Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq

Impact of Circulating Lymphoma Cells on HLA Typing Outcomes in Patients with Diffuse Large B-Cell Lymphoma: A Case Report

BACKGROUND

Recipient's high resolution HLA typing is required in allogeneic hematopoietic cell transplantation from unrelated donors, as well as for haploidentical family donors. For these purposes, Next-Generation Sequencing (NGS) methods are the gold standard.

METHODS

We present a case of a patient with an incorrect HLA typing result caused by the population of circulating lymphoma cells. The first HLA examination was performed from peripheral blood (PB) using NGS in the active phase of diffuse large B-cell lymphoma with bone marrow involvement.

RESULTS

Because of rare and inconclusive results, confirmed twice for the A* locus (A*02:32N), real-time polymerase chain reaction (RT-PCR)was performed. With RT-PCR method, we obtained more expected results according to the population allele frequency: in HLA-A locus (A*02:01) but also in DQB1 (DQB1*03:01, not as in NGS - DQB1*03:10). For the final verification, we used swab material and we obtained unambiguous NGS result with expected, frequent HLA-A*02:01 and DQB1*03:01 alleles corresponding to the RT-PCR result from PB.

CONCLUSIONS

To conclude, we suspect that the discrepancies between NGS and RT-PCR results were caused by the presence of a significant amount of circulating lymphoma cells in the peripheral blood sample. Lymphomagenic mutations may involve the histocompatibility antigen coding region and affect HLA expressed on malignant cells. This finding may be relevant for the selection of test material in primary and confirmatory HLA testing in patients with active hematological malignancies because of the strong impact of incorrect HLA typing on the procedure of a donor selection.

Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Intraductal papillary mucinous neoplasms (IPMN) are cystic precursor lesions to pancreatic ductal adenocarcinoma (PDAC). IPMNs undergo multistep progression from low-grade (LG) to high-grade (HG) dysplasia, culminating in invasive neoplasia. While patterns of IPMN progression have been analyzed using multiregion sequencing for somatic mutations, there is no integrated assessment of molecular events, including copy-number alterations (CNA) and transcriptional changes that accompany IPMN progression. We performed laser capture microdissection on surgically resected IPMNs of varying grades of histologic dysplasia obtained from 23 patients, followed by whole-exome and whole-transcriptome sequencing. Overall, HG IPMNs displayed a significantly greater aneuploidy score than LG lesions, with chromosome 1q amplification being associated with HG progression and with cases that harbored co-occurring PDAC. Furthermore, the combined assessment of single-nucleotide variants (SNV) and CNAs identified both linear and branched evolutionary trajectories, underscoring the heterogeneity in the progression of LG lesions to HG and PDAC. At the transcriptome level, upregulation of MYC-regulated targets and downregulation of transcripts associated with the MHC class I antigen presentation machinery as well as pathways related to glycosylation were a common feature of progression to HG. In addition, the established PDAC transcriptional subtypes (basal-like and classical) were readily apparent within IPMNs. Taken together, this work emphasizes the role of 1q copy-number amplification as a putative biomarker of high-risk IPMNs, underscores the importance of immune evasion even in noninvasive precursor lesions, and reinforces that evolutionary pathways in IPMNs are heterogenous, comprised of both SNV and CNA-driven events.

SIGNIFICANCE

Integrated molecular analysis of genomic and transcriptomic alterations in the multistep progression of IPMNs, which are bona fide precursors of pancreatic cancer, identifies features associated with progression of low-risk lesions to high-risk lesions and cancer, which might enable patient stratification and cancer interception strategies.

