Design of targeted, capture-based, next generation sequencing tests for precision cancer therapy

A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan

BACKGROUND

Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing.

RESULTS

During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified.

CONCLUSIONS

The presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary "screening" tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.

Fishing for DNA? Designing baits for population genetics in target enrichment experiments: Guidelines, considerations and the new tool supeRbaits

Targeted sequencing is an increasingly popular next-generation sequencing (NGS) approach for studying populations that involves focusing sequencing efforts on specific parts of the genome of a species of interest. Methodologies and tools for designing targeted baits are scarce but in high demand. Here, we present specific guidelines and considerations for designing capture sequencing experiments for population genetics for both neutral genomic regions and regions subject to selection. We describe the bait design process for three diverse fish species: Atlantic salmon, Atlantic cod and tiger shark, which was carried out in our research group, and provide an evaluation of the performance of our approach across both historical and modern samples. The workflow used for designing these three bait sets has been implemented in the R-package supeRbaits, which encompasses our considerations and guidelines for bait design for the benefit of researchers and practitioners. The supeRbaits R-package is user-friendly and versatile. It is written in C++ and implemented in R. supeRbaits and its manual are available from Github: https://github.com/BelenJM/supeRbaits.

Targeted sequencing of crucial cancer causing genes of breast cancer in Saudi patients

Breast cancer is the most common cancer among women worldwide, causing 15% of cancer-related deaths among women. Breast cancer incidence rate is increasing in most countries. In Saudi Arabia, breast cancer constitutes nearly 22% of the newly diagnosed cancer cases in women. Breast cancer incidence in the women population of Saudi Arabia is 25.9%, with 18.2% mortality. In this study, targeted sequencing of 164 selected genes was performed on germline and somatic DNA derived from the blood and tissue samples of 50 breast cancer patients using customized panel on Ion torrent platform. This study focused on the identification of genetic variations of different cancer-causing genes, raising the hope for identification of personalized prognosis. After final filtration and validation, we found protein-truncating, non-synonymous missense, and splice site mutations in the known susceptibility genes for breast cancer. We identified a total of 14 point mutations and one deletion in BRCA1, BRCA2, and RAD50 genes from the BRCA panel analysis of breast cancer samples. In the customized panel analysis, we identified 37 potential mutations in 25 breast cancer risk associated genes. Out of these, most mutations were observed in TP53. After filtration, we observed 7 mutations in TP53 genes (n = 7:- one stop gain (p.R81X), four non-synonymous (p.R81X, p.Y88C, p.R141H, and p.V25D), and two deletions (c.59delC and c.327delC)). Among the mutations detected in our study, TP53 (p.R81X), VHL (p.E52X), and BRCA2 (p.K3326X) mutations, which lead to an aberrant transcript with a premature stop codon, were reported for the first time in breast cancer patients from Saudi Arabia. Our study will help in identifying the damaging mutations and predisposing genes in Saudi breast cancer patients.

Real-Time Selective Sequencing with RUBRIC: Read Until with Basecall and Reference-Informed Criteria

The Oxford MinION, the first commercial nanopore sequencer, is also the first to implement molecule-by-molecule real-time selective sequencing or “Read Until”. As DNA transits a MinION nanopore, real-time pore current data can be accessed and analyzed to provide active feedback to that pore. Fragments of interest are sequenced by default, while DNA deemed non-informative is rejected by reversing the pore bias to eject the strand, providing a novel means of background depletion and/or target enrichment. In contrast to the previously published pattern-matching Read Until approach, our RUBRIC method is the first example of real-time selective sequencing where on-line basecalling enables alignment against conventional nucleic acid references to provide the basis for sequence/reject decisions. We evaluate RUBRIC performance across a range of optimizable parameters, apply it to mixed human/bacteria and CRISPR/Cas9-cut samples, and present a generalized model for estimating real-time selection performance as a function of sample composition and computing configuration.

Bloom Syndrome Protein Activates AKT and PRAS40 in Prostate Cancer Cells

Purpose

Prostate cancer (PC) is a common malignant tumor and a leading cause of cancer-related death in men worldwide. In order to design new therapeutic interventions for PC, an understanding of the molecular events underlying PC tumorigenesis is required. Bloom syndrome protein (BLM) is a RecQ-like helicase, which helps maintain genetic stability. BLM dysfunction has been implicated in tumor development, most recently during PC tumorigenesis. However, the molecular basis for BLM-induced PC progression remains poorly characterized. In this study, we investigated whether BLM modulates the phosphorylation of an array of prooncogenic signaling pathways to promote PC progression.

