If your employer is interested in identifying new biomarkers for oncology and immunology therapies, you should be investigating HLA-typing of new and legacy data. There is considerable insight to be gained from these exciting new research opportunities.

Human Leukocyte Antigen (HLA) typing has long been a standard tool for tissue matching in transplant medicine, however the HLA region also has significant applications for oncology biomarkers, disease association and pharmacogenomics. And with the recent advent of next-generation sequencing technology and advances in statistical phasing, there are now multiple, cost-effective options to HLA-type individuals in addition to the current “gold standard” technology of “Sequence-Based Typing”, or SBT.

Some of these innovations are also enabling researchers to identify previously unknown biomarkers in legacy databases, which can be validated with orthogonal assays and ultimately applied to clinical trials. The utility of highly predictive biomarkers, including biomarkers from the HLA region, can better inform which patients will benefit from a drug, the dosage needed for benefit, and which will have serious adverse effects (SAEs). Validated, predictive biomarkers can thus increase the likelihood for clinical trial success through careful patient selection and dosage based on these parameters.

A window of opportunity

New wet-lab and software technologies offer both a cost-effective and innovative research opportunity that should drive a wave of biopharmaceutical companies interested in developing new oncology and immunology treatments.

There’s just one problem: The perception by many industry scientists is that these new HLA-typing techniques demand a multidisciplinary background, and thus are wary of jumping into HLA-based research projects.

They aren’t wrong. HLA-typing for oncology and immunology applications requires a unique combination of expertise in genomics, immunology, proteomics, and oncology. Only a handful of individuals in the world possess expertise in all four disciplines, but that shouldn’t be a barrier to progress in this research. It simply calls for a business model in which experts from each of these fields come together to collaborate with the goal of jointly achieving disruptions in the field.

And now is the time to do it.

Statistical phasing techniques breathe new life into massive legacy databases by allowing them to be HLA-typed through the use of new, publicly available and validated applications. Additionally, low-cost HLA typing tools offered by new commercial ventures enable sequencing of multiple HLA genes from many samples in a single, next-generation-sequencing (NGS) run. Currently, few organizations pursue anything other than the gold standard of SBT to perform HLA-typing, which means there is a valuable window of opportunity for companies to gain a competitive advantage in the field.

But to do so requires breaking down scientific siloes and creating new collaborations that bring together experts in genomics, immunology, proteomics, and oncology in order to jointly pursue these opportunities. Organizations following this path will be the benefactors of improved understanding in biomarkers for immuno-oncology, better immuno-therapies, and new cures.

Topics in this blog post: Biopharma, Biologics, Data and Technology, Oncology, R&D