Last week, the New York Times had a nice piece “A Faster Way to Try Many Drugs on Many Cancers” on basket clinical trials, which matches patients to a therapy based on the genetics of their tumor as opposed to the site of their primary tumor. This type of trial feeds into the current excitement about precision medicine, exemplified by the recent National Institutes of Health Precision Medicine Initiative. Unfortunately, the reality of using genetic mutations to fight cancer is not straightforward.
The following tweet came through my stream during the Miami Breast Cancer Conference last weekend.
Dr. Sledge, a Professor of Oncology at Stanford, was giving a talk called “Tumor Heterogeneity: What it Means for Patient Care and Research”, which is summarized here (video). One of the key takeaways is that each patient with cancer can have different cancerous cells in the main tumor as well as at each metastatic site.
Perhaps that is why a few stories this week that caught my eye about “macroscopic” approaches to improve selectivity (and outcomes) of cancer treatment. Here is a small sampling:
- Could location of a colon cancer be a factor in survival? From researchers at University of Southern California Norris Comprehensive Cancer Center in Los Angeles.
- Does the pattern of immune system cells in a breast cancer biopsy better measure immune response than number of cells? From researchers at the Institute of Cancer Research in London.
- Determining sequence of treatment (surgery vs. chemotherapy) by a score from laparoscopy is highly predictive of optimal tumor resection for ovarian cancer patients, which is significant as residual disease is a strong indicator of overall survival. From researchers at The University of Texas MD Anderson Cancer Center in Houston.
While apparently less glamorous than the genomics that seemed to capture media attention, the NIH’s Precision Medicine Initiative Workshop had sessions on informatics, EHRs and data access (see the white papers and presentations). Of note, the EHR section demonstrated the pitfalls of finding genetic data in the EHRs. Capturing results from surgical descriptions or scans is likely to be similarly challenging. Given the biological complexity of cancer, the macroscopic data should be a prominent part of the development of precision medicine in oncology.
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