Use of the Total Cancer Care System to Enrich Screening for CD30-Positive Solid Tumors for Patient Enrollment Into a Brentuximab Vedotin Clinical Trial: A Pilot Study to Evaluate Feasibility.
BACKGROUND
One approach to identify patients who meet specific eligibility criteria for target-based clinical trials is to use patient and tumor registries to prescreen patient populations.


OBJECTIVE
Here we demonstrate that the Total Cancer Care (TCC) Protocol, an ongoing, observational study, may provide a solution for rapidly identifying patients with CD30-positive tumors eligible for CD30-targeted therapies such as brentuximab vedotin.


METHODS
The TCC patient gene expression profiling database was retrospectively screened for CD30 gene expression determined using HuRSTA-2a520709 Affymetrix arrays (GPL15048). Banked tumor tissue samples were used to determine CD30 protein expression by semiquantitative immunohistochemistry. Statistical comparisons of Z- and H-scores were performed using R statistical software (The R Foundation), and the predictive value, accuracy, sensitivity, and specificity of CD30 gene expression versus protein expression was estimated.


RESULTS
As of March 2015, 120,887 patients have consented to the institutional review board-approved TCC Protocol. A total of 39,157 fresh frozen tumor specimens have been collected, from which over 14,000 samples have gene expression data available. CD30 RNA was expressed in a number of solid tumors; the highest median CD30 RNA expression was observed in primary tumors from lymph node, soft tissue (many sarcomas), lung, skin, and esophagus (median Z-scores 1.011, 0.399, 0.202, 0.152, and 1.011, respectively). High level CD30 gene expression significantly enriches for CD30-positive protein expression in breast, lung, skin, and ovarian cancer; accuracy ranged from 72% to 79%, sensitivity from 75% to 100%, specificity from 70% to 76%, positive predictive value from 20% to 40%, and negative predictive value from 95% to 100%.


CONCLUSIONS
The TCC gene expression profiling database guided tissue selection that enriched for CD30 protein expression in a number of solid tumor types. Such an approach may improve screening efficiency for enrolling patients into biomarker-based clinical trials.
Takeda Pharmaceuticals International Company, Takeda Data Science Institute, Cambridge, MA, United States.
Bin
http://orcid.org/0000-0002-3419-5665
B
Li
H Lee Moffitt Cancer Center and Research Institute, Biostatistics and Bioinformatics, Tampa, FL, United States.
Steven A
http://orcid.org/0000-0002-9833-2788
SA
Eschrich
H Lee Moffitt Cancer Center and Research Institute, Biostatistics and Bioinformatics, Tampa, FL, United States.
Anders
http://orcid.org/0000-0002-0393-3530
A
Berglund
M2Gen, Administration, Tampa, FL, United States.
Melissa
http://orcid.org/0000-0002-6449-3364
M
Mitchell
MedImmune, LLC, Research Bioinformatics, Gaithersburg, MD, United States.
David
http://orcid.org/0000-0001-5168-1801
D
Fenstermacher
Takeda Pharmaceuticals International Company, Translational and Biomarker Research, Cambridge, MA, United States.
Hadi
http://orcid.org/0000-0003-1225-1301
H
Danaee
M2Gen, Bioinformatics, Tampa, FL, United States.
Hongyue
http://orcid.org/0000-0002-6609-9141
H
Dai
H Lee Moffitt Cancer Center and Research Institute, Blood and Marrow Transplantation, Tampa, FL, United States.
Daniel
http://orcid.org/0000-0002-2183-1773
D
Sullivan
Takeda Pharmaceuticals International Company, Translational and Biomarker Research, Cambridge, MA, United States.
William L
http://orcid.org/0000-0002-9989-0183
WL
Trepicchio
M2Gen, Administration, Tampa, FL, United States.
William S
http://orcid.org/0000-0003-2582-0454
WS
Dalton
CD30 antigen; antitumor agents; clinical trial; database management systems; medical oncology