Clinical Next Generation Sequencing for Precision Medicine in Cancer

Laboratory diagnostics for primary spinal infections in pediatric and adult populations: a narrative review

Primary spinal infection (PSI) is a generic term covering a heterogeneous group of infections that can affect the vertebral body, intervertebral disks, the content of the medullary cavity, and adjacent paraspinal tissues. Patients' characteristics can vary significantly, notably according to their age, and some of these characteristics undoubtedly play a primordial role in the occurrence of a PSI and in the type of offending pathogen. Before approaching the subject of laboratory diagnostics, it is essential to define the characteristics of the patient and their infection, which can then guide the physician toward specific diagnostic approaches. This review critically examined the roles and usefulness of traditional and modern laboratory diagnostics in supporting clinicians' decision-making in cases of pediatric and adult primary spinal infection (PSI). It appears impossible to compare PSIs in children and adults, whether from an epidemiological, clinical, bacteriological, or biological perspective. The recipients are really too different, and the responsible germs are closely correlated to their age. Secondly, the interpretation of traditional laboratory blood tests appears to contribute little guidance for clinicians attempting to diagnose a PSI. Biopsy or needle aspiration for bacterial identification remains a controversial subject, as the success rates of these procedures for identifying causative organisms are relatively uncertain in pediatric populations.Using nucleic acid amplification assays (NAAAs) on biopsy samples has been demonstrated to be more sensitive than conventional cultures for diagnosing PSI. Recent advances in next-generation sequencing (NGS) are particularly interesting for establishing a microbiological diagnosis of a PSI when standard cultures and NAAAs have failed to detect the culprit. We can even imagine that plasma metagenomic NGS using plasma (known as "liquid biopsy") is a diagnostic approach that can detect not only pathogens circulating in the bloodstream but also those causing focal infections, and thus eliminate the need for source sample collection using costly invasive surgical procedures.

Cancer chemotherapy and beyond: Current status, drug candidates, associated risks and progress in targeted therapeutics

Cancer is an abnormal state of cells where they undergo uncontrolled proliferation and produce aggressive malignancies that causes millions of deaths every year. With the new understanding of the molecular mechanism(s) of disease progression, our knowledge about the disease is snowballing, leading to the evolution of many new therapeutic regimes and their successive trials. In the past few decades, various combinations of therapies have been proposed and are presently employed in the treatment of diverse cancers. Targeted drug therapy, immunotherapy, and personalized medicines are now largely being employed, which were not common a few years back. The field of cancer discoveries and therapeutics are evolving fast as cancer type-specific biomarkers are progressively being identified and several types of cancers are nowadays undergoing systematic therapies, extending patients' disease-free survival thereafter. Although growing evidence shows that a systematic and targeted approach could be the future of cancer medicine, chemotherapy remains a largely opted therapeutic option despite its known side effects on the patient's physical and psychological health. Chemotherapeutic agents/pharmaceuticals served a great purpose over the past few decades and have remained the frontline choice for advanced-stage malignancies where surgery and/or radiation therapy cannot be prescribed due to specific reasons. The present report succinctly reviews the existing and contemporary advancements in chemotherapy and assesses the status of the enrolled drugs/pharmaceuticals; it also comprehensively discusses the emerging role of specific/targeted therapeutic strategies that are presently being employed to achieve better clinical success/survival rate in cancer patients.

Budget Impact Analysis of Comprehensive Genomic Profiling in Advanced Non-Small Cell Lung Cancer in Taiwan

OBJECTIVES

The concept of precision oncology using genetic testing has become popular for cancer treatment in recent years. This research aimed to evaluate the financial impact of comprehensive genomic profiling (CGP) in patients with advanced non-small cell lung cancer before receiving any systemic treatments, compared with current practice using single-gene testing, in the hope that the findings can inform the National Health Insurance Administration the decision regarding CGP reimbursement.

METHODS

A budget impact analysis model was developed comparing the sum of gene testing costs, the first-line and subsequent systemic treatment costs, and other medical costs between the current practice of traditional molecular testing and the new test strategy of CGP. The evaluation time horizon is 5 years from the perspective of the National Health Insurance Administration. Outcome endpoints were incremental budget impact and life-year gained.

RESULTS

This research indicated CGP reimbursement would benefit 1072 to 1318 more patients receiving target therapies than the current practice and consequently had incremental 232 to 1844 life-years gained from 2022 to 2026. The new test strategy also led to higher gene testing cost and systemic treatment cost. Nevertheless, less medical resource utilization and better patient outcome were demonstrated. The incremental budget impact ranged from US dollar 19 to US dollar 27 million in the 5-year period.

CONCLUSION

This research shows that CGP could pave the way for personalized healthcare with moderate increase of National Health Insurance budget.

Circulating Tumor DNA: An Emerging Tool in Gastrointestinal Cancers

Circulating tumor DNA (ctDNA) is tumor-derived fragmented DNA in the bloodstream that has come from primary or metastatic cancer sites. Neoplasm-specific genetic and epigenetic abnormalities are increasingly being identified through liquid biopsy: a novel, minimally invasive technique used to isolate and analyze ctDNA in the peripheral circulation. Liquid biopsy and other emerging ctDNA technologies represent a paradigm shift in cancer diagnostics because they allow for the detection of minimal residual disease in patients with early-stage disease, improve risk stratification, capture tumor heterogeneity and genomic evolution, and enhance ctDNA-guided adjuvant and palliative cancer therapy. Moreover, ctDNA can be used to monitor the tumor response to neoadjuvant and postoperative therapy in patients with metastatic disease. Using clearance of ctDNA as an endpoint for escalation/de-escalation of adjuvant chemotherapy for patients considered to have high-risk disease has become an important area of research. The possibility of using ctDNA as a surrogate for treatment response-including for overall survival, progression-free survival, and disease-free survival-is an attractive concept; this surrogate will arguably reduce study duration and expedite the development of new therapies. In this review, we summarize the current evidence on the applications of ctDNA for the diagnosis and management of gastrointestinal tumors. Gastrointestinal cancers-including tumors of the esophagus, stomach, colon, liver, and pancreas-account for one-quarter of global cancer diagnoses and contribute to more than one-third of cancer-related deaths. Given the prevalence of gastrointestinal malignancies, ctDNA technology represents a powerful tool to reduce the global burden of disease.

