Clinical applications of next generation sequencing in cancer: from panels, to exomes, to genomes

The use of next-generation sequencing in personalized medicine

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Whole exome sequencing identifies novel variants of PIK3CA and validation of hotspot mutation by droplet digital PCR in breast cancer among Indian population

BACKGROUND

Breast cancer (BC) is the most common malignancy with very high incidence and relatively high mortality in women. The PIK3CA gene plays a pivotal role in the pathogenicity of breast cancer. Despite this, the mutational status of all exons except exons 9 and 20 still remains unknown.

METHODS

This study uses the whole exome sequencing (WES) based approach to identify somatic PIK3CA mutations in Indian BC cohorts. The resultant hotspot mutations were validated by droplet digital PCR (ddPCR). Further, molecular dynamics (MD) simulation was applied to elucidate the conformational and functional effects of hotspot position on PIK3CA protein.

RESULTS

In our cohort, PIK3CA showed a 44.4% somatic mutation rate and was among the top mutated genes. The mutations of PIK3CA were confined in Exons 5, 9, 11, 18, and 20, whereas the maximum number of mutations lies within exons 9 and 20. A total of 9 variants were found in our study, of which 2 were novel mutations observed on exons 9 (p.H554L) and 11 (p.S629P). However, H1047R was the hotspot mutation at exon 20 (20%). In tumor tissues, there was a considerable difference between copy number of wild-type and H1047R mutant was detected by ddPCR. Significant structural and conformational changes were observed during MD simulation, induced due to point mutation at H1047R/L position.

CONCLUSIONS

The current study provides a comprehensive view of novel as well as reported single nucleotide variants (SNVs) in PIK3CA gene associated with Indian breast cancer cases. The mutation status of H1047R/L could serve as a prognostic value in terms of selecting targeted therapy in BC.

Comparison of genetic variation between primary colorectal cancer and metastatic peritoneal cancer

BACKGROUND

Among cancer metastases by primary colorectal cancer (CRC), peritoneal metastasis is the second most common metastatic lesion after liver metastasis. In treating metastatic CRC, it is very important to differentiate targeted-therapy and chemotherapy according to the characteristics of each lesion because the genetic variation of the primary and metastatic lesions are different. However, there are few studies of genetic characteristics on peritoneal metastasis caused by primary CRC, so molecular-level studies are continuously required.

OBJECTIVE

We propose an appropriate peritoneal metastasis treatment policy by identifying the genetic characteristics between primary CRC and synchronous peritoneal metastatic lesions.

METHODS

Primary CRC and synchronous peritoneal metastasis samples were analyzed in pairs from six patients using Comprehensive Cancer Panel (409 cancer-related genes, Thermo Fisher Scientific, USA) and next-generation sequencing (NGS).

RESULTS

The mutations were commonly found on the KMT2C and THBS1 genes in both primary CRC and peritoneal metastasis. The PDE4DIP gene was mutated in all cases except for on a sample of peritoneal metastasis. As a result of analysis using the mutation database, we confirmed that the gene mutations of primary CRC and the peritoneal metastasis derived from it showed the same tendency, although we did not accompany the gene expression level or epigenetic study.

CONCLUSION

It is thought that the treatment policy through molecular genetic testing of primary CRC can also be applied to peritoneal metastasis treatment. Our study is expected to be the basis for further peritoneal metastasis research.

Two Distinct Deleterious Causative Variants in a Family with Multiple Cancer-Affected Patients

Background

Only 5 to 10% of cancers are hereditary, but they are particularly important since they can be passed down from generation to generation, and family members are at elevated risk. Although screening methods are one of the essential strategies for dealing with hereditary cancers, they do not have high specificity and sensitivity. The emergence of whole-exome sequencing (WES) causes a significant increase in the diagnostic rate of cancer-causing variants in at-risk families.

Materials and Methods

We performed WES on the proband's DNA sample from an Iranian family with multiple cancer-affected members to identify potential causative variants. Multiple in silico tools were used to evaluate the candidate variants' pathogenicity and their effects on the protein's structure, function, and stability. Moreover, the candidate variants were co-segregated in the family with Sanger sequencing.

Results

The WES data analysis identified two pathogenic variants (CHEK2: NM_007194.4: c.538C>T, p.Arg180Cys and MLH1: NM_000249.4, c.844G>A, p.Ala282Thr). Sanger sequencing data showed each of the variants was incompletely segregated with phenotype, but both of them explained the patient's phenotype together. Also, the structural analysis demonstrated that due to the variant (c.538C>T), a salt bridge between arginine 180 and glutamic acid 149 was lost. Indeed, several protein stability tools described both variants as destabilizing.

Conclusion

Herein, we interestingly identify two distinct deleterious causative variants (CHEK2: NM_007194.4: c.538C>T, p.Arg180Cys and MLH1: NM_000249.4, c.844G>A, p.Ala282Thr) in a family with several cancer-affected members. Furthermore, this study's findings established the utility of WES in the genetic diagnostics of cancer.

Compound heterozygous splicing variants in KIAA0586 cause fetal short-rib thoracic dysplasia and cerebellar malformation: Use of exome sequencing in prenatal diagnosis

BACKGROUND

Short-rib thoracic dysplasia (SRTD) and Joubert syndrome (JS) are rare genetic ciliopathies, and individuals with either syndrome can manifest cerebellar malformation and variable developmental delays. However, neither of these conditions is easily diagnosed during pregnancy due to a limited fetal phenotype. Here, we investigated a fetus that was initially observed to have short limbs and polydactyly and discovered a compound heterozygous pathogenesis through exome sequencing (ES).

METHODS

Simultaneous trio-ES and chromosome microarray analysis was provided for the fetus. The presence and effects of these variants on splicing were further validated at the DNA and RNA levels.

RESULTS

Only short limbs and post-axial polydactyly of the fetus were detected during the second trimester. Two variants (c.3940+1G>A and c.3303G>A), affecting splicing of KIAA0586, were identified from amniocytes through ES and validated by Sanger sequencing. More intensive fetal monitoring was applied, and the fetus was also found to have deformed cerebellar malformation and a constricted thoracic cage.

CONCLUSIONS

Herein, we report the genetic pathogenesis of SRTD and/or JS associated with KIAA0586 in a fetus. The novel splicing variants observed expand the spectrum of KIAA0586 in SRTD and/or JS. Based on the genetic data and the distinct corresponding phenotypes discovered by imaging examination, a comprehensive diagnosis was made during pregnancy and more valuable prognostic information was provided for the parents.

