Published in:
01-08-2015 | Original Article
Gene transcript analysis blood values correlate with 68Ga-DOTA-somatostatin analog (SSA) PET/CT imaging in neuroendocrine tumors and can define disease status
Published in: European Journal of Nuclear Medicine and Molecular Imaging | Issue 9/2015
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Purpose
Precise determination of neuroendocrine tumor (NET) disease status and response to therapy remains a rate-limiting concern for disease management. This reflects limitations in biomarker specificity and resolution capacity of imaging. In order to evaluate biomarker precision and identify if combinatorial blood molecular markers and imaging could provide added diagnostic value, we assessed the concordance between 68Ga-somatostatin analog (SSA) positron emission tomography (PET), circulating NET gene transcripts (NETest), chromogranin A (CgA), and Ki-67 in NETs.
Methods
We utilized two independent patient groups with positive 68Ga-SSA PET: data set 1 (68Ga-SSA PETs undertaken for peptide receptor radionuclide therapy (PRRT), as primary or salvage treatment, n = 27) and data set 2 (68Ga-SSA PETs performed in patients referred for initial disease staging or restaging after various therapies, n = 22). We examined the maximum standardized uptake value (SUVmax), circulating gene transcripts, CgA levels, and baseline Ki-67. Regression analyses, generalized linear modeling, and receiver-operating characteristic (ROC) analyses were undertaken to determine the strength of the relationships.
Results
SUVmax measured in two centers were mathematically evaluated (regression modeling) and determined to be comparable. Of 49 patients, 47 (96 %) exhibited a positive NETest. Twenty-six (54 %) had elevated CgA (χ2 = 20.1, p < 2.5×10−6). The majority (78 %) had Ki-67 < 20 %. Gene transcript scores were predictive of imaging with >95 % concordance and significantly correlated with SUVmax (R
2 = 0.31, root-mean-square error = 9.4). The genes MORF4L2 and somatostatin receptors SSTR1, 3, and 5 exhibited the highest correlation with SUVmax. Progressive disease was identified by elevated levels of a quotient of MORF4L2 expression and SUVmax [ROC-derived AUC (R
2 = 0.7, p < 0.05)]. No statistical relationship was identified between CgA and Ki-67 and no relationship with imaging parameters was evident.
Conclusion
68Ga-SSA PET imaging parameters (SUVmax) correlated with a circulating NET transcript signature. Disease status could be predicted by an elevated quotient of gene expression (MORF4L2) and SUVmax. These observations provide the basis for further exploration of strategies that combine imaging parameters and disease-specific molecular data for the improvement of NET management.