Budget Impact Analysis of Comprehensive Genomic Profiling in Patients With Advanced Non-Small-Cell Lung Cancer

PURPOSE

This study assessed the economic impact of increased use of comprehensive genomic profiling (CGP) versus conventional testing strategies among patients with advanced non-small-cell lung cancer (aNSCLC) from a US commercial health plan perspective.

METHODS

A decision analytic model was developed to estimate the incremental benefits and costs across testing methodologies (CGP v non-CGP), as well as across sample types (tissue-based and liquid-based), for patients with newly diagnosed aNSCLC. Model outcomes included total direct costs, testing costs, and per member per month budget impact. Secondary model outcomes included the number of patients needed to test with CGP to add 1 life-year, and the number of patients needed to test with CGP to treat one individual with a biomarker-matched therapy.

RESULTS

In a hypothetical 2,000,000-member health plan, 790 members were estimated to have incident aNSCLC; 609 underwent molecular diagnostic testing with 122 (20%) tested with CGP (109 tissue-based and 13 liquid) in the base-case. An increase in CGP from 20% to 30% (an additional 61 patients tested with CGP) was associated with 3.11 additional life-years gained and a $0.01 in US dollars per member per month budget impact. Approximately 19.6 patients would need to be tested with CGP versus non-CGP to add one life-year and 5.9 patients would need to be tested with CGP to treat at least one patient with a biomarker-matched therapy.

CONCLUSION

An increase in CGP from 20% to 30% among patients with aNSCLC undergoing molecular diagnostic testing was associated with modest budget impact, most of which was attributable to prolonged survival associated with increased use of more effective treatments.

Early Cost Effectiveness of Whole-Genome Sequencing as a Clinical Diagnostic Test for Patients with Inoperable Stage IIIB,C/IV Non-squamous Non-small-Cell Lung Cancer

BACKGROUND

Advanced non-small-cell lung cancer (NSCLC) harbours many genetic aberrations that can be targeted with systemic treatments. Whole-genome sequencing (WGS) can simultaneously detect these (and possibly new) molecular targets. However, the exact added clinical value of WGS is unknown.

OBJECTIVE

The objective of this study was to determine the early cost effectiveness of using WGS in diagnostic strategies compared with currently used molecular diagnostics for patients with inoperable stage IIIB,C/IV non-squamous NSCLC from a Dutch healthcare perspective.

METHODS

A decision tree represented the diagnostic pathway, and a cohort state transition model represented disease progression. Three diagnostic strategies were modelled: standard of care (SoC) alone, WGS as a diagnostic test, and SoC followed by WGS. Treatment effectiveness was based on a systematic review. Probabilistic cost-effectiveness analyses were performed, and threshold analyses (using €80,000 per quality-adjusted life-year [QALY]) was used to explore the early cost effectiveness of WGS.

RESULTS

WGS as a diagnostic test resulted in more QALYs (0.002) and costs (€1534 [incremental net monetary benefit -€1349]), and SoC followed by WGS resulted in fewer QALYs (-0.002) and more costs (€1059 [-€1194]) compared with SoC alone. WGS as a diagnostic test was only cost effective if it was priced at €2000 per patient and identified 2.7% more actionable patients than SoC alone. Treating these additional identified patients with new treatments costing >€4069 per month decreased the probability of cost effectiveness.

CONCLUSIONS

Our analysis suggests that providing WGS as a diagnostic test is cost effective compared with SoC followed by WGS and SoC alone if costs for WGS decrease and additional patients with actionable targets are identified. This cost-effectiveness model can be used to incorporate new findings iteratively and to support ongoing decision making regarding the use of WGS in this rapidly evolving field.

Next-Generation Sequencing with Liquid Biopsies from Treatment-Naïve Non-Small Cell Lung Carcinoma Patients

Recently, the liquid biopsy (LB), a non-invasive and easy to repeat approach, has started to compete with the tissue biopsy (TB) for detection of targets for administration of therapeutic strategies for patients with advanced stages of lung cancer at tumor progression. A LB at diagnosis of late stage non-small cell lung carcinoma (NSCLC) is also being performed. It may be asked if a LB can be complementary (according to the clinical presentation or systematics) or even an alternative to a TB for treatment-naïve advanced NSCLC patients. Nucleic acid analysis with a TB by next-generation sequencing (NGS) is gradually replacing targeted sequencing methods for assessment of genomic alterations in lung cancer patients with tumor progression, but also at baseline. However, LB is still not often used in daily practice for NGS. This review addresses different aspects relating to the use of LB for NGS at diagnosis in advanced NSCLC, including its advantages and limitations.

Molecular Signatures of Gynecological Cancers: Clinicians Perspective

Large-scale molecular profiling and DNA sequencing has revolutionized cancer research. Precision medicine is a rapidly developing area in cancer care but it is not uniformly applied across different tumor types. Biomarker-based therapy is associated with improved outcomes, both in terms of progression-free survival and overall survival. Comprehensive genomic profiling (CGP) uses next-generation sequencing to analyze the complete coding sequence of hundreds of genes from a small amount of tissue. Genes included in these assays are those associated with cancer development or have diagnostic, prognostic, familial, or therapeutic implications Genomic profiling is emerging as a clinically viable tool to personalize patient's treatment. This article discusses how the insights gained through CGP can impact treatment plan in common gynecological cancers.