Methods

We analyzed differentially expressed proteins (DEPs) using iTRAQ technology. Site-directed knockout of BLM in PC-3 prostate cancer cells was performed using CRISPR/Cas9-mediated homologous recombination gene editing to confirm the effects of BLM on DEPs. PathScan® Antibody Array Kits were used to analyze the phosphorylation of nodal proteins in PC tissue. Immunohistochemistry and automated western blot (WES) analyses were used to validate these findings.

Results

We found that silencing BLM in PC-3 cells significantly reduced their proliferative capacity. In addition, BLM downregulation significantly reduced levels of phosphorylated protein kinase B (AKT (Ser473)) and proline-rich AKT substrate of 40 kDa (PRAS40 (Thr246)), and this was accompanied by enhanced ROS (reactive oxygen species) levels. In addition, we found that AKT and PRAS40 inhibition reduced BLM, increased ROS levels, and induced PC cell apoptosis.

Conclusions

We demonstrated that BLM activates AKT and PRAS40 to promote PC cell proliferation and survival. We further propose that ROS act in concert with BLM to facilitate PC oncogenesis, potentially via further enhancing AKT signaling and downregulating PTEN expression. Importantly, inhibiting the BLM-AKT-PRAS40 axis induced PC cell apoptosis. Thus, we highlight new avenues for novel anti-PC treatments.

Describing the Reportable Range Is Important for Reliable Treatment Decisions: A Multiple Laboratory Study for Molecular Tumor Profiling Using Next-Generation Sequencing

Because interpretation of next-generation sequencing (NGS) data remains challenging, optimization of the NGS process is needed to obtain correct sequencing results. Therefore, extensive validation and continuous monitoring of the quality is essential. NGS performance was compared with traditional detection methods and technical quality of nine NGS technologies was assessed. First, nine formalin-fixed, paraffin-embedded patient samples were analyzed by 114 laboratories by using different detection methods. No significant differences in performance were observed between analyses with NGS and traditional techniques. Second, two DNA control samples were analyzed for a selected number of variants by 26 participants with the use of nine different NGS technologies. Quality control metrics were analyzed from raw data files and a survey about routine procedures. Results showed large differences in coverages, but observed variant allele frequencies in raw data files were in line with predefined variant allele frequencies. Many false negative results were found because of low-quality regions, which were not reported as such. It is recommended to disclose the reportable range, the fraction of targeted genomic regions for which calls of acceptable quality can be generated, to avoid any errors in therapy decisions. NGS can be a reliable technique, only if essential quality control during analysis is applied and reported.

Circulating tumor DNA in blood: Future genomic biomarkers for cancer detection

Cancer is characterized by Darwinian evolution and is a primary cause of mortality and morbidity around the globe. Over the preceding decade, the treatment of cancer has been markedly improved by many targeted therapies, but these treatments have given birth to new challenges and issues. Clonal evolution and tumor heterogeneity present a significant challenge in designing cancer therapies. Fortunately, these restrictions have been overcome by technological advancements allowing us to track both genetic and epigenetic aberrations. Cell-free circulating tumor DNA (ctDNA) analysis, or "liquid biopsy" from a blood sample, provides the opportunity to track the genetic landscape of cancerous lesions. This review focuses on ctDNA analysis as a noninvasive method and versatile biomarker for cancer treatment and technological advancements for ctDNA analysis. This method may able to cope with all the challenges associated with previous cancer therapies and has the potential to monitor minimal residual disease, tumor burden, and therapy response and provide rapid detection of relapse. However, there are many challenges that still need to be addressed. Future prognosis, diagnosis, and analysis of ctDNA require reproducibility and accuracy of results, which are not possible without the validation and optimization of procedures. Integrated digital error suppression has thus far shown promise in the detection of ctDNA in cancer.

MERIT reveals the impact of genomic context on sequencing error rate in ultra-deep applications

BACKGROUND

Rapid progress in high-throughput sequencing (HTS) and the development of novel library preparation methods have improved the sensitivity of detecting mutations in heterogeneous samples, specifically in high-depth (> 500×) clinical applications. However, HTS methods are bounded by their technical and theoretical limitations and sequencing errors cannot be completely eliminated. Comprehensive quantification of the background noise can highlight both the efficiency and the limitations of any HTS methodology, and help differentiate true mutations at low abundance from artifacts.

