Diagnostic cancer genome sequencing and the contribution of germline variants

Elucidating the Transcriptional States of Spermatogenesis-Joint Analysis of Germline and Supporting Cell, Mice and Human, Normal and Perturbed, Bulk and Single-Cell RNA-Seq

In studying the molecular underpinning of spermatogenesis, we expect to understand the fundamental biological processes better and potentially identify genes that may lead to novel diagnostic and therapeutic strategies toward precision medicine in male infertility. In this review, we emphasized our perspective that the path forward necessitates integrative studies that rely on complementary approaches and types of data. To comprehensively analyze spermatogenesis, this review proposes four axes of integration. First, spanning the analysis of spermatogenesis in the healthy state alongside pathologies. Second, the experimental analysis of model systems (in which we can deploy treatments and perturbations) alongside human data. Third, the phenotype is measured alongside its underlying molecular profiles using known markers augmented with unbiased profiles. Finally, the testicular cells are studied as ecosystems, analyzing the germ cells alongside the states observed in the supporting somatic cells. Recently, the study of spermatogenesis has been advancing using single-cell RNA sequencing, where scientists have uncovered the unique stages of germ cell development in mice, revealing new regulators of spermatogenesis and previously unknown cell subtypes in the testis. An in-depth analysis of meiotic and postmeiotic stages led to the discovery of marker genes for spermatogonia, Sertoli and Leydig cells and further elucidated all the other germline and somatic cells in the testis microenvironment in normal and pathogenic conditions. The outcome of an integrative analysis of spermatogenesis using advanced molecular profiling technologies such as scRNA-seq has already propelled our biological understanding, with additional studies expected to have clinical implications for the study of male fertility. By uncovering new genes and pathways involved in abnormal spermatogenesis, we may gain insights into subfertility or sterility.

SNV/indel hypermutator phenotype in biallelic RAD51C variant: Fanconi anemia

We previously reported a fetus with Fanconi anemia (FA), complementation group O due to compound heterozygous variants involving RAD51C. Interestingly, the trio exome sequencing analysis also detected eight apparent de novo mosaic variants with variant allele fraction (VAF) ranging between 11.5 and 37%. Here, using whole genome sequencing and a 'home-brew' variant filtering pipeline and DeepMosaic module, we investigated the number and signature of de novo heterozygous and mosaic variants and the hypothesis of a rare phenomenon of hypermutation. Eight-hundred-thirty apparent de novo SNVs and 21 de novo indels had VAFs below 37.41% and were considered postzygotic somatic mosaic variants. The VAFs showed a bimodal distribution, with one component having an average VAF of 25% (range: 18.7-37.41%) (n = 446), representing potential postzygotic first mitotic events, and the other component with an average VAF of 12.5% (range 9.55-18.69%) (n = 384), describing potential second mitotic events. No increased rate of CNV formation was observed. The mutational pattern analysis for somatic single base substitution showed SBS40, SBS5, and SBS3 as the top recognized signatures. SBS3 is a known signature associated with homologous recombination-based DNA damage repair error. Our data demonstrate that biallelic RAD51C variants show evidence for defective genomic DNA damage repair and thereby result in a hypermutator phenotype with the accumulation of postzygotic de novo mutations, at least in the prenatal period. This 'genome hypermutator phenomenon' might contribute to the observed hematological manifestations and the predisposition to tumors in patients with FA. We propose that other FA groups should be investigated for genome-wide de novo variants.

Current and future applications of biomarkers in samples collected through minimally invasive methods for cancer medicine and population-based research

Despite advances in cancer medicine and research, invasive and potentially risky procedures such as biopsies, venous blood tests, imaging, colonoscopy, and pap smear tests are still primarily used for screening, staging, and assessing response to therapy. The development and interdisciplinary use of biomarkers from urine, feces, saliva, scent, and capillary blood collected with minimally invasive methods represents a potential opportunity for integration with biomarker analysis for cancers, both in clinical practice (e.g., in screening, treatment, and disease monitoring, and improved quality of life for patients) and population-based research (e.g., in epidemiology/public health, studies of social and environmental determinants, and evolutionary medicine). In this article, we review the scientific rationale, benefits, challenges, and potential opportunities for measuring cancer-related biomarkers in samples collected through minimally invasive methods.

Occam's razor gets a new edge: the use of symmetries in model selection

We demonstrate the power of using symmetries for model selection in the context of mechanistic modelling. We analyse two different models called the power law model (PLM) and the immunological model (IM) describing the increase in cancer risk with age, due to mutation accumulation or immunosenescence, respectively. The IM fits several cancer types better than the PLM implying that it would be selected based on minimizing residuals. However, recently a symmetry-based method for model selection has been developed, which has been successfully used in an in silico setting to find the correct model when traditional model fitting has failed. Here, we apply this method in a real-world setting to investigate the mechanisms of carcinogenesis. First, we derive distinct symmetry transformations of the two models and then we select the model which not only fits the original data but is also invariant under transformations by its symmetry. Contrary to the initial conclusion, we conclude that the PLM realistically describes the mechanism underlying the colon cancer dataset. These conclusions agree with experimental knowledge, and this work demonstrates how a model selection criterion based on biological properties can be implemented using symmetries.

