Biomarkers in oncology drug development: rescuers or troublemakers?

The growing role of precision and personalized medicine for cancer treatment

Cancer is a devastating disease that takes the lives of hundreds of thousands of people every year. Due to disease heterogeneity, standard treatments, such as chemotherapy or radiation, are effective in only a subset of the patient population. Tumors can have different underlying genetic causes and may express different proteins in one patient versus another. This inherent variability of cancer lends itself to the growing field of precision and personalized medicine (PPM). There are many ongoing efforts to acquire PPM data in order to characterize molecular differences between tumors. Some PPM products are already available to link these differences to an effective drug. It is clear that PPM cancer treatments can result in immense patient benefits, and companies and regulatory agencies have begun to recognize this. However, broader changes to the healthcare and insurance systems must be addressed if PPM is to become part of standard cancer care.

Biomarkers and receptor targeted therapies reduce clinical trial risk in non-small-cell lung cancer

INTRODUCTION

This study analyzed the risk of clinical trial failure during non-small-cell lung cancer (NSCLC) drug development between 1998 and January 2012. We also looked for factors that impacted clinical trial risk in NSCLC.

METHODS

NSCLC drug development was investigated using trial disclosures from http://www.clinicaltrials.gov and other publically available resources. Compounds were excluded from the analysis if they had begun phase I clinical testing before 1998, did not use treatment-relevant endpoints, or if they did not have a completed phase I trial in NSCLC. Analysis was conducted in regard to treatment indication, compound classification, and mechanism of action.

RESULTS

Six hundred seventy-six clinical trials that included 199 unique compounds met our inclusion criteria. The likelihood, or cumulative clinical trial success rate, that a new drug would pass all phases of clinical testing and be approved was found to be 11%, which is less than industry aggregate rates. Over half of the biomarkers used in NSCLC have not yet been approved by the Food and Drug Administration in any indication. Biomarker targeted therapies (62%) and receptor targeted therapies (31%) were found to have the highest success rates. The risk-adjusted cost for NSCLC clinical drug development was calculated to be U.S. $1.89 billion.

CONCLUSION

Biomarker use alone in this indication resulted in a sixfold increase in clinical trial success whereas receptor targeted therapies did so by almost threefold. Physicians who enroll patients in NSCLC trials should prioritize their participation in clinical trial programs that use biomarkers and receptor targeted therapies.

Benefit–risk management in the age of personalized healthcare

The ongoing developments in personalized healthcare are opening new possibilities for the optimization of the benefit–risk profiles of drugs based on the stratification of patients. Beyond this straightforward application of pharmacogenomics to the optimization of benefit–risk profiles, other approaches, such as metabolomics and systems pharmacology, may contribute to an improved use of medicines in a personalized healthcare setting. These will, however, require fundamental adaptations or new developments in various areas and by all stakeholders, including the pharmaceutical and diagnostics industries, regulators, physicians and patients. Ultimately, personalized healthcare should enable patients to take personal decisions on treatment options based on their preferred benefit–risk profiles of therapeutics.

Image analysis as an adjunct to manual HER-2 immunohistochemical review: a diagnostic tool to standardize interpretation

Dobson L, Conway C, Hanley A, Johnson A, Costello S, O’Grady A, Connolly Y, Magee H, O’Shea D, Jeffers M & Kay E (2010) Histopathology57, 27–38 Image analysis as an adjunct to manual HER-2 immunohistochemical review: a diagnostic tool to standardize interpretation

The application of biomarkers in clinical trials for motor neuron disease

The interest and research into disease-related biomarkers has greatly accelerated over the last 10 years. The potential clinical benefits for disease-specific biomarkers include a more rapid and accurate disease diagnosis, and potential reduction in size and duration of clinical drug trials, which would speed up drug development. The application of biomarkers into the clinical arena of motor neuron disease should both determine if a drug hits its proposed target and whether the drug alters the course of disease. This article will highlight the progress made in discovering suitable biomarker candidates from a variety of sources, including imaging, neurophysiology and proteomics. For biomarkers to have clinical utility, specific criteria must be satisfied. While there has been tremendous effort to discover biomarkers, very few have been translated to the clinic. The bottlenecks in the biomarker pipeline will be highlighted as well as lessons that can be learned from other disciplines, such as oncology.

Targeted therapies in epithelial ovarian cancer

Molecularly targeted therapy is relatively new to ovarian cancer despite the unquestionable success with these agents in other solid tumours such as breast and colorectal cancer. Advanced ovarian cancer is chemosensitive and patients can survive several years on treatment. However chemotherapy diminishes in efficacy over time whilst toxicities persist. Newer biological agents that target explicit molecular pathways and lack specific chemotherapy toxicities such as myelosuppression offer the advantage of long-term therapy with a manageable toxicity profile enabling patients to enjoy a good quality of life. In this review we appraise the emerging data on novel targeted therapies in ovarian cancer. We discuss the role of these compounds in the front-line treatment of ovarian cancer and in relapsed disease; and describe how the development of predictive clinical, molecular and imaging biomarkers will define the role of biological agents in the treatment of ovarian cancer.

Clinical states model for biomarkers in bladder cancer

Bladder cancer is a significant healthcare problem in the USA, with a high recurrence rate, the need for expensive continuous surveillance and limited treatment options for patients with advanced disease. Research has contributed to an understanding of the molecular pathways involved in the development and progression of bladder cancer, and that understanding has led to the discovery of potentially diagnostic, predictive and prognostic biomarkers. In this review, a clinical states model of bladder cancer is introduced and integrated into a paradigm for biomarker development. Biomarkers are systematically incorporated with predefined end points to aid in clinical management.

Novel opportunities for computational biology and sociology in drug discovery

Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.

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.