From diagnostic tools to clinical trial enrichment and surrogate endpoint markers, biomarkers are important tools that have the potential to reduce the length, cost, and uncertainty of drug development.
A biomarker is defined as an observable characteristic or signature that can be measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions. For example, BRCA1 and BRCA2 gene mutations can determine a patient’s risk of developing breast cancer, or HIV viral load can be related to treatment response. Biomarkers can help to detect diseases for early intervention or help to determine the appropriate treatment and dose for each patient. Moreover, biomarkers are useful tools in drug development that can increase the success rate of clinical trials by predicting which patients are most likely to derive benefit from the treatment or even serve as surrogate endpoints.
Eureka! Potential Biomarkers
Advancements in transcriptomic, genomic, metabolomic, and other “-omic” technologies have facilitated high-throughput screening for the discovery of new biomarker candidates. As a result, many novel biomarkers have emerged in the last few years that may be potentially useful in the diagnosis, prognosis, and prediction of certain diseases.
For example, Multiple Sclerosis (MS) is a complex disease that is currently difficult to diagnose early and screen for. Diagnostic testing for MS is also costly, invasive, and not definitive. Recently, researchers at the University of Sydney used small RNA next generation sequencing to identify a set of serum exosomal micro-RNAs that are differentially expressed in MS patients. Moreover, some of these micro-RNAs can distinguish between relapsing-remitting from progressive disease and therefore constitute potential biomarkers for diagnosis and prediction of disease subtype.
Giving that microbiome studies are in fashion, many studies have shown associations between gut microbiota and efficacy of checkpoint inhibitors for cancer treatment. One such study led by Dr. Zitvogel (France) revealed that non-responders to PD-1 blockade had low levels of the commensal Akkermansia muciniphila, while oral supplementation of these bacteria to antibiotic-treated mice restored the response. These findings demonstrate the utility of microbiome composition as potential biomarkers for patient stratification in clinical trials as well as a potential therapeutic approach.
Single-cell proteomics has also become an attractive approach for biomarker discovery. Recently, a mass cytometry analysis using a panel of 32 antibodies revealed an increased frequency of an effector memory Treg subset and two NK subsets in blood from children with high risk for type 1 diabetes compared to age-matched healthy children. Hence, these immune cell subpopulations could be easily tested in patients as a predictive biomarker before the disease onset.
Next Step: Qualification
As previously mentioned, biomarkers can function as useful tools in drug development. In previous years, regulatory agencies evaluated biomarkers for use in clinical trials on a drug-by-drug basis, but now, through a process termed qualification, biomarkers can be used in different drug development studies without the need of reconfirming their suitability and going through the long approval process. In 2016 biomarker qualification officially rolled out when Health Canada announced the adoption of the Guidance E16 “Biomarkers Related to Drug or Biotechnology Product Development: Context, Structure and Format of Qualification Submissions” from the International Conference on Harmonization of Technical Requirements for the Registration of Pharmaceuticals for Human Use (ICH). On December last year, the Food and Drug Administration (FDA) agency released a Draft Guidance entitled “Biomarker Qualification: Evidentiary Framework”, which provides recommendations on general considerations to address when developing a biomarker for qualification.
How can be benefit from biomarker qualification? Qualified biomarkers can function to greatly accelerate the approval of better therapeutics. For example, the time taken to achieve clinically significant progression free survival data in multiple myeloma patients has increased to over 5 years. Minimal residual disease (MRD) has been brought forward as a surrogate endpoint biomarker for multiple myeloma drug trials because multiple studies have demonstrated that achieving MRD negativity after treatment is a strong predictor of responding to treatment. Qualification of MRD as a biomarker of responsiveness to treatment will allow it to be widely used in clinical trials for multiple myeloma, greatly enhancing the development of novel therapeutics for patients battling this disease.
The Future is Now
We are currently entering the era of precision medicine, which aims to match each patient with the treatment that will work best for them based on their biomarker profile. Heterogeneous diseases such as cancer or autoimmunity may require more complex and multidimensional biomarker panels for accurate predictions. In this case, emerging approaches such as integrative data analysis and multi-omics seem to be very promising.
Dr. Bapat’s group at UofT has been working on a project to validate integrated biomarker panels for prostate cancer. Their latest publication that resulted from this study describes a 3-marker panel consisting of two micro-RNAs and a DNA methylation biomarker from serum and urine samples that is able to accurately predict reclassification in prostate cancer patients on active surveillance.
There are still some analytical and interpretation challenges that must be addressed to enable the widespread adoption of integrative omics in clinical practice; however, there is no doubt that the development of these approaches, as well as the discovery and qualification of new biomarker sets, will bring us closer and closer to the future of precision medicine and personalized therapeutic options.