Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV

Genetic and epigenetic alterations in precursor lesions of endometrial endometrioid carcinoma

The hyperplasia-carcinoma sequence is a stepwise tumourigenic programme towards endometrial cancer in which normal endometrial epithelium becomes neoplastic through non-atypical endometrial hyperplasia (NAEH) and atypical endometrial hyperplasia (AEH), under the influence of unopposed oestrogen. NAEH and AEH are known to exhibit polyclonal and monoclonal cell growth, respectively; yet, aside from focal PTEN protein loss, the genetic and epigenetic alterations that occur during the cellular transition remain largely unknown. We sought to explore the potential molecular mechanisms that promote the NAEH-AEH transition and identify molecular markers that could help to differentiate between these two states. We conducted target-panel sequencing on the coding exons of 596 genes, including 96 endometrial cancer driver genes, and DNA methylome microarrays for 48 NAEH and 44 AEH lesions that were separately collected via macro- or micro-dissection from the endometrial tissues of 30 cases. Sequencing analyses revealed acquisition of the PTEN mutation and the clonal expansion of tumour cells in AEH samples. Further, across the transition, alterations to the DNA methylome were characterised by hypermethylation of promoter/enhancer regions and CpG islands, as well as hypo- and hyper-methylation of DNA-binding regions for transcription factors relevant to endometrial cell differentiation and/or tumourigenesis, including FOXA2, SOX17, and HAND2. The identified DNA methylation signature distinguishing NAEH and AEH lesions was reproducible in a validation cohort with modest discriminative capability. These findings not only support the concept that the transition from NAEH to AEH is an essential step within neoplastic cell transformation of endometrial epithelium but also provide deep insight into the molecular mechanism of the tumourigenic programme. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Comprehensive molecular characterization of long-term glioblastoma survivors

Fewer than 5 % glioblastoma (GBM) patients survive over five years and are termed long-term survivors (LTS), yet their molecular background is unclear. The present cohort included 72 isocitrate dehydrogenase (IDH)-wildtype GBM patients, consisting of 35 LTS and 37 short-term survivors (STS), and we employed whole exome sequencing, RNA-seq and DNA methylation array to delineate this largest LTS cohort to date. Although LTS and STS demonstrated analogous clinical characters and classical GBM biomarkers, CASC5 (P = 0.002) and SPEN (P = 0.013) mutations were enriched in LTS, whereas gene-to-gene fusions were concentrated in STS (P = 0.007). Importantly, LTS exhibited higher tumor mutation burden (P < 0.001) and copy number (CN) increase (P = 0.013), but lower mutant-allele tumor heterogeneity score (P < 0.001) and CN decrease (P = 0.026). Additionally, LTS demonstrated hypermethylated genome (P < 0.001) relative to STS. Differentially expressed and methylated genes both enriched in olfactory transduction. Further, analysis of the tumor microenvironment revealed higher infiltration of M1 macrophages (P = 0.043), B cells (P = 0.016), class-switched memory B cells (P = 0.002), central memory CD4+ T cells (P = 0.031) and CD4+ Th1 cells (P = 0.005) in LTS. We also separately analyzed a subset of patients who were methylation class-defined GBM, contributing 70.8 % of the entire cohort, and obtained similar results relative to prior analyses. Finally, we demonstrated that LTS and STS could be distinguished using a subset of molecular features. Taken together, the present study delineated unique molecular attributes of LTS GBM.

Whole-exome sequencing has revealed novel genetic characteristics in intracranial germ cell tumours in the Chinese

AIMS

Intracranial germ cell tumour (IGCT) is a type of rare central nervous system tumour that mainly occurs in children and adolescents, with great variation in its incidence rate and molecular characteristics in patients from different populations. The genetic alterations of IGCT in the Chinese population are still unknown.

METHODS AND RESULTS

In this study, 47 patients were enrolled and their tumour specimens were analysed by whole-exome sequencing (WES). We found that KIT was the most significantly mutated gene (15/47, 32%), which mainly occurred in the germinoma group (13/20, 65%), and less frequently in NGGCT (2/27, 7%). Copy number variations (CNVs) of FGF6 and TFE3 only appeared in NGGCT patients (P = 0.003 and 0.032, respectively), while CNVs of CXCR4, RAC2, PDGFA, and FEV only appeared in germinoma patients (P = 0.004 of CXCR4 and P = 0.027 for the last three genes). Compared with a previous Japanese cohort, the somatic mutation rates of RELN and SYNE1 were higher in the Chinese. Prognostic analysis showed that the NF1 mutation was associated with shorter overall survival and progression-free survival in IGCT patients. Clonal evolution analysis revealed an early branched evolutionary pattern in two IGCT patients who underwent changes in the histological subtype or degree of differentiation during disease surveillance.

CONCLUSION

This study indicated that Chinese IGCT patients may have distinct genetic characteristics and identified several possible genetic alterations that have the potential to become prognostic biomarkers of NGGCT patients.

Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches

Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.

Copy number variation analysis in 138 families with steroid-resistant nephrotic syndrome identifies causal homozygous deletions in PLCE1 and NPHS2 in two families

BACKGROUND

Steroid-resistant nephrotic syndrome (SRNS) is the second most common cause of kidney failure in children and adults under the age of 20 years. Previously, we were able to detect by exome sequencing (ES) a known monogenic cause of SRNS in 25-30% of affected families. However, ES falls short of detecting copy number variants (CNV). Therefore, we hypothesized that causal CNVs could be detected in a large SRNS cohort.

METHODS

We performed genome-wide single nucleotide polymorphism (SNP)-based CNV analysis on a cohort of 138 SRNS families, in whom we previously did not identify a genetic cause through ES. We evaluated ES and CNV data for variants in 60 known SRNS genes and in 13 genes in which variants are known to cause a phenocopy of SRNS. We applied previously published, predefined criteria for CNV evaluation.

RESULTS

We detected a novel CNV in two genes in 2 out of 138 families (1.5%). The 9,673 bp homozygous deletion in PLCE1 and the 6,790 bp homozygous deletion in NPHS2 were confirmed across the breakpoints by PCR and Sanger sequencing.

CONCLUSIONS

We confirmed that CNV analysis can identify the genetic cause in SRNS families that remained unsolved after ES. Though the rate of detected CNVs is minor, CNV analysis can be used when there are no other genetic causes identified. Causative CNVs are less common in SRNS than in other monogenic kidney diseases, such as congenital anomalies of the kidneys and urinary tract, where the detection rate was 5.3%. A higher resolution version of the Graphical abstract is available as Supplementary information.

OTSUCNV: an adaptive segmentation and OTSU-based anomaly classification method for CNV detection using NGS data

Copy-number variations (CNVs), which refer to deletions and duplications of chromosomal segments, represent a significant source of variation among individuals, contributing to human evolution and being implicated in various diseases ranging from mental illness and developmental disorders to cancer. Despite the development of several methods for detecting copy number variations based on next-generation sequencing (NGS) data, achieving robust detection performance for CNVs with arbitrary coverage and amplitude remains challenging due to the inherent complexity of sequencing samples. In this paper, we propose an alternative method called OTSUCNV for CNV detection on whole genome sequencing (WGS) data. This method utilizes a newly designed adaptive sequence segmentation algorithm and an OTSU-based CNV prediction algorithm, which does not rely on any distribution assumptions or involve complex outlier factor calculations. As a result, the effective detection of CNVs is achieved with lower computational complexity. The experimental results indicate that the proposed method demonstrates outstanding performance, and hence it may be used as an effective tool for CNV detection.