DEEPGENTM-A Novel Variant Calling Assay for Low Frequency Variants

Detection of genetic variants in clinically relevant genomic hot-spot regions has become a promising application of next-generation sequencing technology in precision oncology. Effective personalized diagnostics requires the detection of variants with often very low frequencies. This can be achieved by targeted, short-read sequencing that provides high sequencing depths. However, rare genetic variants can contain crucial information for early cancer detection and subsequent treatment success, an inevitable level of background noise usually limits the accuracy of low frequency variant calling assays. To address this challenge, we developed DEEPGEN^TM, a variant calling assay intended for the detection of low frequency variants within liquid biopsy samples. We processed reference samples with validated mutations of known frequencies (0%-0.5%) to determine DEEPGEN^TM's performance and minimal input requirements. Our findings confirm DEEPGEN^TM's effectiveness in discriminating between signal and noise down to 0.09% variant allele frequency and an LOD(90) at 0.18%. A superior sensitivity was also confirmed by orthogonal comparison to a commercially available liquid biopsy-based assay for cancer detection.

Case Report: A Chronological Combination Treatment of Icotinib, Osimertinib, and Crizotinib on Lung Adenocarcinoma Guided by Serial Genetic Tests of Circulating Tumor DNA and Sediment Cell Genomic DNA From Pleural Effusion

Precision medicine has been getting more attention in lung cancer treatment. Here, we report an unusual case of a 71-year-old Chinese male patient with poorly differentiated lung adenocarcinoma with lymph node metastasis. A 5 years' treatment history of this patient is reported. By serial genetic tests of circulating tumor DNA (ctDNA) from peripheral blood and sediment cell genomic DNA (PE-sDNA) from pleural effusion, a novel chronological combination treatment of icotinib, osimertinib, and crizotinib was adopted for the present genetic mutations, including EGFR exon 19 deletion, EGFR p.T790M, and MET amplification.

Validation and clinical application of a targeted next-generation sequencing gene panel for solid and hematologic malignancies

Background

Next-generation sequencing (NGS) is a high-throughput technology that has become widely integrated in molecular diagnostics laboratories. Among the large diversity of NGS-based panels, the Trusight Tumor 26 (TsT26) enables the detection of low-frequency variants across 26 genes using the MiSeq platform.

Methods

We describe the inter-laboratory validation and subsequent clinical application of the panel in 399 patients presenting a range of tumor types, including gastrointestinal (GI, 29%), hematologic (18%), lung (13%), gynecological and breast (8% each), among others.

Results

The panel is highly accurate with a test sensitivity of 92%, and demonstrated high specificity and positive predictive values (95% and 96%, respectively). Sequencing testing was successful in two-thirds of patients, while the remaining third failed due to unsuccessful quality-control filtering. Most detected variants were observed in the TP53 (28%), KRAS (16%), APC (10%) and PIK3CA (8%) genes. Overall, 372 variants were identified, primarily distributed as missense (81%), stop gain (9%) and frameshift (7%) altered sequences and mostly reported as pathogenic (78%) and variants of uncertain significance (19%). Only 14% of patients received targeted treatment based on the variant determined by the panel. The variants most frequently observed in GI and lung tumors were: KRAS c.35G > A (p.G12D), c.35G > T (p.G12V) and c.34G > T (p.G12C).

Conclusions

Prior panel validation allowed its use in the laboratory daily practice by providing several relevant and potentially targetable variants across multiple tumors. However, this study is limited by high sample inadequacy rate, raising doubts as to continuity in the clinical setting.

Precision and Personalized Medicine: How Genomic Approach Improves the Management of Cardiovascular and Neurodegenerative Disease

Life expectancy has gradually grown over the last century. This has deeply affected healthcare costs, since the growth of an aging population is correlated to the increasing burden of chronic diseases. This represents the interesting challenge of how to manage patients with chronic diseases in order to improve health care budgets. Effective primary prevention could represent a promising route. To this end, precision, together with personalized medicine, are useful instruments in order to investigate pathological processes before the appearance of clinical symptoms and to guide physicians to choose a targeted therapy to manage the patient. Cardiovascular and neurodegenerative diseases represent suitable models for taking full advantage of precision medicine technologies applied to all stages of disease development. The availability of high technology incorporating artificial intelligence and advancement progress made in the field of biomedical research have been substantial to understand how genes, epigenetic modifications, aging, nutrition, drugs, microbiome and other environmental factors can impact health and chronic disorders. The aim of the present review is to address how precision and personalized medicine can bring greater clarity to the clinical and biological complexity of these types of disorders associated with high mortality, involving tremendous health care costs, by describing in detail the methods that can be applied. This might offer precious tools for preventive strategies and possible clues on the evolution of the disease and could help in predicting morbidity, mortality and detecting chronic disease indicators much earlier in the disease course. This, of course, will have a major effect on both improving the quality of care and quality of life of the patients and reducing time efforts and healthcare costs.

Translational Opportunities for Microfluidic Technologies to Enable Precision Epigenomics

Personalizing health care by taking genetic, environmental, and lifestyle factors into account is central to modern medicine. The crucial and pervasive roles epigenetic factors play in shaping gene-environment interactions are now well recognized. However, identifying robust epigenetic biomarkers and translating them to clinical tests has been difficult due in part to limitations of available platforms to detect epigenetic features genome-wide (epigenomic assays). This Feature introduces several important prospects for precision epigenomics, highlights capabilities and limitations of current laboratory technologies, and emphasizes opportunities for microfluidic tools to facilitate translation of epigenetic analyses to the clinic, with a particular focus on methods to profile gene-associated histone modifications and their impacts on chromatin structure and gene expression.

A BRAF new world

BRAF is a rare targetable mutation in non-small-cell lung cancer (NSCLC). Emerging evidence underlines that, rather than a single point mutation, BRAF genes present with a wide array of mutations, essentially in lung adenocarcinoma. Different BRAF mutations have divergent clinical and therapeutic implications, with a particular distinction between V600E and non-V600E mutations. The latter are at least as frequent in NSCLC as V600E, but lack any proven targeted therapy. In this paper, we briefly review the current literature and provide an update of scientific knowledge about different types of BRAF mutations in NSCLC.

