There is a lot to unpack regarding the latest science around immune-oncology and the dizzying pace of breakthrough approvals for checkpoint inhibitors and emerging science addressing personalized medicine. Basically, the outcomes have outpaced our understanding of the biology--but the forum of the World Vaccine Congress certainly softens the learning curve.
Jessica Fletcher, PhD from Genocea, a "vaccine company" shared an informative slide on the correlation of mutation profile to objective response rate (ORR), the proportion of patients with reduction in tumor burden of a predefined amount, to checkpoint blockade therapy. As depicted on the graphic below, mutation mismatch repair deficient (MMR-D) colorectal cancers (CRCs) have a more favorable stage-adjusted prognosis or outcome compared with MMR-proficient tumors (MMR-P). Not to over-simplify, but the more non-self an antigen, the more likely it is to elicit an immune response.
The Cancer Genome Atlas (TCGA) data portal contains harmonized cancer datasets within the National Cancer Institute Data Portal. This is an important resource for data projects within oncology reliant on genomic data. As a big believer in transparency and accessibility, I only share data sources that are either free or have minimal fees for access. I can answer specific questions on how to access this data or perform advanced search queries but what follows here are illustrative examples to highlight the complexity of mutational landscapes.
Somatic variants from 3,281 tumors across 12 tumor types from the TCGA Pan-Cancer analysis highlight "distributions of mutation frequencies, types and contexts across tumor types, and establish their links to tissues of origin, environmental/carcinogen influences, and DNA repair defects". What is important to observe is the sheer volume of mutations accumulated within human cancers with the majority being unique to individual patients. Below it is apparent that only a small percentage of these mutations are mutagenic.
It begs the question regarding broad epidemiological frameworks applied to genetically unique clinical outcomes. Outcome measures and clinical trial endpoint selection are hotly debated as they are inconsistently applied across immune-oncology trials. A convenient chart published in Oncology Endpoints in a Changing Landscape is an informative introduction to surrogate endpoints used in clinical research when overall survival isn't feasible.
There is much to learn, discuss, and discover in the evolution of our understanding of immune-oncology. Join the discussion or read along--stay-tuned...
Epidemiological, genetic and molecular biological studies have collectively provided us with a rich source of data that underpins our current understanding of the aetiology and molecular pathogenesis of cancer. But this perspective focuses on proximate mechanisms, and does not provide an adequate explanation for the prevalence of tumours and cancer in animal species or what seems to be the striking vulnerability of Homo sapiens. The central precept of Darwinian medicine is that vulnerability to cancer, and other major diseases, arises at least in part as a consequence of the 'design' limitations, compromises and trade-offs that characterize evolutionary processes.--Mel Greaves, Darwinian medicine: a case for cancer
What a fantastic time to be in the world of scientific discovery. I have been at the bench, in the halls of academia (as a student and medical writer), worked in industry, employed as a medical education executive, and most recently, I work as a datapreneur. What is that? I like to describe datapreneur as a journalist taking cues only from data.
Discovery in the sciences is dynamic. Regardless of your pedigree or educational attainment, if you aren't in lockstep with advances in your chosen discipline, you are obsolete. There is texture in experience. And insights to gain from tireless scientists hoping to advance if not a cure perhaps a better quality of life during advanced and chronic cancers.
Bonny is a data enthusiast applying curated analysis and visualization to persistent tensions between health policy, economics, and clinical research in oncology.