Microsatellite instability assessment is instrumental for Predictive, Preventive and Personalised Medicine: status quo and outlook

A form of genomic alteration called microsatellite instability (MSI) occurs in a class of tandem repeats (TRs) called microsatellites (MSs) or short tandem repeats (STRs) due to the failure of a post-replicative DNA mismatch repair (MMR) system. Traditionally, the strategies for determining MSI events have been low-throughput procedures that typically require assessment of tumours as well as healthy samples. On the other hand, recent large-scale pan-tumour studies have consistently highlighted the potential of massively parallel sequencing (MPS) on the MSI scale. As a result of recent innovations, minimally invasive methods show a high potential to be integrated into the clinical routine and delivery of adapted medical care to all patients. Along with advances in sequencing technologies and their ever-increasing cost-effectiveness, they may bring about a new era of Predictive, Preventive and Personalised Medicine (3PM). In this paper, we offered a comprehensive analysis of high-throughput strategies and computational tools for the calling and assessment of MSI events, including whole-genome, whole-exome and targeted sequencing approaches. We also discussed in detail the detection of MSI status by current MPS blood-based methods and we hypothesised how they may contribute to the shift from conventional medicine to predictive diagnosis, targeted prevention and personalised medical services. Increasing the efficacy of patient stratification based on MSI status is crucial for tailored decision-making. Contextually, this paper highlights drawbacks both at the technical level and those embedded deeper in cellular/molecular processes and future applications in routine clinical testing.

Genomic profiling for clinical decision making in myeloid neoplasms and acute leukemia

Myeloid neoplasms and acute leukemias derive from the clonal expansion of hematopoietic cells driven by somatic gene mutations. Although assessment of morphology plays a crucial role in the diagnostic evaluation of patients with these malignancies, genomic characterization has become increasingly important for accurate diagnosis, risk assessment, and therapeutic decision making. Conventional cytogenetics, a comprehensive and unbiased method for assessing chromosomal abnormalities, has been the mainstay of genomic testing over the past several decades and remains relevant today. However, more recent advances in sequencing technology have increased our ability to detect somatic mutations through the use of targeted gene panels, whole-exome sequencing, whole-genome sequencing, and whole-transcriptome sequencing or RNA sequencing. In patients with myeloid neoplasms, whole-genome sequencing represents a potential replacement for both conventional cytogenetic and sequencing approaches, providing rapid and accurate comprehensive genomic profiling. DNA sequencing methods are used not only for detecting somatically acquired gene mutations but also for identifying germline gene mutations associated with inherited predisposition to hematologic neoplasms. The 2022 International Consensus Classification of myeloid neoplasms and acute leukemias makes extensive use of genomic data. The aim of this report is to help physicians and laboratorians implement genomic testing for diagnosis, risk stratification, and clinical decision making and illustrates the potential of genomic profiling for enabling personalized medicine in patients with hematologic neoplasms.

Performance comparison of two next-generation sequencing panels to detect actionable mutations in cell-free DNA in cancer patients

Background Genomic alterations studies in cell-free DNA (cfDNA) have increasing clinical use in oncology. Next-generation sequencing (NGS) technology provides the most complete mutational analysis, but nowadays limited data are available related to the comparison of results reported by different platforms. Here we compare two NGS panels for cfDNA: Oncomine™ Pan-Cancer Cell-Free Assay (Thermo Fisher Scientific), suitable for clinical laboratories, and Guardant360® (GuardantHealth), with more genes targeted but only available in an outsourcing laboratory. Methods Peripheral blood was obtained from 16 advanced cancer patients in which Guardant360® (G360) was requested as part of their clinical assistance. Blood samples were sent to be analyzed with G360 panel, and an additional blood sample was drawn to obtain and analyze cfDNA with Oncomine™ Pan-Cancer (OM) panel in an Ion GeneStudio S5™ System. Results cfDNA analysis globally rendered 101 mutations. Regarding the 55/101 mutations claimed to be included by manufacturers in both panels, 17 mutations were reported only by G360, 10 only by OM and 28 by both. In those coincident cases, there was a high correlation between the variant allele fractions (VAFs) calculated with each panel (r = 0.979, p < 0.01). Regarding the six actionable mutations with an FDA-approved therapy reported by G360, one was missed with OM. Also, 12 mutations with clinical trials available were reported by G360 but not by OM. Conclusions In summary, G360 and OM can produce different mutational profile in the same sample, even in genes included in both panels, which is especially important if these mutations are potentially druggable.

Paired analysis of tumor mutation burden calculated by targeted deep sequencing panel and whole exome sequencing in non-small cell lung cancer

Owing to rapid advancements in NGS (next generation sequen-cing), genomic alteration is now considered an essential pre-dictive biomarkers that impact the treatment decision in many cases of cancer. Among the various predictive biomarkers, tumor mutation burden (TMB) was identified by NGS and was con-sidered to be useful in predicting a clinical response in cancer cases treated by immunotherapy. In this study, we directly com-pared the lab-developed-test (LDT) results by target sequencing panel, K-MASTER panel v3.0 and whole-exome sequencing (WES) to evaluate the concordance of TMB. As an initial step, the reference materials (n = 3) with known TMB status were used as an exploratory test. To validate and evaluate TMB, we used one hundred samples that were acquired from surgically resected tissues of non-small cell lung cancer (NSCLC) patients. The TMB of each sample was tested by using both LDT and WES methods, which extracted the DNA from samples at the same time. In addition, we evaluated the impact of capture re-gion, which might lead to different values of TMB; the evalu-ation of capture region was based on the size of NGS and target sequencing panels. In this pilot study, TMB was evalu-ated by LDT and WES by using duplicated reference samples; the results of TMB showed high concordance rate (R² = 0.887). This was also reflected in clinical samples (n = 100), which showed R² of 0.71. The difference between the coding sequence ratio (3.49%) and the ratio of mutations (4.8%) indicated that the LDT panel identified a relatively higher number of mutations. It was feasible to calculate TMB with LDT panel, which can be useful in clinical practice. Furthermore, a customized approach must be developed for calculating TMB, which differs according to cancer types and specific clinical settings.