Analysis of tafazzin and deoxyribonuclease 1 like 1 transcripts and X chromosome sequencing in the evaluation of the effect of mosaicism in the TAZ gene on phenotypes in a family affected by Barth syndrome

Barth syndrome is a rare disease affecting mitochondria structure and function in males. In our previous study, we have shown a new mutation (c.83T>A, p.Val28Glu) in the TAZ gene in two affected patients with congenital cardiomyopathy. Furthermore, women in this family had no mutations in their blood cells, whereas they only had mutations in the oral epithelial cells. The objective of the project was to evaluate the effect of intertissue mosaicisms on the Barth syndrome phenotypes, searching for another disease-related loci on chromosome X and finally to assess the consequences of the mutation. We conducted the advanced genetic study including cytogenetic research (constitutional karyotyping in blood and fibroblasts), NGS sequencing (with custom chromosome X sequencing together with the evaluation of loss of heterozygosity (LOH) and aberrations (CNV) in the whole genome) in four different tissues and sequencing of tafazzin and deoxyribonuclease 1 like 1 transcripts. The presence of deletions within the 5'untranslated region of the TAZ gene and/or the noncoding regions of the DNASE1L1 gene were detected in several tissues. Whereas, there is no intertissue mosaicism regarding point mutation in TAZ gene in all investigated tissues in female carriers. Only the male patient presented biochemical markers and neurological symptoms of Barth syndrome. All the female carriers are healthy and have normal tafazzin and deoxyribonuclease 1 like 1 transcripts in 2 analyzed tissues. The conclusion of this study is that we cannot rule out or confirm mosaicism in the noncoding regions of TAZ or DNASE1L1 genes, but this is not clinically relevant in female carriers because they are healthy. Finally, it has been proven that mutation (c.83T>A, p.Val28Glu) is responsible for disease in males in this family.

Allelic Complexity of KMT2A Partial Tandem Duplications in Acute Myeloid Leukemia and Myelodysplastic Syndromes

KMT2A-PTD undergo complex allelic events associated with advanced disease stage (AML over MDS), progression, and increased PTD expression.

KMT2A-PTD detection, quantification, and allelic characterization can be integrated into standard panel-based DNA sequencing tests.

KMT2A partial tandem duplication (KMT2A-PTD) is an adverse risk factor in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS), a potential therapeutic target, and an attractive marker of measurable residual disease. High initial KMT2A-PTD RNA levels have been linked to poor prognosis, but mechanisms regulating KMT2A-PTD expression are not well understood. Although KMT2A-PTD has been reported to affect only a single allele, it has been theorized but not proven that genomic gains of a monoallelic KMT2A-PTD may occur, thereby potentially driving high expression and disease progression. In this study, we identified 94 patients with KMT2A-PTDs using targeted DNA next-generation sequencing (NGS) and found that 16% (15/94) had complex secondary events, including copy-neutral loss of heterozygosity and selective gain involving the KMT2A-PTD allele. High copy numbers indicating complexity were significantly enriched in AML vs MDS and correlated with higher RNA expression. Moreover, in serial samples, complexity was associated with relapse and secondary transformation. Taken together, we provide approaches to integrate quantitative and allelic assessment of KMT2A-PTDs into targeted DNA NGS and demonstrate that secondary genetic events occur in KMT2A-PTD by multiple mechanisms that may be linked to myeloid disease progression by driving increased expression from the affected allele.

Chromosomal imbalances detected via RNA-sequencing in 28 cancers

MOTIVATION

RNA-sequencing (RNA-seq) of tumor tissue is typically only used to measure gene expression. Here, we present a statistical approach that leverages existing RNA-seq data to also detect somatic copy number alterations (SCNAs), a pervasive phenomenon in human cancers, without a need to sequence the corresponding DNA.

RESULTS

We present an analysis of 4942 participant samples from 28 cancers in The Cancer Genome Atlas (TCGA), demonstrating robust detection of SCNAs from RNA-seq. Using genotype imputation and haplotype information, our RNA-based method had a median sensitivity of 85% to detect SCNAs defined by DNA analysis, at high specificity (∼95%). As an example of translational potential, we successfully replicated SCNA features associated with breast cancer subtypes. Our results credential haplotype-based inference based on RNA-seq to detect SCNAs in clinical and population-based settings.

