumference (P < 0.05), while QD cattle exhibited a significant correlation between weight and body length with normal individuals (P < 0.05). Moreover, QC bovine duplication individuals outperformed other types, with copy number variation significantly associated with chest depth, chest width, and body length (P < 0.05). The results validate the correlation between copy number variation (CNV) of the STAT5A gene and growth characteristics in five different cattle breeds, providing a reliable benchmark for the purpose of cattle breeding.

Chromosomal deletions on 16p11.2 encompassing SH2B1 are associated with accelerated metabolic disease.

New approaches are needed to treat people whose obesity and type 2 diabetes (T2D) are driven by specific mechanisms. We investigate a deletion on chromosome 16p11.2 (breakpoint 2-3 [BP2-3]) encompassing SH2B1, a mediator of leptin and insulin signaling. Phenome-wide association scans in the UK (N = 502,399) and Estonian (N = 208,360) biobanks show that deletion carriers have increased body mass index (BMI; p = 1.3 × 10-10) and increased rates of T2D. Compared with BMI-matched controls, deletion carriers have an earlier onset of T2D, with poorer glycemic control despite higher medication usage. Cystatin C, a biomarker of kidney function, is significantly elevated in deletion carriers, suggesting increased risk of renal impairment. In a Mendelian randomization study, decreased SH2B1 expression increases T2D risk (p = 8.1 × 10-6). We conclude that people with 16p11.2 BP2-3 deletions have early, complex obesity and T2D and may benefit from therapies that enhance leptin and insulin signaling.

Copy Number Variations (CNVs) Account for 10.8% of Pathogenic Variants in Patients Referred for Hereditary Cancer Testing.

BACKGROUND/AIM: Germline copy number variation (CNV) is a type of genetic variant that predisposes significantly to inherited cancers. Today, next-generation sequencing (NGS) technologies have contributed to multi gene panel analysis in clinical practice. MATERIALS AND METHODS: A total of 2,163 patients were screened for cancer susceptibility, using a solution-based capture method. A panel of 52 genes was used for targeted NGS. The capture-based approach enables computational analysis of CNVs from NGS data. We studied the performance of the CNV module of the commercial software suite SeqPilot (JSI Medical Systems) and of the non-commercial tool panelcn.MOPS. Additionally, we tested the performance of digital multiplex ligation-dependent probe amplification (digitalMLPA). RESULTS: Pathogenic/likely pathogenic variants (P/LP) were identified in 464 samples (21.5%). CNV accounts for 10.8% (50/464) of pathogenic variants, referring to deletion/duplication of one or more exons of a gene. In patients with breast and ovarian cancer, CNVs accounted for 10.2% and 6.8% of pathogenic variants, respectively. In colorectal cancer patients, CNV accounted for 28.6% of pathogenic/likely pathogenic variants. CONCLUSION: In silico CNV detection tools provide a viable and cost-effective method to identify CNVs from NGS experiments. CNVs constitute a substantial percentage of P/LP variants, since they represent up to one of every ten P/LP findings identified by NGS multigene analysis; therefore, their evaluation is highly recommended to improve the diagnostic yield of hereditary cancer analysis.

SEC24D gene as a biomarker in human cancers and its association with CD8+ T cell immune cell infiltration.