Genetic and chemotherapeutic influences on germline hypermutation

Mutations in the germline generates all evolutionary genetic variation and is a cause of genetic disease. Parental age is the primary determinant of the number of new germline mutations in an individual's genome1,2. Here we analysed the genome-wide sequences of 21,879 families with rare genetic diseases and identified 12 individuals with a hypermutated genome with between two and seven times more de novo single-nucleotide variants than expected. In most families (9 out of 12), the excess mutations came from the father. Two families had genetic drivers of germline hypermutation, with fathers carrying damaging genetic variation in DNA-repair genes. For five of the families, paternal exposure to chemotherapeutic agents before conception was probably a key driver of hypermutation. Our results suggest that the germline is well protected from mutagenic effects, hypermutation is rare, the number of excess mutations is relatively modest and most individuals with a hypermutated genome will not have a genetic disease.

Prediction of hereditary nonpolyposis colorectal cancer using mRNA MSH2 quantitative and the correlation with nonmodifiable factor

BACKGROUND

Hereditary non-polyposis colon cancer is a dominantly inherited syndrome of colorectal cancer (CRC), with heightened risk for younger population. Previous studies link its susceptibility to the DNA sequence polymorphism along with Amsterdam and Bethesda criteria. However, those fail in term of applicability.

AIM

To determine a clear cut-off of MSH2 gene expression for CRC heredity grouping factor. Further, the study also aims to examine the association of risk factors to the CRC heredity.

METHODS

The cross-sectional study observed 71 respondents from May 2018 to December 2019 in determining the CRC hereditary status through MSH2 mRNA expression using reverse transcription-polymerase chain reaction and the disease’s risk factors. Data were analyzed through Chi-Square, Fischer exact, t-test, Mann-Whitney, and multiple logistics.

RESULTS

There are significant differences of MSH2 within CRC group among tissue and blood; yet, negative for significance between groups. Through the blood gene expression fifth percentile, the hereditary CRC cut-off is 11059 fc, dividing the 40 CRC respondents to 32.5% with hereditary CRC. Significant risk factors include age, family history, and staging. Nonetheless, after multivariate control, age is just a confounder. Further, the study develops a probability equation with area under the curve 82.2%.

CONCLUSION

Numerous factors have significant relations to heredity of CRC patients. However, true important factors are staging and family history, while age and others are confounders. The study also established a definite cut-off point for heredity CRC based on mRNA MSH2 expression, 11059 fc. These findings shall act as concrete foundations on further risk factors and/or genetical CRC future studies.

Prediction of hereditary nonpolyposis colorectal cancer using mRNA MSH2 quantitative and the correlation with nonmodifiable factor

BACKGROUND

Hereditary non-polyposis colon cancer is a dominantly inherited syndrome of colorectal cancer (CRC), with heightened risk for younger population. Previous studies link its susceptibility to the DNA sequence polymorphism along with Amsterdam and Bethesda criteria. However, those fail in term of applicability.

AIM

To determine a clear cut-off of MSH2 gene expression for CRC heredity grouping factor. Further, the study also aims to examine the association of risk factors to the CRC heredity.

METHODS

The cross-sectional study observed 71 respondents from May 2018 to December 2019 in determining the CRC hereditary status through MSH2 mRNA expression using reverse transcription-polymerase chain reaction and the disease's risk factors. Data were analyzed through Chi-Square, Fischer exact, t-test, Mann-Whitney, and multiple logistics.

RESULTS

There are significant differences of MSH2 within CRC group among tissue and blood; yet, negative for significance between groups. Through the blood gene expression fifth percentile, the hereditary CRC cut-off is 11059 fc, dividing the 40 CRC respondents to 32.5% with hereditary CRC. Significant risk factors include age, family history, and staging. Nonetheless, after multivariate control, age is just a confounder. Further, the study develops a probability equation with area under the curve 82.2%.

CONCLUSION

Numerous factors have significant relations to heredity of CRC patients. However, true important factors are staging and family history, while age and others are confounders. The study also established a definite cut-off point for heredity CRC based on mRNA MSH2 expression, 11059 fc. These findings shall act as concrete foundations on further risk factors and/or genetical CRC future studies.

Preferences to receive unsolicited findings of germline genome sequencing in a large population of patients with cancer

BACKGROUND

In precision medicine, somatic and germline DNA sequencing are essential to make genome-guided treatment decisions in patients with cancer. However, it can also uncover unsolicited findings (UFs) in germline DNA that could have a substantial impact on the lives of patients and their relatives. It is therefore critical to understand the preferences of patients with cancer concerning UFs derived from whole-exome (WES) or whole-genome sequencing (WGS).

