Multiple imputation and direct estimation for qPCR data with non-detects.

BACKGROUND: Quantitative real-time PCR (qPCR) is one of the most widely used methods to measure gene expression. An important aspect of qPCR data that has been largely ignored is the presence of non-detects: reactions failing to exceed the quantification threshold and therefore lacking a measurement of expression. While most current software replaces these non-detects with a value representing the limit of detection, this introduces substantial bias in the estimation of both absolute and differential expression. Single imputation procedures, while an improvement on previously used methods, underestimate residual variance, which can lead to anti-conservative inference. RESULTS: We propose to treat non-detects as non-random missing data, model the missing data mechanism, and use this model to impute missing values or obtain direct estimates of model parameters. To account for the uncertainty inherent in the imputation, we propose a multiple imputation procedure, which provides a set of plausible values for each non-detect. We assess the proposed methods via simulation studies and demonstrate the applicability of these methods to three experimental data sets. We compare our methods to mean imputation, single imputation, and a penalized EM algorithm incorporating non-random missingness (PEMM). The developed methods are implemented in the R/Bioconductor package nondetects. CONCLUSIONS: The statistical methods introduced here reduce discrepancies in gene expression values derived from qPCR experiments in the presence of non-detects, providing increased confidence in downstream analyses.

Moving Genomics to Routine Care: An Initial Pilot in Acute Cardiovascular Disease.

BACKGROUND: Whole-genome sequencing (WGS) costs are falling, yet, outside oncology, this information is seldom used in adult clinics. We piloted a rapid WGS (rWGS) workflow, focusing initially on estimating power for a feasibility study of introducing genome information into acute cardiovascular care. METHODS: A prospective implementation study was conducted to test the feasibility and clinical utility of rWGS in acute cardiovascular care. rWGS was performed on 50 adult patients with acute cardiovascular events and cardiac arrest survivors, testing for primary and secondary disease-causing variants, cardiovascular-related pharmacogenomics, and carrier status for recessive diseases. The impact of returning rWGS results on short-term clinical care of participants was investigated. The utility of polygenic risk scores to stratify coronary artery disease was also assessed. RESULTS: Pathogenic variants, typically secondary findings, were identified in 20% (95% CI, 11.7-34.3). About 60% (95% CI, 46.2-72.4) of participants were carriers for one or more recessive traits, most commonly in HFE and SERPINA1 genes. Although 64% (95% CI, 50.1-75.9) of participants carried at least one pharmacogenetic variant of cardiovascular relevance, these were actionable in only 14% (95% CI, 7-26.2). Coronary artery disease prevalence among participants at the 95th percentile of polygenic risk score was 88.2% (95% CI, 71.8-95.7). CONCLUSIONS: We demonstrated the feasibility of rWGS integration into the inpatient management of adults with acute cardiovascular events. Our pilot identified pathogenic variants in one out of 5 acute vascular patients. Integrating rWGS in clinical care will progressively increase actionability.

Clinical and molecular characterization of virus-positive and virus-negative Merkel cell carcinoma.

BACKGROUND: Merkel cell carcinoma (MCC) is a highly aggressive neuroendocrine carcinoma of the skin caused by either the integration of Merkel cell polyomavirus (MCPyV) and expression of viral T antigens or by ultraviolet-induced damage to the tumor genome from excessive sunlight exposure. An increasing number of deep sequencing studies of MCC have identified significant differences between the number and types of point mutations, copy number alterations, and structural variants between virus-positive and virus-negative tumors. However, it has been challenging to reliably distinguish between virus positive and UV damaged MCC. METHODS: In this study, we assembled a cohort of 71 MCC patients and performed deep sequencing with OncoPanel, a clinically implemented, next-generation sequencing assay targeting over 400 cancer-associated genes. To improve the accuracy and sensitivity for virus detection compared to traditional PCR and IHC methods, we developed a hybrid capture baitset against the entire MCPyV genome and software to detect integration sites and structure. RESULTS: Sequencing from this approach revealed distinct integration junctions in the tumor genome and generated assemblies that strongly support a model of microhomology-initiated hybrid, virus-host, circular DNA intermediate that promotes focal amplification of host and viral DNA. Using the clear delineation between virus-positive and virus-negative tumors from this method, we identified recurrent somatic alterations common across MCC and alterations specific to each class of tumor, associated with differences in overall survival. Finally, comparing the molecular and clinical data from these patients revealed a surprising association of immunosuppression with virus-negative MCC and significantly shortened overall survival. CONCLUSIONS: These results demonstrate the value of high-confidence virus detection for identifying molecular mechanisms of UV and viral oncogenesis in MCC. Furthermore, integrating these data with clinical data revealed features that could impact patient outcome and improve our understanding of MCC risk factors.