OBJECTIVE: The SEC24D (SEC24 Homolog D, COPII Coat Complex Component) gene belongs to the SEC24 subfamily of genes. The protein encoded by this gene, along with its other binding partners, mediates the transport of newly-synthesized proteins from the endoplasmic reticulum to the Golgi apparatus. METHODS: A pan-cancer analysis of this gene, as well as its diagnostic and prognostic implications, are lacking in the medical literature. First, we analyzed SEC24D gene expression, its prognostic effect, promoter methylation level, genetic alteration landscape, pathways, CD8+ T immune cell infiltration, and gene-drug network in various types of cancer through various online databases and bioinformatic tools. Then, we performed the expression and methylation validation analysis of the SEC24D gene on cell lines using RNA sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq) techniques. RESULTS: Bioinformatic analysis showed that the SEC24D gene was overexpressed in metastasis across Kidney Renal Clear Cell Carcinoma (KIRC), Lung Squamous Cell Carcinoma (LUSC), and Stomach Adenocarcinoma (STAD) patients and was a prognostic risk factor. Then, using RNA sequencing and targeted bisulfite sequencing analysis, it was validated in cell lines that SEC24D was overexpressed and hypomethylated in KIRC patients. Mutational analysis revealed that SEC24D was mutated less frequently in KIRC, LUSC, and STAD patients. It was further observed that CD8+ T cell infiltration levels were increased in SEC24D-overexpressed KIRC, LUSC, and STAD samples. Pathway enrichment analysis of SEC24D-associated genes revealed their participation in two important pathways. Moreover, we suggested a few valuable drugs for treating KIRC, LUSC, and STAD patients with respect to overexpressed SEC24D. CONCLUSION: This is the first pan-cancer study that details the oncogenic roles of SEC24D among different cancers.

Identification and Molecular Characterization of a Novel Large-Scale Variant (Exons 4_18 Loss) in the LDLR Gene as a Cause of Familial Hypercholesterolaemia in an Italian Family.

Next-generation sequencing (NGS) is nowadays commonly used for clinical purposes, and represents an efficient approach for the molecular diagnosis of familial hypercholesterolemia (FH). Although the dominant form of the disease is mostly due to the low-density lipoprotein receptor (LDLR) small-scale pathogenic variants, the copy number variations (CNVs) represent the underlying molecular defects in approximately 10% of FH cases. Here, we reported a novel large deletion in the LDLR gene involving exons 4-18, identified by the bioinformatic analysis of NGS data in an Italian family. A long PCR strategy was employed for the breakpoint region analysis where an insertion of six nucleotides (TTCACT) was found. Two Alu sequences, identified within intron 3 and exon 18, could underlie the identified rearrangement by a nonallelic homologous recombination (NAHR) mechanism. NGS proved to be an effective tool suitable for the identification of CNVs, together with small-scale alterations in the FH-related genes. For this purpose, the use and implementation of this cost-effective, efficient molecular approach meets the clinical need for personalized diagnosis in FH cases.

Landscape of the intratumroal microenvironment in bladder cancer: Implications for prognosis and immunotherapy.

Introduction: This study aims to present the landscape of the intratumoral microenvironment and by which establish a classification system that can be used to predict the prognosis of bladder cancer patients and their response to anti-PD-L1 immunotherapy. Methods: The expression profiles of 1554 bladder cancer cases were downloaded from seven public datasets. Single-sample gene set enrichment analysis (ssGSEA), univariate Cox regression analysis, and meta-analysis were employed to establish the bladder cancer immune prognostic index (BCIPI). Extensive analyses were executed to investigate the association between BCIPI and overall survival, tumor-infiltrated immunocytes, immunotherapeutic response, mutation load, etc. Results: The results obtained from seven independent cohorts and meta-analyses suggested that the BCIPI is an effective classification system for estimating bladder cancer patients' overall survival. Patients in the BCIPI-High subgroup revealed different immunophenotypic outcomes from those in the BCIPI-Low subgroup regarding tumor-infiltrated immunocytes and mutated genes. Subsequent analysis suggested that patients in the BCIPI-High subgroup were more sensitive to anti-PD-L1 immunotherapy than those in the BCIPI-Low subgroup. Conclusions: The newly established BCIPI is a valuable tool for predicting overall survival outcomes and immunotherapeutic responses in patients with bladder cancer.

Pathogenic/likely pathogenic copy number variations and regions of homozygosity in fetal central nervous system malformations.