Genetic landscape and PD-L1 expression in Epstein-Barr virus-associated gastric cancer according to the histological pattern

Epstein-Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer. This study aims to investigate genomic and clinicopathological characteristics of EBVaGC according to the histological pattern. We retrospectively collected 18 specimens of surgically resected EBVaGCs. Whole-exome sequencing was performed for all cases. Moreover, PD-L1 expression and tumor-infiltrating lymphocyte (TIL) percentage were investigated. Among 18 EBVaGCs, 10 cases were of intestinal histology, 3 were of poorly cohesive histology, and the remaining 5 were of gastric carcinoma with lymphoid stroma histology. Whole-exome sequencing revealed that EBVaGCs with intestinal histology harbored pathogenic mutations known to frequently occur in tubular or papillary adenocarcinoma, including TP53, KRAS, FBXW7, MUC6, ERBB2, CTNNB1, and ERBB2 amplifications. One patient with poorly cohesive carcinoma histology harbored a CDH1 mutation. Patients with EBVaGCs with intestinal or poorly cohesive carcinoma histology frequently harbored driver mutations other than PIK3CA, whereas those with EBVaGCs with gastric carcinoma with lymphoid stroma histology lacked other driver mutations. Moreover, the histological pattern of EBVaGCs was significantly associated with the levels of TILs (P = 0.005) and combined positive score (P = 0.027). In conclusion, patients with EBVaGCs with different histological patterns exhibited distinct genetic alteration, PD-L1 expression, and degree of TILs.

Super-enhancer hijacking drives ectopic expression of hedgehog pathway ligands in meningiomas

Hedgehog signaling mediates embryologic development of the central nervous system and other tissues and is frequently hijacked by neoplasia to facilitate uncontrolled cellular proliferation. Meningiomas, the most common primary brain tumor, exhibit Hedgehog signaling activation in 6.5% of cases, triggered by recurrent mutations in pathway mediators such as SMO. In this study, we find 35.6% of meningiomas that lack previously known drivers acquired various types of somatic structural variations affecting chromosomes 2q35 and 7q36.3. These cases exhibit ectopic expression of Hedgehog ligands, IHH and SHH, respectively, resulting in Hedgehog signaling activation. Recurrent tandem duplications involving IHH permit de novo chromatin interactions between super-enhancers within DIRC3 and a locus containing IHH. Our work expands the landscape of meningioma molecular drivers and demonstrates enhancer hijacking of Hedgehog ligands as a route to activate this pathway  in neoplasia.

Longitudinal multi-omics study of palbociclib resistance in HR-positive/HER2-negative metastatic breast cancer

BACKGROUND

Cyclin-dependent kinase 4/6 inhibitor (CDK4/6) therapy plus endocrine therapy (ET) is an effective treatment for patients with hormone receptor-positive/human epidermal receptor 2-negative metastatic breast cancer (HR+/HER2- MBC); however, resistance is common and poorly understood. A comprehensive genomic and transcriptomic analysis of pretreatment and post-treatment tumors from patients receiving palbociclib plus ET was performed to delineate molecular mechanisms of drug resistance.

METHODS

Tissue was collected from 89 patients with HR+/HER2- MBC, including those with recurrent and/or metastatic disease, receiving palbociclib plus an aromatase inhibitor or fulvestrant at Samsung Medical Center and Seoul National University Hospital from 2017 to 2020. Tumor biopsy and blood samples obtained at pretreatment, on-treatment (6 weeks and/or 12 weeks), and post-progression underwent RNA sequencing and whole-exome sequencing. Cox regression analysis was performed to identify the clinical and genomic variables associated with progression-free survival.

RESULTS

Novel markers associated with poor prognosis, including genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four prognostic clusters with distinct molecular features were identified. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly to palbociclib plus ET. Comparisons of paired pre- and post-treatment samples revealed that tumors became enriched in APOBEC mutation signatures, and many switched to aggressive molecular subtypes with estrogen-independent characteristics. We identified frequent genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C.

CONCLUSIONS

We identified novel molecular features associated with poor prognosis and molecular mechanisms that could be targeted to overcome resistance to CKD4/6 plus ET.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03401359. The trial was posted on 18 January 2018 and registered prospectively.

A Clinician's Guide to Bioinformatics for Next-Generation Sequencing

Next-generation sequencing (NGS) technologies are high-throughput methods for DNA sequencing and have become a widely adopted tool in cancer research. The sheer amount and variety of data generated by NGS assays require sophisticated computational methods and bioinformatics expertise. In this review, we provide background details of NGS technology and basic bioinformatics concepts for the clinician investigator interested in cancer research applications, with a focus on DNA-based approaches. We introduce the general principles of presequencing library preparation, postsequencing alignment, and variant calling. We also highlight the common variant annotations and NGS applications for other molecular data types. Finally, we briefly discuss the revealed utility of NGS methods in NSCLC research and study design considerations for research studies that aim to leverage NGS technologies for clinical care.

Multi-region sequencing depicts intratumor heterogeneity and clonal evolution in cervical cancer

Cervical cancer is a heterogeneous malignancy mainly caused by human papillomavirus (HPV). While a few studies have revealed heterogeneity of cervical cancer in chromosome levels, the correlation between genetic heterogeneity and HPV integration in cervical cancer remains unknown. Here, we applied multi-region whole-exome sequencing and HPV integration analysis to explore intratumor heterogeneity in cervical cancer. We sequenced 20 tumor regions and 5 adjacent normal tissues from 5 cervical cancer patients, analysis based on somatic mutations and somatic copy number alterations (SCNAs) levels were performed. Variable heterogeneity was observed between the five patients with different tumor stages and HPV infection statuses. We found HPV integration has a positive effect on somatic mutation burden, but the relation to SCNAs remains unclear. Frequently mutated genes in cervical cancer were identified as trunk events, such as FBXW7, PIK3CA, FAT1 in somatic mutations and TP63, MECOM, PIK3CA, TBL1XR1 in SCNAs. New potential driver genes in cervical cancer were summarized including POU2F2, TCF7 and UBE2A. The SCNAs level has potential relation with tumor stage, and Signature 3 related to homologous recombination deficiency may be the appropriate biomarker in advanced cervical cancer. Mutation signature analysis also revealed a potential pattern that APOBEC-associated signature occurs in early stage and signatures associated with DNA damage repair arise at the later stage of cervical cancer evolution. In a conclusion, our study provides insights into the potential relationship between HPV infection and tumor heterogeneity. Those results enhanced our understanding of tumorigenesis and progression in cervical cancer.

Efficacy and safety of a triple combination of atezolizumab, bevacizumab plus GEMOX for advanced biliary tract cancer: a multicenter, single-arm, retrospective study

Background

Anti-programmed cell death ligand 1/vascular endothelial growth factor inhibition, coupled with chemotherapy, may potentiate antitumor immunity leading to enhanced clinical benefit, but it has not been investigated in advanced biliary tract cancer (BTC).

Objectives

We investigated the efficacy and safety of atezolizumab, bevacizumab, and gemcitabine plus oxaliplatin (GEMOX) in advanced BTC and explore the potential biomarkers related to the response.

Design

Multicenter, single-arm, retrospective study.

Methods

Advanced BTC patients, who received a triple combination therapy at three medical centers between 18 March 2020 and 1 September 2021, were included. Treatment response was evaluated via mRECIST and RECIST v1.1. Endpoints included the overall response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and safety. The whole exome sequencing of pathological tissues was conducted for bioinformatic analysis.

Results

In all, 30 patients were enrolled. The best ORR was 76.7% and the DCR was 90.0%. The median PFS was 12.0 months, and the median OS was not reached. During the treatment, 10.0% (3/30) of patients suffered from ⩾grade 3 treatment-related adverse events (TRAEs). Furthermore, fever (73.3%), neutropenia (63.3%), increased aspartate transaminase and alanine aminotransferase levels (50.0% and 43.3%, respectively) are the most common TRAEs. Bioinformatics analysis revealed patients with altered ALS2CL had a higher ORR.

Conclusion

The triple combination of atezolizumab, bevacizumab, and GEMOX may be efficacious and safe for patients with advanced BTC. ALS2CL may be a potential predictive biomarker for the efficacy of triple combination therapy.

Whole-exome sequencing identifies a set of genes as markers of hepatocellular carcinoma early recurrence

BACKGROUND

Hepatocellular carcinoma (HCC) is characterized by a high recurrence rate and poor prognosis. In recent years, the therapeutic regimen of programmed cell death protein 1 (PD-1) antibody combined with multi-targeted tyrosine kinase inhibitors (mTKIs) has achieved better results in the clinical application of hepatocellular carcinoma. Whole-exome sequencing can reflect the mutational characteristics of patients' exons and guide the clinical selection of molecular targeting drugs more accurately, which is in line with the concept of precision medicine.

