Leveling the playing field: bringing development of biomarkers and molecular diagnostics up to the standards for drug development

Medical Applications of Molecular Biotechnologies in the Context of Hashimoto's Thyroiditis

Hashimoto's thyroiditis (HT) is a gender autoimmune disease that is manifested by chronic inflammation of the thyroid. Clinical trial studies (CTSs) use molecular biotechnologies (MB) to approach HT appearance. The aims of this study were to analyze the applications of MB in CTSs carried out in HT populations (HT-CTSs). Further, to evaluate the role of MB in the context of the hygiene hypothesis (HH). From 75 HT-CTSs found at clinicaltrials.gov web place, forty-five were considered for this investigation. Finally, six HT-CTSs were reported as molecular HT-CTSs (mHT-CTSs) because these were planning to utilize MB. Two of mHT-CTSs were programmed on the French population to isolate DNA viral sequences. Blood, urine, and thyroid tissue biospecimens were analyzed to pick out the parvo and polyoma viruses. Two mHT-CTSs carried out in China aimed to identify oral and fecal microbiotas by measuring PCR sequencing of the 16S rRNA gene. Two mHT-CTSs were programmed in the USA and Greece, respectively, for interception of DNA polymorphisms to associate with genetic susceptibility to HT. In conclusion, MB are mainly employed in HT-CTSs for infective pathogenesis and genetic fingerprinting of HT. Furthermore, MB do not provide evidence of HH; however, they are useful for providing direct evidence of the presence of viruses.

The Implementation of Laboratory Information Management System in Multi-Site Genetics Study in Africa: The Challenges and Up-Scaling Opportunities

This study describes the roles of laboratory information management systems (LIMS) in multi-site genetics studies in Africa. We used the HiGeneS Africa project as a case study. The study participants were recruited in six African countries between 2019 to 2021. The Baobab LIMS, a server–client-based system (an African-led innovation) was used for the coordination of the biospecimen. The development phase of the LIMS showcased the team formation, data collection, biospecimen collection, and shipment strategies. The implementation phase showcased the biospecimen registration, processing, and quality control (QC) analytics. The sample QC was done using Nanodrop, Qubit, and PicoGreen/gDNATapestation assays. The results showed that a total of 3144 study participants were recruited from Cameroon, Ghana, Mali, Rwanda, Senegal, and South Africa. The biospecimen registration provided a comprehensive registry that included patient demographics, genetic information, and clinical and blood/saliva samples from the proband and family relatives. The QC analyzes identified 30 samples that failed QC, linked to overdue storage in the freezer before DNA extraction. The LIMS components implemented in this project formed a structure that can be upscaled to artificial intelligence-based LIMS. In conclusion, this study represents the largest and the most diverse collection of biospecimens for the genetic study of hearing impairment in Africa to date. A well-characterized LIMS should be recommended for multi-site molecular studies, particularly in Africa, to enhance African participation in global genomic medicine.

Biomarker development: bedside to bench

This commentary complements the report from Nixon and colleagues by addressing the critical definitions, assay and analytical quality control and interpretation, and resources available to advance similar fit-for-purpose biomarker development.

Clinical Utility of Oncuria™, a Multiplexed Liquid Biopsy for the Non-Invasive Detection of Bladder Cancer-A Pilot Study

Oncuria™ is a validated quantitative multiplex immunoassay capable of detecting bladder cancer from a voided urine sample. Herein, we sought to determine whether Oncuria™ affects physicians' use of non-invasive and invasive diagnostic tests for microhematuria, gross hematuria, and bladder cancer surveillance. We conducted a survey-based study to assess physician management of nine clinical scenarios involving real-world data from patients with gross hematuria, microhematuria, and bladder cancer on surveillance. We randomly sampled 15 practicing urologists and generated data including 135 patient-by-urologist interactions and 2160 decision points. Urologists recommended a selection of diagnostic tests and procedures before and after Oncuria™ results were provided. We assessed changes in provider use of non-invasive and invasive diagnostic tests after Oncuria™ results were provided. Over 90% of all urologists changed their diagnostic behavior in at least one patient case with the addition of Oncuria™ results. The total number of diagnostic procedures was reduced by 31% following the disclosure of a negative Oncuria™ test and 27% following the disclosure of a positive Oncuria™ test. This is pilot study has the potential to shed light on the analysis of our four large multicenter international studies deploying OncuriaTM. The Oncuria™ urine-based test, a molecular diagnostic capable of ruling out the presence of bladder cancer, reduces both unnecessary invasive and non-invasive diagnostics and has the potential to reduce costs and improve patient outcomes.