Pisces: an accurate and versatile variant caller for somatic and germline next-generation sequencing data

Motivation

Next-generation sequencing technology is transitioning quickly from research labs to clinical settings. The diagnosis and treatment selection for many acquired and autosomal conditions necessitate a method for accurately detecting somatic and germline variants.

Results

We have developed Pisces, a rapid, versatile and accurate small-variant calling suite designed for somatic and germline amplicon sequencing applications. Accuracy is achieved by four distinct modules, each incorporating a number of novel algorithmic strategies.

Availability and implementation

Pisces is distributed under an open source license and can be downloaded from https://github.com/Illumina/Pisces. Pisces is available on the BaseSpace™ SequenceHub. It is distributed on Illumina sequencing platforms such as the MiSeq™ and is included in the Praxis™ Extended RAS Panel test which was recently approved by the FDA.

Supplementary information

Supplementary data are available at Bioinformatics online.

Clinical validation of qPCR Target Selector™ assays using highly specific switch-blockers for rare mutation detection

AIMS

The identification of actionable DNA mutations associated with a patient's tumour is critical for devising a targeted, personalised cancer treatment strategy. However, these molecular analyses are typically performed using tissue obtained via biopsy, which involves substantial risk and is often not feasible. In addition, biopsied tissue does not always reflect tumour heterogeneity, and sequential biopsies to track disease progression (eg, emergence of drug resistance mutations) are not well tolerated. To overcome these and other biopsy-associated limitations, we have developed non-invasive 'liquid biopsy' technologies to enable the molecular characterisation of a patient's cancer using peripheral blood samples.

METHODS

The Target Selector ctDNA platform uses a real-time PCR-based approach, coupled with DNA sequencing, to identify cancer-associated genetic mutations within circulating tumour DNA. This is accomplished via a patented blocking approach suppressing wild-type DNA amplification, while allowing specific amplification of mutant alleles.

RESULTS

To promote the clinical uptake of liquid biopsy technologies, it is first critical to demonstrate concordance between results obtained via liquid and traditional biopsy procedures. Here, we focused on three genes frequently mutated in cancer: EGFR (Del19, L858, and T790), BRAF (V600) and KRAS (G12/G13). For each Target Selector assay, we demonstrated extremely high accuracy, sensitivity and specificity compared with results obtained from tissue biopsies. Overall, we found between 93% and 96% concordance to blinded tissue samples across 127 clinical assays.

CONCLUSIONS

The switch-blocker technology reported here offers a highly effective method for non-invasively determining the molecular signatures of patients with cancer.

A continuous-time Markov model approach for modeling myelodysplastic syndromes progression from cross-sectional data

The integration of both genomics and clinical data to model disease progression is now possible, thanks to the increasing availability of molecular patients' profiles. This may lead to the definition of novel decision support tools, able to tailor therapeutic interventions on the basis of a "precise" patients' risk stratification, given their health status evolution. However, longitudinal analysis requires long-term data collection and curation, which can be time demanding, expensive and sometimes unfeasible. Here we present a clinical decision support framework that combines the simulation of disease progression from cross-sectional data with a Markov model that exploits continuous-time transition probabilities derived from Cox regression. Trajectories between patients at different disease stages are stochastically built according to a measure of patient similarity, computed with a matrix tri-factorization technique. Such trajectories are seen as realizations drawn from the stochastic process driving the transitions between the disease stages. Eventually, Markov models applied to the resulting longitudinal dataset highlight potentially relevant clinical information. We applied our method to cross-sectional genomic and clinical data from a cohort of Myelodysplastic syndromes (MDS) patients. MDS are heterogeneous clonal hematopoietic disorders whose patients are characterized by different risks of Acute Myeloid Leukemia (AML) development, defined by an international score. We computed patients' trajectories across increasing and subsequent levels of risk of developing AML, and we applied a Cox model to the simulated longitudinal dataset to assess whether genomic characteristics could be associated with a higher or lower probability of disease progression. We then used the learned parameters of such Cox model to calculate the transition probabilities of a continuous-time Markov model that describes the patients' evolution across stages. Our results are in most cases confirmed by previous studies, thus demonstrating that simulated longitudinal data represent a valuable resource to investigate disease progression of MDS patients.

Economic Impact of Next-Generation Sequencing Versus Single-Gene Testing to Detect Genomic Alterations in Metastatic Non–Small-Cell Lung Cancer Using a Decision Analytic Model

PURPOSE

The aim of the current study was to assess the economic impact of using next-generation sequencing (NGS) versus single-gene testing strategies among patients with metastatic non–small-cell lung cancer (mNSCLC) from the perspective of the Centers for Medicare & Medicaid Services (CMS) and US commercial payers.

METHODS

A decision analytic model considered patients who were newly diagnosed with mNSCLC who received programmed death ligand 1 and genomic alteration tests— EGFR, ALK, ROS1, BRAF, MET, HER2, RET, and NTRK1—using upfront NGS (all alterations tested simultaneously plus KRAS), sequential testing (sequence of single-gene tests), exclusionary testing ( KRAS plus sequential testing), and hotspot panels ( EGFR, ALK, ROS1, and BRAF tested simultaneously plus single-gene tests or NGS for MET, HER2, RET, and NTRK1). Model outcomes for each strategy were time-to-test results, the proportion of patients identified harboring alterations with or without US Food and Drug Administration–approved therapies, and total testing costs. A budget impact analysis assessed the economic effects of increasing the proportion of NGS-tested patients.

RESULTS

In a hypothetical 1,000,000-member health plan, 2,066 Medicare-insured patients and 156 commercially insured patients were estimated to have mNSCLC and to be eligible for testing. Time-to-test results were 2.0 weeks for NGS and the hotspot panel, faster than exclusionary and sequential testing by 2.7 and 2.8 weeks, respectively. NGS was associated with cost savings for both CMS ($1,393,678; $1,530,869; and $2,140,795 less than exclusionary, sequential testing, and hotspot panels, respectively) and commercial payers ($3,809; $127,402; and $250,842 less than exclusionary, sequential testing, and hotspot panels, respectively). Increasing the proportion of NGS-tested patients translated into substantial cost savings for both CMS and commercial payers.