METHODS

We performed exome sequencing on 63 patients with HCC treated with radical surgery at our hospital and collected their clinical indexes and postoperative follow-up data. Using machine learning, a prediction model for recurrence within 1 year was constructed and the model was presented in a nomogram. Patients treated with PD-1 antibodies in combination with mTKIs after relapse were grouped by prognosis, and the valuable mutated genes were screened according to whole-exome sequencing data. The tumor tissue immune cells were analyzed using the UCSC Xena database. The expressions of target proteins were verified by Polymerase Chain Reaction (PCR) and Immunohistochemistry (IHC), respectively, on commercial HCC cell lines and pathological specimens of hepatocellular carcinoma collected clinically.

RESULTS

The proportion of patients who relapsed within a year was 41% and the prognosis of those patients was poor. The characteristic exon mutation profile with a high frequency of variants in multiple mucin genes was present in Chinese HCC patients. Multiple nidi and 30 exon variants were brought into the prediction model with an area under the curve (AUC) = 0.94. MUC6 gene mutation was obvious in patients with an early recurrence, and MUC3A and MUC4 gene mutations were evident in patients with poorer responses to PD-1 antibodies combined with mTKIs. Those three mucins were negatively correlated with immune infiltrating cells.

CONCLUSIONS

We depicted the exon characteristics of hepatocellular carcinoma in the Chinese population and established a predictive model for recurrence within 1 year after radical surgical treatment. Moreover, we found that mucins were worthy targets of hepatocellular carcinoma.

Genomic characterization of intracranial teratomas using whole genome sequencing

Background

Intracranial teratoma is a rare neoplasm of the central nervous system, often classified into mature and immature types and occurs mainly in children and adolescents. To date, there has been no comprehensive genomic characterization analysis of teratoma due to its rarity of the cases.

Methods

Forty-six patients with intracranial teratomas were collected and 22 of them underwent whole-exome sequencing, including 8 mature teratomas and 14 immature teratomas. A comprehensive analysis was performed to analyze somatic mutations, copy number variants (CNVs), mutational signatures, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway in our cohort.

Results

The most common somatic mutated gene in intracranial teratomas was CARD11 (18%) and IRS1 (18%), followed by PSMD11, RELN, RRAS2, SMC1A, SYNE1 and ZFHX3, with mutation rates of 14% for the latter six genes. Copy number variation was dominated by amplification, among which ARAF (50%), ATP2B3 (41%), GATA1 (41%), ATP6AP1 (36%), CCND2 (36%) and ZMYM3 (36%) were the most frequently amplified genes. Copy number deletion of SETDB2 and IL2 only appeared in immature teratoma (43% and 36%, respectively), but not in mature teratoma (p = 0.051 and 0.115, respectively). Prognostic analysis showed that TP53 mutations might be associated with poor prognosis of intracranial teratomas patients.

Conclusions

Our study revealed the genetic characteristics of intracranial teratoma which might be valuable for guiding future targeted therapies.

Read Count Patterns and Detection of Cancerous Copy Number Alterations in Plasma Cell-Free DNA Whole Exome Sequencing Data for Advanced Non-Small Cell Lung Cancer

Plasma cell-free DNA (cfDNA) sequencing data have been widely studied for early diagnosis and treatment response or recurrence monitoring of cancers because of the non-invasive benefits. In cancer studies, whole exome sequencing (WES) is mostly used for discovering single nucleotide variants (SNVs), but it also has the potential to detect copy number alterations (CNAs) that are mostly discovered by whole genome sequencing or microarray. In clinical settings where the quantity of the acquired blood from the patients is limited and where various sequencing experiments are not possible, providing various types of mutation information such as CNAs and SNVs using only WES will be helpful in the treatment decision. Here, we questioned whether the plasma cfDNA WES data for patients with advanced non-small cell lung cancer (NSCLC) could be exploited for CNA detection. When the read count (RC) signals of the WES data were investigated, a similar fluctuation pattern was observed among the signals of different samples, and it can be a major challenge hindering CNA detection. When these RC patterns among cfDNA were suppressed by the method we proposed, the cancerous CNAs were more distinguishable in some samples with higher cfDNA quantity. Although the potential to detect CNAs using the plasma cfDNA WES data for NSCLC patients was studied here, further studies with other cancer types, with more samples, and with more sophisticated techniques for bias correction are required to confirm our observation. In conclusion, the detection performance for cancerous CNAs can be improved by controlling RC bias, but it depends on the quantity of cfDNA in plasma.

Integrative genomic analysis of drug resistance in MET exon 14 skipping lung cancer using patient-derived xenograft models

Background

Non-small cell lung cancer (NSCLC) driven by MET exon 14 skipping (METex14) occurs in 3-4% of NSCLC cases and defines a subset of patients with distinct characteristics. While MET targeted therapy has led to strong clinical results in METex14 patients, acquired drug resistance seemed to be unavoidable during treatment. Limited information is available regarding acquired resistance during MET targeted therapy, nor has there been any report on such patient-derived xenografts (PDXs) model facilitating the research.

Methods

We describe a patient case harboring METex14 who exhibited drug resistance after treatment with crizotinib. Subcutaneous xenografts were generated from pretreatment and post-resistance patient specimens. PDX mice were then treated with MET inhibitors (crizotinib and tepotinib) and EGFR-MET bispecific antibodies (EMB-01 and amivantamab) to evaluate their drug response in vivo. DNA and RNA sequencing analysis was performed on patient tumor specimens and matching xenografts.

Results

PDXs preserved most of the histological and molecular profiles of the parental tumors. Drug resistance to MET targeted therapy was confirmed in PDX models through in vivo drug analysis. Newly acquired MET D1228H mutations and EGFR amplificated were detected in patient-resistant tumor specimens. Although the mutations were not detected in the PDX, EGFR overexpression was observed in RNA sequencing analysis indicating possible off-target resistance through the EGFR bypass signaling pathway. As expected, EGFR-MET bispecific antibodies overcome drug resistant in the PDX model.

Conclusions

We detected a novel MET splice site deletion mutation that could lead to METex14. We also established and characterized a pair of METex14 NSCLC PDXs, including the first crizotinib resistant METex14 PDX. And dual inhibition of MET and EGFR might be a therapeutic strategy for EGFR-driven drug resistance METex14 lung cancer.

Tangent normalization for somatic copy-number inference in cancer genome analysis

MOTIVATION

Somatic copy-number alterations (SCNAs) play an important role in cancer development. Systematic noise in sequencing and array data present a significant challenge to the inference of SCNAs for cancer genome analyses. As part of The Cancer Genome Atlas, the Broad Institute Genome Characterization Center developed the Tangent normalization method to generate copy-number profiles using data from single-nucleotide polymorphism (SNP) arrays and whole-exome sequencing (WES) technologies for over 10 000 pairs of tumors and matched normal samples. Here, we describe the Tangent method, which uses a unique linear combination of normal samples as a reference for each tumor sample, to subtract systematic errors that vary across samples. We also describe a modification of Tangent, called Pseudo-Tangent, which enables denoising through comparisons between tumor profiles when few normal samples are available.

RESULTS

Tangent normalization substantially increases signal-to-noise ratios (SNRs) compared to conventional normalization methods in both SNP array and WES analyses. Tangent and Pseudo-Tangent normalizations improve the SNR by reducing noise with minimal effect on signal and exceed the contribution of other steps in the analysis such as choice of segmentation algorithm. Tangent and Pseudo-Tangent are broadly applicable and enable more accurate inference of SCNAs from DNA sequencing and array data.

AVAILABILITY AND IMPLEMENTATION

Tangent is available at https://github.com/broadinstitute/tangent and as a Docker image (https://hub.docker.com/r/broadinstitute/tangent). Tangent is also the normalization method for the copy-number pipeline in Genome Analysis Toolkit 4 (GATK4).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Copy Number Variation Analysis Facilitates Identification of Genetic Causation in Patients with Congenital Anomalies of the Kidney and Urinary Tract

Background

Congenital anomalies of the kidneys and urinary tract (CAKUT) are the most common cause of chronic kidney disease among children and adults younger than 30 yr. In our previous study, whole-exome sequencing (WES) identified a known monogenic cause of isolated or syndromic CAKUT in 13% of families with CAKUT. However, WES has limitations and detection of copy number variations (CNV) is technically challenging, and CNVs causative of CAKUT have previously been detected in up to 16% of cases.

