Predicting Effectiveness of Drugs by Analyzing Molecular-Based Biomarkers
The genetic material of a tumor can reveal potential opportunites which predict that a treatment is more likely to work. But there are more molecular-based biomarkers that have been associated with treatment outcomes. They can be tested to give the physician the predictive information needed to make a treatment decision. Molecular-based biomarkers in cancer can be alterations in the genetic code, differences in gene expression or changes in protein expression. No single technology can offer all of the necessary answers. Thus using a multiplatform approach based on relevant, clinically proven molecular-based biomarkers which associate well with the treatment, makes the most sense.
After careful consideration we decided to collaborate with Paradigm Diagnostics, Inc. This company offers such analysis and interpretation of data. The service is called PCDx™ (Paradigm Cancer Diagnostic).
The unique feature of PCDx™ is the entire service as a whole. Multiple tumor profiling technologies – including Immunohistochemistry (IHC) and Next-Generation Sequencing (NGS) – are used in order to detect and analyze molecular-based biomarkers. Via PCDx™ the most clinically actionable genomic alterations in cancer including mutations, copy number variations, amplifications, insertions, deletions, fusions, microsatellite instability (MSI), tumor mutation burden (TMB) and protein expression are analyzed. Coupled with an exhaustive review of literature correlating molecular-based biomarkers to drug responses, PCDx™ provides the information oncologists need in order to personalize cancer treatment based on the biology of their patient’s tumor.
The laboratory of Paradigm Diagnostics is CLIA-certified.
The results of PCDx™ are available after 5 business days. This is significantly faster than other comparable biomarker analyses.
With a depth of coverage of >5000x PCDx™ provides an enormous level of accuracy.
PCDx™ can also be performed with a very small amount of patient material.
Clinical relevance of PCDx™: patients who were treated according to PCDx™ results showed an increasement of the progression free survival interval by 43%.
The databases, which are used for PCDx™, are updated continuously. There also is a continuous verification, which genetic data or other molecular-based biomarker data can have a therapeutic relevance for cancer patients. The conducted analyses are constantly extended over time. Currently there are 234 oncogenes, which are analyzed by next-generation sequencing and up to 25 proteins which are analyzed by IHC. The results of the molecular-based biomarker analysis are currently associated with the efficacy of about 95 cancer therapies.
The analyzed molecular-based Biomarkers
A comprehensive list of analyzed molecular-based biomarkers as well as testable associated cancer drugs you can find here:
Possible Prediction of Effectiveness for the following Drugs
The therapeutic alternatives, which can result out of the genes, include about 95 approved drug therapies and drugs, which are available in the context of clinical development. These drugs are chemotherapeutics as well as targeted drugs inlcuding anti-hormone-drugs and immunotherapies.
The drugs which appear on the final report will vary from tumor type to tumor type, and are always changing. Therefore the following lists give only an orientation.
Approved drugs, for which the effectiveness is interpreted:
Abiraterone, Abemaciclib Ado-trastuzumab emtansine, Afatinib, Alectinib, Anastrozole, Atezolizumab, Avelumab, Bevacizumab, Bicalutamide, Binimetinib, Brigatinib, Cabozantinib, Capecitabine, Carboplatin, Carmustine, Ceritinib, Cetuximab, Cisplatin, Crizotinib, Dabrafenib, Dacarbazine, Dacomitinib, Dasatinib, Diethylstilbestrol, Dinutuximab, Docetaxel, Doxorubicin, Durvalumab, Encorafenib, Enzalutamide, Epirubicin, Eribulin, Erlotinib, Everolimus, Exemestane, Fluorouracil, Flutamide, Fulvestrant, Gefitinib, Gemcitabine, Idelalisib, Imatinib, Interleukin-2, Ipilimumab, Irinotecan, Ketoconazole, Lapatinib, Lenvatinib, Letrozole, liposomal-Doxorubicin, Lorlatinib, Medroxyprogesterone, Megestrol, Mitomycin, Neratinib, Nilotinib, Nintedanib, Niraparib, Nivolumab, Olaparib, Olaratumab, Osimertinib, Oxaliplatin, Paclitaxel, Palbociclib, Panitumumab, Pazopanib, Pembrolizumab, Pemetrexed, Pertuzumab, Procarbazine, Regorafenib, Ribociclip, Rucaparib, Sonidegib, Sorafenib, Streptozocin, Sunitinib, Talazoparib, Tamoxifen, Temozolomide, Temsirolimus, Topotecan, Toremifene, Trametinib, Trastuzumab, Vandetanib, Vemurafenib, Vincristine, Vismodegib, Zoledronic acid
Drugs in clinical development, for which the effectiveness is interpreted: