Role of Biomarkers in Clinical Development of Cancer Therapies


The rapid expansion of our knowledge about cancer genome and biology has provided hypothesis for an increasing number of potential therapeutic targets. Technical advancement in medicinal chemistry and biotechnology has also significantly enhanced the drug design for optimal potency and specificity against the intended targets. Successful development of molecularly targeted agents (MTA), however, must overcome the challenges posed by the very nature of cancer: the pathway complexity within tumors, the heterogeneity between individual patients and the exploitation by cancer cells of the essential survival mechanism of normal tissue.

Given the high attrition rate of late-stage clinical trials with MTAs, there is a great need to enhance the robustness of early clinical trials to address the objectives key to future directions: credentialing the agent, optimizingthe dose and schedule, obtaining preliminary proof of concept for the target, and identifying patient selection markers for further studies. For most MTAs, incorporation of biomarkers to characterize the tumors and the drug effect on molecular levels is not only desirable but also indispensible for successful transition from target discovery to target validation and clinical benefit.

In response to the need for improving the efficiency of drug development, FDA's critical pathway initiative was launched in 2004, with the primary objective to foster collaboration between academic and industry partners as well as regulatory authorities, in order to integrate preclinical scientific process with all stages of clinical trials. Key areas identified as high priority include better development and utilization of biomarker of safety and efficacy.

This chapter will provide definitions of key biomarkers used in drug development, the potential utility of the biomarkers in different stages of clinical trials and the current challenges and future directions.

A Few Definitions and General Concepts

Proper use of biomarkers should start with a clear understanding of the nature and the intended use of various markers in clinical trials and treatment decisions. Biomarkers are commonly defined as "...a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention." 1 Definitions of various biomarkers and the terminology for steps in clinical and analytical validations have been reviewed in several guideline reports.2,3 The main concepts for markers commonly used in clinical trials for cancer drugs are defined below.

Based on the purposes in clinical studies, biomarkers can be categorized in a few types:

• Pharmacodynamics markers (PD Markers'): Changes in molecular measurements due to the drug effect (e.g.,

A Few Definitions and General Concepts 77

downregulation of PAPR activity after administration of PARP inhibitors)

  • Predictive markers: characteristics associated with response to a therapy (e.g., HER2 amplification as measured by FISH is predictive of activity with trastuzumab)
  • Prognostic markers: characteristics associated with the inherent nature of the cancers and outcome, independent of therapy (e.g., the multi-gene OncoType Dx scores predicts survival outcome in patients with ER/PR positive breast cancer)
  • Surrogate markers: measurements that can be used as an substitute of a clinically relevant endpoint

Biomarkers can be measured on tissue and blood specimens or imaging modalities. A few examples are included in Table 3.1. In general, these markers can be derived from the tumor or normal tissue/cells, assayed on single- or multi-analyte platforms, and based on DNA, RNA, protein, or microRNA measurements.

For biomarkers to be used for their intended purposes in clinical trials or clinical care, itisimportantto recognize thelevelsofanalytical and clinical qualifications, in order to avoid misinterpretation or misuse of the data. In the REMARK report,4 the author noted that there had been numerous publications on many "predictive” markers, but very few were confirmed to be clinically useful. Issues identified included lack of assay validation, inappropriate statistical designs and inadequate or improper specimen collections. For both the developer and user of biomarkers, a common language with respect to the status of marker development and validation is critical. Validation of a biomarker requires two major steps:

  • Assay validation: process that ensure that the assay characteristics (e.g., precision, linearity and reproducibility) is sufficient for the marker to be measured in the intended context (e.g., on frozen tissue obtained from biopsies) and for the proposed purpose (e.g., to detect more than 50% target protein reduction)
  • Biomarker qualification: establishment of the correlation between a biomarker and the clinical or biological significance (e.g., KRAS mutation in colon cancer is associated with resistance to anti-EGFR monoclonal antibody therapy).


Table 3.1 Biomarker classifications by assay categories



Assay platform


Tumor tissue

Genetic alteration

• Mutation

PCR based single or multi-gene platform;

Whole genome sequencing;

Whole exome sequencing

• EGFR mutation;


• Gene copy loss or gain



• Translocation




• Gene expression profile


In situ hybridization

• OncoType Dx


• In situ analysis



• Lysate

Proteomics ELISA


• Proliferation


• Metabolism (glycolysis)


• Drug distribution

14C-, 128In- or other tracer-labeled drug entity




• Numbers and markers




  • • ELISA
  • • Proteomics


  • • Germline DNA polymorphism
  • • Germline mutation

Genome wide or specific gene based

• UGR1A1

Role of Biomarkers in Clinical Development of Cancer Therapies

Role of Biomarkers in the Different Stages of Drug Development 79

Depending on the goals of biomarker evaluations in clinic or drug development, the required levels of assay validation and marker qualification may differ but they should all "fit for purpose". Degree of validation should also be considered in interpreting the outcomes of biomarker analysis.

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