Objective

To detect CNVs causing CAKUT in this WES cohort and increase the diagnostic yield.

Design setting and participants

We performed a genome-wide single nucleotide polymorphism (SNP)-based CNV analysis on the same CAKUT cohort for whom WES was previously conducted.

Outcome measurements and statistical analysis

We evaluated and classified the CNVs using previously published predefined criteria.

Results and limitations

In a cohort of 170 CAKUT families, we detected a pathogenic CNV known to cause CAKUT in nine families (5.29%, 9/170). There were no competing variants on genome-wide CNV analysis or WES analysis. In addition, we identified novel likely pathogenic CNVs that may cause a CAKUT phenotype in three of the 170 families (1.76%).

Conclusions

CNV analysis in this cohort of 170 CAKUT families previously examined via WES increased the rate of diagnosis of genetic causes of CAKUT from 13% on WES to 18% on WES + CNV analysis combined. We also identified three candidate loci that may potentially cause CAKUT.

Patient summary

We conducted a genetics study on families with congenital anomalies of the kidney and urinary tract (CAKUT). We identified gene mutations that can explain CAKUT symptoms in 5.29% of the families, which increased the percentage of genetic causes of CAKUT to 18% from a previous study, so roughly one in five of our patients with CAKUT had a genetic cause. These analyses can help patients with CAKUT and their families in identifying a possible genetic cause.

Multifocal organoids reveal clonal associations between synchronous intestinal tumors with pervasive heterogeneous drug responses

Multifocal colorectal cancer (CRC) comprises both clonally independent primary tumors caused by inherited predisposition and clonally related tumors mainly due to intraluminal spreading along an intact basement membrane. The distinction between these multifocal CRCs is essential because therapeutic strategies vary according to the clonal association of multiple tumor masses. Here, we report one unique case of synchronous intestinal cancer (SIC) with tumors occurring along the entire bowel tract, including the small intestine. We established six patient-derived organoids (PDOs), and patient-derived cell lines (PDCs) from each site of the SIC, which were subjected to extensive genomic, transcriptomic, and epigenomic sequencing. We also estimated the drug responses of each multifocal SIC to 25 clinically relevant therapeutic compounds to validate how the clinically actionable alternations between SICs were associated with drug sensitivity. Our data demonstrated distinct clonal associations across different organs, which were consistently supported by multi-omics analysis, as well as the accordant responses to various therapeutic compounds. Our results indicated the imminent drawback of a single tumor-based diagnosis of multifocal CRC and suggested the necessity of an in-depth molecular analysis of all tumor regions to avoid unexpected resistance to the currently available targeted therapies.

Multi-modal molecular programs regulate melanoma cell state

Melanoma cells display distinct intrinsic phenotypic states. Here, we seek to characterize the molecular regulation of these states using multi-omic analyses of whole exome, transcriptome, microRNA, long non-coding RNA and DNA methylation data together with reverse-phase protein array data on a panel of 68 highly annotated early passage melanoma cell lines. We demonstrate that clearly defined cancer cell intrinsic transcriptomic programs are maintained in melanoma cells ex vivo and remain highly conserved within melanoma tumors, are associated with distinct immune features within tumors, and differentially correlate with checkpoint inhibitor and adoptive T cell therapy efficacy. Through integrative analyses we demonstrate highly complex multi-omic regulation of melanoma cell intrinsic programs that provide key insights into the molecular maintenance of phenotypic states. These findings have implications for cancer biology and the identification of new therapeutic strategies. Further, these deeply characterized cell lines will serve as an invaluable resource for future research in the field.

Computational analysis of cancer genome sequencing data

Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.

Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application

Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade. However, the exact molecular basis of AD development and progression remains elusive. The emerging single-cell sequencing technology can potentially provide cell-level insights into the disease. Here we systematically review the state-of-the-art bioinformatics approaches to analyze single-cell sequencing data and their applications to AD in 14 major directions, including 1) quality control and normalization, 2) dimension reduction and feature extraction, 3) cell clustering analysis, 4) cell type inference and annotation, 5) differential expression, 6) trajectory inference, 7) copy number variation analysis, 8) integration of single-cell multi-omics, 9) epigenomic analysis, 10) gene network inference, 11) prioritization of cell subpopulations, 12) integrative analysis of human and mouse sc-RNA-seq data, 13) spatial transcriptomics, and 14) comparison of single cell AD mouse model studies and single cell human AD studies. We also address challenges in using human postmortem and mouse tissues and outline future developments in single cell sequencing data analysis. Importantly, we have implemented our recommended workflow for each major analytic direction and applied them to a large single nucleus RNA-sequencing (snRNA-seq) dataset in AD. Key analytic results are reported while the scripts and the data are shared with the research community through  GitHub. In summary, this comprehensive review provides insights into various approaches to analyze single cell sequencing data and offers specific guidelines for study design and a variety of analytic directions. The review and the accompanied software tools will serve as a valuable resource for studying cellular and molecular mechanisms of AD, other diseases, or biological systems at the single cell level.

CoverageMaster: comprehensive CNV detection and visualization from NGS short reads for genetic medicine applications

CoverageMaster (CoM) is a copy number variation (CNV) calling algorithm based on depth-of-coverage maps designed to detect CNVs of any size in exome [whole exome sequencing (WES)] and genome [whole genome sequencing (WGS)] data. The core of the algorithm is the compression of sequencing coverage data in a multiscale Wavelet space and the analysis through an iterative Hidden Markov Model. CoM processes WES and WGS data at nucleotide scale resolution and accurately detects and visualizes full size range CNVs, including single or partial exon deletions and duplications. The results obtained with this approach support the possibility for coverage-based CNV callers to replace probe-based methods such as array comparative genomic hybridization and multiplex ligation-dependent probe amplification in the near future.

Clinical exome sequencing - mistakes and caveats

Massive parallel sequencing technology has become the predominant technique for genetic diagnostics and research. Many genetic laboratories have wrestled with the challenges of setting up genetic testing workflows based on a completely new technology. The learning curve we went through as a laboratory was accompanied by growing pains while we gained new knowledge and expertise. Here we discuss some important mistakes that have been made in our laboratory through 10 years of clinical exome sequencing but that have given us important new insights on how to adapt our working methods. We provide these examples and the lessons that we learned to help other laboratories avoid to make the same mistakes.

Detection of Small CYP11B1 Deletions and One Founder Chimeric CYP11B2/CYP11B1 Gene in 11β-Hydroxylase Deficiency

OBJECTIVE

11β-Hydroxylase deficiency (11β-OHD) caused by mutations in the CYP11B1 gene is the second most common form of congenital adrenal hyperplasia. Both point mutations and genomic rearrangements of CYP11B1 are important causes of 11β-OHD. However, the high degree of sequence identity between CYP11B1 and its homologous gene CYP11B2, presents unique challenges for molecular diagnosis of suspected 11β-OHD. The aim of this study was to detect the point mutation, indel, small deletion of CYP11B1 and chimeric CYP11B2/CYP11B1 gene in a one-tube test, improving the genetic diagnosis of 11β-OHD.

METHODS

Optimized custom-designed target sequencing strategy was performed in three patients with suspected 11β-OHD, in which both the coverage depth of paired-end reads and the breakpoint information of split reads from sequencing data were analysed in order to detect genomic rearrangements covering CYP11B1. Long-range PCR was peformed to validate the speculated CYP11B1 rearrangements with the breakpoint-specifc primers.

RESULTS

Using the optimized target sequencing approach, we detected two intragenic/intergenic deletions of CYP11B1 and one chimeric CYP11B2/CYP11B1 gene from three suspected patients with 11β-OHD besides three pathogenic heterozygous point mutation/indels. Furthermore, we mapped the precise breakpoint of this chimeric CYP11B2/CYP11B1 gene located on chr8:143994517 (hg19) and confirmed it as a founder rearrangement event in the Chinese population.

CONCLUSIONS

Our optimized target sequencing approach improved the genetic diagnosis of 11β-OHD.

