Personalizing the approach to precision oncology

Researchers from Memorial Sloan Kettering Cancer Center believe that imaging biomarkers will play an increasingly large role in oncology through the philosophy of precision medicine, especially in the case of heterogeneous tumors.

Data derived from imaging may enable clinicians to distinguish between benign and cancerous tissue and predict treatment response, but certain challenges must be addressed first, according to Evis Sala, MD, PhD, et al.

Heterogeneity in tumors arises through their unorthodox growth—the same growth that makes them dangerous. This diverse growth can pose challenges for treatment including drug resistance and obfuscating diagnoses.

Previous studies have shown that a pixel-by-pixel texture analysis distinguished between benign and malignant breast lesions with a high level of accuracy. Termed the gray level co-occurrence matrix, analyses like this one have the potential to expedite diagnosis and begin treatment sooner.

A dynamic-contrast-enhanced MRI can even grade the aggressiveness of prostate tumors by providing a Gleason score, a scale measuring how strongly the cancerous cells resemble typical prostate tissue. A PET scan can identify ideal biopsy sites and guide the procedure, using quantitative analysis of tumor features.

However, the biggest impact of biomarkers on heterogeneous tumors is in the evaluation of treatment response.

Specific imaging phenotypes of liver cancer have been used to predict response to chemotherapy, weighing biomarker data such as shape or texture. Finding high cell density in brain or spinal cancer can flag those cells as resistant to therapy, because of the poor environmental conditions the cells are accustomed to (low oxygen and nutrient deprivation).

Translating these advances to clinical care will take some time, despite the large amount of research underway. Many imaging measures have limited prognostic value because of reproducibility issues and small study populations—not to mention the baseline difficulty in treating heterogeneous tumors.

The National Cancer Institute is addressing many of these challenges through the Quantitative Imaging Network, which promotes the development and standardization of imaging methods, protocols and software tools.

Still, a group undertaking is necessary if quantitative biomarkers are the become fully realized, according to Sala et al.

“Complementary innovations in massive parallel sequencing, proteomics and imaging that allow spatial and temporal quantification of tumor heterogeneity and its changes during drug treatment will provide the basis for the realization of precision oncology,” the authors wrote.