Ovarian Cancer Immunotherapy and Personalized Medicine

Ovarian cancer response to immunotherapy is limited; however, the evaluation of sensitive/resistant target treatment subpopulations based on stratification by tumor biomarkers may improve the predictiveness of response to immunotherapy. These markers include tumor mutation burden, PD-L1, tumor-infiltrating lymphocytes, homologous recombination deficiency, and neoantigen intratumoral heterogeneity. Future directions in the treatment of ovarian cancer include the utilization of these biomarkers to select ideal candidates. This paper reviews the role of immunotherapy in ovarian cancer as well as novel therapeutics and study designs involving tumor biomarkers that increase the likelihood of success with immunotherapy in ovarian cancer.

Moving Next-Generation Sequencing into the Clinic

With an advancement in the field of molecular diagnostics, there has been a profound evolution in the testing modalities, especially in the field of oncology. In the past decade, sequencing technology has evolved drastically with the advent of high-throughput next-generation sequencing (NGS). Subsequently, the single-gene tests have been replaced by multigene panel-based assays, deep sequencing, massively parallel whole genome, whole-exome sequencing, and so on. NGS has provided molecular diagnostics professionals a wonderful tool to explore and unearth the genetic alterations, underpinning the pathophysiology of the disease. However, this development has posed new challenges which consist of the following; understanding the technology, types of platforms available, various sequencing strategies, bioinformatics and data analysis algorithm, reporting of various variants, and validation of assays and overall for developing NGS assay for clinical utility. The challenges involved sometimes impede development of these high-end assays in laboratories. The present article provides a broad overview of our journey in setting up the NGS assay in a molecular pathology laboratory at a tertiary care oncology center. We hereby describe various important points and steps to be followed while working on the NGS setup, right from its inception to final drafting of the reports, with inclusion of various validation steps. We aim at providing a beginner’s guide to set up NGS assays in the laboratory using recommended best practices and various international guidelines.

UMIc: A Preprocessing Method for UMI Deduplication and Reads Correction

A recent refinement in high-throughput sequencing involves the incorporation of unique molecular identifiers (UMIs), which are random oligonucleotide barcodes, on the library preparation steps. A UMI adds a unique identity to different DNA/RNA input molecules through polymerase chain reaction (PCR) amplification, thus reducing bias of this step. Here, we propose an alignment free framework serving as a preprocessing step of fastq files, called UMIc, for deduplication and correction of reads building consensus sequences from each UMI. Our approach takes into account the frequency and the Phred quality of nucleotides and the distances between the UMIs and the actual sequences. We have tested the tool using different scenarios of UMI-tagged library data, having in mind the aspect of a wide application. UMIc is an open-source tool implemented in R and is freely available from https://github.com/BiodataAnalysisGroup/UMIc.

Integrative Data Analytic Framework to Enhance Cancer Precision Medicine

With the advancement of high-throughput biotechnologies, we increasingly accumulate biomedical data about diseases, especially cancer. There is a need for computational models and methods to sift through, integrate, and extract new knowledge from the diverse available data, to improve the mechanistic understanding of diseases and patient care. To uncover molecular mechanisms and drug indications for specific cancer types, we develop an integrative framework able to harness a wide range of diverse molecular and pan-cancer data. We show that our approach outperforms the competing methods and can identify new associations. Furthermore, it captures the underlying biology predictive of drug response. Through the joint integration of data sources, our framework can also uncover links between cancer types and molecular entities for which no prior knowledge is available. Our new framework is flexible and can be easily reformulated to study any biomedical problem.

Performance comparison: exome sequencing as a single test replacing Sanger sequencing

Next generation sequencing tests are used routinely as first-choice tests in the clinic. However, systematic performance comparing the results of exome sequencing as a single test replacing Sanger sequencing of targeted gene(s) is still lacking. Performance comparison data are critically important for clinical case management. In this study, we compared Sanger-sequencing results of 258 genes to those obtained from next generation sequencing (NGS) using two exome-sequencing enrichment kits: Agilent-SureSelectQXT and Illumina-Nextera. Sequencing was performed on leukocytes and buccal-derived DNA from a single individual, and all 258 genes were sequenced a total of 11 times (using different sequencing methods and DNA sources). Sanger sequencing was completed for all exons, including flanking ± 8 bp regions. For the 258 genes, NGS mean coverage was > 20 × for > 98 and > 91% of the regions targeted by SureSelect and Nextera, respectively. Overall, 449 variants were identified in at least one experiment, and 407/449 (90.6%) were detected by all. Of the 42 discordant variants, 23 were determined as true calls, summing-up to a truth set of 430 variants. Sensitivity of true-variant detection was 99% for Sanger sequencing and 97-100% for the NGS experiments. Mean false-positive rates were 3.7E-6 for Sanger sequencing, 2.5E-6 for SureSelect-NGS and 5.2E-6 for Nextera-NGS. Our findings suggest a high overall concordance between Sanger sequencing and NGS performances. Both methods demonstrated false-positive and false-negative calls. High clinical suspicion for a specific diagnosis should, therefore, override negative results of either Sanger sequencing or NGS.

xGAP: A python based efficient, modular, extensible and fault tolerant genomic analysis pipeline for variant discovery

MOTIVATION

Since the first human genome was sequenced in 2001, there has been a rapid growth in the number of bioinformatic methods to process and analyze next generation sequencing (NGS) data for research and clinical studies that aim to identify genetic variants influencing diseases and traits. To achieve this goal, one first needs to call genetic variants from NGS data which requires multiple computationally intensive analysis steps. Unfortunately, there is a lack of an open source pipeline that can perform all these steps on NGS data in a manner which is fully automated, efficient, rapid, scalable, modular, user-friendly and fault tolerant. To address this, we introduce xGAP, an extensible Genome Analysis Pipeline, which implements modified GATK best practice to analyze DNA-seq data with aforementioned functionalities.

RESULTS

xGAP implements massive parallelization of the modified GATK best practice pipeline by splitting a genome into many smaller regions with efficient load-balancing to achieve high scalability. It can process 30x coverage whole-genome sequencing (WGS) data in approximately 90 minutes. In terms of accuracy of discovered variants, xGAP achieves average F1 scores of 99.37% for SNVs and 99.20% for Indels across seven benchmark WGS datasets. We achieve highly consistent results across multiple on-premises (SGE & SLURM) high performance clusters. Compared to the Churchill pipeline, with similar parallelization, xGAP is 20% faster when analyzing 50X coverage WGS in AWS. Finally, xGAP is user-friendly and fault tolerant where it can automatically re-initiate failed processes to minimize required user intervention.