In silico tools and databases for designing cancer immunotherapy

Immunotherapy is a rapidly growing therapy for cancer which have numerous benefits over conventional treatments like surgery, chemotherapy, and radiation. Overall survival of cancer patients has improved significantly due to the use of immunotherapy. It acts as a novel pillar for treating different malignancies from their primary to the metastatic stage. Recent preferments in high-throughput sequencing and computational immunology leads to the development of targeted immunotherapy for precision oncology. In the last few decades, several computational methods and resources have been developed for designing immunotherapy against cancer. In this review, we have summarized cancer-associated genomic, transcriptomic, and mutation profile repositories. We have also enlisted in silico methods for the prediction of vaccine candidates, HLA binders, cytokines inducing peptides, and potential neoepitopes. Of note, we have incorporated the most important bioinformatics pipelines and resources for the designing of cancer immunotherapy. Moreover, to facilitate the scientific community, we have developed a web portal entitled ImmCancer (https://webs.iiitd.edu.in/raghava/immcancer/), comprises cancer immunotherapy tools and repositories.

Mitotic Errors Promote Genomic Instability and Leukemia in a Novel Mouse Model of Fanconi Anemia

Fanconi anemia (FA) is a disease of genomic instability and cancer. In addition to DNA damage repair, FA pathway proteins are now known to be critical for maintaining faithful chromosome segregation during mitosis. While impaired DNA damage repair has been studied extensively in FA-associated carcinogenesis in vivo, the oncogenic contribution of mitotic abnormalities secondary to FA pathway deficiency remains incompletely understood. To examine the role of mitotic dysregulation in FA pathway deficient malignancies, we genetically exacerbated the baseline mitotic defect in Fancc-/- mice by introducing heterozygosity of the key spindle assembly checkpoint regulator Mad2. Fancc-/-;Mad2+/- mice were viable, but died from acute myeloid leukemia (AML), thus recapitulating the high risk of myeloid malignancies in FA patients better than Fancc-/-mice. We utilized hematopoietic stem cell transplantation to propagate Fancc-/-; Mad2+/- AML in irradiated healthy mice to model FANCC-deficient AMLs arising in the non-FA population. Compared to cells from Fancc-/- mice, those from Fancc-/-;Mad2+/- mice demonstrated an increase in mitotic errors but equivalent DNA cross-linker hypersensitivity, indicating that the cancer phenotype of Fancc-/-;Mad2+/- mice results from error-prone cell division and not exacerbation of the DNA damage repair defect. We found that FANCC enhances targeting of endogenous MAD2 to prometaphase kinetochores, suggesting a mechanism for how FANCC-dependent regulation of the spindle assembly checkpoint prevents chromosome mis-segregation. Whole-exome sequencing revealed similarities between human FA-associated myelodysplastic syndrome (MDS)/AML and the AML that developed in Fancc-/-; Mad2+/- mice. Together, these data illuminate the role of mitotic dysregulation in FA-pathway deficient malignancies in vivo, show how FANCC adjusts the spindle assembly checkpoint rheostat by regulating MAD2 kinetochore targeting in cell cycle-dependent manner, and establish two new mouse models for preclinical studies of AML.

Cold and heterogeneous T cell repertoire is associated with copy number aberrations and loss of immune genes in small-cell lung cancer

Small-cell lung cancer (SCLC) is speculated to harbor complex genomic intratumor heterogeneity (ITH) associated with high recurrence rate and suboptimal response to immunotherapy. Here, using multi-region whole exome/T cell receptor (TCR) sequencing as well as immunohistochemistry, we reveal a rather homogeneous mutational landscape but extremely cold and heterogeneous TCR repertoire in limited-stage SCLC tumors (LS-SCLCs). Compared to localized non-small cell lung cancers, LS-SCLCs have similar predicted neoantigen burden and genomic ITH, but significantly colder and more heterogeneous TCR repertoire associated with higher chromosomal copy number aberration (CNA) burden. Furthermore, copy number loss of IFN-γ pathway genes is frequently observed and positively correlates with CNA burden. Higher mutational burden, higher T cell infiltration and positive PD-L1 expression are associated with longer overall survival (OS), while higher CNA burden is associated with shorter OS in patients with LS-SCLC.

Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model

BACKGROUND

Intra-tumor heterogeneity (ITH) encompasses cellular differences in tumors and is related to clinical outcomes such as drug resistance. However, little is known about the dynamics of ITH, owing to the lack of time-series analysis at the single-cell level. Mouse models that recapitulate cancer development are useful for controlled serial time sampling.

RESULTS

We performed single-cell exome and transcriptome sequencing of 200 cells to investigate how ITH is generated in a mouse colorectal cancer model. In the model, a single normal intestinal cell is grown into organoids that mimic the intestinal crypt structure. Upon RNAi-mediated downregulation of a tumor suppressor gene APC, the transduced organoids were serially transplanted into mice to allow exposure to in vivo microenvironments, which play relevant roles in cancer development. The ITH of the transcriptome increased after the transplantation, while that of the exome decreased. Mutations generated during organoid culture did not greatly change at the bulk-cell level upon the transplantation. The RNA ITH increase was due to the emergence of new transcriptional subpopulations. In contrast to the initial cells expressing mesenchymal-marker genes, new subpopulations repressed these genes after the transplantation. Analyses of colorectal cancer data from The Cancer Genome Atlas revealed a high proportion of metastatic cases in human subjects with expression patterns similar to the new cell subpopulations in mouse. These results suggest that the birth of transcriptional subpopulations may be a key for adaptation to drastic micro-environmental changes when cancer cells have sufficient genetic alterations at later tumor stages.

CONCLUSIONS

This study revealed an evolutionary dynamics of single-cell RNA and DNA heterogeneity in tumor progression, giving insights into the mesenchymal-epithelial transformation of tumor cells at metastasis in colorectal cancer.

Enhancer reprogramming in PRC2-deficient malignant peripheral nerve sheath tumors induces a targetable de-differentiated state

Malignant peripheral nerve sheath tumors (MPNSTs) are soft tissue sarcomas that frequently harbor genetic alterations in polycomb repressor complex 2 (PRC2) components-SUZ12 and EED. Here, we show that PRC2 loss confers a dedifferentiated early neural-crest phenotype which is exclusive to PRC2-mutant MPNSTs and not a feature of neurofibromas. Neural crest phenotype in PRC2 mutant MPNSTs was validated via cross-species comparative analysis using spontaneous and transgenic MPNST models. Systematic chromatin state profiling of the MPNST cells showed extensive epigenomic reprogramming or chromatin states associated with PRC2 loss and identified gains of active enhancer states/super-enhancers on early neural crest regulators in PRC2-mutant conditions around genomic loci that harbored repressed/poised states in PRC2-WT MPNST cells. Consistently, inverse correlation between H3K27me3 loss and H3K27Ac gain was noted in MPNSTs. Epigenetic editing experiments established functional roles for enhancer gains on DLX5-a key regulator of neural crest phenotype. Consistently, blockade of enhancer activity by bromodomain inhibitors specifically suppressed this neural crest phenotype and tumor burden in PRC2-mutant PDXs. Together, these findings reveal accumulation of dedifferentiated neural crest like state in PRC2-mutant MPNSTs that can be targeted by enhancer blockade.

Shall genomic correlation structure be considered in copy number variants detection?

Copy number variation has been identified as a major source of genomic variation associated with disease susceptibility. With the advent of whole-exome sequencing (WES) technology, massive WES data have been generated, allowing for the identification of copy number variants (CNVs) in the protein-coding regions with direct functional interpretation. We have previously shown evidence of the genomic correlation structure in array data and developed a novel chromosomal breakpoint detection algorithm, LDcnv, which showed significantly improved detection power through integrating the correlation structure in a systematic modeling manner. However, it remains unexplored whether the genomic correlation exists in WES data and how such correlation structure integration can improve the CNV detection accuracy. In this study, we first explored the correlation structure of the WES data using the 1000 Genomes Project data. Both real raw read depth and median-normalized data showed strong evidence of the correlation structure. Motivated by this fact, we proposed a correlation-based method, CORRseq, as a novel release of the LDcnv algorithm in profiling WES data. The performance of CORRseq was evaluated in extensive simulation studies and real data analysis from the 1000 Genomes Project. CORRseq outperformed the existing methods in detecting medium and large CNVs. In conclusion, it would be more advantageous to model genomic correlation structure in detecting relatively long CNVs. This study provides great insights for methodology development of CNV detection with NGS data.