RESULTS

We introduce MERIT (Mutation Error Rate Inference Toolkit), designed for in-depth quantification of erroneous substitutions and small insertions and deletions. MERIT incorporates an all-inclusive variant caller and considers genomic context, including the nucleotides immediately at 5 'and 3 ', thereby establishing error rates for 96 possible substitutions as well as four single-base and 16 double-base indels. We applied MERIT to ultra-deep sequencing data (1,300,000 ×) obtained from the amplification of multiple clinically relevant loci, and showed a significant relationship between error rates and genomic contexts. In addition to observing significant difference between transversion and transition rates, we identified variations of more than 100-fold within each error type at high sequencing depths. For instance, T >G transversions in trinucleotide GTCs occurred 133.5 ± 65.9 more often than those in ATAs. Similarly, C >T transitions in GCGs were observed at 73.8 ± 10.5 higher rate than those in TCTs. We also devised an in silico approach to determine the optimal sequencing depth, where errors occur at rates similar to those of expected true mutations. Our analyses showed that increasing sequencing depth might improve sensitivity for detecting some mutations based on their genomic context. For example, T >G rate of error in GTCs did not change when sequenced beyond 10,000 ×; in contrast, T >G rate in TTAs consistently improved even at above 500,000 ×.

CONCLUSIONS

Our results demonstrate significant variation in nucleotide misincorporation rates, and suggest that genomic context should be considered for comprehensive profiling of specimen-specific and sequencing artifacts in high-depth assays. This data provide strong evidence against assigning a single allele frequency threshold to call mutations, for it can result in substantial false positive as well as false negative variants, with important clinical consequences.

Cancer diagnostics: The journey from histomorphology to molecular profiling

Although histomorphology has made significant advances into the understanding of cancer etiology, classification and pathogenesis, it is sometimes complicated by morphologic ambiguities, and other shortcomings that necessitate the development of ancillary tests to complement its diagnostic value. A new approach to cancer patient management consists of targeting specific molecules or gene mutations in the cancer genome by inhibitory therapy. Molecular diagnostic tests and genomic profiling methods are increasingly being developed to identify tumor targeted molecular profile that is the basis of targeted therapy. Novel targeted therapy has revolutionized the treatment of gastrointestinal stromal tumor, renal cell carcinoma and other cancers that were previously difficult to treat with standard chemotherapy. In this review, we discuss the role of histomorphology in cancer diagnosis and management and the rising role of molecular profiling in targeted therapy. Molecular profiling in certain diagnostic and therapeutic difficulties may provide a practical and useful complement to histomorphology and opens new avenues for targeted therapy and alternative methods of cancer patient management.

Development of a targeted sequencing approach to identify prognostic, predictive and diagnostic markers in paediatric solid tumours

The implementation of personalised medicine in childhood cancers has been limited by a lack of clinically validated multi-target sequencing approaches specific for paediatric solid tumours. In order to support innovative clinical trials in high-risk patients with unmet need, we have developed a clinically relevant targeted sequencing panel spanning 311 kb and comprising 78 genes involved in childhood cancers. A total of 132 samples were used for the validation of the panel, including Horizon Discovery cell blends (n=4), cell lines (n=15), formalin-fixed paraffin embedded (FFPE, n=83) and fresh frozen tissue (FF, n=30) patient samples. Cell blends containing known single nucleotide variants (SNVs, n=528) and small insertion-deletions (indels n=108) were used to define panel sensitivities of ≥98% for SNVs and ≥83% for indels [95% CI] and panel specificity of ≥98% [95% CI] for SNVs. FFPE samples performed comparably to FF samples (n=15 paired). Of 95 well-characterised genetic abnormalities in 33 clinical specimens and 13 cell lines (including SNVs, indels, amplifications, rearrangements and chromosome losses), 94 (98.9%) were detected by our approach. We have validated a robust and practical methodology to guide clinical management of children with solid tumours based on their molecular profiles. Our work demonstrates the value of targeted gene sequencing in the development of precision medicine strategies in paediatric oncology.

Formalin-fixed paraffin-embedded sample conditions for deep next generation sequencing

INTRODUCTION

Precision medicine is only possible in oncology practice if targetable genes in fragmented DNA, such as DNA from formalin-fixed paraffin-embedded (FFPE) samples, can be sequenced using next generation sequencing (NGS). The aim of this study was to examine the quality and quantity of DNA from FFPE cancerous tissue samples from surgically resected and biopsy specimens.