AVAILABILITY AND IMPLEMENTATION

The analyses presented use the data publicly available from TCGA Research Network (http://cancergenome.nih.gov/). See Methods for details regarding data downloads. hapLOHseq software is freely available under The MIT license and can be downloaded from http://scheet.org/software.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Pan cancer patterns of allelic imbalance from chromosomal alterations in 33 tumor types

Somatic copy number alterations (SCNAs) serve as hallmarks of tumorigenesis and often result in deviations from one-to-one allelic ratios at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation algorithm, providing segment mean copy number estimates from single-nucleotide polymorphism DNA microarray total intensities (log R ratio), but not allele-specific intensities ("B allele" frequencies) that inform of AI. Our approach provides more sensitive identification of SCNAs by modeling the "B allele" frequencies jointly, thereby bolstering the catalog of chromosomal alterations in this widely utilized resource. Here we present AI summaries for all 33 tumor sites in TCGA, including those induced by SCNAs and copy-neutral loss-of-heterozygosity (cnLOH). We identified AI in 94% of the tumors, higher than in previous reports. Recurrent events included deletions of 17p, 9q, 3p, amplifications of 8q, 1q, 7p, as well as mixed event types on 8p and 13q. We also observed both site-specific and pan-cancer (spanning 17p) cnLOH, patterns which have not been comprehensively characterized. The identification of such cnLOH events elucidates tumor suppressors and multi-hit pathways to carcinogenesis. We also contrast the landscapes inferred from AI- and total intensity-derived SCNAs and propose an automated procedure to improve and adjust SCNAs in TCGA for cases where high levels of aneuploidy obscured baseline intensity identification. Our findings support the exploration of additional methods for robust automated inference procedures and to aid empirical discoveries across TCGA.

Defining the Comprehensive Genomic Landscapes of Pancreatic Ductal Adenocarcinoma Using Real-World Endoscopic Aspiration Samples

PURPOSE

Most patients with pancreatic ductal adenocarcinoma (PDAC) present with surgically unresectable cancer. As a result, endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is the most common biospecimen source available for diagnosis in treatment-naïve patients. Unfortunately, these limited samples are often not considered adequate for genomic analysis, precluding the opportunity for enrollment on precision medicine trials.

EXPERIMENTAL DESIGN

Applying an epithelial cell adhesion molecule (EpCAM)-enrichment strategy, we show the feasibility of using real-world EUS-FNA for in-depth, molecular-barcoded, whole-exome sequencing (WES) and somatic copy-number alteration (SCNA) analysis in 23 patients with PDAC.

RESULTS

Potentially actionable mutations were identified in >20% of patients. Further, an increased mutational burden and higher aneuploidy in WES data were associated with an adverse prognosis. To identify predictive biomarkers for first-line chemotherapy, we developed an SCNA-based complexity score that was associated with response to platinum-based regimens in this cohort.

CONCLUSIONS

Collectively, these results emphasize the feasibility of real-world cytology samples for in-depth genomic characterization of PDAC and show the prognostic potential of SCNA for PDAC diagnosis.

Multiomics profiling of primary lung cancers and distant metastases reveals immunosuppression as a common characteristic of tumor cells with metastatic plasticity

BACKGROUND

Metastasis is the primary cause of cancer mortality accounting for 90% of cancer deaths. Our understanding of the molecular mechanisms driving metastasis is rudimentary.

RESULTS

We perform whole exome sequencing (WES), RNA sequencing, methylation microarray, and immunohistochemistry (IHC) on 8 pairs of non-small cell lung cancer (NSCLC) primary tumors and matched distant metastases. Furthermore, we analyze published WES data from 35 primary NSCLC and metastasis pairs, and transcriptomic data from 4 autopsy cases with metastatic NSCLC and one metastatic lung cancer mouse model. The majority of somatic mutations are shared between primary tumors and paired distant metastases although mutational signatures suggest different mutagenesis processes in play before and after metastatic spread. Subclonal analysis reveals evidence of monoclonal seeding in 41 of 42 patients. Pathway analysis of transcriptomic data reveals that downregulated pathways in metastases are mainly immune-related. Further deconvolution analysis reveals significantly lower infiltration of various immune cell types in metastases with the exception of CD4+ T cells and M2 macrophages. These results are in line with lower densities of immune cells and higher CD4/CD8 ratios in metastases shown by IHC. Analysis of transcriptomic data from autopsy cases and animal models confirms that immunosuppression is also present in extracranial metastases. Significantly higher somatic copy number aberration and allelic imbalance burdens are identified in metastases.

