Multi-Biomarker
Integration
Pilot Study
A canine study was conducted with a cohort of 151 patients consisting of 76 normal controls, 31 lymphomas, and 44 solid tumors using δ(65)Cu, TK1, and CRP.
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Dogs presenting for evaluation for newly diagnosed cancer, and undergoing routine evaluation and staging, had serum collected at the time of evaluation. Any dog with a confirmed diagnosis of cancer was eligible, and included cases were sampled before treatment.
Testing Methods
Isotopic Fractionation
Stable isotopes of copper 63Cu and 65Cu and its ratio δ(65)Cu - were measures by a multicollector-inductively coupled plasma mass spectrometer (MC-ICPMS).
Thymidine Kinase, Type 1
C-Reactive Protein
The TK1 assay is an indirect, modified 2-step, competitive chemiluminesence immunoassay (CLIA) for the quantitative determination of TK1 in canine serum.
The cCRP assay is a canine-specific sandwich enzyme linked immunosorbent assay (ELISA) for the quantitative determination of CRP in canine serum.
Cancer Activity
Multi-Biomarker Integration
Each biomarker independently measures different aspects of cancer. δ(65)Cu measures cellular metabolism, TK1 measures dysregulated proliferation, and cCRP measures inflammation. A challenge every blood biomarker test available is low-grade solid tumor sensitivity; the cancer activity multi-biomarker approach works to solve this problem.
![BoxWhiskers v1.png](https://static.wixstatic.com/media/3923bd_6db29a92128049a785e99b3133aab4e9~mv2.png/v1/fill/w_430,h_450,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/BoxWhiskers%20v1.png)
The integration of δ(65)Cu, TK1, and cCRP helps to separate out different aspects of tumor groups. In this plot, LSA is well separated from solid tumors. TK1 activity in lymphoma is well documented and metabolically shifts from solid tumors.
![solid chart green arrows.jpg](https://static.wixstatic.com/media/3923bd_f182203231074e34b8fe43561580a50e~mv2.jpg/v1/fill/w_467,h_350,al_c,q_80,usm_0.66_1.00_0.01,enc_auto/solid%20chart%20green%20arrows.jpg)
Looking more closely at just solid tumors, certain tumor groups aggregate into relatively distinct zones. Osteosarcoma has a pronounced metabolic shift from sarcomas. Mast cell tumors fall in-between and are generally known for their low proliferated state.
Other tumor groups likewise fall into metabolic/proliferative “zones” reflecting their unique OXPHOS/Glycolysis/Dysregulated Proliferative state.
![Cu.CRP with green arrows . normals.jpg](https://static.wixstatic.com/media/3923bd_c3afdc7c91714f64b95514eb702394cb~mv2.jpg/v1/crop/x_85,y_0,w_3131,h_2469/fill/w_481,h_379,al_c,q_80,usm_0.66_1.00_0.01,enc_auto/Cu_CRP%20with%20green%20arrows%20_%20normals.jpg)
When the inflammatory state is then added via cCRP, normal controls aggregate by their inflammatory and metabolic state. A similar relationship occurs with TK1 regarding dysregulated proliferation.
Using multiple regression, an algorithm was developed to cleanly separate normal controls from solid tumors and lymphomas. With a ROC of 0.922 and ROC 0.927, solid tumor and LSA respectively, there was excellent separation of normal cohort.
Solid Tumor:
Sensitivity: 0.82
Specificity: 0.90
Lymphoma:
Sensitivity: 0.74
Specificity: 0.99
![Picture13.jpg](https://static.wixstatic.com/media/3923bd_f5743f35c8804ca7a9247c0b2caa114f~mv2.jpg/v1/fill/w_388,h_399,al_c,q_80,usm_0.66_1.00_0.01,enc_auto/3923bd_f5743f35c8804ca7a9247c0b2caa114f~mv2.jpg)
![Picture14.jpg](https://static.wixstatic.com/media/3923bd_c5fa2d5675ac49e0badcb855e513a800~mv2.jpg/v1/fill/w_376,h_399,al_c,q_80,usm_0.66_1.00_0.01,enc_auto/3923bd_c5fa2d5675ac49e0badcb855e513a800~mv2.jpg)