METHODS

DNA was extracted from unstained FFPE tissue sections prepared from surgically resected specimens of breast, colorectal and gastric cancer, and biopsy specimens of breast cancer. A total quantity of DNA ≥60 ng from a sample was considered adequate for NGS. The DNA quality was assessed by Q-ratios, with a Q-ratio >0.1 considered sufficient for NGS.

RESULTS

The Q-ratio for DNA from FFPE tissue processed with neutral-buffered formalin was significantly better than that processed with unbuffered formalin. All Q-ratios for DNA from breast, colorectal and gastric cancer samples indicated DNA levels sufficient for NGS. DNA extracted from gastric cancer FFPE samples prepared within the last 7 years is suitable for NGS analysis, whereas those older than 7 years may not be suitable. Our data suggested that adequate amounts of DNA can be extracted from FFPE samples, not only of surgically resected tissue but also of biopsy specimens.

CONCLUSIONS

The type of formalin used for fixation and the time since FFPE sample preparation affect DNA quality. Sufficient amounts of DNA can be extracted from FFPE samples of both surgically resected and biopsy tissue, thus expanding the potential diagnostic uses of NGS in a clinical setting.

Good Laboratory Standards for Clinical Next-Generation Sequencing Cancer Panel Tests

Next-generation sequencing (NGS) has recently emerged as an essential component of personalized cancer medicine due to its high throughput and low per-base cost. However, no sufficient guidelines for implementing NGS as a clinical molecular pathology test are established in Korea. To ensure clinical grade quality without inhibiting adoption of NGS, a taskforce team assembled by the Korean Society of Pathologists developed laboratory guidelines for NGS cancer panel testing procedures and requirements for clinical implementation of NGS. This consensus standard proposal consists of two parts: laboratory guidelines and requirements for clinical NGS laboratories. The laboratory guidelines part addressed several important issues across multistep NGS cancer panel tests including choice of gene panel and platform, sample handling, nucleic acid management, sample identity tracking, library preparation, sequencing, analysis and reporting. Requirements for clinical NGS tests were summarized in terms of documentation, validation, quality management, and other required written policies. Together with appropriate pathologist training and international laboratory standards, these laboratory standards would help molecular pathology laboratories to successfully implement NGS cancer panel tests in clinic. In this way, the oncology community would be able to help patients to benefit more from personalized cancer medicine.

Validation of OncoPanel: A Targeted Next-Generation Sequencing Assay for the Detection of Somatic Variants in Cancer

CONTEXT

- The analysis of somatic mutations across multiple genes in cancer specimens may be used to aid clinical decision making. The analytical validation of targeted next-generation sequencing panels is important to assess accuracy and limitations.

OBJECTIVE

- To report the development and validation of OncoPanel, a custom targeted next-generation sequencing assay for cancer.

DESIGN

- OncoPanel was designed for the detection of single-nucleotide variants, insertions and deletions, copy number alterations, and structural variants across 282 genes with evidence as drivers of cancer biology. We implemented a validation strategy using formalin-fixed, paraffin-embedded, fresh or frozen samples compared with results obtained by clinically validated orthogonal technologies.

RESULTS

- OncoPanel achieved 98% sensitivity and 100% specificity for the detection of single-nucleotide variants, and 84% sensitivity and 100% specificity for the detection of insertions and deletions compared with single-gene assays and mass spectrometry-based genotyping. Copy number detection achieved 86% sensitivity and 98% specificity compared with array comparative genomic hybridization. The sensitivity of structural variant detection was 74% compared with karyotype, fluorescence in situ hybridization, and polymerase chain reaction. Sensitivity was affected by inconsistency in the detection of FLT3 and NPM1 alterations and IGH rearrangements due to design limitations. Limit of detection studies demonstrated 98.4% concordance across triplicate runs for variants with allele fraction greater than 0.1 and at least 50× coverage.

CONCLUSIONS

- The analytical validation of OncoPanel demonstrates the ability of targeted next-generation sequencing to detect multiple types of genetic alterations across a panel of genes implicated in cancer biology.

Molecular Testing in Breast Cancer: A Guide to Current Practices

CONTEXT

-Molecular diagnostics play a role in the management of many cancers, including breast cancer.

