Biomarkers in oncology drug development

Assessing clinical response in early oncology development with a predictive biomarker

In early oncology clinical trials there is often limited data for biomarkers and their association with response to treatment. Thus, it is challenging to decide whether a biomarker should be used for patient selection and enrollment. Most evidence about any potential predictive biomarker comes from preclinical research and, sometimes, clinical observations. How to translate the preclinical predictive biomarker data to clinical study remains an active field of research. Here, we propose a method to incorporate existing knowledge about a predictive biomarker - its prevalence, association with response and the performance of the assay used to measure the biomarker - to estimate the response rate in a clinical study designed with or without using the predictive biomarker. Importantly, we quantify the uncertainty associated with the biomarker and its predictability in a probabilistic model. This model estimates the distribution of the clinical response when a predictive biomarker is used to select patients and compares it to unselected cohort. We applied this method to two real world cases of approved biomarker-guided therapies to demonstrate its utility and potential value. This approach helps to make a data-driven decision whether to select patients with a predictive biomarker in early oncology clinical development.

A Sol-gel Integrated Dual-readout Microarray Platform for Quantification and Identification of Prostate-specific Antigen

Here, we report a sol-gel integrated affinity microarray for on-chip matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) that enables capture and identification of prostate?specific antigen (PSA) in samples. An anti-PSA antibody (H117) was mixed with a sol?gel, and the mixture was spotted onto a porous silicon (pSi) surface without additional surface modifications. The antibody easily penetrates the sol-gel macropore fluidic network structure, making possible high affinities. To assess the capture affinity of the platform, we performed a direct assay using fluorescein isothiocyanate-labeled PSA. Pure PSA was subjected to on-chip MALDI-TOF-MS analysis, yielding three clear mass peptide peaks (m/z = 1272, 1407, and 1872). The sol-gel microarray platform enables dual readout of PSA both fluorometric and MALDI-TOF MS analysis in biological samples. Here we report a useful method for a means for discovery of biomarkers in complex body fluids.

Clinically Viable Gene Expression Assays with Potential for Predicting Benefit from MEK Inhibitors

Purpose: To develop a clinically viable gene expression assay to measure RAS/RAF/MEK/ERK (RAS-ERK) pathway output suitable for hypothesis testing in non-small cell lung cancer (NSCLC) clinical studies.Experimental Design: A published MEK functional activation signature (MEK signature) that measures RAS-ERK functional output was optimized for NSCLC in silico NanoString assays were developed for the NSCLC optimized MEK signature and the 147-gene RAS signature. First, platform transfer from Affymetrix to NanoString, and signature modulation following treatment with KRAS siRNA and MEK inhibitor, were investigated in cell lines. Second, the association of the signatures with KRAS mutation status, dynamic range, technical reproducibility, and spatial and temporal variation was investigated in NSCLC formalin-fixed paraffin-embedded tissue (FFPET) samples.Results: We observed a strong cross-platform correlation and modulation of signatures in vitro Technical and biological replicates showed consistent signature scores that were robust to variation in input total RNA; conservation of scores between primary and metastatic tumor was statistically significant. There were statistically significant associations between high MEK (P = 0.028) and RAS (P = 0.003) signature scores and KRAS mutation in 50 NSCLC samples. The signatures identify overlapping but distinct candidate patient populations from each other and from KRAS mutation testing.Conclusions: We developed a technically and biologically robust NanoString gene expression assay of MEK pathway output, compatible with the quantities of FFPET routinely available. The gene signatures identified a different patient population for MEK inhibitor treatment compared with KRAS mutation testing. The predictive power of the MEK signature should be studied further in clinical trials. Clin Cancer Res; 23(6); 1471-80. ©2016 AACRSee related commentary by Xue and Lito, p. 1365.

