Translating genomics for precision cancer medicine

Strategic partnerships to improve surgical care in the Asia-Pacific region: proceedings

Emergency and essential surgery is a critical component of universal health coverage. Session three of the three-part virtual meeting series on Strategic Planning to Improve Surgical, Obstetric, Anaesthesia, and Trauma Care in the Asia-Pacific Region focused on strategic partnerships. During this session, a range of partner organisations, including intergovernmental organisations, professional associations, academic and research institutions, non-governmental organisations, and the private sector provided an update on their work in surgical system strengthening in the Asia-Pacific region. Partner organisations could provide technical and implementation support for National Surgical, Obstetric, and Anaesthesia Planning (NSOAP) in a number of areas, including workforce strengthening, capacity building, guideline development, monitoring and evaluation, and service delivery. Participants emphasised the importance of several forms of strategic collaboration: 1) collaboration across the spectrum of care between emergency, critical, and surgical care, which share many common underlying health system requirements; 2) interprofessional collaboration between surgery, obstetrics, anaesthesia, diagnostics, nursing, midwifery among other professions; 3) regional collaboration, particularly between Pacific Island Countries, and 4) South-South collaboration between low- and middle-income countries (LMICs) in mutual knowledge sharing. Partnerships between high-income countries (HIC) and LMIC organisations must include LMIC participants at a governance level for shared decision-making. Areas for joint action that emerged in the discussion included coordinated advocacy efforts to generate political view, developing common monitoring and evaluation frameworks, and utilising remote technology for workforce development and service delivery.

Research gaps and opportunities in precision nutrition: an NIH workshop report

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

A framework to predict the applicability of Oncotype DX, MammaPrint, and E2F4 gene signatures for improving breast cancer prognostic prediction

To improve cancer precision medicine, prognostic and predictive biomarkers are critically needed to aid physicians in deciding treatment strategies in a personalized fashion. Due to the heterogeneous nature of cancer, most biomarkers are expected to be valid only in a subset of patients. Furthermore, there is no current approach to determine the applicability of biomarkers. In this study, we propose a framework to improve the clinical application of biomarkers. As part of this framework, we develop a clinical outcome prediction model (CPM) and a predictability prediction model (PPM) for each biomarker and use these models to calculate a prognostic score (P-score) and a confidence score (C-score) for each patient. Each biomarker’s P-score indicates its association with patient clinical outcomes, while each C-score reflects the biomarker applicability of the biomarker’s CPM to a patient and therefore the confidence of the clinical prediction. We assessed the effectiveness of this framework by applying it to three biomarkers, Oncotype DX, MammaPrint, and an E2F4 signature, which have been used for predicting patient response, pathologic complete response versus residual disease to neoadjuvant chemotherapy (a classification problem), and recurrence-free survival (a Cox regression problem) in breast cancer, respectively. In both applications, our analyses indicated patients with higher C scores were more likely to be correctly predicted by the biomarkers, indicating the effectiveness of our framework. This framework provides a useful approach to develop and apply biomarkers in the context of cancer precision medicine.

Integrated Analysis of Whole Genome and Epigenome Data Using Machine Learning Technology: Toward the Establishment of Precision Oncology

With the completion of the International Human Genome Project, we have entered what is known as the post-genome era, and efforts to apply genomic information to medicine have become more active. In particular, with the announcement of the Precision Medicine Initiative by U.S. President Barack Obama in his State of the Union address at the beginning of 2015, "precision medicine," which aims to divide patients and potential patients into subgroups with respect to disease susceptibility, has become the focus of worldwide attention. The field of oncology is also actively adopting the precision oncology approach, which is based on molecular profiling, such as genomic information, to select the appropriate treatment. However, the current precision oncology is dominated by a method called targeted-gene panel (TGP), which uses next-generation sequencing (NGS) to analyze a limited number of specific cancer-related genes and suggest optimal treatments, but this method causes the problem that the number of patients who benefit from it is limited. In order to steadily develop precision oncology, it is necessary to integrate and analyze more detailed omics data, such as whole genome data and epigenome data. On the other hand, with the advancement of analysis technologies such as NGS, the amount of data obtained by omics analysis has become enormous, and artificial intelligence (AI) technologies, mainly machine learning (ML) technologies, are being actively used to make more efficient and accurate predictions. In this review, we will focus on whole genome sequencing (WGS) analysis and epigenome analysis, introduce the latest results of omics analysis using ML technologies for the development of precision oncology, and discuss the future prospects.

DDX3X Suppresses the Susceptibility of Hindbrain Lineages to Medulloblastoma

DEAD-Box Helicase 3 X-Linked (DDX3X) is frequently mutated in the Wingless (WNT) and Sonic hedghog (SHH) subtypes of medulloblastoma-the commonest malignant childhood brain tumor, but whether DDX3X functions as a medulloblastoma oncogene or tumor suppressor gene is not known. Here, we show that Ddx3x regulates hindbrain patterning and development by controlling Hox gene expression and cell stress signaling. In mice predisposed to Wnt- or Shh medulloblastoma, Ddx3x sensed oncogenic stress and suppressed tumor formation. WNT and SHH medulloblastomas normally arise only in the lower and upper rhombic lips, respectively. Deletion of Ddx3x removed this lineage restriction, enabling both medulloblastoma subtypes to arise in either germinal zone. Thus, DDX3X is a medulloblastoma tumor suppressor that regulates hindbrain development and restricts the competence of cell lineages to form medulloblastoma subtypes.