OBJECTIVE

-To provide an update on molecular testing in current clinical practice, targeted at practicing pathologists who are not breast cancer specialists.

DATA SOURCES

-This study is a narrative literature review.

CONCLUSIONS

-In addition to routine hormone (estrogen and progesterone) receptor testing, new and recurrent tumors are tested for HER2 amplification by in situ hybridization or overexpression by immunohistochemistry. Intrinsic subtyping of tumors represents a fundamental advance in our understanding of breast cancer biology, but currently it has an indirect role in patient management. Clinical next-generation sequencing (tumor profiling) is increasingly used to identify potentially actionable mutations in tumor tissue. Multianalyte assays with algorithmic analysis, including MammaPrint, Oncotype DX, and Prosigna, play a larger role in breast cancer than in many other malignancies. Given that a proportion of breast cancers are familial, testing of nontumor tissue for cancer predisposition mutations also plays a role in breast cancer care.

Integrating next-generation sequencing into clinical oncology: strategies, promises and pitfalls

We live in an era of genomic medicine. The past five years brought about many significant achievements in the field of cancer genetics, driven by rapidly evolving technologies and plummeting costs of next-generation sequencing (NGS). The official completion of the Cancer Genome Project in 2014 led many to envision the clinical implementation of cancer genomic data as the next logical step in cancer therapy. Stemming from this vision, the term 'precision oncology' was coined to illustrate the novelty of this individualised approach. The basic assumption of precision oncology is that molecular markers detected by NGS will predict response to targeted therapies independently from tumour histology. However, along with a ubiquitous availability of NGS, the complexity and heterogeneity at the individual patient level had to be acknowledged. Not only does the latter present challenges to clinical decision-making based on sequencing data, it is also an obstacle to the rational design of clinical trials. Novel tissue-agnostic trial designs were quickly developed to overcome these challenges. Results from some of these trials have recently demonstrated the feasibility and efficacy of this approach. On the other hand, there is an increasing amount of whole-exome and whole-genome NGS data which allows us to assess ever smaller differences between individual patients with cancer. In this review, we highlight different tumour sequencing strategies currently used for precision oncology, describe their individual strengths and weaknesses, and emphasise their feasibility in different clinical settings. Further, we evaluate the possibility of NGS implementation in current and future clinical trials, and point to the significance of NGS for translational research.

Next-Generation Sequencing in Cancer Diagnostics

This commentary highlights the article by Misyura et al that underscores the use of next-generation sequencing platforms for detection and verification of somatic variants.

Next generation sequencing in cancer: opportunities and challenges for precision cancer medicine

Over the past decade, testing the genes of patients and their specific cancer types has become standardized practice in medical oncology since somatic mutations, changes in gene expression and epigenetic modifications are all hallmarks of cancer. However, while cancer genetic assessment has been limited to single biomarkers to guide the use of therapies, improvements in nucleic acid sequencing technologies and implementation of different genome analysis tools have enabled clinicians to detect these genomic alterations and identify functional and disease-associated genomic variants. Next-generation sequencing (NGS) technologies have provided clues about therapeutic targets and genomic markers for novel clinical applications when standard therapy has failed. While Sanger sequencing, an accurate and sensitive approach, allows for the identification of potential novel variants, it is however limited by the single amplicon being interrogated. Similarly, quantitative and qualitative profiling of gene expression changes also represents a challenge for the cancer field. Both RT-PCR and microarrays are efficient approaches, but are limited to the genes present on the array or being assayed. This leaves vast swaths of the transcriptome, including non-coding RNAs and other features, unexplored. With the advent of the ability to collect and analyze genomic sequence data in a timely fashion and at an ever-decreasing cost, many of these limitations have been overcome and are being incorporated into cancer research and diagnostics giving patients and clinicians new hope for targeted and personalized treatment. Below we highlight the various applications of next-generation sequencing in precision cancer medicine.

Ultra-rare Disease and Genomics-Driven Precision Medicine

Since next-generation sequencing (NGS) technique was adopted into clinical practices, revolutionary advances in diagnosing rare genetic diseases have been achieved through translating genomic medicine into precision or personalized management. Indeed, several successful cases of molecular diagnosis and treatment with personalized or targeted therapies of rare genetic diseases have been reported. Still, there are several obstacles to be overcome for wider application of NGS-based precision medicine, including high sequencing cost, incomplete variant sensitivity and accuracy, practical complexities, and a shortage of available treatment options.