Use of biomarkers in ALS drug development and clinical trials

The past decade has seen a dramatic increase in the discovery of candidate biomarkers for ALS. These biomarkers typically can either differentiate ALS from control subjects or predict disease course (slow versus fast progression). At the same time, late-stage clinical trials for ALS have failed to generate improved drug treatments for ALS patients. Incorporation of biomarkers into the ALS drug development pipeline and the use of biologic and/or imaging biomarkers in early- and late-stage ALS clinical trials have been absent and only recently pursued in early-phase clinical trials. Further clinical research studies are needed to validate biomarkers for disease progression and develop biomarkers that can help determine that a drug has reached its target within the central nervous system. In this review we summarize recent progress in biomarkers across ALS model systems and patient population, and highlight continued research directions for biomarkers that stratify the patient population to enrich for patients that may best respond to a drug candidate, monitor disease progression and track drug responses in clinical trials. It is crucial that we further develop and validate ALS biomarkers and incorporate these biomarkers into the ALS drug development process. This article is part of a Special Issue entitled ALS complex pathogenesis.

Tumoral TP53 and/or CDKN2A alterations are not reliable prognostic biomarkers in patients with localized Ewing sarcoma: a report from the Children's Oncology Group

BACKGROUND

A growing collection of retrospective studies have suggested that TP53 mutations and/or CDKN2A deletions have prognostic significance in Ewing sarcoma. We sought to evaluate these variables in patients with localized disease treated prospectively on a single Children's Oncology Group protocol.

PROCEDURE

Of the 568 patients enrolled on Children's Oncology Group protocol AEWS0031 (NCT00006734), 112 had tumor specimens of sufficient quality and quantity to allow for analysis of TP53 mutations status by DNA sequencing, and CDKN2A deletion by dual color fluorescent in situ hybridization.

RESULTS

Eight of 93 cases (8.6%) were found to have TP53 point mutations and 12 of 107 cases (11.2%) demonstrated homozygous CDKN2A deletion. Two cases were found to have an alteration in both genes. There was no significant difference in event-free survival of patients with TP53 mutations and/or CDKN2A deletions compared to patients with normal TP53/CDKN2A gene status, as demonstrated by log rank test (p = 0.58).

CONCLUSIONS

Although previous retrospective studies suggest their significance, TP53 mutation and/or CDKN2A deletion are not reliable prognostic biomarkers in localized Ewing sarcoma.

A matrix approach to guide IHC-based tissue biomarker development in oncology drug discovery

Immunohistochemistry (IHC) is a core platform for the analysis of tissue samples, and there is an increasing demand for reliable and quantitative IHC-based tissue biomarkers in oncology clinical research and development (R&D) environments. Biomarker assay and drug development proceed in parallel. Furthermore, biomarker assay requirements change with each phase of drug development. We have therefore developed a matrix tool to enable researchers to evaluate whether a particular IHC biomarker assay is fit for purpose. Experience gained from the development of 130 IHC biomarkers, supporting a large number of oncology drug projects, was used to formulate a practical approach to IHC assay development. The resultant matrix grid and accompanying work flow incorporates 16 core decision points that link antibody and assay specificity and sensitivity, and assay performance in preclinical and clinical samples, with stages of drug development. The matrix provides a means to ensure that relevant information on an IHC assay in development is recorded and communicated consistently and that minimum assay validation requirements are met.

Human biological sample biobanking to support tissue biomarkers in pharmaceutical research and development

Advances in the understanding of molecular pathology and thereby the mechanisms that could be amenable to therapeutic manipulation are the reason that pharmaceutical research and development is focused increasingly on measurement of molecular biomarkers in human biological samples. Obtaining direct or indirect access to sufficient samples that are fit for research purposes can be a major challenge. A biobanking infrastructure has a significant role in the acquisition, storage and usage of human biological samples and here we review some key requirements for establishing a biobank. These include ensuring; that appropriate governance mechanisms are in place, that samples available are appropriate and fit for the intended research purposes that the infrastructure is sustainable in the future and that use of the biobank assets meets the strategic aims of the host organisation. Finally we present a case study--the STRATUM project which has recently completed and through a collaborative approach involving six industry and public partners drawing on a network of experts, examined biobank policies, public attitudes to biobanking, donor consent, sample and data standards, technical requirements for a register and biobanking financial models, albeit from a UK perspective.