METHODS

In a quantitative multicentre study, adult patients with cancer (any stage and origin of disease) were surveyed through a digital questionnaire based on previous semi-structured interviews. Background knowledge was provided by showing two videos, introducing basic concepts of genetics and general information about different categories of UFs (actionable, non-actionable, reproductive significance, unknown significance).

RESULTS

In total 1072 patients were included of whom 701 participants completed the whole questionnaire. Overall, 686 (85.1%) participants wanted to be informed about UFs in general. After introduction of four UFs categories, 113 participants (14.8%) changed their answer: 718 (94.2%) participants opted for actionable variants, 537 (72.4%) for non-actionable variants, 635 (87.0%) participants for UFs of reproductive significance and 521 (71.8%) for UFs of unknown significance. Men were more interested in receiving certain UFs than women: non-actionable: OR 3.32; 95% CI 2.05 to 5.37, reproductive significance: OR 1.97; 95% CI 1.05 to 3.67 and unknown significance: OR 2.00; 95% CI 1.25 to 3.21. In total, 244 (33%) participants conceded family members to have access to their UFs while still alive. 603 (82%) participants agreed to information being shared with relatives, after they would pass away.

CONCLUSION

Our study showed that the vast majority of patients with cancer desires to receive all UFs of genome testing, although a substantial minority does not wish to receive non-actionable findings. Incorporation of categories in informed consent procedures supports patients in making informed decisions on UFs.

Somatic mutation panels: Time to clear their names

With improvements in DNA sequencing technologies and the consequent reduction in costs, next generation sequencing is being utilized increasingly in panel-based testing to perform molecular profiling of tumors. Such tumor-based panels are often referred to as 'somatic' panels, but this term is misleading and should not be used, since not all DNA variants within a tumor are somatic in nature. Every cell in a person's body contains that person's germline DNA, including tumor cells. Moreover, tumor samples are invariably contaminated with blood, a tissue that can contain somatic mutations itself in a process now called clonal hematopoiesis. Differentiating between germline variants or tumor-associated somatic mutations versus clonal hematopoiesis can be challenging. In this review, we address how to interpret the results of somatic mutation panels, how to differentiate between germline and truly somatic events, and discuss the importance of this distinction.

Cancer biomarker discovery and translation: proteomics and beyond

INTRODUCTION

Cancer is often diagnosed at late stages when the chance of cure is relatively low and although research initiatives in oncology discover many potential cancer biomarkers, few transition to clinical applications. This review addresses the current landscape of cancer biomarker discovery and translation with a focus on proteomics and beyond. Areas covered: The review examines proteomic and genomic techniques for cancer biomarker detection and outlines advantages and challenges of integrating multiple omics approaches to achieve optimal sensitivity and address tumor heterogeneity. This discussion is based on a systematic literature review and direct participation in translational studies. Expert commentary: Identifying aggressive cancers early on requires improved sensitivity and implementation of biomarkers representative of tumor heterogeneity. During the last decade of genomic and proteomic research, significant advancements have been made in next generation sequencing and mass spectrometry techniques. This in turn has led to a dramatic increase in identification of potential genomic and proteomic cancer biomarkers. However, limited successes have been shown with translation of these discoveries into clinical practice. We believe that the integration of these omics approaches is the most promising molecular tool for comprehensive cancer evaluation, early detection and transition to Precision Medicine in oncology.

Paravertebral dexmedetomidine as an adjuvant to ropivacaine protects against independent lung injury during one-lung ventilation: a preliminary randomized clinical trial

Background

To investigate the effect of paravertebral dexmedetomidine as an adjuvant to ropivacaine on independent lung injury during one-lung ventilation.

Methods

In total, 120 patients who underwent elective radical resection of pulmonary carcinoma were randomly assigned to one of six groups (n = 20): normal saline (C group), ropivacaine (R group), intravenous dexmedetomidine (Div group), 0.5 μg/kg paravertebral dexmedetomidine as an adjuvant to ropivacaine (RD0.5 group), 1.0 μg/kg paravertebral dexmedetomidine as an adjuvant to ropivacaine (RD1.0 group), or 2.0 μg/kg paravertebral dexmedetomidine as an adjuvant to ropivacaine (RD2.0 group).

Patients in the R, Div, RD0.5, RD1.0 and RD2.0 groups underwent a thoracic paravertebral block, and normal saline was administered as a control to C group. Small marginal lung samples next to the tumor were harvested immediately after the tumor tissues were excised.

Lung injury was evaluated as follows: an injury score was determined via light microscopy, and cell apoptosis was determined via a TUNEL assay. TNF-α, IL-6, miRNA-210, HIF-1α, Tom20 and ISCU2 were also detected.