OBJECTIVE: To explore pathogenic/likely pathogenic copy number variations (P/LP CNVs) and regions of homozygosity (ROHs) in fetal central nervous system (CNS) malformations. METHODS: A cohort of 539 fetuses with CNS malformations diagnosed by ultrasound/MRI was retrospectively analyzed between January 2016 and December 2019. All fetuses were analyzed by chromosomal microarray analysis (CMA). Three cases with ROHs detected by CMA were subjected to whole-exome sequencing (WES). The fetuses were divided into two groups according to whether they had other structural abnormalities. The CNS phenotypes of the two groups were further classified as simple (one type) or complicated (≥ 2 types). RESULTS: (1) A total of 35 cases with P/LP CNVs were found. The incidence of P/LP CNVs was higher in the extra-CNS group [18.00% (9/50)] than in the isolated group [5.32% (26/489)] (P < 0.01), while there was no significant difference between the simpletype and complicated-type groups. (2) In the simple-type group, the three most common P/LP CNV phenotypes were holoprosencephaly, Dandy-Walker syndrome, and exencephaly. There were no P/LP CNVs associated with anencephaly, microcephaly, arachnoid cysts, ependymal cysts, or intracranial hemorrhage. (3) Only four cases with ROHs were found, and there were no cases of uniparental disomy or autosomal diseases. CONCLUSION: The P/LP CNV detection rates varied significantly among the different phenotypes of CNS malformations, although simple CNS abnormalities may also be associated with genetic abnormalities.

Copy Number Variations in Pancreatic Cancer: From Biological Significance to Clinical Utility.

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, characterized by high tumor heterogeneity and a poor prognosis. Inter- and intra-tumoral heterogeneity in PDAC is a major obstacle to effective PDAC treatment; therefore, it is highly desirable to explore the tumor heterogeneity and underlying mechanisms for the improvement of PDAC prognosis. Gene copy number variations (CNVs) are increasingly recognized as a common and heritable source of inter-individual variation in genomic sequence. In this review, we outline the origin, main characteristics, and pathological aspects of CNVs. We then describe the occurrence of CNVs in PDAC, including those that have been clearly shown to have a pathogenic role, and further highlight some key examples of their involvement in tumor development and progression. The ability to efficiently identify and analyze CNVs in tumor samples is important to support translational research and foster precision oncology, as copy number variants can be utilized to guide clinical decisions. We provide insights into understanding the CNV landscapes and the role of both somatic and germline CNVs in PDAC, which could lead to significant advances in diagnosis, prognosis, and treatment. Although there has been significant progress in this field, understanding the full contribution of CNVs to the genetic basis of PDAC will require further research, with more accurate CNV assays such as single-cell techniques and larger cohorts than have been performed to date.

Maternal Copy Number Imbalances in Non-Invasive Prenatal Testing: Do They Matter?

Non-invasive prenatal testing (NIPT) has become a routine practice in screening for common aneuploidies of chromosomes 21, 18, and 13 and gonosomes X and Y in fetuses worldwide since 2015 and has even expanded to include smaller subchromosomal events. In fact, the fetal fraction represents only a small proportion of cell-free DNA on a predominant background of maternal DNA. Unlike fetal findings that have to be confirmed using invasive testing, it has been well documented that NIPT provides information on maternal mosaicism, occult malignancies, and hidden health conditions due to copy number variations (CNVs) with diagnostic resolution. Although large duplications or deletions associated with certain medical conditions or syndromes are usually well recognized and easy to interpret, very little is known about small, relatively common copy number variations on the order of a few hundred kilobases and their potential impact on human health. We analyzed data from 6422 NIPT patient samples with a CNV detection resolution of 200 kb for the maternal genome and identified 942 distinct CNVs; 328 occurred repeatedly. We defined them as multiple occurring variants (MOVs). We scrutinized the most common ones, compared them with frequencies in the gnomAD SVs v2.1, dbVar, and DGV population databases, and analyzed them with an emphasis on genomic content and potential association with specific phenotypes.

Mapping the genetic features of T-ALL cases through simplified NGS approach.