Recent advances in mass spectrometry-based approaches for proteomics and biologics: Great contribution for developing therapeutic antibodies

Since the turn of the century, mass spectrometry (MS) technologies have continued to improve dramatically, and advanced strategies that were impossible a decade ago are increasingly becoming available. The basic characteristics behind these advancements are MS resolution, quantitative accuracy, and information science for appropriate data processing. The spectral data from MS contain various types of information. The benefits of improving the resolution of MS data include accurate molecular structural-derived information, and as a result, we can obtain a refined biomolecular structure determination in a sequential and large-scale manner. Moreover, in MS data, not only accurate structural information but also the generated ion amount plays an important rule. This progress has greatly contributed a research field that captures biological events as a system by comprehensively tracing the various changes in biomolecular dynamics. The sequential changes of proteome expression in biological pathways are very essential, and the amounts of the changes often directly become the targets of drug discovery or indicators of clinical efficacy. To take this proteomic approach, it is necessary to separate the individual MS spectra derived from each biomolecule in the complexed biological samples. MS itself is not so infinite to perform the all peak separation, and we should consider improving the methods for sample processing and purification to make them suitable for injection into MS. The above-described characteristics can only be achieved using MS with any analytical instrument. Moreover, MS is expected to be applied and expand into many fields, not only basic life sciences but also forensic medicine, plant sciences, materials, and natural products. In this review, we focus on the technical fundamentals and future aspects of the strategies for accurate structural identification, structure-indicated quantitation, and on the challenges for pharmacokinetics of high-molecular-weight protein biopharmaceuticals.

Non-coding RNAs Enabling Prognostic Stratification and Prediction of Therapeutic Response in Colorectal Cancer Patients

Colorectal cancer (CRC) is a heterogeneous disease and current treatment options for patients are associated with a wide range of outcomes and tumor responses. Although the traditional TNM staging system continues to serve as a crucial tool for estimating CRC prognosis and for stratification of treatment choices and long-term survival, it remains limited as it relies on macroscopic features and cases of surgical resection, fails to incorporate new molecular data and information, and cannot perfectly predict the variety of outcomes and responses to treatment associated with tumors of the same stage. Although additional histopathologic features have recently been applied in order to better classify individual tumors, the future might incorporate the use of novel molecular and genetic markers in order to maximize therapeutic outcome and to provide accurate prognosis. Such novel biomarkers, in addition to individual patient tumor phenotyping and other validated genetic markers, could facilitate the prediction of risk of progression in CRC patients and help assess overall survival. Recent findings point to the emerging role of non-protein-coding regions of the genome in their contribution to the progression of cancer and tumor formation. Two major subclasses of non-coding RNAs (ncRNAs), microRNAs and long non-coding RNAs, are often dysregulated in CRC and have demonstrated their diagnostic and prognostic potential as biomarkers. These ncRNAs are promising molecular classifiers and could assist in the stratification of patients into appropriate risk groups to guide therapeutic decisions and their expression patterns could help determine prognosis and predict therapeutic options in CRC.

Implantation and extravillous trophoblast invasion: From rare archival specimens to modern biobanking

Extravillous trophoblast invasion serves to attach the placenta to the uterus and to enable access to nutrients for the embryo throughout pregnancy - secretions of the uterine glands in the first trimester, maternal blood in the second and third trimester. For assessing extravillous trophoblast invasion, histology (in combination with immunohistochemistry) still plays a major role in placental research. This is especially true for the re-assessment of rare archival specimens from early human implantation sites or placenta in utero with the background of recent knowledge which may help to strengthen current hypotheses. This review summarizes the recently expanded picture of extravillous trophoblast invasion, gives an overview about fundamental archival specimens in placental research, presents new images of archival specimens, gives insights into the latest developments in the field of biobanking and provides insight into the current situation on sample usage in the absence of biobanks. Modern techniques allow expanding our hitherto believed concept of extravillous trophoblast invasion, which is not restricted to spiral arteries: Extravillous trophoblasts also invade into uterine glands and uterine veins and thereby connect all these luminal structures with the intervillous space. All biomedical research dramatically depends on the quality of the assessed biological samples. Hence, researchers should be aware that the time between collection of a sample from a body and the beginning of analysis (pre-analytical phase) may have more impact on the outcome of a study than previously assumed.