CONCLUSION

Use of upfront NGS testing in patients with mNSCLC was associated with substantial cost savings and shorter time-to-test results for both CMS and commercial payers.

Pharmacogenetic and pharmacogenomic discovery strategies

Genetic/genomic profiling at a single-patient level is expected to provide critical information for determining inter-individual drug toxicity and potential efficacy in cancer therapy. A better definition of cancer subtypes at a molecular level, may correspondingly complement such pharmacogenetic and pharmacogenomic approaches, for more effective personalized treatments. Current pharmacogenetic/pharmacogenomic strategies are largely based on the identification of known polymorphisms, thus limiting the discovery of novel or rarer genetic variants. Recent improvements in cost and throughput of next generation sequencing (NGS) are now making whole-genome profiling a plausible alternative for clinical procedures. Beyond classical pharmacogenetic/pharmacogenomic traits for drug metabolism, NGS screening programs of cancer genomes may lead to the identification of novel cancer-driving mutations. These may not only constitute novel therapeutic targets, but also effector determinants for metabolic pathways linked to drug metabolism. An additional advantage is that cancer NGS profiling is now leading to discovering targetable mutations, e.g., in glioblastomas and pancreatic cancers, which were originally discovered in other tumor types, thus allowing for effective repurposing of active drugs already on the market.

Method for Identifying Cancer-Related Genes Using Gene Similarity-Based Collaborative Filtering

The aim of this study is to diagnose the stage of renal cell carcinoma and to predict the prognosis of breast cancer by using RNA sequencing and microarray data that are representative gene expression data. To identify biomarkers for prediction, top-N genes of each class of cancer or noncancer are recommended by collaborative filtering method based on three gene similarity coefficients. We then construct a machine learning model for classification using the union of the recommended genes as the final feature set. The optimal genetic markers were used to identify the set with the highest classification performance in the model. Experiments conducted by the proposed method showed higher performance than those conducted by the machine learning model using all the gene features without performing feature selection. In addition, it showed better performance than other studies based on existing correlation-based feature selection.

DNAscan: personal computer compatible NGS analysis, annotation and visualisation

BACKGROUND

Next Generation Sequencing (NGS) is a commonly used technology for studying the genetic basis of biological processes and it underpins the aspirations of precision medicine. However, there are significant challenges when dealing with NGS data. Firstly, a huge number of bioinformatics tools for a wide range of uses exist, therefore it is challenging to design an analysis pipeline. Secondly, NGS analysis is computationally intensive, requiring expensive infrastructure, and many medical and research centres do not have adequate high performance computing facilities and cloud computing is not always an option due to privacy and ownership issues. Finally, the interpretation of the results is not trivial and most available pipelines lack the utilities to favour this crucial step.

RESULTS

We have therefore developed a fast and efficient bioinformatics pipeline that allows for the analysis of DNA sequencing data, while requiring little computational effort and memory usage. DNAscan can analyse a whole exome sequencing sample in 1 h and a 40x whole genome sequencing sample in 13 h, on a midrange computer. The pipeline can look for single nucleotide variants, small indels, structural variants, repeat expansions and viral genetic material (or any other organism). Its results are annotated using a customisable variety of databases and are available for an on-the-fly visualisation with a local deployment of the gene.iobio platform. DNAscan is implemented in Python. Its code and documentation are available on GitHub: https://github.com/KHP-Informatics/DNAscan . Instructions for an easy and fast deployment with Docker and Singularity are also provided on GitHub.

CONCLUSIONS

DNAscan is an extremely fast and computationally efficient pipeline for analysis, visualization and interpretation of NGS data. It is designed to provide a powerful and easy-to-use tool for applications in biomedical research and diagnostic medicine, at minimal computational cost. Its comprehensive approach will maximise the potential audience of users, bringing such analyses within the reach of non-specialist laboratories, and those from centres with limited funding available.

Application of next-generation sequencing technology to precision medicine in cancer: joint consensus of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology

Next-generation sequencing (NGS) technology is capable of sequencing millions or billions of DNA molecules simultaneously. Therefore, it represents a promising tool for the analysis of molecular targets for the initial diagnosis of disease, monitoring of disease progression, and identifying the mechanism of drug resistance. On behalf of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology (CSCO) and the China Actionable Genome Consortium (CAGC), the present expert group hereby proposes advisory guidelines on clinical applications of NGS technology for the analysis of cancer driver genes for precision cancer therapy. This group comprises an assembly of laboratory cancer geneticists, clinical oncologists, bioinformaticians, pathologists, and other professionals. After multiple rounds of discussions and revisions, the expert group has reached a preliminary consensus on the need of NGS in clinical diagnosis, its regulation, and compliance standards in clinical sample collection. Moreover, it has prepared NGS criteria, the sequencing standard operation procedure (SOP), data analysis, report, and NGS platform certification and validation.

Nanopore sequencing: An enrichment-free alternative to mitochondrial DNA sequencing

Mitochondrial DNA sequence data are often utilized in disease studies, conservation genetics and forensic identification. The current approaches for sequencing the full mtGenome typically require several rounds of PCR enrichment during Sanger or MPS protocols followed by fairly tedious assembly and analysis. Here we describe an efficient approach to sequencing directly from genomic DNA samples without prior enrichment or extensive library preparation steps. A comparison is made between libraries sequenced directly from native DNA and the same samples sequenced from libraries generated with nine overlapping mtDNA amplicons on the Oxford Nanopore MinION™ device. The native and amplicon library preparation methods and alternative base calling strategies were assessed to establish error rates and identify trends of discordance between the two library preparation approaches. For the complete mtGenome, 16 569 nucleotides, an overall error rate of approximately 1.00% was observed. As expected with mtDNA, the majority of error was detected in homopolymeric regions. The use of a modified basecaller that corrects for ambiguous signal in homopolymeric stretches reduced the error rate for both library preparation methods to approximately 0.30%. Our study indicates that direct mtDNA sequencing from native DNA on the MinION™ device provides comparable results to those obtained from common mtDNA sequencing methods and is a reliable alternative to approaches using PCR‐enriched libraries.