BACKGROUND: Despite the irruption of massive sequencing technologies in clinical routine, the genetic diagnosis of T-cell acute lymphoblastic leukemia (T-ALL) continues to be based on traditional techniques. The integration of old and new technologies with diagnostic and prognostic purposes represents a major challenge. METHODS: A High-Throughput Sequencing (HTS) approach was applied to analyze the genetic landscape of two patients diagnosed with T-ALL and one early T cell precursor acute leukemia. Orthogonal standard techniques were used to confirm the findings of NGS analysis. RESULTS: By using a single test, a complete genetic map including 2 previously unreported missense mutations in BCL11B gene are reported. Cooperating oncogenic lesions including CDKN2A/B deletions, SIL-TAL1 rearrangement and FLT3 amplification were also captured by using a single test. CONCLUSIONS: HTS is a useful approach that allows simultaneously analyzing mutations, CNVs and the clonal repertoire in T-ALL patients. This approach may simplify the genetic assessment of ALL.

Genomic mapping of copy number variations influencing immune response in breast cancer.

Identification of genomic alterations that influence the immune response within the tumor microenvironment is mandatory in order to identify druggable vulnerabilities. In this article, by interrogating public genomic datasets we describe copy number variations (CNV) present in breast cancer (BC) tumors and corresponding subtypes, associated with different immune populations. We identified regulatory T-cells associated with the Basal-like subtype, and type 2 T-helper cells with HER2 positive and the luminal subtype. Using gene set enrichment analysis (GSEA) for the Type 2 T-helper cells, the most relevant processes included the ERBB2 signaling pathway and the Fibroblast Growth Factor Receptor (FGFR) signaling pathway, and for CD8+ T-cells, cellular response to growth hormone stimulus or the JAK-STAT signaling pathway. Amplification of ERBB2, GRB2, GRB7, and FGF receptor genes strongly correlated with the presence of type 2 T helper cells. Finally, only 8 genes were highly upregulated and present in the cellular membrane: MILR1, ACE, DCSTAMP, SLAMF8, CD160, IL2RA, ICAM2, and SLAMF6. In summary, we described immune populations associated with genomic alterations with different BC subtypes. We observed a clear presence of inhibitory cells, like Tregs or Th2 when specific chromosomic regions were amplified in basal-like or HER2 and luminal groups. Our data support further evaluation of specific therapeutic strategies in specific BC subtypes, like those targeting Tregs in the basal-like subtype.

Copy Number Variation of Circulating Tumor DNA (ctDNA) Detected Using NIPT in Neoadjuvant Chemotherapy-Treated Ovarian Cancer Patients.

Analysis of circulating tumor DNA (ctDNA) can be used to characterize and monitor cancers. Recently, non-invasive prenatal testing (NIPT) as a new next-generation sequencing (NGS)-based approach has been applied for detecting ctDNA. This study aimed to investigate the copy number variations (CNVs) utilizing the non-invasive prenatal testing in plasma ctDNA from ovarian cancer (OC) patients who were treated with neoadjuvant chemotherapy (NAC). The plasma samples of six patients, including stages II-IV, were collected during the pre- and post-NAC treatment that were divided into NAC-sensitive and NAC-resistant groups during the follow-up time. CNV analysis was performed using the NIPT via two methods "an open-source algorithm WISECONDORX and NextGENe software." Results of these methods were compared in pre- and post-NAC of OC patients. Finally, bioinformatics tools were used for data mining from The Cancer Genome Atlas (TCGA) to investigate CNVs in OC patients. WISECONDORX analysis indicated fewer CNV changes on chromosomes before treatment in the NAC-sensitive rather than NAC-resistant patients. NextGENe data indicated that CNVs are not only observed in the coding genes but also in non-coding genes. CNVs in six genes were identified, including HSF1, TMEM249, MROH1, GSTT2B, ABR, and NOMO2, only in NAC-resistant patients. The comparison of these six genes in NAC-resistant patients with The Cancer Genome Atlas data illustrated that the total alteration frequency is amplification, and the highest incidence of the CNVs (≥35% based on TCGA data) is found in MROH1, TMEM249, and HSF1 genes on the chromosome (Chr) 8. Based on TCGA data, survival analysis showed a significant reduction in the overall survival among chemotherapy-resistant patients as well as a high expression level of these three genes compared to that of sensitive samples (all, p < 0.0001). The continued Chr8 study using WISECONDORX revealed CNV modifications in NAC-resistant patients prior to NAC therapy, but no CNV changes were observed in NAC-sensitive individuals. Our findings showed that low coverage whole-genome sequencing analysis used for NIPT could identify CNVs in ctDNA of OC patients before and after chemotherapy. These CNVs are different in NAC-sensitive and -resistant patients highlighting the potential application of this approach in cancer patient management.