Reproductive history determines Erbb2 locus amplification, WNT signalling and tumour phenotype in a murine breast cancer model

Understanding the mechanisms underlying tumour heterogeneity is key to the development of treatments that can target specific tumour subtypes. We have previously targeted CRE recombinase-dependent conditional deletion of the tumour suppressor genes Brca1, Brca2, p53 (also known as Trp53) and/or Pten to basal or luminal oestrogen receptor-negative (ER⁻) cells of the mouse mammary epithelium. We demonstrated that both the cell-of-origin and the tumour-initiating genetic lesions cooperate to influence mammary tumour phenotype. Here, we use a CRE-activated HER2 orthologue to specifically target HER2/ERBB2 oncogenic activity to basal or luminal ER⁻ mammary epithelial cells and perform a detailed analysis of the tumours that develop. We find that, in contrast to our previous studies, basal epithelial cells are less sensitive to transformation by the activated NeuKI allele, with mammary epithelial tumour formation largely confined to luminal ER⁻ cells. Histologically, most tumours that developed were classified as either adenocarcinomas of no special type or as metaplastic adenosquamous tumours. The former were typically characterized by amplification of the NeuNT/Erbb2 locus; in contrast, tumours displaying squamous metaplasia were enriched in animals that had been through at least one pregnancy and typically had lower levels of NeuNT/Erbb2 locus amplification but had activated canonical WNT signalling. Squamous changes in these tumours were associated with activation of the epidermal differentiation cluster. Thus, in this model of HER2 breast cancer, cell-of-origin, reproductive history, NeuNT/Erbb2 locus amplification and the activation of specific branches of the WNT signalling pathway all interact to drive inter-tumour heterogeneity.

Summary: Using a mouse model of breast cancer, the authors show mammary epithelial cell-type sensitivity to transformation by HER2, as well as a change in tumour phenotype associated with reproductive history and driven by WNT signalling.

Low mutation burden and frequent loss of CDKN2A/B and SMARCA2, but not PRC2, define premalignant neurofibromatosis type 1-associated atypical neurofibromas

BACKGROUND

Neurofibromatosis type 1 (NF1) is a tumor-predisposition disorder caused by germline mutations in NF1. NF1 patients have an 8-16% lifetime risk of developing a malignant peripheral nerve sheath tumor (MPNST), a highly aggressive soft-tissue sarcoma, often arising from preexisting benign plexiform neurofibromas (PNs) and atypical neurofibromas (ANFs). ANFs are distinct from both PN and MPNST, representing an intermediate step in malignant transformation.

METHODS

In the first comprehensive genomic analysis of ANF originating from multiple patients, we performed tumor/normal whole-exome sequencing (WES) of 16 ANFs. In addition, we conducted WES of 3 MPNSTs, copy-number meta-analysis of 26 ANFs and 28 MPNSTs, and whole transcriptome sequencing analysis of 5 ANFs and 5 MPNSTs.

RESULTS

We identified a low number of mutations (median 1, range 0-5) in the exomes of ANFs (only NF1 somatic mutations were recurrent), and frequent deletions of CDKN2A/B (69%) and SMARCA2 (42%). We determined that polycomb repressor complex 2 (PRC2) genes EED and SUZ12 were frequently mutated, deleted, or downregulated in MPNSTs but not in ANFs. Our pilot gene expression study revealed upregulated NRAS, MDM2, CCND1/2/3, and CDK4/6 in ANFs and MPNSTs, and overexpression of EZH2 in MPNSTs only.

CONCLUSIONS

The PN-ANF transition is primarily driven by the deletion of CDKN2A/B. Further progression from ANF to MPNST likely involves broad chromosomal rearrangements and frequent inactivation of the PRC2 genes, loss of the DNA repair genes, and copy-number increase of signal transduction and cell-cycle and pluripotency self-renewal genes.

Next Generation Sequencing Technology in the Clinic and Its Challenges

Simple Summary

Precise identification and annotation of mutations are of utmost importance in clinical oncology. Insights of the DNA sequence can provide meaningful knowledge to unravel the underlying genetics of disease. Hence, tailoring of personalized medicine often relies on specific genomic alteration for treatment efficacy. The aim of this review is to highlight that sequencing harbors much more than just four nucleotides. Moreover, the gradual transition from first to second generation sequencing technologies has led to awareness for choosing the most appropriate bioinformatic analytic tools based on the aim, quality and demand for a specific purpose. Thus, the same raw data can lead to various results reflecting the intrinsic features of different datamining pipelines.

Abstract

Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many tools have been developed since the advent of NGS, featuring their own peculiarities. Increased awareness when interpreting alterations in the genome is therefore of utmost importance, as the same data using different tools can provide diverse outcomes. Hence, it is crucial to evaluate and validate bioinformatic pipelines in clinical settings. Moreover, personalized medicine implies treatment targeting efficacy of biological drugs for specific genomic alterations. Here, we focused on different sequencing technologies, features underlying the genome complexity, and bioinformatic tools that can impact the final annotation. Additionally, we discuss the clinical demand and design for implementing NGS.

HCMMCNVs: hierarchical clustering mixture model of copy number variants detection using whole exome sequencing technology

SUMMARY

In this article, we introduce a hierarchical clustering and Gaussian mixture model with expectation-maximization (EM) algorithm for detecting copy number variants (CNVs) using whole exome sequencing (WES) data. The R shiny package 'HCMMCNVs' is also developed for processing user-provided bam files, running CNVs detection algorithm and conducting visualization. Through applying our approach to 325 cancer cell lines in 22 tumor types from Cancer Cell Line Encyclopedia (CCLE), we show that our algorithm is competitive with other existing methods and feasible in using multiple cancer cell lines for CNVs estimation. In addition, by applying our approach to WES data of 120 oral squamous cell carcinoma (OSCC) samples, our algorithm, using the tumor sample only, exhibits more power in detecting CNVs as compared with the methods using both tumors and matched normal counterparts.

AVAILABILITY AND IMPLEMENTATION

HCMMCNVs R shiny software is freely available at github repository https://github.com/lunching/HCMM_CNVs.and Zenodo https://doi.org/10.5281/zenodo.4593371.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Sequential filtering for clinically relevant variants as a method for clinical interpretation of whole exome sequencing findings in glioma

Background

In the clinical setting, workflows for analyzing individual genomics data should be both comprehensive and convenient for clinical interpretation. In an effort for comprehensiveness and practicality, we attempted to create a clinical individual whole exome sequencing (WES) analysis workflow, allowing identification of genomic alterations and presentation of neurooncologically-relevant findings.

Methods

The analysis workflow detects germline and somatic variants and presents: (1) germline variants, (2) somatic short variants, (3) tumor mutational burden (TMB), (4) microsatellite instability (MSI), (5) somatic copy number alterations (SCNA), (6) SCNA burden, (7) loss of heterozygosity, (8) genes with double-hit, (9) mutational signatures, and (10) pathway enrichment analyses. Using the workflow, 58 WES analyses from matched blood and tumor samples of 52 patients were analyzed: 47 primary and 11 recurrent diffuse gliomas.

Results

The median mean read depths were 199.88 for tumor and 110.955 for normal samples. For germline variants, a median of 22 (14–33) variants per patient was reported. There was a median of 6 (0–590) reported somatic short variants per tumor. A median of 19 (0–94) broad SCNAs and a median of 6 (0–12) gene-level SCNAs were reported per tumor. The gene with the most frequent somatic short variants was TP53 (41.38%). The most frequent chromosome-/arm-level SCNA events were chr7 amplification, chr22q loss, and chr10 loss. TMB in primary gliomas were significantly lower than in recurrent tumors (p = 0.002). MSI incidence was low (6.9%).

Conclusions

We demonstrate that WES can be practically and efficiently utilized for clinical analysis of individual brain tumors. The results display that NOTATES produces clinically relevant results in a concise but exhaustive manner.