Diagnostic and prognostic value of miR-205 in colorectal cancer

Emerging evidence has shown associations of microRNA-205 (miR-205) with crucial cell processes such as the epithelial-mesenchymal transition (EMT) and aberrant expression with tumorigenesis in many types of human malignancy. This prospective study characterized the contribution of miR-205 to the colorectal cancer (CRC) tumorigenesis. The real-time reverse transcription-polymerase chain reaction was used to examine miR-205 levels prospectively in 36 pairs of samples of CRC tissue and adjacent noncancerous tissue (>2 cm from cancer tissue). In addition, the relationship between miR-205 levels and clinicopathological features was explored. The capability of miR-205 to function as a tumor marker was also examined. miR-205 expression levels did not show significant changes overall. However, miR-205 was significantly downregulated in a group of CRC samples compared with matched noncancerous tissue samples. Moreover, decreased miR-205 correlated significantly with lymphatic metastasis. A receiver operating characteristic (ROC) curve also showed an optimum cut off point of 1.4?10-3 to distinguish lymphatic metastatic CRCs from non-metastatic CRCs. Interestingly we found lymphatic metastasis in almost 80% of the depressed samples. This study suggested that miR-205 could be reduced in the majority of metastatic CRCs and the risk of CRC metastasis may be predicted by monitoring miR-205 in patient samples collected at the time of the initial diagnosis. Therefore, targeting miR-205 and its potential environmental activators might be a promising therapeutic option to prevent malignant progression toward metastasis.

Combined Ang-2 and VEGF serum levels: holding hands as a new integral biomarker in non-small-cell lung cancers

AIM

Evaluate if serum levels of VEGF and Ang-2 are correlated in non-small-cell lung cancers (NSCLCs) and its implications in the diagnostic and prognostic of the disease.

PATIENTS & METHODS

Unselected cohort of 145 NSCLC patients and 30 control individuals. The serum levels of Ang-2 and VEGF of each patient were measured by ELISA prior to treatment.

RESULTS & CONCLUSIONS

Serum levels of Ang-2 and VEGF are correlated (p < 0.0001). High serum levels of Ang-2 and VEGF isolated and both combined (high(Ang-2/VEGF)) correlate with likelihood of presenting NSCLC (p = 0.016; p = 0.003; p < 0.0001, respectively). Serum levels of Ang-2 and high(Ang-2/VEGF) but not VEGF alone are independent prognostic factors (p = 0.001; p = 0.619; p = 0.005). High(Ang-2/VEGF) serum levels could be exploited as a new valuable integral biomarker in NSCLC.

Developments in biospecimen research

INTRODUCTION

Biobanking refers to the infrastructure, policies and practices involved in collecting, processing, storing and disseminating biological samples. Biospecimen methods research to support biobanking through evidence-based practices is now recognized as critical to the success of biobanking and translational research.

SOURCES OF DATA

Data concerning biospecimen research have appeared in the literature for many years, primarily in journals and textbooks focused on clinical chemistry, epidemiology and pathology. Recently, new efforts have been initiated to support the development of evidence-based biobanking practices.

AREAS OF AGREEMENT

Generally, researchers who are engaged in studies involving biospecimen collection are aware of the effects of pre-analytical variables on their downstream analyses, and they normally take steps to control those variables to publish reproducible results. Knowledge of such biospecimen research data is often unknown in the clinical setting unless the researchers are engaged in a project requiring strict protocols.

AREAS OF CONTROVERSY

There is broad agreement of the need to develop evidence-based practices to achieve consistent quality for biospecimens and data. However, due to inconsistencies in the literature, there is some disagreement on whether biospecimens need to be collected according to a 'platinum' standard or local biobank standards for collecting samples as 'fit-for-purpose' will be sufficient.

GROWING POINTS

New and expanded efforts, on an international basis where possible, need to be developed to better harmonize biospecimen management practices.

AREAS TIMELY FOR DEVELOPING RESEARCH

Additional biospecimen methods research leading to the development of evidence-based practices is critical to translational research and personalized medicine.

Monitoring Trastuzumab Resistance and Cardiotoxicity: A Tale of Personalized Medicine

While approval of trastuzumab, a recombinant monoclonal antibody directed against HER2, along with a diagnostic kit to detect breast cancers which are positive for HER2 overexpression, has advanced a new era of stratified and personalized medicine, it also created several challenges to our scientific and clinical practice. These problems include trastuzumab resistance and trastuzumab-induced cardiotoxicity. In this review, we will summarize data from the literature regarding mechanisms of trastuzumab resistance and trastuzumab-induced cardiotoxicity and present some promising model systems that may advance our understanding of these mechanisms. Our discussion will include development of circulating tumor cells and circulating tumor DNA for monitoring tumor burden, of patient-derived xenograft models for preclinical testing of novel therapies, and of novel therapeutic strategies for trastuzumab-resistance and possible integration of these strategies in the design of co-clinical studies for testing in relevant patient subpopulations.