Technological advances in precision medicine and drug development

New technologies are rapidly becoming available to expand the arsenal of tools accessible for precision medicine and to support the development of new therapeutics. Advances in liquid biopsies, which analyze cells, DNA, RNA, proteins, or vesicles isolated from the blood, have gained particular interest for their uses in acquiring information reflecting the biology of tumors and metastatic tissues. Through advancements in DNA sequencing that have merged unprecedented accuracy with affordable cost, personalized treatments based on genetic variations are becoming a real possibility. Extraordinary progress has been achieved in the development of biological therapies aimed to even further advance personalized treatments. We provide a summary of current and future applications of blood based liquid biopsies and how new technologies are utilized for the development of biological therapeutic treatments. We discuss current and future sequencing methods with an emphasis on how technological advances will support the progress in the field of precision medicine.

Integrating Heterogeneous Biomedical Data for Cancer Research: the CARPEM infrastructure

Cancer research involves numerous disciplines. The multiplicity of data sources and their heterogeneous nature render the integration and the exploration of the data more and more complex. Translational research platforms are a promising way to assist scientists in these tasks. In this article, we identify a set of scientific and technical principles needed to build a translational research platform compatible with ethical requirements, data protection and data-integration problems. We describe the solution adopted by the CARPEM cancer research program to design and deploy a platform able to integrate retrospective, prospective, and day-to-day care data. We designed a three-layer architecture composed of a data collection layer, a data integration layer and a data access layer. We leverage a set of open-source resources including i2b2 and tranSMART.

Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives

Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical and socio-economic relevance. However, as these conditions usually originate from a complex interplay between genetic and environmental factors, precise prediction remains a considerable challenge. The current progress in genotyping technology has resulted in a substantial increase of knowledge regarding the genetic basis of such diseases and disorders. Consequently, common genetic risk variants are increasingly being included in epidemiological models to improve risk prediction. This work reviews recent high-quality publications targeting the prediction of common complex diseases. To be included in this review, articles had to report both, numerical measures of prediction performance based on traditional (non-genetic) risk factors, as well as measures of prediction performance when adding common genetic variants to the model. Systematic PubMed-based search finally identified 55 eligible studies. These studies were compared with respect to the chosen approach and methodology as well as results and clinical impact. Phenotypes analysed included tumours, diabetes mellitus, and cardiovascular diseases. All studies applied one or more statistical measures reporting on calibration, discrimination, or reclassification to quantify the benefit of including SNPs, but differed substantially regarding the methodological details that were reported. Several examples for improved risk assessments by considering disease-related SNPs were identified. Although the add-on benefit of including SNP genotyping data was mostly moderate, the strategy can be of clinical relevance and may, when being paralleled by an even deeper understanding of disease-related genetics, further explain the development of enhanced predictive and diagnostic strategies for complex diseases.

[Cytological material for molecular pathology]

Personalized therapy concepts in which the active agent is adapted to genetic alterations in the tumor of the patient, have in recent years led to a paradigm shift in oncology. A comprehensive molecular diagnostic tumor characterization is therefore essential before initiating therapy in order to select the optimal therapy for the patient. The continuously increasing number of genetic alterations which can be treated and known resistance mechanisms together with limited availability of test material represents a completely new challenge for molecular diagnostics. The possibility of being able to determine mutations, translocations and changes in the number of copies not only from paraffin-embedded tumor tissue but also from cytological material and even circulating tumor DNA, substantially extends the diagnostic options.

Diagnostic yield of targeted next generation sequencing in various cancer types: an information-theoretic approach

The information-theoretic concept of Shannon entropy can be used to quantify the information provided by a diagnostic test. We hypothesized that in tumor types with stereotyped mutational profiles, the results of NGS testing would yield lower average information than in tumors with more diverse mutations. To test this hypothesis, we estimated the entropy of NGS testing in various cancer types, using results obtained from clinical sequencing. A set of 238 tumors were subjected to clinical targeted NGS across all exons of 27 genes. There were 120 actionable variants in 109 cases, occurring in the genes KRAS, EGFR, PTEN, PIK3CA, KIT, BRAF, NRAS, IDH1, and JAK2. Sequencing results for each tumor were modeled as a dichotomized genotype (actionable mutation detected or not detected) for each of the 27 genes. Based upon the entropy of these genotypes, sequencing was most informative for colorectal cancer (3.235 bits of information/case) followed by high grade glioma (2.938 bits), lung cancer (2.197 bits), pancreatic cancer (1.339 bits), and sarcoma/STTs (1.289 bits). In the most informative cancer types, the information content of NGS was similar to surgical pathology examination (modeled at approximately 2-3 bits). Entropy provides a novel measure of utility for laboratory testing in general and for NGS in particular. This metric is, however, purely analytical and does not capture the relative clinical significance of the identified variants, which may also differ across tumor types.