Copy Number Variation: Methods and Clinical Applications

Gains and losses of large segments of genomic DNA, known as copy number variants (CNVs) gained considerable interest in clinical diagnostics lately, as particular forms may lead to inherited genetic diseases. In recent decades, researchers developed a wide variety of cytogenetic and molecular methods with different detection capabilities to detect clinically relevant CNVs. In this review, we summarize methodological progress from conventional approaches to current state of the art techniques capable of detecting CNVs from a few bases up to several megabases. Although the recent rapid progress of sequencing methods has enabled precise detection of CNVs, determining their functional effect on cellular and whole-body physiology remains a challenge. Here, we provide a comprehensive list of databases and bioinformatics tools that may serve as useful assets for researchers, laboratory diagnosticians, and clinical geneticists facing the challenge of CNV detection and interpretation.

Genetic diagnoses in pediatric patients with epilepsy and comorbid intellectual disability

PURPOSE

The aim of this retrospective study is to investigate the genetic etiology and propose a diagnostic strategy for pediatric patients with epilepsy and comorbid intellectual disability (ID).

METHODS

From September 2014 to May 2020, a total of 102 pediatric patients diagnosed with epilepsy with co-morbid ID with unknown causes were included in this study. All patients underwent tests of single nucleotide polymorphism (SNP) array for chromosomal abnormalities. Whole exome sequencing (WES) was consecutively performed in patients without diagnostic copy number variants (CNVs) (n = 85) for single nucleotide variants (SNVs). Subgroup analyses based on the age of seizure onset and ID severity were done.

RESULTS

The overall diagnostic yield of genetic aberrations was 33.3 % (34/102), which comprised 50.0 % with diagnostic CNVs and 50.0 % with diagnostic SNVs. The yield nominally increased with ID severity and decreased with age of seizure onset, though this result was not statistically significant. The diagnostic yield of SNVs in patients with seizure onset in the first year of life (25.0 % (11/44)) was significantly higher than those with childhood-onset epilepsy (10.3 % (6/58)) (p = 0.049), however, the diagnostic yield of CNVs in patients with childhood-onset epilepsy (17.2 % (10/58) was higher than the diagnostic yield of SNVs (10.3 % (6/58)). The most frequently syndromic epilepsy detected by SNP array was Angelman syndrome (n=4), including one confirmed with paternal uniparental disomy. Meanwhile, the most frequent SNVs were mutations of MECP2 (n=2) and IQSEC2 (n = 2) in sporadic cases.

CONCLUSION

Both CMA and WES are advantageous as unbiased approaches for a genetically heterogeneous condition. We proposed an effective diagnostic strategy for pediatric patients with epilepsy. For patients with seizure onset in the first year of life, WES is recommended as the first-tier test. However, for patients with childhood-onset epilepsy, SNP array should be considered for the first-tier test.

Mutations and Copy Number Alterations in IDH Wild-Type Glioblastomas Are Shaped by Different Oncogenic Mechanisms

Little is known about the mutational processes that shape the genetic landscape of gliomas. Numerous mutational processes leave marks on the genome in the form of mutations, copy number alterations, rearrangements or their combinations. To explore gliomagenesis, we hypothesized that gliomas with different underlying oncogenic mechanisms would have differences in the burden of various forms of these genomic alterations. This was an analysis on adult diffuse gliomas, but IDH-mutant gliomas as well as diffuse midline gliomas H3-K27M were excluded to search for the possible presence of new entities among the very heterogenous group of IDH-WT glioblastomas. The cohort was divided into two molecular subsets: (1) Molecularly-defined GBM (mGBM) as those that carried molecular features of glioblastomas (including TERT promoter mutations, 7/10 pattern, or EGFR-amplification), and (2) those who did not (others). Whole exome sequencing was performed for 37 primary tumors and matched blood samples as well as 8 recurrences. Single nucleotide variations (SNV), short insertion or deletions (indels) and copy number alterations (CNA) were quantified using 5 quantitative metrics (SNV burden, indel burden, copy number alteration frequency-wGII, chromosomal arm event ratio-CAER, copy number amplitude) as well as 4 parameters that explored underlying oncogenic mechanisms (chromothripsis, double minutes, microsatellite instability and mutational signatures). Findings were validated in the TCGA pan-glioma cohort. mGBM and “Others” differed significantly in their SNV (only in the TCGA cohort) and CNA metrics but not indel burden. SNV burden increased with increasing age at diagnosis and at recurrences and was driven by mismatch repair deficiency. On the contrary, indel and CNA metrics remained stable over increasing age at diagnosis and with recurrences. Copy number alteration frequency (wGII) correlated significantly with chromothripsis while CAER and CN amplitude correlated significantly with the presence of double minutes, suggesting separate underlying mechanisms for different forms of CNA.

CopyDetective: Detection threshold-aware copy number variant calling in whole-exome sequencing data

BACKGROUND

Copy number variants (CNVs) are known to play an important role in the development and progression of several diseases. However, detection of CNVs with whole-exome sequencing (WES) experiments is challenging. Usually, additional experiments have to be performed.

FINDINGS

We developed a novel algorithm for somatic CNV calling in matched WES data called "CopyDetective". Different from other approaches, CNV calling with CopyDetective consists of a 2-step procedure: first, quality analysis is performed, determining individual detection thresholds for every sample. Second, actual CNV calling on the basis of the previously determined thresholds is performed. Our algorithm evaluates the change in variant allele frequency of polymorphisms and reports the fraction of affected cells for every CNV. Analyzing 4 WES data sets (n = 100) we observed superior performance of CopyDetective compared with ExomeCNV, VarScan2, ControlFREEC, ExomeDepth, and CNV-seq.

CONCLUSIONS

Individual detection thresholds reveal that not every WES data set is equally apt for CNV calling. Initial quality analyses, determining individual detection thresholds-as realized by CopyDetective-can and should be performed prior to actual variant calling.

Molecular diagnosis based on comprehensive genetic testing in 800 Chinese families with non-syndromic inherited retinal dystrophies

IMPORTANCE

Inherited retinal dystrophies (IRDs) are a group of monogenic diseases, one of the leading causes of blindness.

BACKGROUND

Introducing a comprehensive genetic testing strategy by combining single gene Sanger sequencing, next-generation sequencing (NGS) including whole exome sequencing (WES), and a specific hereditary eye disease enrichment panel (HEDEP) sequencing, to identify the disease-causing variants of 800 Chinese probands affected with non-syndromic IRDs.

DESIGN

Retrospective analysis.

PARTICIPANTS

Eight hundred Chinese non-syndromic IRDs probands and their families.

METHODS

A total of 149 patients were subjected to Sanger sequencing. Of the 651 patients subjected to NGS, 86 patients underwent WES and 565 underwent HEDEP. Patients that likely carried copy number variations (CNVs) detected by HEDEP were further validated by multiplex ligation-dependent probe amplification (MLPA) or quantitative fluorescence PCR (QF-PCR).

MAIN OUTCOME MEASURES

The diagnostic rate.

RESULTS

(Likely) pathogenic variants were determined in 481 cases (60.13% detection rate). The detection rates of single gene Sanger sequencing, WES and HEDEP were 86.58%, 31.40% and 56.99%, respectively. Approximately 11.64% of 481 cases carried autosomal dominant variants, 72.97% carried AR variants and 15.39% were found to be X-linked. CNVs were confirmed by MLPA or QF-PCR in 17 families. Fourteen genes that each caused disease in 1% or more of the cohort were detected, and these genes were collectively responsible for disease in almost one half (46.38%) of the families.

CONCLUSIONS AND RELEVANCE

Sanger sequencing is ideal to detect pathogenic variants of clinical homogeneous diseases, whereas NGS is more appropriate for patients without an explicit clinical diagnosis.

Whole-exome sequencing identifies prognostic mutational signatures in gastric cancer

Background

Gastric cancer (GC) is a heterogeneous disease, and is a leading cause of cancer deaths in Eastern Asia. Genomic analysis, such as whole-exome sequencing (WES), can help identify key genetic alterations leading to the malignancy and diversity of GC, and may help identify new drug targets.

Methods

We identified genomic alterations in a cohort of 38 GC patients, including 26 metastatic and 12 non-metastatic patients. We analyzed the association between novel gene mutations and copy number variations (CNVs) with tumor metastasis and patient survival.