AVAILABILITY

xGAP is available at https://github.com/Adigorla/xgap.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Simulation of African and non-African low and high coverage whole genome sequence data to assess variant calling approaches

Current variant calling (VC) approaches have been designed to leverage populations of long-range haplotypes and were benchmarked using populations of European descent, whereas most genetic diversity is found in non-European such as Africa populations. Working with these genetically diverse populations, VC tools may produce false positive and false negative results, which may produce misleading conclusions in prioritization of mutations, clinical relevancy and actionability of genes. The most prominent question is which tool or pipeline has a high rate of sensitivity and precision when analysing African data with either low or high sequence coverage, given the high genetic diversity and heterogeneity of this data. Here, a total of 100 synthetic Whole Genome Sequencing (WGS) samples, mimicking the genetics profile of African and European subjects for different specific coverage levels (high/low), have been generated to assess the performance of nine different VC tools on these contrasting datasets. The performances of these tools were assessed in false positive and false negative call rates by comparing the simulated golden variants to the variants identified by each VC tool. Combining our results on sensitivity and positive predictive value (PPV), VarDict [PPV = 0.999 and Matthews correlation coefficient (MCC) = 0.832] and BCFtools (PPV = 0.999 and MCC = 0.813) perform best when using African population data on high and low coverage data. Overall, current VC tools produce high false positive and false negative rates when analysing African compared with European data. This highlights the need for development of VC approaches with high sensitivity and precision tailored for populations characterized by high genetic variations and low linkage disequilibrium.

Insight updating of the molecular hallmarks in ovarian carcinoma

Background and purpose

Ovarian cancer (OC) is the deadliest gynaecologic cancer characterised by a high heterogeneity not only at the clinical point of view but also at the molecular level. This review focuses on the new insights about the OC molecular classification.

Materials and methods

We performed a bibliographic search for different indexed articles focused on the new molecular classification of OC. All of them have been published in PubMed and included information about the most frequent molecular alterations in OC confirmed by omics approaches. In addition, we have extracted information about the role of liquid biopsy in the OC diagnosis and prognosis.

Results

New molecular insights into OC have allowed novel clinical entities to be defined. Among OC, high-grade serous ovarian carcinoma (HGSOC) which is the most common OC is characterised by omics approaches, mutations in TP53 and in other genes involved in the homologous recombination repair, especially BRCA1/2. Recent studies in HGSOC have allowed a new molecular classification in subgroups according to their mutational, transcriptional, methylation and copy number variation signatures with a real impact in the characterisation of new therapeutic targets for OC to be defined. Furthermore, despite the intrinsic intra-tumour heterogeneity, the advances in next generation sequencing (NGS) analyses of ascetic liquid from OC have opened new ways for its characterisation and treatment.

Conclusions

The advances in genomic approaches have been used for the identification of new molecular profiling techniques which define OC subgroups and has supposed advances in the diagnosis and in the personalised treatment of OC.

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Classification of ovarian cancer regarding to widespread genetic and genomic data.

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Highlighted role of p53 and BRCA1/2 in ovarian cancer for diagnosis and treatment.

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Intra-tumour genetic heterogeneity in ovarian cancer.

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Useful of liquid biopsy study in ovarian cancer diagnosis.

Detection of Microsatellite Instability from Circulating Tumor DNA by Targeted Deep Sequencing

Currently, microsatellite instability (MSI) detection is limited to tissue samples with sufficient tumor content. Detection of MSI from blood has been explored but confounded by low sensitivity due to limited circulating tumor DNA (ctDNA). We developed a next-generation sequencing-based algorithm, blood MSI signature enrichment analysis, to detect MSI from blood. Blood MSI signature enrichment analysis development involved three major steps. First, marker sites that can effectively distinguish high MSI (MSI-H) from microsatellite stable tumors were extracted. Second, MSI signature enrichment analysis was performed based on hypergeometric probability, under the null hypothesis that plasma samples have similar MSI-H and microsatellite stable read coverage patterns for particular marker sites as the white blood cells from the training data set. Finally, enrichment scores of marker sites were normalized, and all markers were collectively considered to determine the MSI status of a plasma sample. In vitro dilution experiments with cell lines and in silico simulation experiments based on mixtures of MSI-H plasma and paired white blood cell DNA demonstrated 98% sensitivity and 100% specificity at a minimum of 1% ctDNA and 91.8% sensitivity and 100% specificity with 0.4% ctDNA. An independent validation cohort of 87 colorectal cancer patients with orthogonal confirmation of MSI status of tissues confirmed performance, achieving 94.1% sensitivity (16/17) and 100% specificity (27/27) for samples with ctDNA >0.4%.

Molecular subtyping of cancer: current status and moving toward clinical applications

Cancer is a collection of genetic diseases, with large phenotypic differences and genetic heterogeneity between different types of cancers and even within the same cancer type. Recent advances in genome-wide profiling provide an opportunity to investigate global molecular changes during the development and progression of cancer. Meanwhile, numerous statistical and machine learning algorithms have been designed for the processing and interpretation of high-throughput molecular data. Molecular subtyping studies have allowed the allocation of cancer into homogeneous groups that are considered to harbor similar molecular and clinical characteristics. Furthermore, this has helped researchers to identify both actionable targets for drug design as well as biomarkers for response prediction. In this review, we introduce five frequently applied techniques for generating molecular data, which are microarray, RNA sequencing, quantitative polymerase chain reaction, NanoString and tissue microarray. Commonly used molecular data for cancer subtyping and clinical applications are discussed. Next, we summarize a workflow for molecular subtyping of cancer, including data preprocessing, cluster analysis, supervised classification and subtype characterizations. Finally, we identify and describe four major challenges in the molecular subtyping of cancer that may preclude clinical implementation. We suggest that standardized methods should be established to help identify intrinsic subgroup signatures and build robust classifiers that pave the way toward stratified treatment of cancer patients.

POT1 mutation spectrum in tumour types commonly diagnosed among POT1-associated hereditary cancer syndrome families

BACKGROUND

The shelterin complex is composed of six proteins that protect and regulate telomere length, including protection of telomeres 1 (POT1). Germline POT1 mutations are associated with an autosomal dominant familial cancer syndrome presenting with diverse malignancies, including glioma, angiosarcoma, colorectal cancer and melanoma. Although somatic POT1 mutations promote telomere elongation and genome instability in chronic lymphocytic leukaemia, the contribution of POT1 mutations to development of other sporadic cancers is largely unexplored.