ViroPanel: Hybrid Capture and Massively Parallel Sequencing for Simultaneous Detection and Profiling of Oncogenic Virus Infection and Tumor Genome.

Precision cancer medicine aims to classify tumors by site, histology, and molecular testing to determine an individualized profile of cancer alterations. Viruses are a major contributor to oncogenesis, causing 12% to 20% of all human cancers. Several viruses are causal of specific types of cancer, promoting dysregulation of signaling pathways and resulting in carcinogenesis. In addition, integration of viral DNA into the host (human) genome is a hallmark of some viral species. Tests for the presence of viral infection used in the clinical setting most often use quantitative PCR or immunohistochemical staining. Both approaches have limitations and need to be interpreted/scored appropriately. In some cases, results are not binary (virus present/absent), and it is unclear what to do with a weakly or partially positive result. In addition, viral testing of cancers is performed separately from tests to detect human genomic alterations and can thus be time-consuming and use limited valuable specimen. We present a hybrid-capture and massively parallel sequencing approach to detect viral infection that is integrated with targeted genomic analysis to provide a more complete tumor profile from a single sample.

Genomic landscape of colorectal cancer in Japan: clinical implications of comprehensive genomic sequencing for precision medicine.

BACKGROUND: Comprehensive genomic sequencing (CGS) has the potential to revolutionize precision medicine for cancer patients across the globe. However, to date large-scale genomic sequencing of cancer patients has been limited to Western populations. In order to understand possible ethnic and geographic differences and to explore the broader application of CGS to other populations, we sequenced a panel of 415 important cancer genes to characterize clinically actionable genomic driver events in 201 Japanese patients with colorectal cancer (CRC). METHODS: Using next-generation sequencing methods, we examined all exons of 415 known cancer genes in Japanese CRC patients (n = 201) and evaluated for concordance among independent data obtained from US patients with CRC (n = 108) and from The Cancer Genome Atlas-CRC whole exome sequencing (WES) database (n = 224). Mutation data from non-hypermutated Japanese CRC patients were extracted and clustered by gene mutation patterns. Two different sets of genes from the 415-gene panel were used for clustering: 61 genes with frequent alteration in CRC and 26 genes that are clinically actionable in CRC. RESULTS: The 415-gene panel is able to identify all of the critical mutations in tumor samples as well as WES, including identifying hypermutated tumors. Although the overall mutation spectrum of the Japanese patients is similar to that of the Western population, we found significant differences in the frequencies of mutations in ERBB2 and BRAF. We show that the 415-gene panel identifies a number of clinically actionable mutations in KRAS, NRAS, and BRAF that are not detected by hot-spot testing. We also discovered that 26% of cases have mutations in genes involved in DNA double-strand break repair pathway. Unsupervised clustering revealed that a panel of 26 genes can be used to classify the patients into eight different categories, each of which can optimally be treated with a particular combination therapy. CONCLUSIONS: Use of a panel of 415 genes can reliably identify all of the critical mutations in CRC patients and this information of CGS can be used to determine the most optimal treatment for patients of all ethnicities.