Biomarkers in Ewing Sarcoma: The Promise and Challenge of Personalized Medicine. A Report from the Children's Oncology Group

A goal of the COG Ewing Sarcoma (ES) Biology Committee is enabling identification of reliable biomarkers that can predict treatment response and outcome through the use of prospectively collected tissues and correlative studies in concert with COG therapeutic studies. In this report, we aim to provide a concise review of the most well-characterized prognostic biomarkers in ES, and to provide recommendations concerning design and implementation of future biomarker studies. Of particular interest and potentially high clinical relevance are studies of cell-cycle proteins, sub-clinical disease, and copy number alterations. We discuss findings of particular interest from recent biomarker studies and examine factors important to the success of identifying and validating clinically relevant biomarkers in ES. A number of promising biomarkers have demonstrated prognostic significance in numerous retrospective studies and now need to be validated prospectively in larger cohorts of equivalently treated patients. The eventual goal of refining the discovery and use of clinically relevant biomarkers is the development of patient specific ES therapeutic modalities.

Prognostic and predictive roles for circulating biomarkers in gastrointestinal cancer

Circulating tumor cells (CTCs) and circulating free DNA (cfDNA) have been studied as promising prognostic and predictive tumor-derived biomarkers in the bloodstream of patients with gastrointestinal malignancies because they may be an alternative noninvasive tool to tumor tissue biopsies. Quantification and molecular characterization of CTCs and cfDNA may provide additional insights into cancer biology, potentially revealing novel targets to individualize cancer care. The present article aims to review the biology and current methods to assess CTCs and cfDNA, and the efforts to establish both tumor-derived biomarkers as prognostic and predictive factors in esophageal, gastric and colorectal cancer.

Practical perspectives of personalized healthcare in oncology

There is an increasing prevalence of drug-diagnostic combinations in oncology. This has placed diagnostic stakeholders directly into the complex benefit-risk, cost, value and uncertainty-driven development paradigm traditionally the preserve of the drug development community. In this review we focus on the delivery of the clinical data required to advance such drug-diagnostic combination development programmes and ultimately satisfy regulators and payors of the value of contemporaneous changes in diagnostic and treatment practice. Ideally all stakeholders would like to initially estimate, and ultimately specify, the comparative benefit-risk for a new treatment option with and without changing diagnostic practice. Hence, in an ideal world clinical trial design is focused on acquiring biomarker treatment interaction data. In this review we describe the key scientific and feasibility inputs required to design and deliver such trials and the drivers, advantages and disadvantages associated with departing from this model. We do not discuss the discovery of new biomarkers nor the analytical validation and marketing of diagnostic products. Following on from trial design we describe how subsequent success then depends upon the concepts that guide trial design being driven into the complex world of large, multinational clinical trial delivery. For every aspect of a traditional clinical drug trial such as supply, recruitment and adherence, there is a corresponding concept for the diagnostic element. In practice, this means that each patient's contribution to the decision making data-set is subject to double jeopardy (attrition on clinical outcome and biomarker status). Historically, this has led to significantly reduced power for detecting biomarker-treatment interactions, reduced decision making confidence and a waste of valuable human and financial resources. We describe recent practice changes and experience that have led to the successful delivery of such trials focusing on both pre- and on trial aspects. The former includes the pivotal role of tissue banks in accurate estimation of evaluability and prevalence for biomarker assays and the latter several practices designed to engage and incentivize key stakeholders particularly CRAs and pathologists. The result is that in the new world of developing personalized treatments for cancer patients the real-time acquisition and monitoring of biomarker data receives similar support to that traditionally reserved for clinical outcome data and far more patients contribute to the testing of personalized medicine hypotheses.

