Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood.

Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European American (EA) ancestry group compared to those of Hispanic American (HA), African American (AA), and East Asian (EAS) ancestry. Further, we identified two genes ( CFHR1 and LRP6 ) that harbor multiple rare, putatively deleterious variants associated with mLOY susceptibility, show that subsets of human hematopoietic stem cells are enriched for activity of mLOY susceptibility variants, and that certain alleles on chromosome Y are more likely to be lost than others.

Determinants of mosaic chromosomal alteration fitness.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.

Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.

Determinants of mosaic chromosomal alteration fitness.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well-understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our estimates of mCA fitness were correlated (R 2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using a theoretical probability distribution. Individuals with lymphoid-associated mCAs had a significantly higher white blood cell count and faster clonal expansion rate. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified TCL1A , NRIP1 , and TERT locus variants as modulators of mCA clonal expansion rate.

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.

Risk factors for clonal hematopoiesis of indeterminate potential and mosaic chromosomal alterations.

Clonal hematopoiesis of indeterminate potential (CHIP) and mosaic chromosomal alterations (mCAs) of the autosomes, X, and Y chromosomes are aging-related somatic mutations detectable in peripheral blood. The presence of these acquired mutations predisposes otherwise healthy adults to increased risk of several chronic aging-related conditions including hematologic cancers, atherosclerotic cardiovascular diseases, other inflammatory conditions, and mortality. While the public health impact and disease associations of these blood-derived somatic mutations continue to expand, the inherited, behavioral/lifestyle, environmental risk factors and comorbid conditions that influence their occurrence and progression have been less well characterized. Age is the strongest risk factor for all types of CHIP and mCAs. CHIP and mCAs are generally more common in individuals of European than non-European ancestry. Evidence for a genetic predisposition has been strongest for mosaic loss of Y chromosome in men. Genome-wide association studies have recently begun to identify common and rare germline genetic variants associated with CHIP and mCAs. These loci include genes involving cell cycle regulation, cell proliferation/survival, hematopoietic progenitor cell regulation, DNA damage repair, and telomere maintenance. Some loci, such as TERT, ATM, TP53, CHEK2, and TCL1A, have overlapping associations with different types of CHIP, mCAs, and cancer predisposition. Various environmental or co-morbid contexts associated with presence or expansion of specific CHIP or mCA mutations are beginning to be elucidated, such as cigarette smoking, diet, cancer chemotherapy, particulate matter, and premature menopause. Further characterization of the germline genetic and environmental correlates of CHIP/mCAs may inform our ability to modify their progression and ultimately reduce the risk and burden of chronic diseases associated with these clonal somatic phenomena.

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.

Genomic landscape of allelic imbalance in premalignant atypical adenomatous hyperplasias of the lung.

BACKGROUND: Genomic investigation of atypical adenomatous hyperplasia (AAH), the only known precursor lesion to lung adenocarcinomas (LUAD), presents challenges due to the low mutant cell fractions. This necessitates sensitive methods for detection of chromosomal aberrations to better study the role of critical alterations in early lung cancer pathogenesis and the progression from AAH to LUAD. METHODS: We applied a sensitive haplotype-based statistical technique to detect chromosomal alterations leading to allelic imbalance (AI) from genotype array profiling of 48 matched normal lung parenchyma, AAH and tumor tissues from 16 stage-I LUAD patients. To gain insights into shared developmental trajectories among tissues, we performed phylogenetic analyses and integrated our results with point mutation data, highlighting significantly-mutated driver genes in LUAD pathogenesis. FINDINGS: AI was detected in nine AAHs (56%). Six cases exhibited recurrent loss of 17p. AI and the enrichment of 17p events were predominantly identified in patients with smoking history. Among the nine AAH tissues with detected AI, seven exhibited evidence for shared chromosomal aberrations with matched LUAD specimens, including losses harboring tumor suppressors on 17p, 8p, 9p, 9q, 19p, and gains encompassing oncogenes on 8q, 12p and 1q. INTERPRETATION: Chromosomal aberrations, particularly 17p loss, appear to play critical roles early in AAH pathogenesis. Genomic instability in AAH, as well as truncal chromosomal aberrations shared with LUAD, provide evidence for mutation accumulation and are suggestive of a cancerized field contributing to the clonal selection and expansion of these premalignant lesions. FUND: Supported in part by Cancer Prevention and Research Institute of Texas (CPRIT) grant RP150079 (PS and HK), NIH grant R01HG005859 (PS) and The University of Texas MD Anderson Cancer Center Core Support Grant.

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.

Assessing inter-component heterogeneity of biphasic uterine carcinosarcomas.

OBJECTIVE: Uterine carcinosarcoma (UCS) is a rare and aggressive form of uterine cancer. It is bi-phasic, exhibiting histological features of both malignant epithelial (carcinoma) and mesenchymal (sarcoma) elements, reflected in ambiguity in accepted treatment guidelines. We sought to study the genomic and transcriptomic profiles of these elements individually to gain further insights into the development of these tumors. METHODS: We macro-dissected carcinomatous, sarcomatous, and normal tissues from formalin fixed paraffin embedded uterine samples of 10 UCS patients. Single nucleotide polymorphism microarrays, targeted DNA sequencing and whole-transcriptome RNA-sequencing were performed. Somatic chromosomal alterations (SCAs), point mutation and gene expression profiles were compared between carcinomatous and sarcomatous components. RESULTS: In addition to TP53, other recurrently mutated genes harboring putative driver or loss-of-function mutations included PTEN, FBXW7, FGFR2, KRAS, PIK3CA and CTNNB1, genes known to be involved in UCS. Intra-patient somatic mutation and SCA profiles were highly similar between paired carcinoma and sarcoma samples. An epithelial-mesenchymal transition (EMT) signature tended to differentiate components, with EMT-like status more common in advanced-stage patients exhibiting higher inter-component SCA heterogeneity. CONCLUSIONS: From DNA analysis, our results indicate a monoclonal disease origin for this cohort. Yet expression-derived EMT statuses of the carcinomatous and sarcomatous components were often discrepant, and advanced cases displayed greater genomic heterogeneity. Therefore, separately-profiled components of UCS tumors may better inform disease progression or potential.

A model of binding on DNA microarrays: understanding the combined effect of probe synthesis failure, cross-hybridization, DNA fragmentation and other experimental details of affymetrix arrays.

BACKGROUND: DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin. RESULTS: For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform. CONCLUSIONS: To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These two factors are sequence dependent and have a large impact on probe intensity. The results presented here provide novel insight into the effect of probe synthesis errors on Affymetrix microarrays; furthermore, the algorithms developed in this work provide useful tools for the analysis of cross-hybridization, probe synthesis efficiency, fragmentation, wash stringency, temperature, and salt concentration on microarray intensities.