Evidence of clinical utility: an unmet need in molecular diagnostics for patients with cancer

This article defines and describes best practices for the academic and business community to generate evidence of clinical utility for cancer molecular diagnostic assays. Beyond analytical and clinical validation, successful demonstration of clinical utility involves developing sufficient evidence to demonstrate that a diagnostic test results in an improvement in patient outcomes. This discussion is complementary to theoretical frameworks described in previously published guidance and literature reports by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, Institute of Medicine, and Center for Medical Technology Policy, among others. These reports are comprehensive and specifically clarify appropriate clinical use, adoption, and payer reimbursement for assay manufacturers, as well as Clinical Laboratory Improvement Amendments-certified laboratories, including those that develop assays (laboratory developed tests). Practical criteria and steps for establishing clinical utility are crucial to subsequent decisions for reimbursement without which high-performing molecular diagnostics will have limited availability to patients with cancer and fail to translate scientific advances into high-quality and cost-effective cancer care. See all articles in this CCR Focus section, "The Precision Medicine Conundrum: Approaches to Companion Diagnostic Co-development."

Bayesian Two-stage Biomarker-based Adaptive Design for Targeted Therapy Development

We propose a Bayesian two-stage biomarker-based adaptive randomization (AR) design for the development of targeted agents. The design has three main goals: (1) to test the treatment efficacy, (2) to identify prognostic and predictive markers for the targeted agents, and (3) to provide better treatment for patients enrolled in the trial. To treat patients better, both stages are guided by the Bayesian AR based on the individual patient's biomarker profiles. The AR in the first stage is based on a known marker. A Go/No-Go decision can be made in the first stage by testing the overall treatment effects. If a Go decision is made at the end of the first stage, a two-step Bayesian lasso strategy will be implemented to select additional prognostic or predictive biomarkers to refine the AR in the second stage. We use simulations to demonstrate the good operating characteristics of the design, including the control of per-comparison type I and type II errors, high probability in selecting important markers, and treating more patients with more effective treatments. Bayesian adaptive designs allow for continuous learning. The designs are particularly suitable for the development of multiple targeted agents in the quest of personalized medicine. By estimating treatment effects and identifying relevant biomarkers, the information acquired from the interim data can be used to guide the choice of treatment for each individual patient enrolled in the trial in real time to achieve a better outcome. The design is being implemented in the BATTLE-2 trial in lung cancer at the MD Anderson Cancer Center.

The national biomarker development alliance: confronting the poor productivity of biomarker research and development

Making precision (personalized) medicine a routine clinical reality will require a comprehensive inventory of validated biomarkers and molecular diagnostic tests to stratify disease subtypes and improve accuracy in diagnosis and treatment selection. Realization of this promise has been hindered by the poor productivity of biomarker identification and validation. This situation reflects deficiencies that are pervasive across the entire spectrum of biomarker R&D, from discovery to clinical validation and in the failure of regulatory and reimbursement policies to accommodate new classes of biomarkers. The launch of the National Biomarker Development Alliance is the culmination of a 2-year review and consultation process involving diverse stakeholders to advance standards, best practices and guidelines to enhance biomarker discovery and validation by adoption of systems-based approaches and trans-sector collaboration between academia, clinical medicine and relevant private and public sector stakeholders.

GSTM1 and GSTT1 allele frequencies among various Indian and non-Indian ethnic groups

BACKGROUND

Glutathione-S-transferase (GST) is an important phase II xenobiotic compound metabolizing enzyme family, involved in tolerance to a particular drug or susceptibility to a diseasec. This study focused the GSTM1 and T1 null allele frequency in the Gujarat population with a comparison across other Inter- and Intra-Indian ethnic groups to predict variation in the possible susceptible status.

METHODS

DNA was isolated by a salting out method and GSTM1 and T1 homozygous null genotypes were detected by multiplex polymerase chain reaction in 504 unrelated individuals. The genotype distribution of null alleles was compared with Indian and non Indian ethnics reported earlier in the literature using Fisher's test.

RESULTS

The frequencies of the homozygous null genotypes of GSTM1 and GSTT1 were 20% (95%CI 16.7-23.9) and 35.5% (95%CI 31.4-39.9) respectively. GSTM1 null frequency did not deviate from most other Indian ethnic groups but differed from the majority of those of non Indian ethnicity studied. The frequency of homozygous null type of GSTT1 was significantly higher and deviated from all Indian groups and a few of non Indian ethnicity.