Reverse phase protein microarrays advance to use in clinical trials

Individualizing cancer therapy for molecular targeted inhibitors requires a new class of molecular profiling technology that can map the functional state of the cancer cell signal pathways containing the drug targets. Reverse phase protein microarrays (RPMA) are a technology platform designed for quantitative, multiplexed analysis of specific phosphorylated, cleaved, or total (phosphorylated and non-phosphorylated) forms of cellular proteins from a limited amount of sample. This class of microarray can be used to interrogate tissue samples, cells, serum, or body fluids. RPMA were previously a research tool; now this technology has graduated to use in research clinical trials with clinical grade sensitivity and precision. In this review we describe the application of RPMA for multiplexed signal pathway analysis in therapeutic monitoring, biomarker discovery, and evaluation of pharmaceutical targets, and conclude with a summary of the technical aspects of RPMA construction and analysis.

Tissue proteomics of the human mammary gland: towards an abridged definition of the molecular phenotypes underlying epithelial normalcy

Our limited understanding of the biological impact of the whole spectrum of early breast lesions together with a lack of accurate molecular-based risk criteria for the diagnosis and assignment of prognostic significance to biopsy findings presents an important problem in the clinical management of patients harboring precancerous breast lesions. As a result, there is a need to identify biomarkers that can better determine the outcome of early breast lesions by identifying subpopulations of cells in breast premalignant disease that are at high-risk of progression to invasive disease. A first step towards achieving this goal will be to define the molecular phenotypes of the various cell types and precursors - generated by the stem cell hierarchy - that are present in normal and benign conditions of the breast. To date there have been very few systematic proteomic studies aimed at characterizing the phenotypes of the different cell subpopulations present in normal human mammary tissue, partly due to the formidable heterogeneity of mammary tissue, but also due to limitations of the current proteomic technologies. Work in our laboratories has attempted to address in a systematic fashion some of these limitations and here we present our efforts to search for biomarkers using normal fresh tissue from non-neoplastic breast samples. From the data generated by the 2D gel-based proteomic profiling we were able to compile a protein database of normal human breast epithelial tissue that was used to support the biomarker discovery program. We review and present new data on the putative cell-progenitor marker cytokeratin 15 (CK15), and describe a novel marker, dihydropyriminidase-related protein 3 (DRP3) that in combination with CK15 and other well known proteins were used to define molecular phenotypes of normal human breast epithelial cells and their progenitors in resting acini, lactating alveoli, and large collecting ducts of the nipple. Preliminary results are also presented concerning DRP3 positive usual ductal hyperplasias (UDHs) and on single cell layer columnar cells (CCCs). At least two bona fide biomarkers of undifferentiated ERα/PgR negative luminal cells emerged from these studies, CK15 and c-KIT, which in combination with transformation markers may lead to the establishment of a protein signature able to identify breast precancerous at risk of progressing to invasive disease.

Endosialin: from vascular target to biomarker for human sarcomas

Biomarkers have been the focus of investigations to diagnose disease, track response to therapy and predict prognosis. Meanwhile, the identification of new targets for therapeutic intervention is an ongoing quest in the field of oncology. The recognition of endosialin as an antigen that is selectively overexpressed in human tumor tissues offers new strategies for treating cancer. Not only do the tumor vasculature and stromal compartments upregulate endosialin but, importantly, the malignant cells of sarcomas strongly express endosialin as well. A diagnostic assay that measures the intensity of endosialin expression in malignant tissues would assist in selecting patients that could benefit from an antiendosialin therapy. Thus, endosialin holds potential value both as a therapeutic target and as a biomarker for certain human cancers.