Results

Both intravenous and paravertebral dexmedetomidine attenuated independent lung injury. Downregulation of HIF-1α and miRNA-210 and upregulation of Tom20 and ISCU2 may be the underlying mechanism. No difference was observed between the Div and RD0.5 groups, and no further improvement of lung injury was found in the RD1.0 and RD2.0 groups with increased paravertebral dexmedetomidine doses.

Conclusions

Paravertebral dexmedetomidine as an adjuvant to ropivacaine, which is comparable to intravenous dexmedetomidine, could protect against independent lung injury during one-lung ventilation.

Trial registration

ISRCTN, 13000406; retrospectively registered on 22.05.2018.

A method to reduce ancestry related germline false positives in tumor only somatic variant calling

BACKGROUND

Significant clinical and research applications are driving large scale adoption of individualized tumor sequencing in cancer in order to identify tumors-specific mutations. When a matched germline sample is available, somatic mutations may be identified using comparative callers. However, matched germline samples are frequently not available such as with archival tissues, which makes it difficult to distinguish somatic from germline variants. While population databases may be used to filter out known germline variants, recent studies have shown private germline variants result in an inflated false positive rate in unmatched tumor samples, and the number germline false positives in an individual may be related to ancestry.

METHODS

First, we examined the relationship between the germline false positives and ancestry. Then we developed and implemented a tumor only caller (LumosVar) that leverages differences in allelic frequency between somatic and germline variants in impure tumors. We used simulated data to systematically examine how copy number alterations, tumor purity, and sequencing depth should affect the sensitivity of our caller. Finally, we evaluated the caller on real data.

RESULTS

We find the germline false-positive rate is significantly higher for individuals of non-European Ancestry largely due to the limited diversity in public polymorphism databases and due to population-specific characteristics such as admixture or recent expansions. Our Bayesian tumor only caller (LumosVar) is able to greatly reduce false positives from private germline variants, and our sensitivity is similar to predictions based on simulated data.

CONCLUSIONS

Taken together, our results suggest that studies of individuals of non-European ancestry would most benefit from our approach. However, high sensitivity requires sufficiently impure tumors and adequate sequencing depth. Even in impure tumors, there are copy number alterations that result in germline and somatic variants having similar allele frequencies, limiting the sensitivity of the approach. We believe our approach could greatly improve the analysis of archival samples in a research setting where the normal is not available.

Integrated Genomic Medicine: A Paradigm for Rare Diseases and Beyond

Individualized medicine, or the tailoring of therapeutic interventions to a patient's unique genetic, biochemical, physiological, exposure and behavioral profile, has been enhanced, if not enabled, by modern biomedical technologies such as high-throughput DNA sequencing platforms, induced pluripotent stem cell assays, biomarker discovery protocols, imaging modalities, and wireless monitoring devices. Despite successes in the isolated use of these technologies, however, it is arguable that their combined and integrated use in focused studies of individual patients is the best way to not only tailor interventions for those patients, but also shed light on treatment strategies for patients with similar conditions. This is particularly true for individuals with rare diseases since, by definition, they will require study without recourse to other individuals, or at least without recourse to many other individuals. Such integration and focus will require new biomedical scientific paradigms and infrastructure, including the creation of databases harboring study results, the formation of dedicated multidisciplinary research teams and new training programs. We consider the motivation and potential for such integration, point out areas in need of improvement, and argue for greater emphasis on improving patient health via technological innovations, not merely improving the technologies themselves. We also argue that the paradigm described can, in theory, be extended to the study of individuals with more common diseases.

The cost and cost trajectory of whole-genome analysis guiding treatment of patients with advanced cancers

Background

Limited data exist on the real‐world costs of applying whole‐genome analysis (WGA) in a clinical setting. We estimated the costs of applying WGA to guide treatments for patients with advanced cancers and characterized how costs evolve over time.

Methods

The setting is the British Columbia Cancer Agency Personalized OncoGenomics (POG) program in British Columbia, Canada. Cost data were obtained for patients who enrolled in the program from 2012 to 2015. We estimated mean WGA costs using bootstrapping. We applied time series analysis and produced 10‐year forecasts to determine when costs are expected to reach critical thresholds.

Results

The mean cost of WGA over the study period was CDN$34,886 per patient (95% CI: $34,051, $35,721). Over time, WGA costs decreased, driven by a reduction in costs of sequencing. Yet, costs of other components of WGA increased. Forecasting showed WGA costs may not reach critical thresholds within the next 10 years.

Conclusion

WGA costs decreased over the studied time horizon, but expenditures needed to realize WGA remain significant. Future research exploring costs and benefits of WGA‐guided cancer care are crucial to guide health policy.