Comparison between two different next generation sequencing platforms for clinical relevant gene mutation test in solid tumours

In the present study, we analysed 44 formalin fixed paraffin embedded (FFPE) from different solid tumours by adopting two different next generation sequencing platforms: GeneReader (QIAGEN, Hilden, Germany) and Ion Torrent (Thermo Fisher Scientific, Waltham, Massachusetts, USA). We highlighted a 100% concordance between the platforms. In addition, focusing on variant detection, we evaluated a very good agreement between the two tests (Cohen's kappa=0.84) and, when taking into account variant allele fraction value for each variant, a very high concordance was obtained (Pearson's r=0.94). Our results underlined the high performance rate of GeneReader on FFPE samples and its suitability in routine molecular predictive practice.

The Roles of CD38 and CD157 in the Solid Tumor Microenvironment and Cancer Immunotherapy

The tumor microenvironment (TME) consists of extracellular matrix proteins, immune cells, vascular cells, lymphatics and fibroblasts. Under normal physiological conditions, tissue homeostasis protects against tumor development. However, under pathological conditions, interplay between the tumor and its microenvironment can promote tumor initiation, growth and metastasis. Immune cells within the TME have an important role in the formation, growth and metastasis of tumors, and in the responsiveness of these tumors to immunotherapy. Recent breakthroughs in the field of cancer immunotherapy have further highlighted the potential of targeting TME elements, including these immune cells, to improve the efficacy of cancer prognostics and immunotherapy. CD38 and CD157 are glycoproteins that contribute to the tumorigenic properties of the TME. For example, in the hypoxic TME, the enzymatic functions of CD38 result in an immunosuppressive environment. This leads to increased immune resistance in tumor cells and allows faster growth and proliferation rates. CD157 may also aid the production of an immunosuppressive TME, and confers increased malignancy to tumor cells through the promotion of tumor invasion and metastasis. An improved understanding of CD38 and CD157 in the TME, and how these glycoproteins affect cancer progression, will be useful to develop both cancer prognosis and treatment methods. This review aims to discuss the roles of CD38 and CD157 in the TME and cancer immunotherapy of a range of solid tumor types.

Recent trends in molecular diagnostics of yeast infections: from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside.

Clinical Applications and Utility of a Precision Medicine Approach for Patients With Unexplained Cytopenias

OBJECTIVE

To demonstrate experience and feasibility of a precision medicine approach for patients with unexplained cytopenias, defined as low blood counts in one or more cell lineages, persistent for 6 months or longer, in the absence of known nutritional, autoimmune, infectious, toxic, and neoplastic (secondary) causes.

PATIENTS AND METHODS

Patients were evaluated in our clinic between November 8, 2016, and January 12, 2018. After a thorough evaluation of known causes, family history, and appropriate clinical assays, genomic evaluation was performed in a stepwise manner, through Sanger, targeted, and/or whole-exome sequencing. Variants were analyzed and discussed in a genomics tumor board attended by clinicians, bioinformaticians, and molecular biologists.

RESULTS

Sixty-eight patients were evaluated in our clinic. After genomic interrogation, they were classified into inherited bone marrow failure syndromes (IBMFS) (n=24, 35%), cytopenias without a known clinical syndrome which included idiopathic and clonal cytopenias of undetermined significance (CCUS) (n=30, 44%), and patients who did not fit into the above two categories ("others," n=14, 21%). A significant family history was found in only 17 (25%) patients (9 IBMFS, 2 CCUS, and 6 others), whereas gene variants were found in 43 (63%) patients (34 [79%] pathogenic including 12 IBMFS, 17 CCUS, and 5 others]. Genomic assessment resulted in a change in clinical management in 17 (25%) patients, as evidenced by changes in decisions with regards to therapeutic interventions (n=8, 47%), donor choice (n=6, 35%), and/or choice of conditioning regimen for hematopoietic stem cell transplantation (n=8, 47%).

CONCLUSION

We show clinical utility of a real-world algorithmic precision medicine approach for unexplained cytopenias.

The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome

Aneuploidy, the unbalanced state of the chromosome content, represents a hallmark of most solid tumors, including colorectal cancer. Such aneuploidies result in tumor specific genomic imbalances, which emerge in premalignant precursor lesions. Moreover, increasing levels of chromosomal instability have been observed in adenocarcinomas and are maintained in distant metastases. A number of studies have systematically integrated copy number alterations with gene expression changes in primary carcinomas, cell lines, and experimental models of aneuploidy. In fact, chromosomal aneuploidies target a number of genes conferring a selective advantage for the metabolism of the cancer cell. Copy number alterations not only have a positive correlation with expression changes of the majority of genes on the altered genomic segment, but also have effects on the transcriptional levels of genes genome-wide. Finally, copy number alterations have been associated with disease outcome; nevertheless, the translational applicability in clinical practice requires further studies. Here, we (i) review the spectrum of genetic alterations that lead to colorectal cancer, (ii) describe the most frequent copy number alterations at different stages of colorectal carcinogenesis, (iii) exemplify their positive correlation with gene expression levels, and (iv) discuss copy number alterations that are potentially involved in disease outcome of individual patients.