A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine

The identification of 'druggable' kinase gene alterations has revolutionized cancer treatment in the last decade by providing new and successfully targetable drug targets. Thus, genotyping tumors for matching the right patients with the right drugs have become a clinical routine. Today, advances in sequencing technology and computational genome analyses enable the discovery of a constantly growing number of genome alterations relevant for clinical decision making. As a consequence, several technological approaches have emerged in order to deal with these rapidly increasing demands for clinical cancer genome analyses. Here, we describe challenges on the path to the broad introduction of diagnostic cancer genome analyses and the technologies that can be applied to overcome them. We define three generations of molecular diagnostics that are in clinical use. The latest generation of these approaches involves deep and thus, highly sensitive sequencing of all therapeutically relevant types of genome alterations-mutations, copy number alterations and rearrangements/fusions-in a single assay. Such approaches therefore have substantial advantages (less time and less tissue required) over PCR-based methods that typically have to be combined with fluorescence in situ hybridization for detection of gene amplifications and fusions. Since these new technologies work reliably on routine diagnostic formalin-fixed, paraffin-embedded specimens, they can help expedite the broad introduction of personalized cancer therapy into the clinic by providing comprehensive, sensitive and accurate cancer genome diagnoses in 'real-time'.

Targeted next-generation sequencing panels for monogenetic disorders in clinical diagnostics: the opportunities and challenges

Next-generation sequencing (NGS) will soon be used for clinically heterogeneous, inherited disorders and the increasing number of disease-causing genes reported. Diagnostic laboratories therefore need to decide which NGS methods they are going to invest in and how to implement them. We discuss here the challenges and opportunities of using targeted resequencing (TRS) panels for diagnosing monogenetic disorders. Of the different NGS approaches available, TRS panels offer the opportunity to sequence and analyze a limited set of predetermined target genes. At present, TRS panels offer better base-pair coverage, running times, costs and dataset handling than other NGS applications such as whole genome sequencing and whole exome sequencing. However, working with TRS panels also poses new challenges in variant interpretation, data handling and bioinformatic analyses. To optimize the analyses, TRS panel testing should be performed by bioinformaticians, clinicians and laboratory staff in close collaboration.

Unraveling tumor grading and genomic landscape in lung neuroendocrine tumors

Currently, grading in lung neuroendocrine tumors (NETs) is inherently defined by the histological classification based on cell features, mitosis count, and necrosis, for which typical carcinoids (TC) are low-grade malignant tumors with long life expectation, atypical carcinoids (AC) intermediate-grade malignant tumors with more aggressive clinical behavior, and large cell NE carcinomas (LCNEC) and small cell lung carcinomas (SCLC) high-grade malignant tumors with dismal prognosis. While Ki-67 antigen labeling index, highlighting the proportion of proliferating tumor cells, has largely been used in digestive NETs for assessing prognosis and assisting therapy decisions, the same marker does not play an established role in the diagnosis, grading, and prognosis of lung NETs. Next generation sequencing techniques (NGS), thanks to their astonishing ability to process in a shorter timeframe up to billions of DNA strands, are radically revolutionizing our approach to diagnosis and therapy of tumors, including lung cancer. When applied to single genes, panels of genes, exome, or the whole genome by using either frozen or paraffin tissues, NGS techniques increase our understanding of cancer, thus realizing the bases of precision medicine. Data are emerging that TC and AC are mainly altered in chromatin remodeling genes, whereas LCNEC and SCLC are also mutated in cell cycle checkpoint and cell differentiation regulators. A common denominator to all lung NETs is a deregulation of cell proliferation, which represents a biological rationale for morphologic (mitoses and necrosis) and molecular (Ki-67 antigen) parameters to successfully serve as predictors of tumor behavior (i.e., identification of pathological entities with clinical correlation). It is envisaged that a novel grading system in lung NETs based on the combined assessment of mitoses, necrosis, and Ki-67 LI may offer a better stratification of prognostic classes, realizing a bridge between molecular alterations, morphological features, and clinical behavior.