Continuous Petri Nets and microRNA Analysis in Melanoma

Personalized target therapies represent one of the possible treatment strategies to fight the ongoing battle against cancer. New treatment interventions are still needed for an effective and successful cancer therapy. In this scenario, we simulated and analyzed the dynamics of BRAF V600E melanoma patients treated with BRAF inhibitors in order to find potentially interesting targets that may make standard treatments more effective in particularly aggressive tumors that may not respond to selective inhibitor drugs. To this aim, we developed a continuous Petri Net model that simulates fundamental signalling cascades involved in melanoma development, such as MAPK and PI3K/AKT, in order to deeply analyze these complex kinase cascades and predict new crucial nodes involved in melanomagenesis. The model pointed out that some microRNAs, like hsa-mir-132, downregulates expression levels of p120RasGAP: under high concentrations of p120RasGAP, MAPK pathway activation is significantly decreased and consequently also PI3K/PDK1/AKT activation. Furthermore, our analysis carried out through the Genomic Data Commons (GDC) Data Portal shows the evidence that hsa-mir-132 is significantly associated with clinical outcome in melanoma cancer genomic data sets of BRAF-mutated patients. In conclusion, targeting miRNAs through antisense oligonucleotides technology may suggest the way to enhance the action of BRAF-inhibitors.

Evaluation of Targeted Next-Generation Sequencing for Detection of Bovine Pathogens in Clinical Samples. J Clin Microbiol. 2018;56. [PMID: 29695524 DOI: 10.1128/JCM.00399-18]

The laboratory diagnosis of infectious diseases, especially those caused by mixed infections, is challenging. Routinely, it requires submission of multiple samples to separate laboratories. Advances in next-generation sequencing (NGS) have provided the opportunity for development of a comprehensive method to identify infectious agents. This study describes the use of target-specific primers for PCR-mediated amplification with the NGS technology in which pathogen genomic regions of interest are enriched and selectively sequenced from clinical samples. In the study, 198 primers were designed to target 43 common bovine and small-ruminant bacterial, fungal, viral, and parasitic pathogens, and a bioinformatics tool was specifically constructed for the detection of targeted pathogens. The primers were confirmed to detect the intended pathogens by testing reference strains and isolates. The method was then validated using 60 clinical samples (including tissues, feces, and milk) that were also tested with other routine diagnostic techniques. The detection limits of the targeted NGS method were evaluated using 10 representative pathogens that were also tested by quantitative PCR (qPCR), and the NGS method was able to detect the organisms from samples with qPCR threshold cycle (C_T) values in the 30s. The method was successful for the detection of multiple pathogens in the clinical samples, including some additional pathogens missed by the routine techniques because the specific tests needed for the particular organisms were not performed. The results demonstrate the feasibility of the approach and indicate that it is possible to incorporate NGS as a diagnostic tool in a cost-effective manner into a veterinary diagnostic laboratory.

Simultaneous identification of clinically relevant single nucleotide variants, copy number alterations and gene fusions in solid tumors by targeted next-generation sequencing

In this study, we have set-up a routine pipeline to evaluate the clinical application of Oncomine™ Focus Assay, a panel that allows the simultaneous detection of single nucleotide hotspot mutations in 35 genes, copy number alterations (CNAs) in 19 genes and gene fusions involving 23 genes in cancer samples. For this study we retrospectively selected 106 patients that were submitted to surgical resection for lung, gastric, colon or rectal cancer.

We found that 56 patients out of 106 showed at least one alteration (53%), with 47 patients carrying at least one relevant nucleotide variant, 10 patients carrying at least one CNA and 3 patients carrying one gene fusion. On the basis of the mutational profiles obtained, we have identified 22 patients (20.7%) that were potentially eligible for targeted therapy.

The most frequently mutated genes across all tumor types included KRAS (30 patients), PIK3CA (16 patients), BRAF (6 patients), EGFR (5 patients), NRAS (4 patients) and ERBB2 (3 patients) whereas CCND1, ERBB2, EGFR and MYC were the genes most frequently subjected to copy number gain. Finally, gene fusions were identified only in lung cancer patients and involved MET [MET(13)–MET(15) fusion] and FGFR3 [FGFR3(chr 17)–TACC3(chr 11)].

In conclusion, we demonstrate that the analysis with a multi-biomarker panel of cancer patients after surgery, may present several potential advantages in clinical daily practice, including the simultaneous detection of different potentially druggable alterations, reasonable costs, short time of testing and automated interpretation of results.

Cell-free DNA and next-generation sequencing in the service of personalized medicine for lung cancer

Personalized medicine has emerged as the future of cancer care to ensure that patients receive individualized treatment specific to their needs. In order to provide such care, molecular techniques that enable oncologists to diagnose, treat, and monitor tumors are necessary. In the field of lung cancer, cell free DNA (cfDNA) shows great potential as a less invasive liquid biopsy technique, and next-generation sequencing (NGS) is a promising tool for analysis of tumor mutations. In this review, we outline the evolution of cfDNA and NGS and discuss the progress of using them in a clinical setting for patients with lung cancer. We also present an analysis of the role of cfDNA as a liquid biopsy technique and NGS as an analytical tool in studying EGFR and MET, two frequently mutated genes in lung cancer. Ultimately, we hope that using cfDNA and NGS for cancer diagnosis and treatment will become standard for patients with lung cancer and across the field of oncology.