METHODS

We performed logistic regression, adjusted for tumour mutational burden, to identify associations between POT1 mutation frequency and tumour type in 62 368 tumours undergoing next-generation sequencing.

RESULTS

A total of 1834 tumours harboured a non-benign mutation of POT1 (2.94%), of which 128 harboured a mutation previously reported to confer familial cancer risk in the setting of germline POT1 deficiency. Angiosarcoma was 11 times more likely than other tumours to harbour a POT1 mutation (p=1.4×10^-20), and 65% of POT1-mutated angiosarcoma had >1 mutations in POT1. Malignant gliomas were 1.7 times less likely to harbour a POT1 mutation (p=1.2×10^-3) than other tumour types. Colorectal cancer was 1.2 times less likely to harbour a POT1 mutation (p=0.012), while melanoma showed no differences in POT1 mutation frequency versus other tumours (p=0.67).

CONCLUSIONS

These results confirm a role for shelterin dysfunction in angiosarcoma development but suggest that gliomas arising in the context of germline POT1 deficiency activate a telomere-lengthening mechanism that is uncommon in gliomagenesis.

VIPER: a web application for rapid expert review of variant calls

Summary

With the rapid development in next-generation sequencing, cost and time requirements for genomic sequencing are decreasing, enabling applications in many areas such as cancer research. Many tools have been developed to analyze genomic variation ranging from single nucleotide variants to whole chromosomal aberrations. As sequencing throughput increases, the number of variants called by such tools also grows. Often employed manual inspection of such calls is thus becoming a time-consuming procedure. We developed the Variant InsPector and Expert Rating tool (VIPER) to speed up this process by integrating the Integrative Genomics Viewer into a web application. Analysts can then quickly iterate through variants, apply filters and make decisions based on the generated images and variant metadata. VIPER was successfully employed in analyses with manual inspection of more than 10 000 calls.

Availability and implementation

VIPER is implemented in Java and Javascript and is freely available at https://github.com/MarWoes/viper.

Contact

marius.woeste@uni-muenster.de.

Supplementary information

Supplementary data are available at Bioinformatics online.

Comparing theory and non-theory based implementation approaches to improving referral practices in cancer genetics: a cluster randomised trial protocol

Background

Lynch syndrome (LS) is an inherited, cancer predisposition syndrome associated with an increased risk of colorectal, endometrial and other cancer types. Identifying individuals with LS allows access to cancer risk management strategies proven to reduce cancer incidence and improve survival. However, LS is underdiagnosed and genetic referral rates are poor. Improving LS referral is complex, and requires multisystem behaviour change. Although barriers have been identified, evidence-based strategies to facilitate behaviour change are lacking. The aim of this study is to compare the effectiveness of a theory-based implementation approach against a non-theory based approach for improving detection of LS amongst Australian patients with colorectal cancer (CRC).

Methods

A two-arm parallel cluster randomised trial design will be used to compare two identical, structured implementation approaches, distinguished only by the use of theory to identify barriers and design targeted intervention strategies, to improve LS referral practices in eight large Australian hospital networks. Each hospital network will be randomly allocated to a trial arm, with stratification by state. A trained healthcare professional will lead the following phases at each site: (1) undertake baseline clinical practice audits, (2) form multidisciplinary Implementation Teams, (3) identify target behaviours for practice change, (4) identify barriers to change, (5) generate intervention strategies, (6) support staff to implement interventions and (7) evaluate the effectiveness of the intervention using post-implementation clinical data. The theoretical and non-theoretical components of each trial arm will be distinguished in phases 4–5. Study outcomes include a LS referral process map for each hospital network, with evaluation of the proportion of patients with risk-appropriate completion of the LS referral pathway within 2 months of CRC resection pre and post implementation.

Discussion

This trial will determine the more effective approach for improving the detection of LS amongst patients with CRC, whilst also advancing understanding of the impact of theory-based implementation approaches in complex health systems and the feasibility of training healthcare professionals to use them. Insights gained will guide the development of future interventions to improve LS identification on a larger scale and across different contexts, as well as efforts to address the gap between evidence and practice in the rapidly evolving field of genomic research.

Trial registration

ANZCTR, ACTRN12618001072202. Registered on 27 June 2018.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3457-6) contains supplementary material, which is available to authorized users.

Privacy and ethical challenges in next-generation sequencing

INTRODUCTION

Next-generation sequencing (NGS) is expected to revolutionize health care. NGS allows for sequencing of the whole genome more cheaply and quickly than previous techniques. NGS offers opportunities to advance medical diagnostics and treatments, but also raises complicated ethical questions that need to be addressed.

AREAS CONSIDERED

This article draws from the literature on research and clinical ethics, as well as next-generation sequencing, in order to provide an overview of the ethical challenges involved in next-generation sequencing. This article includes a discussion of the ethics of NGS in research and clinical contexts.

EXPERT OPINION

The use of NGS in clinical and research contexts has features that pose challenges for traditional ethical frameworks for protecting research participants and patients. NGS generates massive amounts of data and results that vary in terms of known clinical relevance. It is important to determine appropriate processes for protecting, managing and communicating the data. The use of machine learning for sequencing and interpretation of genomic data also raises concerns in terms of the potential for bias and potential implications for fiduciary obligations. NGS poses particular challenges in three main ethical areas: privacy, informed consent, and return of results.

Similarities and differences between variants called with human reference genome HG19 or HG38

Background

Reference genome selection is a prerequisite for successful analysis of next generation sequencing (NGS) data. Current practice employs one of the two most recent human reference genome versions: HG19 or HG38. To date, the impact of genome version on SNV identification has not been rigorously assessed.

Methods

We conducted analysis comparing the SNVs identified based on HG19 vs HG38, leveraging whole genome sequencing (WGS) data from the genome-in-a-bottle (GIAB) project. First, SNVs were called using 26 different bioinformatics pipelines with either HG19 or HG38. Next, two tools were used to convert the called SNVs between HG19 and HG38. Lastly we calculated conversion rates, analyzed discordant rates between SNVs called with HG19 or HG38, and characterized the discordant SNVs.