NAD metabolic dependency in cancer is shaped by gene amplification and enhancer remodelling

Precision oncology hinges on linking tumour genotype with molecularly targeted drugs1; however, targeting the frequently dysregulated metabolic landscape of cancer has proven to be a major challenge2. Here we show that tissue context is the major determinant of dependence on the nicotinamide adenine dinucleotide (NAD) metabolic pathway in cancer. By analysing more than 7,000 tumours and 2,600 matched normal samples of 19 tissue types, coupled with mathematical modelling and extensive in vitro and in vivo analyses, we identify a simple and actionable set of 'rules'. If the rate-limiting enzyme of de novo NAD synthesis, NAPRT, is highly expressed in a normal tissue type, cancers that arise from that tissue will have a high frequency of NAPRT amplification and be completely and irreversibly dependent on NAPRT for survival. By contrast, tumours that arise from normal tissues that do not express NAPRT highly are entirely dependent on the NAD salvage pathway for survival. We identify the previously unknown enhancer that underlies this dependence. Amplification of NAPRT is shown to generate a pharmacologically actionable tumour cell dependence for survival. Dependence on another rate-limiting enzyme of the NAD synthesis pathway, NAMPT, as a result of enhancer remodelling is subject to resistance by NMRK1-dependent synthesis of NAD. These results identify a central role for tissue context in determining the choice of NAD biosynthetic pathway, explain the failure of NAMPT inhibitors, and pave the way for more effective treatments.

Review: Precision medicine and driver mutations: Computational methods, functional assays and conformational principles for interpreting cancer drivers

At the root of the so-called precision medicine or precision oncology, which is our focus here, is the hypothesis that cancer treatment would be considerably better if therapies were guided by a tumor’s genomic alterations. This hypothesis has sparked major initiatives focusing on whole-genome and/or exome sequencing, creation of large databases, and developing tools for their statistical analyses—all aspiring to identify actionable alterations, and thus molecular targets, in a patient. At the center of the massive amount of collected sequence data is their interpretations that largely rest on statistical analysis and phenotypic observations. Statistics is vital, because it guides identification of cancer-driving alterations. However, statistics of mutations do not identify a change in protein conformation; therefore, it may not define sufficiently accurate actionable mutations, neglecting those that are rare. Among the many thematic overviews of precision oncology, this review innovates by further comprehensively including precision pharmacology, and within this framework, articulating its protein structural landscape and consequences to cellular signaling pathways. It provides the underlying physicochemical basis, thereby also opening the door to a broader community.

Applications of Bioengineered 3D Tissue and Tumor Organoids in Drug Development and Precision Medicine: Current and Future

Over the past decade, advances in biomedical and tissue engineering technologies, such as cell culture techniques, biomaterials, and biofabrication, have driven increasingly widespread use of three-dimensional (3D) cell culture platforms and, subsequently, the use of organoids in a variety of research endeavors. Given the 3D nature of these organoid systems, and the frequent inclusion of extracellular matrix components, these constructs typically have more physiologically accurate cell-cell and cell-matrix interactions than traditional 2D cell cultures. As a result, 3D organoids can serve as better model systems than their 2D counterparts. Moreover, as organoids can be biofabricated from highly functional human cells, they have certain advantages over animal models, being human in nature and more easily manipulated in the laboratory. In this review, we describe such organoid technologies and their deployment in drug development and precision medicine efforts. Organoid technologies are rapidly being developed for these applications and now represent a wide variety of tissue types and diseases. Evidence is emerging that organoids are poised for widespread adoption, not only in academia but also in the pharmaceutical industry and in clinical diagnostic applications, positioning them as indispensable tools in medicine.

Stromal CD38 regulates outgrowth of primary melanoma and generation of spontaneous metastasis

The outgrowth of primary melanoma, the deadliest skin cancer, and generation of metastasis is supported by the tumor microenvironment (TME) which includes non-cancerous cells. Since the TME plays an important role in melanoma pathogenesis, its targeting is a promising therapeutic approach. Thus, it is important to identify proteins in the melanoma TME that may serve as therapeutic targets. Here we show that the nicotinamide adenine dinucleotide glycohydrolase CD38 is a suitable target for this purpose. Loss of CD38 in the TME as well as inhibition of its enzymatic activity restrained outgrowth of primary melanoma generated by two transplantable models of melanoma, B16F10 and Ret-mCherry-sorted (RMS) melanoma cells. Pathological analysis indicated that loss of CD38 increased cell death and reduced the amount of cancer-associated fibroblasts (CAFs) and blood vessels. Importantly, in addition to inhibiting outgrowth of primary melanoma tumors, loss of CD38 also inhibited spontaneous occurrence of RMS pulmonary and brain metastasis. The underlying mechanism may involve, at least in the brain, inhibition of metastasis expansion, since loss of CD38 inhibited the outgrowth of B16F10 and RMS brain tumors that were generated by direct intracranial implantation. Collectively, our results suggest that targeting CD38 in the melanoma TME provides a new therapeutic approach for melanoma treatment.