Transcriptional pathway signatures predict MEK addiction and response to selumetinib (AZD6244)

Selumetinib (AZD6244, ARRY-142886) is a selective, non-ATP-competitive inhibitor of mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK)-1/2. The range of antitumor activity seen preclinically and in patients highlights the importance of identifying determinants of response to this drug. In large tumor cell panels of diverse lineage, we show that MEK inhibitor response does not have an absolute correlation with mutational or phospho-protein markers of BRAF/MEK, RAS, or phosphoinositide 3-kinase (PI3K) activity. We aimed to enhance predictivity by measuring pathway output through coregulated gene networks displaying differential mRNA expression exclusive to resistant cell subsets and correlated to mutational or dynamic pathway activity. We discovered an 18-gene signature enabling measurement of MEK functional output independent of tumor genotype. Where the MEK pathway is activated but the cells remain resistant to selumetinib, we identified a 13-gene signature that implicates the existence of compensatory signaling from RAS effectors other than PI3K. The ability of these signatures to stratify samples according to functional activation of MEK and/or selumetinib sensitivity was shown in multiple independent melanoma, colon, breast, and lung tumor cell lines and in xenograft models. Furthermore, we were able to measure these signatures in fixed archival melanoma tumor samples using a single RT-qPCR-based test and found intergene correlations and associations with genetic markers of pathway activity to be preserved. These signatures offer useful tools for the study of MEK biology and clinical application of MEK inhibitors, and the novel approaches taken may benefit other targeted therapies.

Molecular characterization of apocrine carcinoma of the breast: validation of an apocrine protein signature in a well-defined cohort

Invasive apocrine carcinomas (IACs), as defined by morphological features, correspond to 0.3-4% of all invasive ductal carcinomas (IDC), and despite the fact that they are histologically distinct from other breast lesions there are currently no standard molecular criteria available for their diagnosis and no unequivocal information as to their prognosis. In an effort to address these concerns we have been using protein expression profiling technologies in combination with mass spectrometry and immunohistochemistry (IHC) to discover specific biomarkers that could allow us to molecularly characterize these lesions as well as to dissect some of the steps in the processes underlying breast apocrine metaplasia and development of precancerous apocrine lesions. Establishing these apocrine-specific markers as best practice for the routine pathology evaluation of breast cancer, however, will require their validation in large cohorts of patients. Towards this goal we have composed a panel of antibodies against components of an apocrine protein signature that includes probes against the apocrine-specific markers 15-prostaglandin dehydrogenase (15-PGDH), and acyl-CoA synthetase medium-chain family member 1 (ACSM1), in addition to a set of categorizing markers that are consistently expressed (AR, CD24) or not expressed (ERα, PgR, Bcl-2, and GATA-3) by apocrine metaplasia in benign breast lesions and apocrine sweat glands. This panel was used to analyze a well-defined cohort consisting of 14 apocrine ductal carcinoma in situ (ADCIS), and 33 IACs diagnosed at the Cancer Institute Hospital, Tokyo between 1997 and 2001. Samples were originally classified on the basis of cellular morphology with all cases having more than 90% of the tumour cells exhibiting cytological features typical of apocrine cells. Using the expression of 15-PGDH and/or ACSM1 as the main criterion, but taking into account the expression of other markers, we were able to identify unambiguously 13 out of 14 ADCIS (92.9%) and 20 out of 33 (60.6%) IAC samples, respectively, as being of apocrine origin. Our results demonstrate that IACs correspond to a distinct, even if heterogeneous, molecular subgroup of breast carcinomas that can be readily identified in an unbiased way using a combination of markers that recapitulate the phenotype of apocrine sweat glands (15-PGDH(+), ACSM1(+), AR(+), CD24(+), ERα(-), PgR(-), Bcl-2(-), and GATA-3(-)). These results pave the way for addressing issues such as prognosis of IACs, patient stratification for targeted therapeutics, as well as research strategies for identifying novel therapeutic targets for developing new cancer therapies.

Biomarkers in oncology drug development

Biomarker measurements have become an essential component of oncology drug development, particularly so in this era of targeted therapies. Such measurements ensure that clinical studies are testing our biological hypotheses and can help make the difficult decisions required to choose which drugs to stop developing or de-prioritise. For those drugs taken forward, biomarker measurements may also help choose the appropriate dose, schedule and patient population. In this review we discuss the intrinsic properties of biological sample based efficacy measurements and how these relate to their implementation in oncology drug development by way of points to consider and examples.