Results

A number of significantly mutated genes in somatic and germline cells were identified. Among them, ATAD3B somatic mutation, a potential biomarker of immunotherapy in stomach cancers, was associated with better patient survival (P=0.0939) and metastasis (P=0.074). POLE germline variation was correlated with shorter overall survival (OS; P=0.0100). Novel CNVs were also identified and can potentially be used as biomarkers. These included 9p24.1 deletion (P=0.0376) and 16p11.2 amplification (P=0.0066), which were both associated with shorter OS. CNVs of several genes including MMP9, PTPN1, and SS18L1 were found to be significantly related to metastasis (P<0.05).

Conclusions

We characterized the mutational landscape of 38 GC patients and discovered several potential new predictive markers of survival and metastasis in GC.

Best practices for variant calling in clinical sequencing

Next-generation sequencing technologies have enabled a dramatic expansion of clinical genetic testing both for inherited conditions and diseases such as cancer. Accurate variant calling in NGS data is a critical step upon which virtually all downstream analysis and interpretation processes rely. Just as NGS technologies have evolved considerably over the past 10 years, so too have the software tools and approaches for detecting sequence variants in clinical samples. In this review, I discuss the current best practices for variant calling in clinical sequencing studies, with a particular emphasis on trio sequencing for inherited disorders and somatic mutation detection in cancer patients. I describe the relative strengths and weaknesses of panel, exome, and whole-genome sequencing for variant detection. Recommended tools and strategies for calling variants of different classes are also provided, along with guidance on variant review, validation, and benchmarking to ensure optimal performance. Although NGS technologies are continually evolving, and new capabilities (such as long-read single-molecule sequencing) are emerging, the “best practice” principles in this review should be relevant to clinical variant calling in the long term.

inCNV: An Integrated Analysis Tool for Copy Number Variation on Whole Exome Sequencing

The detection of copy number variations (CNVs) on whole-exome sequencing (WES) represents a cost-effective technique for the study of genetic variants. This approach, however, has encountered an obstacle with high false-positive rates due to biases from exome sequencing capture kits and GC contents. Although plenty of CNV detection tools have been developed, they do not perform well with all types of CNVs. In addition, most tools lack features of genetic annotation, CNV visualization, and flexible installation, requiring users to put much effort into CNV interpretation. Here, we present “inCNV,” a web-based application that can accept multiple CNV-tool results, then integrate and prioritize them with user-friendly interfaces. This application helps users analyze the importance of called CNVs by generating CNV annotations from Ensembl, Database of Genomic Variants (DGV), ClinVar, and Online Mendelian Inheritance in Man (OMIM). Moreover, users can select and export CNVs of interest including their flanking sequences for primer design and experimental verification. We demonstrated how inCNV could help users filter and narrow down the called CNVs to a potentially novel CNV, a common CNV within a group of samples of the same disease, or a de novo CNV of a sample within the same family. Besides, we have provided in CNV as a docker image for ease of installation (https://github.com/saowwapark/inCNV).

Functional genomic analysis identifies drug targetable pathways in invasive and metastatic cutaneous squamous cell carcinoma

Although cutaneous squamous cell carcinoma (cSCC) is treatable in the majority of cases, deadly invasive and metastatic cases do occur. To date there are neither reliable predictive biomarkers of disease progression nor FDA-approved targeted therapies as standard of care. To address these issues, we screened patient-derived primary cultured cells from invasive/metastatic cSCC with 107 small-molecule inhibitors. In-house bioinformatics tools were used to cross-analyze drug responses and DNA mutations in tumors detected by whole-exome sequencing (WES). Aberrations in molecular pathways with evidence of potential drug targets were identified, including the Eph-ephrin and neutrophil degranulation signaling pathways. Using a screening panel of siRNAs, we identified EPHA6 and EPHA7 as targets within the Eph-ephrin pathway responsible for mitigating decreased cell viability. These studies form a plausible foundation for detecting biomarkers of high-risk progressive disease applicable in dermatopathology and for patient-specific therapeutic options for invasive/metastatic cSCC.

Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing

BACKGROUND

Investigating genome evolution in response to therapy is difficult in human tissue samples. To address this challenge, we develop an unbiased whole-genome plasma DNA sequencing approach that concurrently measures genomic copy number and exome mutations from archival cryostored plasma samples. This approach is applied to study longitudinal blood plasma samples from prostate cancer patients, where longitudinal tissue biopsies from the bone and other metastatic sites have been challenging to collect.

RESULTS

A molecular characterization of archival plasma DNA from 233 patients and genomic profiling of 101 patients identifies clinical correlations of aneuploid plasma DNA profiles with poor survival, increased plasma DNA concentrations, and lower plasma DNA size distributions. Deep-exome sequencing and genomic copy number profiling are performed on 23 patients, including 9 patients with matched metastatic tissues and 12 patients with serial plasma samples. These data show a high concordance in genomic alterations between the plasma DNA and metastatic tissue samples, suggesting the plasma DNA is highly representative of the tissue alterations. Longitudinal sequencing of 12 patients with 2-5 serial plasma samples reveals clonal dynamics and genome evolution in response to hormonal and chemotherapy. By performing an integrated evolutionary analysis, minor subclones are identified in 9 patients that expanded in response to therapy and harbored mutations associated with resistance.

CONCLUSIONS

This study provides an unbiased evolutionary approach to non-invasively delineate clonal dynamics and identify clones with mutations associated with resistance in prostate cancer.

CONY: A Bayesian procedure for detecting copy number variations from sequencing read depths

Copy number variations (CNVs) are genomic structural mutations consisting of abnormal numbers of fragment copies. Next-generation sequencing of read-depth signals mirrors these variants. Some tools used to predict CNVs by depth have been published, but most of these tools can be applied to only a specific data type due to modeling limitations. We develop a tool for copy number variation detection by a Bayesian procedure, i.e., CONY, that adopts a Bayesian hierarchical model and an efficient reversible-jump Markov chain Monte Carlo inference algorithm for whole genome sequencing of read-depth data. CONY can be applied not only to individual samples for estimating the absolute number of copies but also to case-control pairs for detecting patient-specific variations. We evaluate the performance of CONY and compare CONY with competing approaches through simulations and by using experimental data from the 1000 Genomes Project. CONY outperforms the other methods in terms of accuracy in both single-sample and paired-samples analyses. In addition, CONY performs well regardless of whether the data coverage is high or low. CONY is useful for detecting both absolute and relative CNVs from read-depth data sequences. The package is available at https://github.com/weiyuchung/CONY.

Application of Whole-Exome Sequencing in Detecting Copy Number Variants in Patients with Developmental Delay and/or Multiple Congenital Malformations

Overcoming challenges for the unambiguous detection of copy number variations is essential to broaden our understanding of the role of genomic variants in the clinical phenotype. With the improvement of software and databases, whole-exome sequencing quickly can become an excellent strategy in the routine diagnosis of patients with a developmental delay and/or multiple congenital malformations. However, even after a detailed analysis of pathogenic single-nucleotide variants and indels in known disease genes, using whole-exome sequencing, some patients with suspected syndromic conditions are left without a conclusive diagnosis. These negative results could be the result of different factors including nongenetic etiologies, lack of knowledge about the genes that cause different disease phenotypes, or, in some cases, a deletion or duplication of genomic information not routinely detectable by whole-exome sequencing variant calling. Although copy number variant detection is possible using whole-exome sequencing data, such analysis presents significant challenges and cannot yet be used to replace chromosomal arrays for identification of deletions or duplications.

Spatially resolved analyses link genomic and immune diversity and reveal unfavorable neutrophil activation in melanoma

Complex tumor microenvironmental (TME) features influence the outcome of cancer immunotherapy (IO). Here we perform immunogenomic analyses on 67 intratumor sub-regions of a PD-1 inhibitor-resistant melanoma tumor and 2 additional metastases arising over 8 years, to characterize TME interactions. We identify spatially distinct evolution of copy number alterations influencing local immune composition. Sub-regions with chromosome 7 gain display a relative lack of leukocyte infiltrate but evidence of neutrophil activation, recapitulated in The Cancer Genome Atlas (TCGA) samples, and associated with lack of response to IO across three clinical cohorts. Whether neutrophil activation represents cause or consequence of local tumor necrosis requires further study. Analyses of T-cell clonotypes reveal the presence of recurrent priming events manifesting in a dominant T-cell clonotype over many years. Our findings highlight the links between marked levels of genomic and immune heterogeneity within the physical space of a tumor, with implications for biomarker evaluation and immunotherapy response.