Immunomodulatory interplay of the microbiome and therapy of rheumatic diseases

Modulation of the immune system by microbes, especially from the gastrointestinal tract, is increasingly considered a key factor in the onset, course and outcome of rheumatic diseases. The interplay of the microbiome, along with genetic predisposition and environmental exposure, is thought to be an important trigger for rheumatic diseases. Improved identification of the relationship of disease-specific genetic alterations and rheumatic diseases has potential diagnostic and therapeutic applications. Treatment of rheumatic disorders is influenced by microbial actions but this interplay can be challenging due to variable and unpredictable responses to therapies. Expanded knowledge of the microbiome now allows clinicians to more precisely select ideal medication regimens and to predict response to and toxicity from drugs. Rheumatic diseases and associated therapies were among the earliest microbiome interactions investigated, yet it is notable that current research is focused on clinical and immunological associations but, in comparison, a limited number of studies regarding the microbiome's impact on treatment for rheumatic diseases have been published. In the coming years, further knowledge of immunomodulating interactions between the microbiome and the immune system will aid our understanding of autoimmunity and will be increasingly important in selection of therapeutic agents for patients with autoimmune and rheumatic diseases. In this review, recent literature regarding the bidirectional immunomodulatory effects of the microbiome with rheumatic diseases and current understanding and gaps regarding the drug-microbiome interface in the management of these disorders is presented.

Leveraging Genomic Data in Smoking Cessation Trials in the Era of Precision Medicine: Why and How

Implications

This article outlines a framework for the consistent integration of biological data/samples into smoking cessation pharmacotherapy trials, aligned with the objectives of the recently unveiled Precision Medicine Initiative. Our goal is to encourage and provide support for treatment researchers to consider biosample collection and genotyping their existing samples as well as integrating genetic analyses into their study design in order to realize precision medicine in treatment of nicotine dependence.

In vitro patient-derived 3D mesothelioma tumor organoids facilitate patient-centric therapeutic screening

Variability in patient response to anti-cancer drugs is currently addressed by relating genetic mutations to chemotherapy through precision medicine. However, practical benefits of precision medicine to therapy design are less clear. Even after identification of mutations, oncologists are often left with several drug options, and for some patients there is no definitive treatment solution. There is a need for model systems to help predict personalized responses to chemotherapeutics. We have microengineered 3D tumor organoids directly from fresh tumor biopsies to provide patient-specific models with which treatment optimization can be performed before initiation of therapy. We demonstrate the initial implementation of this platform using tumor biospecimens surgically removed from two mesothelioma patients. First, we show the ability to biofabricate and maintain viable 3D tumor constructs within a tumor-on-a-chip microfluidic device. Second, we demonstrate that results of on-chip chemotherapy screening mimic those observed in subjects themselves. Finally, we demonstrate mutation-specific drug testing by considering the results of precision medicine genetic screening and confirming the effectiveness of the non-standard compound 3-deazaneplanocin A for an identified mutation. This patient-derived tumor organoid strategy is adaptable to a wide variety of cancers and may provide a framework with which to improve efforts in precision medicine oncology.

Accurity: accurate tumor purity and ploidy inference from tumor-normal WGS data by jointly modelling somatic copy number alterations and heterozygous germline single-nucleotide-variants

Motivation

Tumor purity and ploidy have a substantial impact on next-gen sequence analyses of tumor samples and may alter the biological and clinical interpretation of results. Despite the existence of several computational methods that are dedicated to estimate tumor purity and/or ploidy from The Cancer Genome Atlas (TCGA) tumor-normal whole-genome-sequencing (WGS) data, an accurate, fast and fully-automated method that works in a wide range of sequencing coverage, level of tumor purity and level of intra-tumor heterogeneity, is still missing.

Results

We describe a computational method called Accurity that infers tumor purity, tumor cell ploidy and absolute allelic copy numbers for somatic copy number alterations (SCNAs) from tumor-normal WGS data by jointly modelling SCNAs and heterozygous germline single-nucleotide-variants (HGSNVs). Results from both in silico and real sequencing data demonstrated that Accurity is highly accurate and robust, even in low-purity, high-ploidy and low-coverage settings in which several existing methods perform poorly. Accounting for tumor purity and ploidy, Accurity significantly increased signal/noise gaps between different copy numbers. We are hopeful that Accurity is of clinical use for identifying cancer diagnostic biomarkers.

Availability and implementation

Accurity is implemented in C++/Rust, available at http://www.yfish.org/software/.

Supplementary information

Supplementary data are available at Bioinformatics online.

A Road Map for Precision Cancer Medicine Using Personalized Models

<b/> A study by Pauli and colleagues in this issue of Cancer Discovery describes the creation of a precision cancer platform for patients with advanced disease, integrating DNA sequencing of patient tumors with the generation of patient-derived organoids and xenografts. They propose the use of this platform for drug testing to nominate therapeutic options for individual patients and for therapeutic biomarker discovery. Cancer Discov; 7(5); 456-8. ©2017 AACRSee related article by Pauli et al., p. 462.

Integration of genomics and histology revises diagnosis and enables effective therapy of refractory cancer of unknown primary with PDL1 amplification