Precision Medicine for CRC Patients in the Veteran Population: State-of-the-Art, Challenges and Research Directions

Colorectal cancer (CRC) accounts for ~9% of all cancers in the Veteran population, a fact which has focused a great deal of the attention of the VA's research and development efforts. A field-based meeting of CRC experts was convened to discuss both challenges and opportunities in precision medicine for CRC. This group, designated as the VA Colorectal Cancer Cell-genomics Consortium (VA4C), discussed advances in CRC biology, biomarkers, and imaging for early detection and prevention. There was also a discussion of precision treatment involving fluorescence-guided surgery, targeted chemotherapies and immunotherapies, and personalized cancer treatment approaches. The overarching goal was to identify modalities that might ultimately lead to personalized cancer diagnosis and treatment. This review summarizes the findings of this VA field-based meeting, in which much of the current knowledge on CRC prescreening and treatment was discussed. It was concluded that there is a need and an opportunity to identify new targets for both the prevention of CRC and the development of effective therapies for advanced disease. Also, developing methods integrating genomic testing with tumoroid-based clinical drug response might lead to more accurate diagnosis and prognostication and more effective personalized treatment of CRC.

Single molecule sequencing of the M13 virus genome without amplification

Next generation sequencing (NGS) has revolutionized life sciences research. However, GC bias and costly, time-intensive library preparation make NGS an ill fit for increasing sequencing demands in the clinic. A new class of third-generation sequencing platforms has arrived to meet this need, capable of directly measuring DNA and RNA sequences at the single-molecule level without amplification. Here, we use the new GenoCare single-molecule sequencing platform from Direct Genomics to sequence the genome of the M13 virus. Our platform detects single-molecule fluorescence by total internal reflection microscopy, with sequencing-by-synthesis chemistry. We sequenced the genome of M13 to a depth of 316x, with 100% coverage. We determined a consensus sequence accuracy of 100%. In contrast to GC bias inherent to NGS results, we demonstrated that our single-molecule sequencing method yields minimal GC bias.

Next-generation sequencing: recent applications to the analysis of colorectal cancer

Since the establishment of the Sanger sequencing method, scientists around the world focused their efforts to progress in the field to produce the utmost technology. The introduction of next-generation sequencing (NGS) represents a revolutionary step and promises to lead to massive improvements in our understanding on the role of nucleic acids functions. Cancer research began to use this innovative and highly performing method, and interesting results started to appear in colorectal cancer (CRC) analysis. Several studies produced high-quality data in terms of mutation discovery, especially about actionable or less frequently mutated genes, epigenetics, transcriptomics. Analysis of results is unveiling relevant perspectives aiding to evaluate the response to therapies. Novel evidences have been presented also in other directions such as gut microbiota or CRC circulating tumor cells. However, despite its unquestioned potential, NGS poses some issues calling for additional studies. This review intends to offer a view of the state of the art of NGS applications to CRC through examination of the most important technologies and discussion of recent published results.

Systematic biobanking, novel imaging techniques, and advanced molecular analysis for precise tumor diagnosis and therapy: The Polish MOBIT project

Personalized and precision medicine is gaining recognition due to the limitations by standard diagnosis and treatment; many areas of medicine, from cancer to psychiatry, are moving towards tailored and individualized treatment for patients based on their clinical characteristics and genetic signatures as well as novel imaging techniques. Advances in whole genome sequencing have led to identification of genes involved in a variety of diseases. Moreover, biomarkers indicating severity of disease or susceptibility to treatment are increasingly being characterized. The continued identification of new genes and biomarkers specific to disease subtypes and individual patients is essential and inevitable for translation into personalized medicine, in estimating both, disease risk and response to therapy. Taking into consideration the mostly unsolved necessity of tailored therapy in oncology the innovative project MOBIT (molecular biomarkers for individualized therapy) was designed. The aims of the project are: (i) establishing integrative management of precise tumor diagnosis and therapy including systematic biobanking, novel imaging techniques, and advanced molecular analysis by collecting comprehensive tumor tissues, liquid biopsies (whole blood, serum, plasma), and urine specimens (supernatant; sediment) as well as (ii) developing personalized lung cancer diagnostics based on tumor heterogeneity and integrated genomics, transcriptomics, metabolomics, and radiomics PET/MRI analysis. It will consist of 5 work packages. In this paper the rationale of the Polish MOBIT project as well as its design is presented. (iii) The project is to draw interest in and to invite national and international, private and public, preclinical and clinical initiatives to establish individualized and precise procedures for integrating novel targeted therapies and advanced imaging techniques.

Empowering Mayo Clinic Individualized Medicine with Genomic Data Warehousing

Individualized medicine enables better diagnoses and treatment decisions for patients and promotes research in understanding the molecular underpinnings of disease. Linking individual patient’s genomic and molecular information with their clinical phenotypes is crucial to these efforts. To address this need, the Center for Individualized Medicine at Mayo Clinic has implemented a genomic data warehouse and a workflow management system to bring data from institutional electronic health records and genomic sequencing data from both clinical and research bioinformatics sources into the warehouse. The system is the foundation for Mayo Clinic to build a suite of tools and interfaces to support various clinical and research use cases. The genomic data warehouse is positioned to play a key role in enhancing the research capabilities and advancing individualized patient care at Mayo Clinic.

Clinical multi-omics strategies for the effective cancer management

Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis.

BIOLOGICAL SIGNIFICANCE

In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer.

Recent developments in the treatment of metastatic colorectal cancer

Over the past decade there have been significant advances in the molecular characterization of colorectal cancer (CRC) that are driving treatment decisions. Expanded RAS testing beyond KRAS exon 2 was established as crucial for identifying patients who will respond to anti-epidermal growth factor receptor (EGFR) therapies and low-frequency mutations in RAS/tumor heterogeneity are gaining recognition as potential mechanisms of resistance. Despite this progress, the fact that we do not understand why left-sided but not right-sided tumors have improved outcomes following anti-EGFR therapy highlights our superficial understanding of this disease. Even with few new targeted agents receiving approval in CRC, the incorporation of next-generation sequencing into clinical decision making represents an important step forward. Biomarkers such as BRAF mutations, microsatellite instability, and HER2 amplification represent promising molecular aberrations with therapies in various stages of development, and highlight the importance of companion diagnostics in supporting targeted agents. In this review, we will discuss the importance of incorporating biomarkers into clinical decision making and regimen selection in CRC. We will particularly focus on the recent evidence suggesting an important role for tumor location in selecting first-line therapy, the importance of recent advances in biomarker development and molecular subtyping, as well as recently approved agents (regorafenib and TAS-102) and promising targeted agents that have the potential to change the standard of care.