Comprehensive characterization of genes associated with the TP53 signal transduction pathway in various tumors

The TP53 signal transduction pathway is an attractive target for cancer treatments. In this study, we conducted a comprehensive molecular evaluation of 907 patients with cancer in Japan to identify genomic alterations in the TP53 pathway. TP53 mutations were frequently detected in many cancers, except melanoma, thymic tumors, gastrointestinal stromal tumors, and renal cancers. The frequencies of non-synonymous single nucleotide variants (SNVs) in the TP53 family members TP63 and TP73 were relatively low, although genes with increased frequencies of SNVs were as follows: PTEN (11.7%) in breast cancer, CDKN2A (11.1 and 9.6%) in pancreas and head and neck cancers, and ATM (18.0 and 11.1%) in liver and esophageal cancers. MDM2 expression was decreased or increased in patients with mutant or wild-type TP53, respectively. CDKN1A expression was increased with mutant TP53 in head and neck cancers. Moreover, TP63 overexpression was characteristically observed in squamous cell carcinomas of the lung, esophagus, and head and neck region. Additionally, overexpression of TP63 and TP73 was frequently observed in thymomas. Our results reveal a spectrum of genomic alterations in the TP53 pathway that is characteristic of many tumor types, and these data may be useful in the trials of targeted therapies.

High-throughput Phenotyping of Lung Cancer Somatic Mutations

Recent genome sequencing efforts have identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood. Here we characterize 194 somatic mutations identified in primary lung adenocarcinomas. We present an expression-based variant-impact phenotyping (eVIP) method that uses gene expression changes to distinguish impactful from neutral somatic mutations. eVIP identified 69% of mutations analyzed as impactful and 31% as functionally neutral. A subset of the impactful mutations induces xenograft tumor formation in mice and/or confers resistance to cellular EGFR inhibition. Among these impactful variants are rare somatic, clinically actionable variants including EGFR S645C, ARAF S214C and S214F, ERBB2 S418T, and multiple BRAF variants, demonstrating that rare mutations can be functionally important in cancer.

Cystatin C as a p53-inducible apoptotic mediator that regulates cathepsin L activity

In response to various cellular stresses, p53 is activated and inhibits malignant transformation through the transcriptional regulation of its target genes. However, the full picture of the p53 downstream pathway still remains to be elucidated. Here we identified cystatin C, a major inhibitor of cathepsins, as a novel p53 target. In response to DNA damage, activated p53 induced cystatin C expression through p53 binding sequence in the first intron. We showed that cathepsin L activity was decreased in HCT116 p53^+/+ cells after adriamycin treatment, but not in HCT116 p53^−/− cells. We also found that knockdown of cystatin C reduced adriamycin‐induced caspase‐3 activation. Cystatin C expression was significantly downregulated in breast cancer cells with p53 mutations, and decreased cystatin C expression was associated with poor prognosis of breast cancer. Our findings revealed an important role of the p53–cystatin C pathway in human carcinogenesis.

Regulation of iron homeostasis by the p53-ISCU pathway

Accumulation of iron in tissues increases the risk of cancer, but iron regulatory mechanisms in cancer tissues are largely unknown. Here, we report that p53 regulates iron metabolism through the transcriptional regulation of ISCU (iron-sulfur cluster assembly enzyme), which encodes a scaffold protein that plays a critical role in Fe-S cluster biogenesis. p53 activation induced ISCU expression through binding to an intronic p53-binding site. Knockdown of ISCU enhanced the binding of iron regulatory protein 1 (IRP1), a cytosolic Fe-S protein, to an iron-responsive element in the 5′ UTR of ferritin heavy polypeptide 1 (FTH1) mRNA and subsequently reduced the translation of FTH1, a major iron storage protein. In addition, in response to DNA damage, p53 induced FTH1 and suppressed transferrin receptor, which regulates iron entry into cells. HCT116 p53^+/+ cells were resistant to iron accumulation, but HCT116 p53^−/− cells accumulated intracellular iron after DNA damage. Moreover, excess dietary iron caused significant elevation of serum iron levels in p53^−/− mice. ISCU expression was decreased in the majority of human liver cancer tissues, and its reduced expression was significantly associated with p53 mutation. Our finding revealed a novel role of the p53-ISCU pathway in the maintenance of iron homeostasis in hepatocellular carcinogenesis.

Identification of cancer predisposition variants in apparently healthy individuals using a next-generation sequencing-based family genomics approach

Cancer, like many common disorders, has a complex etiology, often with a strong genetic component and with multiple environmental factors contributing to susceptibility. A considerable number of genomic variants have been previously reported to be causative of, or associated with, an increased risk for various types of cancer. Here, we adopted a next-generation sequencing approach in 11 members of two families of Greek descent to identify all genomic variants with the potential to predispose family members to cancer. Cross-comparison with data from the Human Gene Mutation Database identified a total of 571 variants, from which 47 % were disease-associated polymorphisms, 26 % disease-associated polymorphisms with additional supporting functional evidence, 19 % functional polymorphisms with in vitro/laboratory or in vivo supporting evidence but no known disease association, 4 % putative disease-causing mutations but with some residual doubt as to their pathological significance, and 3 % disease-causing mutations. Subsequent analysis, focused on the latter variant class most likely to be involved in cancer predisposition, revealed two variants of prime interest, namely MSH2 c.2732T>A (p.L911R) and BRCA1 c.2955delC, the first of which is novel. KMT2D c.13895delC and c.1940C>A variants are additionally reported as incidental findings. The next-generation sequencing-based family genomics approach described herein has the potential to be applied to other types of complex genetic disorder in order to identify variants of potential pathological significance.