Identification of the tissue of origin in cancer of unknown primary (CUP) poses a diagnostic challenge and is critical for directing site-specific therapy. Currently, clinical decision-making in patients with CUP primarily relies on histopathology and clinical features. Comprehensive molecular profiling has the potential to contribute to diagnostic categorization and, most importantly, guide CUP therapy through identification of actionable lesions. We here report the case of an advanced-stage malignancy initially mimicking poorly differentiated soft-tissue sarcoma that did not respond to multiagent chemotherapy. Molecular profiling within a clinical whole-exome and transcriptome sequencing program revealed a heterozygous, highly amplified KRAS G12S mutation, compound-heterozygous TP53 mutation/deletion, high mutational load, and focal high-level amplification of Chromosomes 9p (including PDL1 [CD274] and JAK2) and 10p (including GATA3). Integrated analysis of molecular data and histopathology provided a rationale for immune checkpoint inhibitor (ICI) therapy with pembrolizumab, which resulted in rapid clinical improvement and a lasting partial remission. Histopathological analyses ruled out sarcoma and established the diagnosis of a poorly differentiated adenocarcinoma. Although neither histopathology nor molecular data were able to pinpoint the tissue of origin, our analyses established several differential diagnoses including triple-negative breast cancer (TNBC). We analyzed 157 TNBC samples from The Cancer Genome Atlas, revealing PDL1 copy number gains coinciding with excessive PDL1 mRNA expression in 24% of cases. Collectively, these results illustrate the impact of multidimensional tumor profiling in cases with nondescript histology and immunophenotype, show the predictive potential of PDL1 amplification for immune checkpoint inhibitors (ICIs), and suggest a targeted therapeutic strategy in Chromosome 9p24.1/PDL1-amplified cancers.

Opposing effects of cancer-type-specific SPOP mutants on BET protein degradation and sensitivity to BET inhibitors

It is generally assumed that recurrent mutations within a given cancer driver gene elicit similar drug responses. Cancer genome studies have identified recurrent but divergent missense mutations in the substrate recognition domain of the ubiquitin ligase adaptor SPOP in endometrial and prostate cancer. Their therapeutic implications remain incompletely understood. Here, we analyzed changes in the ubiquitin landscape induced by endometrial cancer-associated SPOP mutations and identified BRD2, BRD3 and BRD4 proteins (BETs) as SPOP-CUL3 substrates that are preferentially degraded by endometrial SPOP mutants. The resulting reduction of BET protein levels sensitized cancer cells to BET inhibitors. Conversely, prostate cancer-specific SPOP mutants impaired degradation of BETs, promoting resistance against their pharmacologic inhibition. These results uncover an oncogenomics paradox, whereby mutations within the same domain evoke opposing drug susceptibilities. Specifically, we provide a molecular rationale for the use of BET inhibitors to treat endometrial but not prostate cancer patients with SPOP mutations.

An Updated Review on Marine Anticancer Compounds: The Use of Virtual Screening for the Discovery of Small-Molecule Cancer Drugs

Marine secondary metabolites are a promising source of unexploited drugs that have a wide structural diversity and have shown a variety of biological activities. These compounds are produced in response to the harsh and competitive conditions that occur in the marine environment. Invertebrates are considered to be among the groups with the richest biodiversity. To date, a significant number of marine natural products (MNPs) have been established as antineoplastic drugs. This review gives an overview of MNPs, both in research or clinical stages, from diverse organisms that were reported as being active or potentially active in cancer treatment in the past seventeen years (from January 2000 until April 2017) and describes their putative mechanisms of action. The structural diversity of MNPs is also highlighted and compared with the small-molecule anticancer drugs in clinical use. In addition, this review examines the use of virtual screening for MNP-based drug discovery and reveals that classical approaches for the selection of drug candidates based on ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering may miss potential anticancer lead compounds. Finally, we introduce a novel and publically accessible chemical library of MNPs for virtual screening purposes.

Synergistic Activity with NOTCH Inhibition and Androgen Ablation in ERG-Positive Prostate Cancer Cells

The oncogenic activation of the ETS-related gene (ERG) due to gene fusions is present in over half of prostate cancers in Western countries. Because of its high incidence and oncogenic role, ERG and components of ERG network have emerged as potential drug targets for prostate cancer. Utilizing gene expression datasets, from matched normal and prostate tumor epithelial cells, an association of NOTCH transcription factors with ERG expression status was identified, confirming that NOTCH factors are direct transcriptional targets of ERG. Inhibition of ERG in TMPRSS2-ERG-positive VCaP cells led to decreased levels of NOTCH1 and 2 proteins and downstream transcriptional targets and partially recapitulated the phenotypes associated with ERG inhibition. Regulation of NOTCH1 and 2 genes by ERG were also noted with ectopic ERG expression in LNCaP (ERG-negative prostate cancer) and RWPE-1 (benign prostate-derived immortalized) cells. Furthermore, inhibition of NOTCH by the small-molecule γ-secretase inhibitor 1, GSI-1, conferred an increased sensitivity to androgen receptor (AR) inhibitors (bicalutamide and enzalutamide) or the androgen biosynthesis inhibitor (abiraterone) in VCaP cells. Combined treatment with bicalutamide and GSI-1 showed strongest inhibition of AR, ERG, NOTCH1, NOTCH2, and PSA protein levels along with decreased cell growth, cell survival, and enhanced apoptosis. Intriguingly, this effect was not observed in ERG-negative prostate cancer cells or immortalized benign/normal prostate epithelial cells. These data underscore the synergy of AR and NOTCH inhibitors in reducing the growth of ERG-positive prostate cancer cells.Implications: Combinational targeting of NOTCH and AR signaling has therapeutic potential in advanced ERG-driven prostate cancers. Mol Cancer Res; 15(10); 1308-17. ©2017 AACR.

Precision medicine in pediatric oncology: Lessons learned and next steps

The maturation of genomic technologies has enabled new discoveries in disease pathogenesis as well as new approaches to patient care. In pediatric oncology, patients may now receive individualized genomic analysis to identify molecular aberrations of relevance for diagnosis and/or treatment. In this context, several recent clinical studies have begun to explore the feasibility and utility of genomics-driven precision medicine. Here, we review the major developments in this field, discuss current limitations, and explore aspects of the clinical implementation of precision medicine, which lack consensus. Lastly, we discuss ongoing scientific efforts in this arena, which may yield future clinical applications.