Current companion diagnostics in advanced colorectal cancer; getting a bigger and better piece of the pie

While the treatment of colorectal cancer continues to rely heavily on conventional cytotoxic therapy, an increasing number of targeted agents are under development. Many of these treatments require companion diagnostic tests in order to define an appropriate population that will derive benefit. In addition, a growing number of biomarkers provide prognostic information about a patient's malignancy. As we learn more about these biomarkers and their assays, selecting the appropriate companion diagnostic becomes increasingly important. In the case of many biomarkers, there are numerous assays which could provide the same information to a treating physician, however each assay has strengths and weaknesses. Institutions must balance cost, assay sensitivity, turn-around time, and labor resources when selecting which assay to offer. In this review we will discuss the current state of companion diagnostics available in metastatic colorectal cancer and explore emerging biomarkers and their assays. We will focus on KRAS, BRAF, HER2, and PIK3CA testing, as well as microsatellite stability assessment and multigene panels.

Role of precision medicine in pancreatic cancer

Pancreatic cancer is one of the most challenging problems in modern oncology. Due to difficultly in early diagnosis and early distant metastasis of pancreatic cancer, surgical resection rate is less than 20% and patients' prognosis is very poor. Despite long-term efforts taken to develop treatments for pancreatic cancer, the survival rate did not significantly improve. Therefore, early diagnosis and treatment are the key to improve the survival rate of patients with pancreatic cancer. The advent of big-data genomic era and the rapid development of biotechnology have led to the recent proposal of a new concept of precise medicine, which has quickly become the focus of world medical conferences. Here, we describe the new progress and challenges of precision medicine in pancreatic cancer, with an aim to provide new ideas for improving the survival rate of patients with pancreatic cancer.

Genomic profiling of gynecologic cancers and implications for clinical practice

PURPOSE OF REVIEW

This article summarizes advances in the application of next-generation sequencing (NGS) to the personalized treatment of gynecologic malignancies.

RECENT FINDINGS

Many recurrent genomic alterations (GA) in gynecologic malignancies have been identified by studies applying NGS to tumor tissue, which can provide insights into tumor biology, diagnostic or prognostic information, and potential targeted therapy options. NGS can be used to assay single genes, portions of multiple genes ("hot-spot" panels), or the complete coding sequence of a broad range of cancer-associated genes [i.e. comprehensive genomic profiling (CGP)]. CGP of a patient's tumor reveals to practitioners clinically relevant GA (CRGA) and associated biomarker-matched treatments, with a goal of improving therapeutic response while limiting cumulative chemotherapeutic toxicities. Although the use of precision medicine for gynecologic cancers holds much promise, the data detailing impact on survival and quality of life is still accumulating, lagging behind other areas of oncology. Enrolling gynecologic oncology patients in genotype-matched trials remains challenging and highlights the need for more molecular-based basket trials for reproductive tract malignancies.

SUMMARY

Identification of molecular subsets with distinct clinical attributes, prognostic significance, and targeted therapy directed options is now feasible in clinical gynecologic oncology practice.

Silent genetic alterations identified by targeted next-generation sequencing in pheochromocytoma/paraganglioma: A clinicopathological correlations

AIMS

The goal of this pilot study was to develop a customized, cost-effective amplicon panel (Ampliseq) for target sequencing in a cohort of patients with sporadic phaeochromocytoma/paraganglioma.

METHODS

Phaeochromocytoma/paragangliomas from 25 patients were analysed by targeted next-generation sequencing approach using an Ion Torrent PGM instrument. Primers for 15 target genes (NF1, RET, VHL, SDHA, SDHB, SDHC, SDHD, SDHAF2, TMEM127, MAX, MEN1, KIF1Bβ, EPAS1, CDKN2 & PHD2) were designed using ion ampliseq designer. Ion Reporter software and Ingenuity® Variant Analysis™ software (www.ingenuity.com/variants) from Ingenuity Systems were used to analysis these results.

RESULTS

Overall, 713 variants were identified. The variants identified from the Ion Reporter ranged from 64 to 161 per patient. Single nucleotide variants (SNV) were the most common. Further annotation with the help of Ingenuity variant analysis revealed 29 of these 713variants were deletions. Of these, six variants were non-pathogenic and four were likely to be pathogenic. The remaining 19 variants were of uncertain significance. The most frequently altered gene in the cohort was KIF1B followed by NF1. Novel KIF1B pathogenic variant c.3375+1G>A was identified. The mutation was noted in a patient with clinically confirmed neurofibromatosis. Chromosome 1 showed the presence of maximum number of variants.

CONCLUSIONS

Use of targeted next-generation sequencing is a sensitive method for the detecting genetic changes in patients with phaeochromocytoma/paraganglioma. The precise detection of these genetic changes helps in understanding the pathogenesis of these tumours.

Clinical Interpretation of Genomic Variations

Novel high-throughput sequencing technologies generate large-scale genomic data and are used extensively for disease mapping of monogenic and/or complex disorders, personalized treatment, and pharmacogenomics. Next-generation sequencing is rapidly becoming routine tool for diagnosis and molecular monitoring of patients to evaluate therapeutic efficiency. The next-generation sequencing platforms generate huge amounts of genetic variation data and it remains a challenge to interpret the variations that are identified. Such data interpretation needs close collaboration among bioinformaticians, clinicians, and geneticists. There are several problems that must be addressed, such as the generation of new algorithms for mapping and annotation, harmonization of the terminology, correct use of nomenclature, reference genomes for different populations, rare disease variant databases, and clinical reports.