CONCLUSIONS

Gujarat ethnicity, possibly the most susceptible for GSTT1 dependent drug disposition and diseases regarding effects of pollution. Further, the results have implications for GSTT1 dependent drugs used for treatment, a serious problem which needs to be solved by physicians and clinical researchers.

uPA and PAI-1 as biomarkers in breast cancer: validated for clinical use in level-of-evidence-1 studies

Urokinase plasminogen activator (uPA) is an extracellular matrix-degrading protease involved in cancer invasion and metastasis, interacting with plasminogen activator inhibitor-1 (PAI-1), which was originally identified as a blood-derived endogenous fast-acting inhibitor of uPA. At concentrations found in tumor tissue, however, both PAI-1 and uPA promote tumor progression and metastasis. Consistent with the causative role of uPA and PAI-1 in cancer dissemination, several retrospective and prospective studies have shown that elevated levels of uPA and PAI-1 in breast tumor tissue are statistically independent and potent predictors of poor patient outcome, including adverse outcome in the subset of breast cancer patients with lymph node-negative disease. In addition to being prognostic, high levels of uPA and PAI-1 have been shown to predict benefit from adjuvant chemotherapy in patients with early breast cancer. The unique clinical utility of uPA/PAI-1 as prognostic biomarkers in lymph node-negative breast cancer has been confirmed in two independent level-of-evidence-1 studies (that is, in a randomized prospective clinical trial in which the biomarker evaluation was the primary purpose of the trial and in a pooled analysis of individual data from retrospective and prospective studies). Thus, uPA and PAI-1 are among the best validated prognostic biomarkers currently available for lymph node-negative breast cancer, their main utility being the identification of lymph node-negative patients who have HER-2-negative tumors and who can be safely spared the toxicity and costs of adjuvant chemotherapy. Recently, a phase II clinical trial using the low-molecular-weight uPA inhibitor WX-671 reported activity in metastatic breast cancer.

Methodological requirements for valid tissue-based biomarker studies that can be used in clinical practice

Paralleling the growth of ever more cost efficient methods to sequence the whole genome in minute fragments of tissue has been the identification of increasingly numerous molecular abnormalities in cancers--mutations, amplifications, insertions and deletions of genes, and patterns of differential gene expression, i.e., overexpression of growth factors and underexpression of tumor suppressor genes. These abnormalities can be translated into assays to be used in clinical decision making. In general terms, the result of such an assay is subject to a large number of variables regarding the characteristics of the available sample, particularities of the used assay, and the interpretation of the results. This review discusses the effects of these variables on assays of tissue-based biomarkers, classified by macromolecule--DNA, RNA (including micro RNA, messenger RNA, long noncoding RNA, protein, and phosphoprotein). Since the majority of clinically applicable biomarkers are immunohistochemically detectable proteins this review focuses on protein biomarkers. However, the principles outlined are mostly applicable to any other analyte. A variety of preanalytical variables impacts on the results obtained, including analyte stability (which is different for different analytes, i.e., DNA, RNA, or protein), period of warm and of cold ischemia, fixation time, tissue processing, sample storage time, and storage conditions. In addition, assay variables play an important role, including reagent specificity (notably but not uniquely an issue concerning antibodies used in immunohistochemistry), technical components of the assay, quantitation, and assay interpretation. Finally, appropriateness of an assay for clinical application is an important issue. Reference is made to publicly available guidelines to improve on biomarker development in general and requirements for clinical use in particular. Strategic goals are formulated in order to improve on the quality of biomarker reporting, including issues of analyte quality, experimental detail, assay efficiency and precision, and assay appropriateness.

A multiplex two-color real-time PCR method for quality-controlled molecular diagnostic testing of FFPE samples

Background

Reverse transcription quantitative real-time PCR (RT-qPCR) tests support personalized cancer treatment through more clinically meaningful diagnosis. However, samples obtained through standard clinical pathology procedures are formalin-fixed, paraffin-embedded (FFPE) and yield small samples with low integrity RNA containing PCR interfering substances. RT-qPCR tests able to assess FFPE samples with quality control and inter-laboratory reproducibility are needed.

Methods

We developed an RT-qPCR method by which 1) each gene was measured relative to a known number of its respective competitive internal standard molecules to control for interfering substances, 2) two-color fluorometric hydrolysis probes enabled analysis on a real-time platform, 3) external standards controlled for variation in probe fluorescence intensity, and 4) pre-amplification maximized signal from FFPE RNA samples. Reagents were developed for four genes comprised by a previously reported lung cancer diagnostic test (LCDT) then subjected to analytical validation using synthetic native templates as test articles to assess linearity, signal-to-analyte response, lower detection threshold, imprecision and accuracy. Fitness of this method and these reagents for clinical testing was assessed in FFPE normal (N = 10) and malignant (N = 10) lung samples.

Results

Reagents for each of four genes, MYC, E2F1, CDKN1A and ACTB comprised by the LCDT had acceptable linearity (R²>0.99), signal-to-analyte response (slope 1.0±0.05), lower detection threshold (<10 molecules) and imprecision (CV <20%). Poisson analysis confirmed accuracy of internal standard concentrations. Internal standards controlled for experimentally introduced interference, prevented false-negatives and enabled pre-amplification to increase signal without altering measured values. In the fitness for purpose testing of this two-color fluorometric LCDT using surgical FFPE samples, the diagnostic accuracy was 93% which was similar to that previously reported for analysis of fresh samples.