CONCLUSIONS

Metastasis is a molecularly late event, and immunosuppression driven by different molecular events, including somatic copy number aberration, may be a common characteristic of tumors with metastatic plasticity.

Detection of mosaicism for segmental and whole chromosome imbalances by targeted sequencing

Mosaic segmental and whole chromosome copy number alterations are postzygotic variations known to be associated with several disorders. We have previously presented an efficient targeted sequencing approach to simultaneously detect point mutations and copy number variations (CNVs). In this study, we evaluated the efficiency of this approach to detect mosaic CNVs, using seven postnatal and 19 tumor samples, previously characterized by chromosomal microarray analyses (CMA). These samples harbored a total of 28 genomic imbalances ranging in size from 0.68 to 171 Mb, and present in 10-80% of the cells. All CNV regions covered by the platform were correctly identified in postnatal samples, and only seven out of 19 CNVs from tumor samples were not identified either because of a lack of target probes in the affected genomic regions or an absence of minimum reads for an alteration call. These results demonstrate that, in a research setting, this is a robust approach for detecting mosaicism in cases of segmental and whole chromosome alterations. Although the current sequencing platform presented a resolution similar to genomic microarrays, it is still necessary to further validate this approach in a clinical setting in order to replace CMA and sequencing analyses by a single test.

Large-scale analysis of acquired chromosomal alterations in non-tumor samples from patients with cancer

Mosaicism, the presence of subpopulations of cells bearing somatic mutations, is associated with disease and aging and has been detected in diverse tissues, including apparently normal cells adjacent to tumors. To analyze mosaicism on a large scale, we surveyed haplotype-specific somatic copy number alterations (sCNAs) in 1,708 normal-appearing adjacent-to-tumor (NAT) tissue samples from 27 cancer sites and in 7,149 blood samples from The Cancer Genome Atlas. We find substantial variation across tissues in the rate, burden and types of sCNAs, including those spanning entire chromosome arms. We document matching sCNAs in the NAT tissue and the adjacent tumor, suggesting a shared clonal origin, as well as instances in which both NAT tissue and tumor tissue harbor a gain of the same oncogene arising in parallel from distinct parental haplotypes. These results shed light on pan-tissue mutations characteristic of field cancerization, the presence of oncogenic processes adjacent to cancer cells.

Investigation of somatic CNVs in brains of synucleinopathy cases using targeted SNCA analysis and single cell sequencing

Synucleinopathies are mostly sporadic neurodegenerative disorders of partly unexplained aetiology, and include Parkinson's disease (PD) and multiple system atrophy (MSA). We have further investigated our recent finding of somatic SNCA (α-synuclein) copy number variants (CNVs, specifically gains) in synucleinopathies, using Fluorescent in-situ Hybridisation for SNCA, and single-cell whole genome sequencing for the first time in a synucleinopathy. In the cingulate cortex, mosaicism levels for SNCA gains were higher in MSA and PD than controls in neurons (> 2% in both diseases), and for MSA also in non-neurons. In MSA substantia nigra (SN), we noted SNCA gains in > 3% of dopaminergic (DA) neurons (identified by neuromelanin) and neuromelanin-negative cells, including olig2-positive oligodendroglia. Cells with CNVs were more likely to have α-synuclein inclusions, in a pattern corresponding to cell categories mostly relevant to the disease: DA neurons in Lewy-body cases, and other cells in the striatonigral degeneration-dominant MSA variant (MSA-SND). Higher mosaicism levels in SN neuromelanin-negative cells may correlate with younger onset in typical MSA-SND, and in cingulate neurons with younger death in PD. Larger sample sizes will, however, be required to confirm these putative findings. We obtained genome-wide somatic CNV profiles from 169 cells from the substantia nigra of two MSA cases, and pons and putamen of one. These showed somatic CNVs in ~ 30% of cells, with clonality and origins in segmental duplications for some. CNVs had distinct profiles based on cell type, with neurons having a mix of gains and losses, and other cells having almost exclusively gains, although control data sets will be required to determine possible disease relevance. We propose that somatic SNCA CNVs may contribute to the aetiology and pathogenesis of synucleinopathies, and that genome-wide somatic CNVs in MSA brain merit further study.