Germline deletions in the tumour suppressor gene FOCAD are associated with polyposis and colorectal cancer development

Heritable genetic variants can significantly affect the lifetime risk of developing cancer, including polyposis and colorectal cancer (CRC). Variants in genes currently known to be associated with a high risk for polyposis or CRC, however, explain only a limited number of hereditary cases. The identification of additional genetic causes is, therefore, crucial to improve CRC prevention, detection and treatment. We have performed genome-wide and targeted DNA copy number profiling and resequencing in early-onset and familial polyposis/CRC patients, and show that deletions affecting the open reading frame of the tumour suppressor gene FOCAD are recurrent and significantly enriched in CRC patients compared with unaffected controls. All patients carrying FOCAD deletions exhibited a personal or family history of polyposis. RNA in situ hybridization revealed FOCAD expression in epithelial cells in the colonic crypt, the site of tumour initiation, as well as in colonic tumours and organoids. Our data suggest that monoallelic germline deletions in the tumour suppressor gene FOCAD underlie moderate genetic predisposition to the development of polyposis and CRC.

Personalized medicine and the clinical laboratory

Personalized medicine is the use of biomarkers, most of them molecular markers, for detection of specific genetic traits to guide various approaches for preventing and treating different conditions. The identification of several genes related to heredity, oncology and infectious diseases lead to the detection of genetic polymorphisms that are involved not only in different clinical progression of these diseases but also in variations in treatment response. Currently, it is possible to detect these polymorphisms using several methodologies: detection of single nucleotide polymorphisms using polymerase chain reaction methods; nucleic acid microarray detection; and nucleic acid sequencing with automatized DNA sequencers using Sanger-derived methods and new generation sequencing. Personalized medicine assays are directed towards detecting genetic variations that alter interactions of drugs with targets or the metabolic pathways of drugs (upstream and downstream) and can be utilized for the selection of drug formulations and detect different immunogenicities of the drug. Personalized medicine applications have already been described in different areas of Medicine and allow specific treatment approaches to be applied to each patient and pathology according to the results of these assays. The application of such a protocol demands an increasing interaction between the clinical laboratory and the clinical staff. For its implementation, a coordinated team composed of basic researchers and physicians highly specialized in their areas supported by a highly specialized team of clinical analysts particularly trained in molecular biology assays is necessary.

Systematic search for rare variants in Finnish early-onset colorectal cancer patients

The heritability of colorectal cancer (CRC) is incompletely understood, and the contribution of undiscovered rare variants may be important. In search of rare disease-causing variants, we exome sequenced 22 CRC patients who were diagnosed before the age of 40 years. Exome sequencing data from 95 familial CRC patients were available as a validation set. Cases with known CRC syndromes were excluded. All patients were from Finland, a country known for its genetically homogenous population. We searched for rare nonsynonymous variants with allele frequencies below 0.1% in 3,374 Finnish and 58,112 non-Finnish controls. In addition, homozygous and compound heterozygous variants were studied. No genes with rare loss-of-function variants were present in more than one early-onset CRC patient. Three genes (ADAMTS4, CYTL1, and SYNE1) harbored rare loss-of-function variants in both early-onset and familial CRC cases. Five genes with homozygous variants in early-onset CRC cases were found (MCTP2, ARHGAP12, ATM, DONSON, and ROS1), including one gene (MCTP2) with a homozygous splice site variant. All discovered homozygous variants were exclusive to one early-onset CRC case. Independent replication is required to associate the discovered variants with CRC. These findings, together with a lack of family history in 19 of 22 (86%) early-onset patients, suggest genetic heterogeneity in unexplained early-onset CRC patients, thus emphasizing the requirement for large sample sizes and careful study designs to elucidate the role of rare variants in CRC susceptibility.

Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions

Systematic interrogation of mutation or protein modification data is important to identify sites with functional consequences and to deduce global consequences from large data sets. Mechismo (mechismo.russellab.org) enables simultaneous consideration of thousands of 3D structures and biomolecular interactions to predict rapidly mechanistic consequences for mutations and modifications. As useful functional information often only comes from homologous proteins, we benchmarked the accuracy of predictions as a function of protein/structure sequence similarity, which permits the use of relatively weak sequence similarities with an appropriate confidence measure. For protein–protein, protein–nucleic acid and a subset of protein–chemical interactions, we also developed and benchmarked a measure of whether modifications are likely to enhance or diminish the interactions, which can assist the detection of modifications with specific effects. Analysis of high-throughput sequencing data shows that the approach can identify interesting differences between cancers, and application to proteomics data finds potential mechanistic insights for how post-translational modifications can alter biomolecular interactions.