Building better biomarkers: brain models in translational neuroimaging

Despite its great promise, neuroimaging has yet to substantially impact clinical practice and public health. However, a developing synergy between emerging analysis techniques and data-sharing initiatives has the potential to transform the role of neuroimaging in clinical applications. We review the state of translational neuroimaging and outline an approach to developing brain signatures that can be shared, tested in multiple contexts and applied in clinical settings. The approach rests on three pillars: (i) the use of multivariate pattern-recognition techniques to develop brain signatures for clinical outcomes and relevant mental processes; (ii) assessment and optimization of their diagnostic value; and (iii) a program of broad exploration followed by increasingly rigorous assessment of generalizability across samples, research contexts and populations. Increasingly sophisticated models based on these principles will help to overcome some of the obstacles on the road from basic neuroscience to better health and will ultimately serve both basic and applied goals.

Functional analysis reveals that RBM10 mutations contribute to lung adenocarcinoma pathogenesis by deregulating splicing

RBM10 is an RNA splicing regulator that is frequently mutated in lung adenocarcinoma (LUAD) and has recently been proposed to be a cancer gene. How RBM10 mutations observed in LUAD affect its normal functions, however, remains largely unknown. Here integrative analysis of RBM10 mutation and RNA expression data revealed that LUAD-associated RBM10 mutations exhibit a mutational spectrum similar to that of tumor suppressor genes. In addition, this analysis showed that RBM10 mutations identified in LUAD patients lacking canonical oncogenes are associated with significantly reduced RBM10 expression. To systematically investigate RBM10 mutations, we developed an experimental pipeline for elucidating their functional effects. Among six representative LUAD-associated RBM10 mutations, one nonsense and one frameshift mutation caused loss-of-function as expected, whereas four missense mutations differentially affected RBM10-mediated splicing. Importantly, changes in proliferation rates of LUAD-derived cells caused by these RBM10 missense mutants correlated with alterations in RNA splicing of RBM10 target genes. Together, our data implies that RBM10 mutations contribute to LUAD pathogenesis, at least in large part, by deregulating splicing. The methods described in this study should be useful for analyzing mutations in additional cancer-associated RNA splicing regulators.

Role of precision medicine in pancreatic cancer

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

Precision medicine in cancer: challenges and recommendations from an EU-funded cervical cancer biobanking study

Background:

Cervical cancer (CC) remains a leading cause of gynaecological cancer-related mortality worldwide. CC pathogenesis is triggered when human papillomavirus (HPV) inserts into the genome, resulting in tumour suppressor gene inactivation and oncogene activation. Collecting tumour and blood samples is critical for identifying these genetic alterations.

Methods:

BIO-RAIDs is the first prospective molecular profiling clinical study to include a substantial biobanking effort that used uniform high-quality standards and control of samples. In this European Union (EU)-funded study, we identified the challenges that were impeding the effective implementation of such a systematic and comprehensive biobanking effort.

Results:

The challenges included a lack of uniform international legal and ethical standards, complexities in clinical and molecular data management, and difficulties in determining the best technical platforms and data analysis techniques. Some difficulties were encountered by all investigators, while others affected only certain institutions, regions, or countries.

Conclusions:

The results of the BIO-RAIDs programme highlight the need to facilitate and standardise regulatory procedures, and we feel that there is also a need for international working groups that make recommendations to regulatory bodies, governmental funding agencies, and academic institutions to achieve a proficient biobanking programme throughout EU countries. This represents the first step in precision medicine.

Integrating cancer genomic data into electronic health records

The rise of genomically targeted therapies and immunotherapy has revolutionized the practice of oncology in the last 10–15 years. At the same time, new technologies and the electronic health record (EHR) in particular have permeated the oncology clinic. Initially designed as billing and clinical documentation systems, EHR systems have not anticipated the complexity and variety of genomic information that needs to be reviewed, interpreted, and acted upon on a daily basis. Improved integration of cancer genomic data with EHR systems will help guide clinician decision making, support secondary uses, and ultimately improve patient care within oncology clinics. Some of the key factors relating to the challenge of integrating cancer genomic data into EHRs include: the bioinformatics pipelines that translate raw genomic data into meaningful, actionable results; the role of human curation in the interpretation of variant calls; and the need for consistent standards with regard to genomic and clinical data. Several emerging paradigms for integration are discussed in this review, including: non-standardized efforts between individual institutions and genomic testing laboratories; “middleware” products that portray genomic information, albeit outside of the clinical workflow; and application programming interfaces that have the potential to work within clinical workflow. The critical need for clinical-genomic knowledge bases, which can be independent or integrated into the aforementioned solutions, is also discussed.

Phenotypic Characterization of a Comprehensive Set of MAPK1/ERK2 Missense Mutants

Tumor-specific genomic information has the potential to guide therapeutic strategies and revolutionize patient treatment. Currently, this approach is limited by an abundance of disease-associated mutants whose biological functions and impacts on therapeutic response are uncharacterized. To begin to address this limitation, we functionally characterized nearly all (99.84%) missense mutants of MAPK1/ERK2, an essential effector of oncogenic RAS and RAF. Using this approach, we discovered rare gain- and loss-of-function ERK2 mutants found in human tumors, revealing that, in the context of this assay, mutational frequency alone cannot identify all functionally impactful mutants. Gain-of-function ERK2 mutants induced variable responses to RAF-, MEK-, and ERK-directed therapies, providing a reference for future treatment decisions. Tumor-associated mutations spatially clustered in two ERK2 effector-recruitment domains yet produced mutants with opposite phenotypes. This approach articulates an allele-characterization framework that can be scaled to meet the goals of genome-guided oncology.