Multi-region exome sequencing reveals genomic evolution from preneoplasia to lung adenocarcinoma

There has been a dramatic increase in the detection of lung nodules, many of which are preneoplasia atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (ADC). The molecular landscape and the evolutionary trajectory of lung preneoplasia have not been well defined. Here, we perform multi-region exome sequencing of 116 resected lung nodules including AAH (n = 22), AIS (n = 27), MIA (n = 54) and synchronous ADC (n = 13). Comparing AAH to AIS, MIA and ADC, we observe progressive genomic evolution at the single nucleotide level and demarcated evolution at the chromosomal level supporting the early lung carcinogenesis model from AAH to AIS, MIA and ADC. Subclonal analyses reveal a higher proportion of clonal mutations in AIS/MIA/ADC than AAH suggesting neoplastic transformation of lung preneoplasia is predominantly associated with a selective sweep of unfit subclones. Analysis of multifocal pulmonary nodules from the same patients reveal evidence of convergent evolution.

There has been a drastic increase in detection of lung nodules, many of which are precancers, preinvasive, minimally invasive or sometimes invasive lung cancers. Here, Hu et al. perform multi-region exome sequencing to discern the evolutional trajectory from precancers to invasive lung cancers.

Directional allelic imbalance profiling and visualization from multi-sample data with RECUR

MOTIVATION

Genetic analysis of cancer regularly includes two or more samples from the same patient. Somatic copy number alterations leading to allelic imbalance (AI) play a critical role in cancer initiation and progression. Directional analysis and visualization of the alleles in imbalance in multi-sample settings allow for inference of recurrent mutations, providing insights into mutation rates, clonality and the genomic architecture and etiology of cancer.

RESULTS

The REpeat Chromosomal changes Uncovered by Reflection (RECUR) is an R application for the comparative analysis of AI profiles derived from SNP array and next-generation sequencing data. The algorithm accepts genotype calls and 'B allele' frequencies (BAFs) from at least two samples derived from the same individual. For a predefined set of genomic regions with AI, RECUR compares BAF values among samples. In the presence of AI, the expected value of a BAF can shift in two possible directions, reflecting an increased or decreased abundance of the maternal haplotype, relative to the paternal. The phenomenon of opposite haplotype shifts, or 'mirrored subclonal allelic imbalance', is a form of heterogeneity, and has been linked to clinico-pathological features of cancer. RECUR detects such genomic segments of opposite haplotypes in imbalance and plots BAF values for all samples, using a two-color scheme for intuitive visualization.

AVAILABILITY AND IMPLEMENTATION

RECUR is available as an R application. Source code and documentation are available at scheet.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

System for Quality-Assured Data Analysis: Flexible, reproducible scientific workflows

The reproducibility of scientific processes is one of the paramount problems of bioinformatics, an engineering problem that must be addressed to perform good research. The System for Quality-Assured Data Analysis (SyQADA), described here, seeks to address reproducibility by managing many of the details of procedural bookkeeping in bioinformatics in as simple and transparent a manner as possible. SyQADA has been used by persons with backgrounds ranging from expert programmer to Unix novice, to perform and repeat dozens of diverse bioinformatics workflows on tens of thousands of samples, consuming over 80 CPU-months of computing on over 300,000 individual tasks of scores of projects on laptops, computer servers, and computing clusters. SyQADA is especially well-suited for paired-sample analyses found in cancer tumor-normal studies. SyQADA executable source code, documentation, tutorial examples, and workflows used in our lab is available from http://scheet.org/software.html.