GWATCH: a web platform for automated gene association discovery analysis

Background

As genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations.

Findings

Here we present a dynamic web-based platform – GWATCH – that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication of candidate or putative genes suggested from other sources, limiting Bonferroni genome-wide association study (GWAS) penalties; 4) Open data release and sharing by eliminating privacy constraints (The National Human Genome Research Institute (NHGRI) Institutional Review Board (IRB), informed consent, The Health Insurance Portability and Accountability Act (HIPAA) of 1996 etc.) on unabridged results, which allows for open access comparative and meta-analysis.

Conclusions

GWATCH is suitable for both GWAS and whole genome sequence association datasets. We illustrate the utility of GWATCH with three large genome-wide association studies for HIV-AIDS resistance genes screened in large multicenter cohorts; however, association datasets from any study can be uploaded and analyzed by GWATCH.

Applying evolutionary biology to address global challenges

Two categories of evolutionary challenges result from escalating human impacts on the planet. The first arises from cancers, pathogens, and pests that evolve too quickly and the second, from the inability of many valued species to adapt quickly enough. Applied evolutionary biology provides a suite of strategies to address these global challenges that threaten human health, food security, and biodiversity. This Review highlights both progress and gaps in genetic, developmental, and environmental manipulations across the life sciences that either target the rate and direction of evolution or reduce the mismatch between organisms and human-altered environments. Increased development and application of these underused tools will be vital in meeting current and future targets for sustainable development.

Polymorphisms in DNA repair genes XRCC2 and XRCC3 risk of gastric cancer in Turkey

We studied the prevalence of polymorphisms in genes XRCC2 and XRCC3 in stomach cancer patients who lived in North Eastern Turkey. A total of 61 cancer patients and 78 controls were included in this study. Single nucleotide changes were studied in XRCC2 and XRCC3 genes at locus Arg188His and Thr241Met. Blood samples were taken from the patients and controls, and DNA was isolated. The regions of interest were amplified using a polymerase chain reaction method. After amplification, we used restriction enzymes (HphI and NcoI) to digest the amplified product. Digested product was then run through gel electrophoresis. We identified changes in the nucleotides in these specific regions. It was found that the Arg188His polymorphism of the XRCC2 gene was about 39% (24 out of the 61) among cancer patients. However, only 15% (12 out of 78) of the control group indicated this polymorphism. We also observed that 18 of the 61 cancer patients (29%) carried the Thr241Met polymorphism of the XRCC3 gene whereas 11 of the 78 (14%) individuals in the control group had the polymorphism. Our results showed a significant difference in polymorphism ratios between the cancer patients and health control group for the regions of interest. This result clearly showed that these polymorphisms increase the risk of stomach cancer and might be a strong marker for early diagnosis of gastric cancer.

Germline variation in cancer-susceptibility genes in a healthy, ancestrally diverse cohort: implications for individual genome sequencing

Technological advances coupled with decreasing costs are bringing whole genome and whole exome sequencing closer to routine clinical use. One of the hurdles to clinical implementation is the high number of variants of unknown significance. For cancer-susceptibility genes, the difficulty in interpreting the clinical relevance of the genomic variants is compounded by the fact that most of what is known about these variants comes from the study of highly selected populations, such as cancer patients or individuals with a family history of cancer. The genetic variation in known cancer-susceptibility genes in the general population has not been well characterized to date. To address this gap, we profiled the nonsynonymous genomic variation in 158 genes causally implicated in carcinogenesis using high-quality whole genome sequences from an ancestrally diverse cohort of 681 healthy individuals. We found that all individuals carry multiple variants that may impact cancer susceptibility, with an average of 68 variants per individual. Of the 2,688 allelic variants identified within the cohort, most are very rare, with 75% found in only 1 or 2 individuals in our population. Allele frequencies vary between ancestral groups, and there are 21 variants for which the minor allele in one population is the major allele in another. Detailed analysis of a selected subset of 5 clinically important cancer genes, BRCA1, BRCA2, KRAS, TP53, and PTEN, highlights differences between germline variants and reported somatic mutations. The dataset can serve a resource of genetic variation in cancer-susceptibility genes in 6 ancestry groups, an important foundation for the interpretation of cancer risk from personal genome sequences.