Results

The conversion rates from HG38 to HG19 (average 95%) were lower than the conversion rates from HG19 to HG38 (average 99%). The conversion rates varied slightly among the various calling pipelines. Around 1.5% SNVs were discordantly converted between HG19 or HG38. The conversions from HG38 to HG19 had more SNVs which failed conversion and more discordant SNVs than the opposite conversion (HG19 to HG38). Most of the discordant SNVs had low read depth, were low confidence SNVs as defined by GIAB, and/or were predominated by G/C alleles (52% observed versus 42% expected).

Conclusion

A significant number of SNVs could not be converted between HG19 and HG38. Based on careful review of our comparisons, we recommend HG38 (the newer version) for NGS SNV analysis. To summarize, our findings suggest caution when translating identified SNVs between different versions of the human reference genome.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2620-0) contains supplementary material, which is available to authorized users.

Smartphone-based clinical diagnostics: towards democratization of evidence-based health care

Recent advancements in bioanalytical techniques have led to the development of novel and robust diagnostic approaches that hold promise for providing optimal patient treatment, guiding prevention programs and widening the scope of personalized medicine. However, these advanced diagnostic techniques are still complex, expensive and limited to centralized healthcare facilities or research laboratories. This significantly hinders the use of evidence-based diagnostics for resource-limited settings and the primary care, thus creating a gap between healthcare providers and patients, leaving these populations without access to precision and quality medicine. Smartphone-based imaging and sensing platforms are emerging as promising alternatives for bridging this gap and decentralizing diagnostic tests offering practical features such as portability, cost-effectiveness and connectivity. Moreover, towards simplifying and automating bioanalytical techniques, biosensors and lab-on-a-chip technologies have become essential to interface and integrate these assays, bringing together the high precision and sensitivity of diagnostic techniques with the connectivity and computational power of smartphones. Here, we provide an overview of the emerging field of clinical smartphone diagnostics and its contributing technologies, as well as their wide range of areas of application, which span from haematology to digital pathology and rapid infectious disease diagnostics.

Genomics-Enabled Precision Medicine for Cancer

Genomic information is increasingly being incorporated into clinical cancer care. Large-scale sequencing efforts have deepened our understanding of the genomic landscape of cancer and contributed to the expanding catalog of alterations being leveraged to aid in cancer diagnosis, prognosis, and treatment. Genomic profiling can provide clinically relevant information regarding somatic point mutations, copy number alterations, translocations, and gene fusions. Genomic features, such as mutational burden, can also be measured by more comprehensive sequencing strategies and have shown value in informing potential treatment options. Ongoing clinical trials are evaluating the use of molecularly targeted agents in genomically defined subsets of cancers within and across tumor histologies. Continued advancements in clinical genomics promise to further expand the application of genomics-enabled medicine to a broader spectrum of oncology patients.

Molecular Pathways in Melanomagenesis: What We Learned from Next-Generation Sequencing Approaches

PURPOSE OF REVIEW

Conventional clinico-pathological features in melanoma patients should be integrated with new molecular diagnostic, predictive, and prognostic factors coming from the expanding genomic profiles. Cutaneous melanoma (CM), even differing in biological behavior according to sun-exposure levels on the skin areas where it arises, is molecularly heterogeneous. The next-generation sequencing (NGS) approaches are providing data on mutation landscapes in driver genes that may account for distinct pathogenetic mechanisms and pathways. The purpose was to group and classify all somatic driver mutations observed in the main NGS-based studies.

RECENT FINDINGS

Whole exome and whole genome sequencing approaches have provided data on spectrum and distribution of genetic and genomic alterations as well as allowed to discover new cancer genes underlying CM pathogenesis. After evaluating the mutational status in a cohort of 686 CM cases from the most representative NGS studies, three molecular CM subtypes were proposed: BRAFmut, RASmut, and non-BRAFmut/non-RASmut.

Application of High-Throughput Sequencing in the Diagnosis of Inherited Thrombocytopenia

Inherited thrombocytopenia is a group of hereditary diseases with a reduction in platelet count as the main clinical manifestation. Clinically, there is an urgent need for a convenient and rapid diagnosis method. We introduced a high-throughput, next-generation sequencing (NGS) platform into the routine diagnosis of patients with unexplained thrombocytopenia and analyzed the gene sequencing results to evaluate the value of NGS technology in the screening and diagnosis of inherited thrombocytopenia. From a cohort of 112 patients with thrombocytopenia, we screened 43 patients with hereditary features. For the blood samples of these 43 patients, a gene sequencing platform for hemorrhagic and thrombotic diseases comprising 89 genes was used to perform gene detection using NGS technology. When we combined the screening results with clinical features and other findings, 15 (34.9%) of 43patients were diagnosed with inherited thrombocytopenia. In addition, 19 pathogenic variants, including 8 previously unreported variants, were identified in these patients. Through the use of this detection platform, we expect to establish a more effective diagnostic approach to such disorders.

Next-generation sequencing (NGS) of cell-free circulating tumor DNA and tumor tissue in patients with advanced urothelial cancer: a pilot assessment of concordance

Background

Advances in cancer genome sequencing have led to the development of various next-generation sequencing (NGS) platforms. There is paucity of data regarding concordance of different NGS tests carried out in the same patient.

Methods

Here, we report a pilot analysis of 22 patients with metastatic urinary tract cancer and available NGS data from paired tumor tissue [FoundationOne (F1)] and cell-free circulating tumor DNA (ctDNA) [Guardant360 (G360)].

Results

The median time between the diagnosis of stage IV disease and the first genomic test was 23.5 days (0-767), after a median number of 0 (0-3) prior systemic lines of treatment of advanced disease. Most frequent genomic alterations (GA) were found in the genes TP53 (50.0%), TERT promoter (36.3%); ARID1 (29.5%); FGFR2/3 (20.5%), PIK3CA (20.5%) and ERBB2 (18.2%). While we identified GA in both tests, the overall concordance between the two platforms was only 16.4% (0%-50%), and 17.1% (0%-50%) for those patients (n = 6) with both tests conducted around the same time (median difference = 36 days). On the contrary, in the subgroup of patients (n = 5) with repeated NGS in ctDNA after a median of 1 systemic therapy between the two tests, average concordance was 55.5% (12.1%-100.0%). Tumor tissue mutational burden was significantly associated with number of GA in G360 report (P < 0.001), number of known GA (P = 0.009) and number of variants of unknown significance (VUS) in F1 report (P < 0.001), and with total number of GA (non-VUS and VUS) in F1 report (P < 0.001).

