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Drug selection through the use of cell-based functional profiling
A study was presented at the symposium about progress in drug selection through the use of cell-based functional profiling. It delt with the so-called "triple negative" breast cancer (TNBC), which is estrogen receptor negative (ER-), progesterone receptor negative (RP-), and Her2 negative (H2-).
When breast cancer presents as locally advanced disease, it is customarily treated with neoadjuvant (preoperative) chemotherapy, followed by definitive surgery. At the time of surgery, the specimen is assessed to determine if all visible tumor has been destroyed by chemotherapy. When this happens, it is said to be a “pathological complete response” (pCR).
Data shows that obtaining a pCR is everything. Get a pCR, and the survival is excellent. Don’t get a pCR and the survival, especially for TNBC patients, is very poor. How can the pCR rate be improved in TNBC?
The speaker went through all the database of breast cancer cell culture assays (using cell death endpoints) and tried to see if there were any drugs which appeared to be uniquely active in TNBC vs non-TNBC.
There were no major differences between the activity of most drugs in TNBC vs non-TNBC, with one glaring exception: cisplatin, which was dramatically more active in TNBC than in non-TNBC.
The speaker went on to present a lot of data further dissecting which specific markers were most associated with TNBC sensitivity to cisplatin. The data will shortly appear on the ASCO website. When they post slide presentations from the 2009 Breast Cancer Symposium, I'll post it here.
But, essentially, the major markers for platinum sensitivity in breast cancer were estrogen receptor negativity and very poorly differentiated tumors. The minor markers for platinum sensitivity in breast cancer were Her2 negativity and progesterone receptor negativity.
The data compared TNBC to other types of tumors. It’s known that renal cell carcinomas are very resistant to cisplatin (less than 10% response rate), and that is reflected by the cell culture (cell death endpoint) data. It’s known that previously-untreated, poorly differentiated ovarian cancers tend to be very sensitive to cisplatin (70% response rate), and that’s also reflected by the cell culture data. When ovarian cancer patients relapse soon (0 to 6 months) after discontinuation of chemotherapy, they have only a 25% response rate to re-treatment with platinum. When ovarian cancer patients relapse greater than 6 months following discontinuation of chemotherapy, they have a 50% response rate to re-treatment with platinum. These clinical findings are also nicely recapitulated by the cell culture assay data.
Now, breast cancers which are either estrogen receptor positive and/or more than very poortly differentiated (Bloom Richardson score of 4 to eight) tend to be even more resistant to cisplatin than are previously treated ovarian cancer which relapse soon (0 to 6 months) after discontinuation of chemotherapy. In contrast, Triple Negative Breast Cancers tend to be as sensitive or more sensitive (especially when also Bloom Richardson 9/9) to cisplatin than are previously-untreated, poorly-differentiated ovarian cancers.
The data clearly showed the utility of cell culture assays in “targeting” chemotherapy to patient sub-groups who are most likely to benefit from treatment with given individual drugs. It is hard to see how molecular profiling tests could have produced similar insights.
Genomics is far too limited in scope to encompass the vagaries and complexities of human cancer biology when it comes to drug selection. Efforts to administer targeted therapies in randomly selected patients often result in low response rates at significant toxicity and cost.
While researchers continue to develop molecular probes to select candidates, the cell culture analysis platform serves as a functional profile capable of examining the nuances of cellular response to drugs. To exploit the full potential of targeted anticancer therapies, physicians will need laboratory tests that match patients to specific drugs.
Cell culture assays are able to accurately predict how an individual patient's cancer cells will respond to an array of drug combinations. It is able to quantify synergistic drug combinations and individually tailor treatment.
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