Conclusions

This quality-controlled two-color fluorometric RT-qPCR approach will facilitate the development of reliable, robust RT-qPCR-based molecular diagnostic tests in FFPE clinical samples.

Profiling of phospho-AKT, phospho-mTOR, phospho-MAPK and EGFR in non-small cell lung cancer

Activation of numerous pathways has been documented in non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) has emerged as a common therapeutic target. The mitogen-activated protein kinase (MAPK) and AKT signaling pathways are downstream of EGFR and deregulated via genetic and epigenetic mechanisms in many human cancers. We evaluated selected markers in the EGFR pathway with reference to outcome. Tissues from 220 cases of NSCLC patients presented in a tissue microarray were assayed with immunohistochemistry for phosphorylated AKT, phosphorylated MAPK, phosphorylated mTOR, and EGFR and then quantified by automated image analysis. Individually, the biomarkers did not predict. Combined as ratios, p-mTOR/p-AKT, and p-MAPK/EGFR function as prognostic markers of survival (p=0.008 and p=0.029, respectively), however, no significance was found after adjustment (p=0.221, p=0.103). The sum of these ratios demonstrates a stronger correlation with survival (p<0.001) and remained statistically significant after adjustment (p=0.026). The algebraic combination of biomarkers offer the capacity to understand factors that predict outcome better than current approaches of evaluating biomarkers individually or in pairs. Our results show the sum of p-mTOR/p-AKT and p-MAPK/EGFR is a potential predictive marker of survival in NSCLC patients.

Recurrence of early stage colon cancer predicted by expression pattern of circulating microRNAs

Systemic treatment of patients with early-stage cancers attempts to eradicate occult metastatic disease to prevent recurrence and increased morbidity. However, prediction of recurrence from an analysis of the primary tumor is limited because disseminated cancer cells only represent a small subset of the primary lesion. Here we analyze the expression of circulating microRNAs (miRs) in serum obtained pre-surgically from patients with early stage colorectal cancers. Groups of five patients with and without disease recurrence were used to identify an informative panel of circulating miRs using quantitative PCR of genome-wide miR expression as well as a set of published candidate miRs. A panel of six informative miRs (miR-15a, mir-103, miR-148a, miR-320a, miR-451, miR-596) was derived from this analysis and evaluated in a separate validation set of thirty patients. Hierarchical clustering of the expression levels of these six circulating miRs and Kaplan-Meier analysis showed that the risk of disease recurrence of early stage colon cancer can be predicted by this panel of miRs that are measurable in the circulation at the time of diagnosis (P = 0.0026; Hazard Ratio 5.4; 95% CI of 1.9 to 15).

Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration

High-throughput 'omics' technologies that generate molecular profiles for biospecimens have been extensively used in preclinical studies to reveal molecular subtypes and elucidate the biological mechanisms of disease, and in retrospective studies on clinical specimens to develop mathematical models to predict clinical endpoints. Nevertheless, the translation of these technologies into clinical tests that are useful for guiding management decisions for patients has been relatively slow. It can be difficult to determine when the body of evidence for an omics-based test is sufficiently comprehensive and reliable to support claims that it is ready for clinical use, or even that it is ready for definitive evaluation in a clinical trial in which it may be used to direct patient therapy. Reasons for this difficulty include the exploratory and retrospective nature of many of these studies, the complexity of these assays and their application to clinical specimens, and the many potential pitfalls inherent in the development of mathematical predictor models from the very high-dimensional data generated by these omics technologies. Here we present a checklist of criteria to consider when evaluating the body of evidence supporting the clinical use of a predictor to guide patient therapy. Included are issues pertaining to specimen and assay requirements, the soundness of the process for developing predictor models, expectations regarding clinical study design and conduct, and attention to regulatory, ethical, and legal issues. The proposed checklist should serve as a useful guide to investigators preparing proposals for studies involving the use of omics-based tests. The US National Cancer Institute plans to refer to these guidelines for review of proposals for studies involving omics tests, and it is hoped that other sponsors will adopt the checklist as well.