Conclusions

This study suggests a significant discordance between clinically available NGS panels in advanced urothelial cancer, even when collected around the same time. There is a need for better understanding of these two possibly complementary NGS platforms for better integration into clinical practice.

Inferring the effect of genomic variation in the new era of genomics

Accurate and detailed understanding of the effects of variants in the coding and noncoding regions of the genome is the next big challenge in the new genomic era of personalized medicine, especially to tackle newer findings of genetic and phenotypic heterogeneity of diseases. This is necessary to resolve the gene-variant-disease relationship, the pathogenic variant spectrum of genes, pathogenic variants with variable clinical consequences, and multiloci diseases. In turn, this will facilitate patient recruitment for relevant clinical trials. In this review, we describe the trends in research at the intersection of basic and clinical genomics aiming to (a) overcome molecular diagnostic challenges and increase the clinical utility of next-generation sequencing (NGS) platforms, (b) elucidate variants associated with disease, (c) determine overall genomic complexity including epistasis, complex inheritance patterns such as "synergistic heterozygosity," digenic/multigenic inheritance, modifier effect, and rare variant load. We describe the newly emerging field of integrated functional genomics, in vivo or in vitro large-scale functional approaches, statistical bioinformatics algorithms that support NGS genomics data to interpret variants for timely clinical diagnostics and disease management. Thus, facilitating the discovery of new therapeutic or biomarker options, and their roles in the future of personalized medicine.

Novel putative drivers revealed by targeted exome sequencing of advanced solid tumors

Next generation sequencing (NGS) is becoming increasingly integrated into oncological practice and clinical research. NGS methods have also provided evidence for clonal evolution of cancers during disease progression and treatment. The number of variants associated with response to specific therapeutic agents keeps increasing. However, the identification of novel driver mutations as opposed to passenger (phenotypically silent or clinically irrelevant) mutations remains a major challenge. We conducted targeted exome sequencing of advanced solid tumors from 44 pre-treated patients with solid tumors including breast, colorectal and lung carcinomas, neuroendocrine tumors, sarcomas and others. We catalogued established driver mutations and putative new drivers as predicted by two distinct algorithms. The established drivers we detected were consistent with published observations. However, we also detected a significant number of mutations with driver potential never described before in each tumor type we studied. These putative drivers belong to key cell fate regulatory networks, including potentially druggable pathways. Should our observations be confirmed, they would support the hypothesis that new driver mutations are selected by treatment in clinically aggressive tumors, and indicate a need for longitudinal genomic testing of solid tumors to inform second line cancer treatment.

Value-based genomics

Advancements in next-generation sequencing have greatly enhanced the development of biomarker-driven cancer therapies. The affordability and availability of next-generation sequencers have allowed for the commercialization of next-generation sequencing platforms that have found widespread use for clinical-decision making and research purposes. Despite the greater availability of tumor molecular profiling by next-generation sequencing at our doorsteps, the achievement of value-based care, or improving patient outcomes while reducing overall costs or risks, in the era of precision oncology remains a looming challenge. In this review, we highlight available data through a pre-established and conceptualized framework for evaluating value-based medicine to assess the cost (efficiency), clinical benefit (effectiveness), and toxicity (safety) of genomic profiling in cancer care. We also provide perspectives on future directions of next-generation sequencing from targeted panels to whole-exome or whole-genome sequencing and describe potential strategies needed to attain value-based genomics.

Identification of novel mutations in FFPE lung adenocarcinomas using DEPArray sorting technology and next-generation sequencing

Formalin-fixed paraffin-embedded (FFPE) tissues are utilized as the standard diagnostic method in pathology laboratories. However, admixture of unwanted tissues and shortage of normal samples, which can be used to detect somatic mutation, are considered critical factors to accurately diagnose cancer. To explore these challenges, we sorted the pure tumor cells from 22 FFPE lung adenocarcinoma tissues via Di-Electro-Phoretic Array (DEPArray) technology, a new cell sorting technology, and analyzed the variants with next-generation sequencing (NGS) for the most accurate analysis. The allele frequencies of the all gene mutations were improved by 1.2 times in cells sorted via DEPArray (tumor suppressor genes, 1.3–10.1 times; oncogenes, 1.3–2.6 times). We identified 16 novel mutations using the sequencing from sorted cells via DEPArray technology, compared to detecting 4 novel mutation by the sequencing from unsorted cells. Using this analysis, we also revealed that five genes (TP53, EGFR, PTEN, RB1, KRAS, and CTNNB1) were somatically mutated in multiple homogeneous lung adenocarcinomas. Together, we sorted pure tumor cells from 22 FFPE lung adenocarcinomas by DEPArray technology and identified 16 novel somatic mutations. We also established the precise genomic landscape for more accurate diagnosis in 22 lung adenocarcinomas with mutations detected in pure tumor cells. The results obtained in this study could offer new avenues for the treatment and the diagnosis of squamous cell lung cancers.

Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine

Nowadays, the personalized approach to health care and cancer care in particular is becoming more and more popular and is taking an important place in the translational medicine paradigm. In some cases, detection of the patient-specific individual mutations that point to a targeted therapy has already become a routine practice for clinical oncologists. Wider panels of genetic markers are also on the market which cover a greater number of possible oncogenes including those with lower reliability of resulting medical conclusions. In light of the large availability of high-throughput technologies, it is very tempting to use complete patient-specific New Generation Sequencing (NGS) or other "omics" data for cancer treatment guidance. However, there are still no gold standard methods and protocols to evaluate them. Here we will discuss the clinical utility of each of the data types and describe a systems biology approach adapted for single patient measurements. We will try to summarize the current state of the field focusing on the clinically relevant case-studies and practical aspects of data processing.

Clinical Impact of Genomic Information in Pediatric Leukemia

Pediatric leukemia remains a significant contributor to childhood lethality rates. However, recent development of new technologies including next-generation sequencing (NGS) has increased our understanding of the biological and genetic underpinnings of leukemia, resulting in novel diagnostic and treatment paradigms. The most prevalent pediatric leukemias include B-cell acute lymphoblastic leukemia (B-ALL) and acute myeloid leukemia (AML). These leukemias are highly heterogeneous, both clinically and genetically. There are multiple genetic subgroups defined by the World Health Organization, each with distinct clinical management. Clinical laboratories have started adopting genomic testing strategies to include high-throughput sequencing assays which, together with conventional cytogenetic techniques, enable optimal patient care. This review summarizes genetic and genomic techniques used in clinical laboratories to support management of pediatric leukemia, highlighting technical, biological, and clinical advances. We illustrate clinical utilities of comprehensive genomic evaluation of leukemia genomes through clinical case examples, which includes the interrogations of hundreds of genes and multiple mutation mechanisms using NGS technologies. Finally, we provide a future perspective on clinical genomics and precision medicine.

