New biomarker that can predict patient responses to cancer therapies

Updates coming soon.

Blocking the interaction between Programmed Death Ligand 1 (PD-L1) and its receptor, PD-1, is an effective method of treating many types of cancers. Certain tumors overexpress PD-L1, causing host immune cells that express PD-1 to bind PD-L1 and cease killing the tumor. Inhibition of PD-L1 and PD-1 binding can restore host immunity towards tumor killing, and many new drugs have been developed to target this interaction. Current methods of PD-L1 diagnosis have shown to vary based on the antibody, detection kit brand, antigen retrieval method, and clinically defined methods by the FDA. To refine detection of PD-L1, we have identified a peptide, RK-10, and used it to detect PD-L1 expressing tumors with immunohistochemistry or flow cytometry. Flow cytometry was performed on cell lines and patient tissues using a fluorescent peptide (RK-10-Cy5). Immunohistochemistry using a biotin-modified peptide (RK-10-Biotin) was tested against the FDA-approved SP263 clone on biopsied patient tissues. For this study, we evaluated specificity of RK-10 using IHC in over 200 patient tissues, including NSCLC and Hodgkin's Lymphoma. RK-10 shows staining in the tumor regions of FFPE tissues where the SP263 kit does not. RK-10-Cy5 peptide also demonstrates PD-L1 detection in NSCLC, breast, squamous cell carcinoma, and melanoma.

Caldwell C, Johnson CE, Balaji VN, Balaji GA, Hammer RD, Kannan R. Sci Rep. 2017;7(1):13682.

The essential job of precision medicine is to match the right drugs to the right patients. In cancer, precision medicine has been nearly synonymous with genomics. However, sobering recent studies have generally shown that most patients with cancer who receive genomic testing do not benefit from a genomic precision medicine strategy. Although some call the entire project of precision cancer medicine into question, I suggest instead that the tools employed must be broadened. Instead of relying exclusively on big data measurements of initial conditions, we should also acquire highly actionable functional information by perturbing-for example, with cancer therapies-viable primary tumor cells from patients with cancer.

Letai A. Nat Med. 2017;23(9):1028-1035.

Precision medicine is about matching the right drugs to the right patients. Although this approach is technology agnostic, in cancer there is a tendency to make precision medicine synonymous with genomics. However, genome-based cancer therapeutic matching is limited by incomplete biological understanding of the relationship between phenotype and cancer genotype. This limitation can be addressed by functional testing of live patient tumour cells exposed to potential therapies. Recently, several 'next-generation' functional diagnostic technologies have been reported, including novel methods for tumour manipulation, molecularly precise assays of tumour responses and device-based in situ approaches; these address the limitations of the older generation of chemosensitivity tests. The promise of these new technologies suggests a future diagnostic strategy that integrates functional testing with next-generation sequencing and immunoprofiling to precisely match combination therapies to individual cancer patients.

Friedman AA, Letai A, Fisher DE, Flaherty KT. Nat Rev Cancer. 2015;15(12):747-56.

Dynamic BH3 profiling can predict patient responses to cancer therapies
Dynamic BCL-2 homology domain 3 (BH3) profiling is an example of a newer, more molecularly precise assay that can be used for ex vivo functional screening. Biopsy material from the patient is dispersed (for solid tumours) and briefly (for 16–24 hours) exposed to potential drug treatments. After incubation, cells are permeabilized and exposed to BH3-domain-containing peptides. Mitochondrial outer membrane permeabilization is measured, generating a kinetic trace of mitochondrial polarization (central graph). In this analysis, drug treatments that shift the apoptotic threshold generate a large increase in the difference between the kinetic trace area under the curve (AUC) for a negative control-treated sample and the drug-treated sample. This difference creates the ‘Δ% priming’ metric of apoptotic threshold (lower left graph). By comparing this metric across control and drug-treated samples, one can select drug treatments that preferentially lead to apoptotic priming (lower right graph).

Related Products

Catalog# Product Standard Size Price
025-87 Bid BH3 peptide 1 mg $134
025-89 RK-10 200 µg $187
B-025-89 RK-10 - Biotin Labeled 20 µg $264
FC5-025-89 RK-10 - Cy5 Labeled 1 nmol $369