Early diagnosis of complex diseases by molecular biomarkers, network biomarkers, and dynamical network biomarkers

Many studies have been carried out for early diagnosis of complex diseases by finding accurate and robust biomarkers specific to respective diseases. In particular, recent rapid advance of high-throughput technologies provides unprecedented rich information to characterize various disease genotypes and phenotypes in a global and also dynamical manner, which significantly accelerates the study of biomarkers from both theoretical and clinical perspectives. Traditionally, molecular biomarkers that distinguish disease samples from normal samples are widely adopted in clinical practices due to their ease of data measurement. However, many of them suffer from low coverage and high false-positive rates or high false-negative rates, which seriously limit their further clinical applications. To overcome those difficulties, network biomarkers (or module biomarkers) attract much attention and also achieve better performance because a network (or subnetwork) is considered to be a more robust form to characterize diseases than individual molecules. But, both molecular biomarkers and network biomarkers mainly distinguish disease samples from normal samples, and they generally cannot ensure to identify predisease samples due to their static nature, thereby lacking ability to early diagnosis. Based on nonlinear dynamical theory and complex network theory, a new concept of dynamical network biomarkers (DNBs, or a dynamical network of biomarkers) has been developed, which is different from traditional static approaches, and the DNB is able to distinguish a predisease state from normal and disease states by even a small number of samples, and therefore has great potential to achieve "real" early diagnosis of complex diseases. In this paper, we comprehensively review the recent advances and developments on molecular biomarkers, network biomarkers, and DNBs in particular, focusing on the biomarkers for early diagnosis of complex diseases considering a small number of samples and high-throughput data (or big data). Detailed comparisons of various types of biomarkers as well as their applications are also discussed.

Actionable gene expression-based patient stratification for molecular targeted therapy in hepatocellular carcinoma

Background

The effectiveness of molecular targeted agents is modest in hepatocellular carcinoma (HCC). Efficacy of molecular targeted therapies has been better in cancer patients with high expression of actionable molecules defined as cognate target molecules. However, patient stratification based on the actionable molecules dictating the effectiveness of targeted drugs has remained understudied in HCC.

Experimental Design & Results

Paired tumor and non-tumoral tissues derived from a total of 130 HCC patients were studied. Real-time RT-PCR was used to analyze the mRNA expression of actionable molecules in the tissues. mRNA levels of EGFR, VEGFR2, PDGFRβ, FGFR1, and mTOR were up-regulated in tumors compared to non-tumors in 35.4, 42.3, 61.5, 24.6, and 50.0% of patients, respectively. Up-regulation of EGFR was observed at early stage and tended to gradually decrease toward late stages (BCLC stage A: 41.9%; B: 30.8%; C: 17.6%). Frequency of VEGFR2 expression in tumors at stage C was lower than that in the other stages (BCLC stage A: 45.9%; B: 41.0%; C: 29.4%). PDGFRβ and mTOR were observed to be up-regulated in more than 50% of tumors in all the stages whereas FGFR1 was up-regulated in only about 20% of HCC irrespective of stages. A cluster analysis of actionable gene expression revealed that HCC can be categorized into different subtypes that predict the effectiveness of molecular targeted agents and combination therapies in clinical trials. Analysis of in vitro sensitivity to sorafenib demonstrated that HCC cells with up-regulation of PDGFRβ and c-Raf mRNA are more susceptible to sorafenib treatment in a dose and time-dependent manner than cells with low expression of the genes.

Conclusions

mRNA expression analysis of actionable molecules could provide the rationale for new companion diagnostics-based therapeutic strategies in the treatment of HCC.

Characteristics of pharmacogenomics/biomarker-guided clinical trials for regulatory approval of anti-cancer drugs in Japan

Pharmacogenomics (PGx) or biomarker (BM) has the potential to facilitate the development of safer and more effective drugs in terms of their benefit/risk profiles by stratifying population into categories such as responders/non-responders and high-/low-risks to drug-induced serious adverse reactions. In the past decade, practical use of PGx or BM has advanced the field of anti-cancer drug development. To identify the characteristics of the PGx/BM-guided clinical trials for regulatory approval of anti-cancer drugs in Japan, we collected information on design features of 'key trials' in the review reports of anti-cancer drugs that were approved after the implementation of the 'Revised Guideline for the Clinical Evaluation of Anti-cancer drugs' in April 2006. On the basis of the information available on the regulatory review data for the newly approved anti-cancer drugs in Japan, this article aims to explain the limitations and points to consider in the study design of PGx/BM-guided clinical trials.

Regulatory perspective on remaining challenges for utilization of pharmacogenomics-guided drug developments

Pharmacogenomics-guided drug development has been implemented in practice in the last decade, resulting in increased labeling of drugs with pharmacogenomic information. However, there are still many challenges remaining in utilizing this process. Here, we describe such remaining challenges from the regulatory perspective, specifically focusing on sample collection, biomarker qualification, ethnic factors, codevelopment of companion diagnostics and means to provide drugs for off-target patients. To improve the situation, it is important to strengthen international harmonization and collaboration among academia, industries and regulatory agencies, followed by the establishment of an international guideline on this topic. Communication with a regulatory agency from an early stage of drug development is also a key to success.