BoBafit : A copy number clustering tool designed to refit and recalibrate the baseline region of tumors' profiles.

Human cancer arises from a population of cells that have acquired a wide range of genetic alterations, most of which are targets of therapeutic treatments or are used as prognostic factors for patient's risk stratification. Among these, copy number alterations (CNAs) are quite frequent. Currently, several molecular biology technologies, such as microarrays, NGS and single-cell approaches are used to define the genomic profile of tumor samples. Output data need to be analyzed with bioinformatic approaches and particularly by employing computational algorithms. Molecular biology tools estimate the baseline region by comparing either the mean probe signals, or the number of reads to the reference genome. However, when tumors display complex karyotypes, this type of approach could fail the baseline region estimation and consequently cause errors in the CNAs call. To overcome this issue, we designed an R-package, BoBafit , able to check and, eventually, to adjust the baseline region, according to both the tumor-specific alterations' context and the sample-specific clustered genomic lesions. Several databases have been chosen to set up and validate the designed package, thus demonstrating the potential of BoBafit to adjust copy number (CN) data from different tumors and analysis techniques. Relevantly, the analysis highlighted that up to 25% of samples need a baseline region adjustment and a redefinition of CNAs calls, thus causing a change in the prognostic risk classification of the patients. We support the implementation of BoBafit within CN analysis bioinformatics pipelines to ensure a correct patient's stratification in risk categories, regardless of the tumor type.

Reliability of Cell-Free DNA and Targeted NGS in Predicting Chromosomal Abnormalities of Patients With Myeloid Neoplasms.

Introduction: Cytogenetic analysis is important for stratifying patients with various neoplasms. We explored the use of targeted next generation sequencing (NGS) in detecting chromosomal structural abnormalities or copy number variations (CNVs) in patients with myeloid neoplasms. Methods: Plasma cell-free DNA (cfDNA) from 2821 myeloid or lymphoid neoplasm patients were collected. cfDNA was sequenced using a 275 gene panel. CNVkit software was used for analyzing and visualizing CNVs. Cytogenetic data from corresponding bone marrow (BM) samples was available on 89 myeloid samples. Results: Of the 2821 samples, 1539 (54.5%) showed evidence of mutations consistent with the presence of neoplastic clones in circulation. Of these 1539 samples, 906 (59%) showed abnormalities associated with myeloid neoplasms and 633 (41%) with lymphoid neoplasms. Chromosomal structural abnormalities in cfDNA were detected in 146 (16%) myeloid samples and 76 (12%) lymphoid samples. Upon comparison of the myeloid samples with 89 BM patients, NGS testing was able to reliably detect chromosomal gain or loss, except for fusion abnormalities. When cytogenetic abnormalities were classified according to prognostic classes, there was a complete (100%) concordance between cfDNA NGS data and cytogenetic data. Conclusions: This data shows that liquid biopsy using targeted NGS is reliable in detecting chromosomal structural abnormalities in myeloid neoplasms. In specific circumstances, targeted NGS may be reliable and efficient to provide adequate information without the need for BM biopsy considering broad mutation profiling can be obtained through adequate sequencing within the same test. Overall, this study supports the use of liquid biopsy for early diagnosis and monitoring of patients with myeloid neoplasms.

CNV assessments associated with outcome distinctions for adult and pediatric cancers: Loss of BRCA1 in neuroblastoma associates with a lower survival probability.