Translational genomics in pancreatic ductal adenocarcinoma: A review with re-analysis of TCGA dataset

Malignancy of the pancreas is a leading cause of cancer-related mortality, with the highest case-fatality of all cancers. Nevertheless, the lack of sensitive biomarkers and presence of biological heterogeneity precludes its early detection and effective treatment. The recent introduction of next-generation sequencing allows characterization of multiple driver mutations at genome- and exome-wide levels. Sequencing of DNA and RNA from circulating tumour cells has also opened an exciting era of non-invasive procedures for tumour detection and prognostication. This massively-parallel sequencing technology has uncovered the previously obscure molecular mechanisms, providing clues for better stratification of patients and identification of druggable targets for the disease. Identification of active oncogenic pathways and gene-gene interactions may reveal oncogene addiction and synthetic lethality. Relevant findings can be extrapolated to develop targeted and personalized therapeutic interventions. In addition to known mutational events, the role of chromosomal rearrangements in pancreatic neoplasms is gradually uncovered. Coupled with bioinformatics pipelines and epidemiological analyses, a better framework for risk stratification and prognostication of pancreatic cancer will be possible in the near future. In this review, we discuss how translational genomic studies facilitate our understanding of pathobiology, and development of novel diagnostics and therapeutics for pancreatic ductal adenocarcinoma with emphases on whole genome sequencing, whole exome sequencing, and liquid biopsies. We have also re-analyzed The Cancer Genome Atlas (TCGA) dataset to look for genetic features associated with altered survival in patients with pancreatic ductal adenocarcinoma.

Dynamic changes during the treatment of pancreatic cancer

This manuscript follows a single patient with pancreatic adenocarcinoma for a five year period, detailing the clinical record, pathology, the dynamic evolution of molecular and cellular alterations as well as the responses to treatments with chemotherapies, targeted therapies and immunotherapies. DNA and RNA samples from biopsies and blood identified a dynamic set of changes in allelic imbalances and copy number variations in response to therapies. Organoid cultures established from biopsies over time were employed for extensive drug testing to determine if this approach was feasible for treatments. When an unusual drug response was detected, an extensive RNA sequencing analysis was employed to establish novel mechanisms of action of this drug. Organoid cell cultures were employed to identify possible antigens associated with the tumor and the patient's T-cells were expanded against one of these antigens. Similar and identical T-cell receptor sequences were observed in the initial biopsy and the expanded T-cell population. Immunotherapy treatment failed to shrink the tumor, which had undergone an epithelial to mesenchymal transition prior to therapy. A warm autopsy of the metastatic lung tumor permitted an extensive analysis of tumor heterogeneity over five years of treatment and surgery. This detailed analysis of the clinical descriptions, imaging, pathology, molecular and cellular evolution of the tumors, treatments, and responses to chemotherapy, targeted therapies, and immunotherapies, as well as attempts at the development of personalized medical treatments for a single patient should provide a valuable guide to future directions in cancer treatment.

Informatics for cancer immunotherapy

The rapid development of immunomodulatory cancer therapies has led to a concurrent increase in the application of informatics techniques to the analysis of tumors, the tumor microenvironment, and measures of systemic immunity. In this review, the use of tumors to gather genetic and expression data will first be explored. Next, techniques to assess tumor immunity are reviewed, including HLA status, predicted neoantigens, immune microenvironment deconvolution, and T-cell receptor sequencing. Attempts to integrate these data are in early stages of development and are discussed in this review. Finally, we review the application of these informatics strategies to therapy development, with a focus on vaccines, adoptive cell transfer, and checkpoint blockade therapies.