Biospecimens, biomarkers, and burgeoning data: the imperative for more rigorous research standards

Knowledge of the altered molecular landscapes in disease offers great promise for developing biomarker-based tests to improve diagnosis and optimize treatment. Progress in biomarker research has been frustratingly slow due to the poor clinical trial design and the lack of standards for specimen collection, biomarker analysis, and data reporting. The ability of high throughput genomics, proteomics, and other 'omics' platforms to profile a large number of analytes in a single assay, together with the pending prospect of rapid expansion of whole exome and whole genome sequencing for clinical use, is increasing the technical and logistical complexity of biomarker validation. Harnessing these new technologies and improved productivity in biomarker validation will depend on adopting systems-based approaches and require major changes in the organization and funding strategies for biomarker research. A systems approach will require new multi-institution collaborations, the integration of diverse technical and clinical activities, greater engagement of industry, and education of regulators, clinicians, and payers about how to use biomarkers for improved patient management and clinical outcomes.

Bridging the gap: moving predictive and prognostic assays from research to clinical use

The development of clinically useful molecular diagnostics requires validation of clinical assay performance and achievement of clinical qualification in clinical trials. As discussed elsewhere in this Focus section on molecular diagnostics, validation of assay performance must be rigorous, especially when the assay will be used to guide treatment decisions. Here we review some of the problems associated with assay development, especially for academic investigators. These include lack of expertise and resources for analytical validation, lack of experience in designing projects for a specific clinical use, lack of specimens from appropriate patient groups, and lack of access to Clinical Laboratory Improvement Amendments-certified laboratories. In addition, financial support for assay validation has lagged behind financial support for marker discovery or drug development, even though the molecular diagnostic may be considered necessary for the successful use of the companion therapeutic. The National Cancer Institute supports a large number of clinical trials and a significant effort in drug development. In order to address some of these barriers for predictive and prognostic assays that will be used in clinical trials to select patients for a particular treatment, stratify patients into molecularly defined subgroups, or choose between treatments for molecularly defined tumors, the National Cancer Institute has begun a pilot program designed to lessen barriers to the development of validated prognostic and predictive assays.

Development and use of integral assays in clinical trials

Clinical trials that include integral biomarkers to determine eligibility, assign treatment, or assess outcome must employ robust assays to measure the molecular analyte of interest. The decision to develop a biomarker assay into a test suitable for use in humans should be driven by clinical need, that is, there should be a clear clinical purpose for undertaking the test development. Supporting in vitro or in vivo research on the ability of the marker to distinguish subgroups of patients with a given characteristic is necessary. The magnitude of the difference in treatment effect expected with use of the marker should be sufficient to support differential treatment prescription for marker-positive and -negative patients. Analytical and clinical validation of the marker assay should be completed before the clinical trial is initiated to ensure that the assay is stable enough for clinical use throughout the trial. Clinical use of the assay requires that it be performed in a Clinical Laboratory Improvement Amendments-accredited laboratory, and the need to apply for an Investigational Device Exemption from the U.S. Food and Drug Administration should be considered. In this article we elaborate on the steps required to get a biomarker assay ready for use as an integral component of a clinical trial and give an example of the use of an integral assay in a phase III trial.

Lessons learned from the investigational device exemption review of Children's Oncology Group trial AAML1031

The U.S. Food and Drug Administration is now exerting its regulatory authority over the use of molecular diagnostics and related assays for medical decision making in clinical trials, by performing pre-Investigational Device Exemption reviews in all phases of clinical trials. In this review, we assess the analytical performance of the assay for the diagnostic, and consider how that performance affects the diagnostic and the patient and their risks and benefits from treatment. We also discuss the process involved in the first review of a new Children's Oncology Group phase III trial in acute myelogenous leukemia. The lessons learned and recommendations for how to prepare for and incorporate this new level of regulatory review into the protocol development process are presented.

Impact of preanalytic factors on the design and application of integral biomarkers for directing patient therapy

Molecular assays have been routinely applied to improve diagnosis for the last 25 years. Assays that guide therapy have a similar history; however, their evolution has lacked the focus on analytic integrity that is required for the molecularly targeted therapies of today. New molecularly targeted agents require assays of greater precision/quantitation to predict the likelihood of response, i.e., to identify patients whose tumors will respond, while at the same time excluding and protecting those patients whose tumors will not respond or in whom treatment will cause unacceptable toxicity. The handling of tissue has followed a fit-for-purpose approach focused on appropriateness for diagnostic needs, which is less rigorous than the demands of new molecular assays that interrogate DNA, RNA, and proteins in a quantitative, multiplex manner. There is a new appreciation of the importance and fragility of tissue specimens as the source of analytes to direct therapy. By applying a total test paradigm and defining and measuring sources of variability in specimens, we can develop a set of specifications that can be incorporated into the clinical-care environment to ensure that a specimen is appropriate for analysis and will return a true result.