Towards precision nephrology: the opportunities and challenges of genomic medicine

The expansion of genomic medicine is furthering our understanding of many human diseases. This is well illustrated in the field of nephrology, through the characterization, discovery, and growing insight into various renal diseases through use of Next Generation Sequencing (NGS) technologies. This review will provide an overview of the diagnostic opportunities of using genetic testing in the clinical setting by describing notable discoveries regarding inherited forms of renal disease that have advanced the field and by highlighting some of the potential benefits of establishing a molecular diagnosis in a clinical practice. In addition, it will discuss some of the challenges associated with the expansion of genetic testing into the clinical setting, including clinical variant interpretation and return of genetic results.

[Cancer: three eras of personalized medicine]

Since the completion of the first human DNA sequence, genomic approaches have penetrated into cancer research and therapy: first through expression profiling for diagnostic, prognostic and predictive purposes, then by sequencing of tumour DNA in order to define and apply targeted therapies. These overlapping changes occurred quite rapidly and are now overshadowed by immuno-oncology approaches that show much promise. There is however still much left to understand to make this more widely applicable, and the extreme cost of these therapies is a serious concern.

Integrative clinical genomics of metastatic cancer

Metastasis is the primary cause of cancer-related deaths. Although The Cancer Genome Atlas has sequenced primary tumour types obtained from surgical resections, much less comprehensive molecular analysis is available from clinically acquired metastatic cancers. Here we perform whole-exome and -transcriptome sequencing of 500 adult patients with metastatic solid tumours of diverse lineage and biopsy site. The most prevalent genes somatically altered in metastatic cancer included TP53, CDKN2A, PTEN, PIK3CA, and RB1. Putative pathogenic germline variants were present in 12.2% of cases of which 75% were related to defects in DNA repair. RNA sequencing complemented DNA sequencing to identify gene fusions, pathway activation, and immune profiling. Our results show that integrative sequence analysis provides a clinically relevant, multi-dimensional view of the complex molecular landscape and microenvironment of metastatic cancers.

The Molecular Revolution in Cutaneous Biology: Era of Next-Generation Sequencing

Like any true conceptual revolution, next-generation sequencing (NGS) has not only radically changed research and clinical practice, it has also modified scientific culture. With the possibility to investigate DNA contents of any organism and in any context, including in somatic disorders or in tissues carrying complex microbial populations, it initially seemed as if the genetic underpinning of any biological phenomenon could now be deciphered in an almost streamlined fashion. However, over the past recent years, we have once again come to understand that there is no such a thing as great opportunities without great challenges. The steadily expanding use of NGS and related applications is now facing biologists and physicians with novel technological obstacles, analytical hurdles and increasingly pressing ethical questions.

Toward biotechnology in space: High-throughput instruments for in situ biological research beyond Earth

Space biotechnology is a nascent field aimed at applying tools of modern biology to advance our goals in space exploration. These advances rely on our ability to exploit in situ high throughput techniques for amplification and sequencing DNA, and measuring levels of RNA transcripts, proteins and metabolites in a cell. These techniques, collectively known as "omics" techniques have already revolutionized terrestrial biology. A number of on-going efforts are aimed at developing instruments to carry out "omics" research in space, in particular on board the International Space Station and small satellites. For space applications these instruments require substantial and creative reengineering that includes automation, miniaturization and ensuring that the device is resistant to conditions in space and works independently of the direction of the gravity vector. Different paths taken to meet these requirements for different "omics" instruments are the subjects of this review. The advantages and disadvantages of these instruments and technological solutions and their level of readiness for deployment in space are discussed. Considering that effects of space environments on terrestrial organisms appear to be global, it is argued that high throughput instruments are essential to advance (1) biomedical and physiological studies to control and reduce space-related stressors on living systems, (2) application of biology to life support and in situ resource utilization, (3) planetary protection, and (4) basic research about the limits on life in space. It is also argued that carrying out measurements in situ provides considerable advantages over the traditional space biology paradigm that relies on post-flight data analysis.

Droplet digital PCR of circulating tumor cells from colorectal cancer patients can predict KRAS mutations before surgery

In colorectal cancer (CRC), KRAS mutations are a strong negative predictor for treatment with the EGFR-targeted antibodies cetuximab and panitumumab. Since it can be difficult to obtain appropriate tumor tissues for KRAS genotyping, alternative methods are required. Circulating tumor cells (CTCs) are believed to be representative of the tumor in real time. In this study we explored the capacity of a size-based device for capturing CTCs coupled with a multiplex KRAS screening assay using droplet digital PCR (ddPCR). We showed that it is possible to detect a mutant ratio of 0.05% and less than one KRAS mutant cell per mL total blood with ddPCR compared to about 0.5% and 50-75 cells for TaqMeltPCR and HRM. Next, CTCs were isolated from the blood of 35 patients with CRC at various stage of the disease. KRAS genotyping was successful for 86% (30/35) of samples with a KRAS codon 12/13 mutant ratio of 57% (17/30). In contrast, only one patient was identified as KRAS mutant when size-based isolation was combined with HRM or TaqMeltPCR. KRAS status was then determined for the 26 available formalin-fixed paraffin-embedded tumors using standard procedures. The concordance between the CTCs and the corresponding tumor tissues was 77% with a sensitivity of 83%. Taken together, the data presented here suggest that is feasible to detect KRAS mutations in CTCs from blood samples of CRC patients which are predictive for those found in the tumor. The minimal invasive nature of this procedure in combination with the high sensitivity of ddPCR might provide in the future an opportunity to monitor patients throughout the course of disease on multiple levels including early detection, prognosis, treatment and relapse as well as to obtain mechanistic insight with respect to tumor invasion and metastasis.

Unmet needs: Research helps regulators do their jobs

A plethora of innovative new medical products along with the need to apply modern technologies to medical-product evaluation has spurred seminal opportunities in regulatory sciences. Here, we provide eight examples of regulatory science research for diverse products. Opportunities abound, particularly in data science and precision health.