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

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

Leadership, Literacy, and Translational Expertise in Genomics: Challenges and Opportunities for Social Work

The transdisciplinary field of genomics is revolutionizing conceptualizations of health, mental health, family formation, and public policy. Many professions must rapidly acquire genomic expertise to maintain state-of-the-art knowledge in their practice. Calls for social workers to build genomic capacity come regularly, yet social work education has not prepared practitioners to join the genomics workforce in providing socially just, ethically informed care to all clients, particularly those from vulnerable and marginalized groups. The authors suggest a set of action steps for bringing social work skills and practice into the 21st century. They propose that good genomic practice entails bringing social work values, skills, and behaviors to genomics. With education and training, social workers may facilitate socially just dissemination of genomic knowledge and services across practice domains. Increased genomic literacy will support the profession's mission to address disparities in health, health care access, and mortality.

Current Challenges in Cancer Treatment

PURPOSE

In this review, we highlight the current concepts and discuss some of the current challenges and future prospects in cancer therapy. We frequently use the example of lung cancer.

METHODS

We conducted a nonsystematic PubMed search, selecting the most comprehensive and relevant research articles, clinical trials, translational papers, and review articles on precision oncology and immuno-oncology. Papers were prioritized and selected based on their originality and potential clinical applicability.

FINDINGS

Two major revolutions have changed cancer treatment paradigms in the past few years: targeting actionable alterations in oncogene-driven cancers and immuno-oncology. Important challenges are still ongoing in both fields of cancer therapy. On the one hand, druggable genomic alterations are diverse and represent only small subsets of patients in certain tumor types, which limits testing their clinical impact in biomarker-driven clinical trials. Next-generation sequencing technologies are increasingly being implemented for molecular prescreening in clinical research, but issues regarding clinical interpretation of large genomic data make their wide clinical use difficult. Further, dealing with tumor heterogeneity and acquired resistance is probably the main limitation for the success of precision oncology. On the other hand, long-term survival benefits with immune checkpoint inhibitors (anti-programmed death cell protein-1/programmed death cell ligand-1[PD-1/L1] and anti-cytotoxic T lymphocyte antigen-4 monoclonal antibodies) are restricted to a minority of patients, and no predictive markers are yet robustly validated that could help us recognize these subsets and optimize treatment delivery and selection. To achieve long-term survival benefits, drug combinations targeting several molecular alterations or cancer hallmarks might be needed. This will probably be one of the most challenging but promising precision cancer treatment strategies in the future.

IMPLICATIONS

Targeting single molecular abnormalities or cancer pathways has achieved good clinical responses that have modestly affected survival in some cancers. However, this approach to cancer treatment is still reductionist, and many challenges need to be met to improve treatment outcomes with our patients.

Enabling personalized cancer medicine decisions: The challenging pharmacological approach of PBPK models for nanomedicine and pharmacogenomics (Review)

The existing tumor heterogeneity and the complexity of cancer cell biology critically demand powerful translational tools with which to support interdisciplinary efforts aiming to advance personalized cancer medicine decisions in drug development and clinical practice. The development of physiologically based pharmacokinetic (PBPK) models to predict the effects of drugs in the body facilitates the clinical translation of genomic knowledge and the implementation of in vivo pharmacology experience with pharmacogenomics. Such a direction unequivocally empowers our capacity to also make personalized drug dosage scheme decisions for drugs, including molecularly targeted agents and innovative nanoformulations, i.e. in establishing pharmacotyping in prescription. In this way, the applicability of PBPK models to guide individualized cancer therapeutic decisions of broad clinical utility in nanomedicine in real-time and in a cost-affordable manner will be discussed. The latter will be presented by emphasizing the need for combined efforts within the scientific borderlines of genomics with nanotechnology to ensure major benefits and productivity for nanomedicine and personalized medicine interventions.

Precision Medicine for Molecularly Targeted Agents and Immunotherapies in Early-Phase Clinical Trials

Precision medicine in oncology promises the matching of genomic, molecular, and clinical data with underlying mechanisms of a range of novel anticancer therapeutics to develop more rational and effective antitumor strategies in a timely manner. However, despite the remarkable progress made in the understanding of novel drivers of different oncogenic processes, success rates for the approval of oncology drugs remain low with substantial fiscal consequences. In this article, we focus on how recent rapid innovations in technology have brought greater clarity to the biological and clinical complexities of different cancers and advanced the development of molecularly targeted agents and immunotherapies in clinical trials. We discuss the key challenges of identifying and validating predictive biomarkers of response and resistance using both tumor and surrogate tissues, as well as the hurdles associated with intratumor heterogeneity. Finally, we outline evolving strategies employed in early-phase trial designs that incorporate omics-based technologies.