DNA copy number variations (CNV) are common in cancer development, however, CNV detection approaches that include assessments of small CNVs, for example, due to locally misaligned sister chromatid exchanges, have not been substantially applied. Using such approaches, CNVs have been detected, in the cancer setting, for regulatory elements common to both proliferation and apoptosis effector genes, but no linkage has yet been made to cancer patient clinical data. Thus, we hypothesized that copy number losses, including local copy number losses, of specific apoptosis effector genes would be associated with reduced survival. Both whole genome and whole exome files were processed for validations and consistency. Results indicated lower late-stage survival for multiple myeloma cases representing reduced BAD and CASP3 copies, as well as for lung adenocarcinoma cases representing reduced BAX and CASP3 copies. Results also indicated that neuroblastoma (NBL) cases representing reduced copies of CASP9 and BRCA1 had reduced overall survival probabilities, with the BRCA1 results being particularly notable due to previous reports of BRCA1 inactivating mutations in NBL. Overall, novel approaches to assessing CNVs offers the promise of establishing patient risk stratifications and of identifying single genes or other small spaces in the genome where a CNV may be linked to specific outcomes.

Genomic Profile in a Non-Seminoma Testicular Germ-Cell Tumor Cohort Reveals a Potential Biomarker of Sensitivity to Platinum-Based Therapy.

Despite having a favorable response to platinum-based chemotherapies, ~15% of Testicular Germ-Cell Tumor (TGCT) patients are platinum-resistant. Mortality rates among Latin American countries have remained constant over time, which makes the study of this population of particular interest. To gain insight into this phenomenon, we conducted whole-exome sequencing, microarray-based comparative genomic hybridization, and copy number analysis of 32 tumors from a Mexican cohort, of which 18 were platinum-sensitive and 14 were platinum-resistant. We incorporated analyses of mutational burden, driver mutations, and SNV and CNV signatures. DNA breakpoints in genes were also investigated and might represent an interesting research opportunity. We observed that sensitivity to chemotherapy does not seem to be explained by any of the mutations detected. Instead, we uncovered CNVs, particularly amplifications on segment 2q11.1 as a novel variant with chemosensitivity biomarker potential. Our data shed light into understanding platinum resistance in a Latin-origin population.

Panel Sequencing for Clinically Oriented Variant Screening and Copy Number Detection in Chronic Lymphocytic Leukemia Patients.

According to current guidelines, in chronic lymphocytic leukemia (CLL), only the TP53 molecular status must be evaluated prior to every treatment's initiation. However, additional heterogeneous genetic events are known to confer a proliferative advantage to the tumor clone and are associated with progression and treatment failure in CLL patients. Here, we describe the implementation of a comprehensive targeted sequencing solution that is suitable for routine clinical practice and allows for the detection of the most common somatic single-nucleotide and copy number variants in genes relevant to CLL. We demonstrate that this cost-effective strategy achieves variant detection with high accuracy, specificity, and sensitivity. Furthermore, we identify somatic variants and copy number variations in genes with prognostic and/or predictive value, according to the most recent literature, and the tool provides evidence about subclonal events. This next-generation sequencing (NGS) capture-based target assay is an improvement on current approaches in defining molecular prognostic and/or predictive variables in CLL patients.

CRIA: An Interactive Gene Selection Algorithm for Cancers Prediction Based on Copy Number Variations.

Genomic copy number variations (CNVs) are among the most important structural variations of genes found to be related to the risk of individual cancer and therefore they can be utilized to provide a clue to the research on the formation and progression of cancer. In this paper, an improved computational gene selection algorithm called CRIA (correlation-redundancy and interaction analysis based on gene selection algorithm) is introduced to screen genes that are closely related to cancer from the whole genome based on the value of gene CNVs. The CRIA algorithm mainly consists of two parts. Firstly, the main effect feature is selected out from the original feature set that has the largest correlation with the class label. Secondly, after the analysis involving correlation, redundancy and interaction for each feature in the candidate feature set, we choose the feature that maximizes the value of the custom selection criterion and add it into the selected feature set and then remove it from the candidate feature set in each selection round. Based on the real datasets, CRIA selects the top 200 genes to predict the type of cancer. The experiments' results of our research show that, compared with the state-of-the-art related methods, the CRIA algorithm can extract the key features of CNVs and a better classification performance can be achieved based on them. In addition, the interpretable genes highly related to cancer can be known, which may provide new clues at the genetic level for the treatment of the cancer.