Clinical implementation of germ line cancer pharmacogenetic variants during the next-generation sequencing era

More than 100 medications approved by the US Food and Drug Administration include pharmacogenetic biomarkers in the drug label, many with cancer indications referencing germ line DNA variations. With the advent of next-generation sequencing (NGS) and its rapidly increasing uptake into cancer research and clinical practice, an enormous amount of data to inform documented gene-drug associations will be collected that must be exploited to optimize patient benefit. This review focuses on the implementation of germ line cancer pharmacogenetics in clinical practice. Specifically, it discusses the importance of germ line variation in cancer and the role of NGS in pharmacogenetic discovery and implementation. In the context of a scenario in which massive amounts of NGS-based genetic information will be increasingly available to health stakeholders, this review explores the ongoing debate regarding the threshold of evidence necessary for implementation, provides an overview of recommendations in cancer by professional organizations and regulatory bodies, and discusses limitations of current guidelines and strategies to improve third-party coverage.

Stem cell systems informatics for advanced clinical biodiagnostics: tracing molecular signatures from bench to bedside

Development of innovative high throughput technologies has enabled a variety of molecular landscapes to be interrogated with an unprecedented degree of detail. Emergence of next generation nucleotide sequencing methods, advanced proteomic techniques, and metabolic profiling approaches continue to produce a wealth of biological data that captures molecular frameworks underlying phenotype. The advent of these novel technologies has significant translational applications, as investigators can now explore molecular underpinnings of developmental states with a high degree of resolution. Application of these leading-edge techniques to patient samples has been successfully used to unmask nuanced molecular details of disease vs healthy tissue, which may provide novel targets for palliative intervention. To enhance such approaches, concomitant development of algorithms to reprogram differentiated cells in order to recapitulate pluripotent capacity offers a distinct advantage to advancing diagnostic methodology. Bioinformatic deconvolution of several “-omic” layers extracted from reprogrammed patient cells, could, in principle, provide a means by which the evolution of individual pathology can be developmentally monitored. Significant logistic challenges face current implementation of this novel paradigm of patient treatment and care, however, several of these limitations have been successfully addressed through continuous development of cutting edge in silico archiving and processing methods. Comprehensive elucidation of genomic, transcriptomic, proteomic, and metabolomic networks that define normal and pathological states, in combination with reprogrammed patient cells are thus poised to become high value resources in modern diagnosis and prognosis of patient disease.

Reflections on the cost of "low-cost" whole genome sequencing: framing the health policy debate

The future clinical applications of whole genome sequencing come with speculation and enthusiasm but require careful consideration of the true system costs and health benefits of the clinical uses of this exciting technology.

The cost of whole genome sequencing is dropping rapidly. There has been a great deal of enthusiasm about the potential for this technological advance to transform clinical care. Given the interest and significant investment in genomics, this seems an ideal time to consider what the evidence tells us about potential benefits and harms, particularly in the context of health care policy. The scale and pace of adoption of this powerful new technology should be driven by clinical need, clinical evidence, and a commitment to put patients at the centre of health care policy.

Genome-wide association and sequencing studies on colorectal cancer

Colorectal cancer is a leading cause of morbidity and mortality worldwide. Understanding its genetic mechanisms is key to improving risk prediction, prognostication and treatment. Results from genome-wide association studies have engendered a growing list of colorectal cancer susceptibility genes whereas the application of genome-wide mutational analysis has enabled the depiction of mutational landscape of colorectal cancer at high resolution. The development of novel technologies, such as metagenomic and single-cell sequencing, is expected to have positive impact on future genetic studies. However, challenges remain to address the changing epidemiology of colorectal cancer, issues on genetic testing, and clinical utilization of genomic data.

Stem cell systems informatics for advanced clinical biodiagnostics: tracing molecular signatures from bench to bedside

Development of innovative high throughput technologies has enabled a variety of molecular landscapes to be interrogated with an unprecedented degree of detail. Emergence of next generation nucleotide sequencing methods, advanced proteomic techniques, and metabolic profiling approaches continue to produce a wealth of biological data that captures molecular frameworks underlying phenotype. The advent of these novel technologies has significant translational applications, as investigators can now explore molecular underpinnings of developmental states with a high degree of resolution. Application of these leading-edge techniques to patient samples has been successfully used to unmask nuanced molecular details of disease vs healthy tissue, which may provide novel targets for palliative intervention. To enhance such approaches, concomitant development of algorithms to reprogram differentiated cells in order to recapitulate pluripotent capacity offers a distinct advantage to advancing diagnostic methodology. Bioinformatic deconvolution of several "-omic" layers extracted from reprogrammed patient cells, could, in principle, provide a means by which the evolution of individual pathology can be developmentally monitored. Significant logistic challenges face current implementation of this novel paradigm of patient treatment and care, however, several of these limitations have been successfully addressed through continuous development of cutting edge in silico archiving and processing methods. Comprehensive elucidation of genomic, transcriptomic, proteomic, and metabolomic networks that define normal and pathological states, in combination with reprogrammed patient cells are thus poised to become high value resources in modern diagnosis and prognosis of patient disease.