Revealing the Complexity of Breast Cancer by Next Generation Sequencing

Over the last few years the increasing usage of "-omic" platforms, supported by next-generation sequencing, in the analysis of breast cancer samples has tremendously advanced our understanding of the disease. New driver and passenger mutations, rare chromosomal rearrangements and other genomic aberrations identified by whole genome and exome sequencing are providing missing pieces of the genomic architecture of breast cancer. High resolution maps of breast cancer methylomes and sequencing of the miRNA microworld are beginning to paint the epigenomic landscape of the disease. Transcriptomic profiling is giving us a glimpse into the gene regulatory networks that govern the fate of the breast cancer cell. At the same time, integrative analysis of sequencing data confirms an extensive intertumor and intratumor heterogeneity and plasticity in breast cancer arguing for a new approach to the problem. In this review, we report on the latest findings on the molecular characterization of breast cancer using NGS technologies, and we discuss their potential implications for the improvement of existing therapies.

Next-Generation Sequencing in Clinical Molecular Diagnostics of Cancer: Advantages and Challenges

The application of next-generation sequencing (NGS) to characterize cancer genomes has resulted in the discovery of numerous genetic markers. Consequently, the number of markers that warrant routine screening in molecular diagnostic laboratories, often from limited tumor material, has increased. This increased demand has been difficult to manage by traditional low- and/or medium-throughput sequencing platforms. Massively parallel sequencing capabilities of NGS provide a much-needed alternative for mutation screening in multiple genes with a single low investment of DNA. However, implementation of NGS technologies, most of which are for research use only (RUO), in a diagnostic laboratory, needs extensive validation in order to establish Clinical Laboratory Improvement Amendments (CLIA) and College of American Pathologists (CAP)-compliant performance characteristics. Here, we have reviewed approaches for validation of NGS technology for routine screening of tumors. We discuss the criteria for selecting gene markers to include in the NGS panel and the deciding factors for selecting target capture approaches and sequencing platforms. We also discuss challenges in result reporting, storage and retrieval of the voluminous sequencing data and the future potential of clinical NGS.

Joubert syndrome: a model for untangling recessive disorders with extreme genetic heterogeneity

BACKGROUND

Joubert syndrome (JS) is a recessive neurodevelopmental disorder characterised by hypotonia, ataxia, cognitive impairment, abnormal eye movements, respiratory control disturbances and a distinctive mid-hindbrain malformation. JS demonstrates substantial phenotypic variability and genetic heterogeneity. This study provides a comprehensive view of the current genetic basis, phenotypic range and gene-phenotype associations in JS.

METHODS

We sequenced 27 JS-associated genes in 440 affected individuals (375 families) from a cohort of 532 individuals (440 families) with JS, using molecular inversion probe-based targeted capture and next-generation sequencing. Variant pathogenicity was defined using the Combined Annotation Dependent Depletion algorithm with an optimised score cut-off.

RESULTS

We identified presumed causal variants in 62% of pedigrees, including the first B9D2 mutations associated with JS. 253 different mutations in 23 genes highlight the extreme genetic heterogeneity of JS. Phenotypic analysis revealed that only 34% of individuals have a 'pure JS' phenotype. Retinal disease is present in 30% of individuals, renal disease in 25%, coloboma in 17%, polydactyly in 15%, liver fibrosis in 14% and encephalocele in 8%. Loss of CEP290 function is associated with retinal dystrophy, while loss of TMEM67 function is associated with liver fibrosis and coloboma, but we observe no clear-cut distinction between JS subtypes.

CONCLUSIONS

This work illustrates how combining advanced sequencing techniques with phenotypic data addresses extreme genetic heterogeneity to provide diagnostic and carrier testing, guide medical monitoring for progressive complications, facilitate interpretation of genome-wide sequencing results in individuals with a variety of phenotypes and enable gene-specific treatments in the future.

Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine

Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL).

Emergency medical genomes: a breakthrough application of precision medicine

Today there exist two medical applications where relatively strong evidence exists to support the broad adoption of genome-informed precision medicine. These are the differential diagnosis of single gene diseases and genotype-based selection of patients for targeted cancer therapies. However, despite the availability of the $1000 genome and $700 exome for research, there is as yet little broad uptake of genomic medicine, even in these applications. Significant impediments to mainstream adoption exist, including unavailability in many institutions, lack of scalability in others, a dearth of physician understanding of interpreted genome or exome results or knowledge of how to translate consequent precision medicine care plans, and a lack of test reimbursement. In short, genomic medicine lacks a breakthrough application. Rapid genome sequencing of acutely ill infants with suspected genetic diseases (STATseq) may become that application when scaled to dozens of trios per day without loss of timeliness or accuracy. Also critical for broad adoption is embedding STATseq in software for timely patient ascertainment, augmented intelligence for interpretation, explanation of results for generalist physicians, and dynamic precision medicine decision support.

Personalized targeted therapy for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma continues to heavily burden clinicians worldwide. Researchers have discovered the genomic landscape of esophageal squamous cell carcinoma, which holds promise for an era of personalized oncology care. One of the most pressing problems facing this issue is to improve the understanding of the newly available genomic data, and identify the driver-gene mutations, pathways, and networks. The emergence of a legion of novel targeted agents has generated much hope and hype regarding more potent treatment regimens, but the accuracy of drug selection is still arguable. Other problems, such as cancer heterogeneity, drug resistance, exceptional responders, and side effects, have to be surmounted. Evolving topics in personalized oncology, such as interpretation of genomics data, issues in targeted therapy, research approaches for targeted therapy, and future perspectives, will be discussed in this editorial.