Chromogranin A: any relevance in neuroendocrine tumors?. Issue 1 (February 2016)

• Record Type: Journal Article
• Authors: Kidd, Mark; Bodei, Lisa; Modlin, Irvin M.
• Is Part Of: Current opinion in endocrinology, diabetes and obesity. Volume 23:Issue 1(2016:Feb.)
• Publication Date: 2016-02
• Subjects: biomarker -- chromogranin A -- multianalyte transcript assay with algorithmic analysis -- multianalyte -- NETest -- neuroendocrine tumor -- transcript; Endocrinology -- Periodicals; Diabetes -- Periodicals; Obesity -- Periodicals; Diabetes Mellitus -- Periodicals; Endocrine System Diseases -- Periodicals; Endocrine Glands -- Periodicals; Obesity -- Periodicals; Endocrinologie -- Périodiques; Diabète -- Périodiques; Obésité -- Périodiques; Diabetes; Endocrinology; Obesity; Periodicals; 616.4
• DOI: 10.1097/MED.0000000000000215
• Languages: English
• ISSNs: 1752-296X

Abstract

Abstract : Purpose of review: The review summarizes the utility and limitations of chromogranin A (CgA) as a circulating biomarker for neuroendocrine tumors (NETs). Recent findings: Blood CgA measurement has numerous clinical limitations including poor assay reproducibility, low sensitivity (meta-analysis: 73%, 95% confidence interval: 0.71–0.76), and a paucity of prospective validation studies. A recent study noted elevation in 27% of NETs with a predictive value of 50% for metastases. These findings are consistent with its efficacy primarily as a monoanalyte secretory rather than multidimensional neoplastic marker. An automated CgA assay (KRYPTOR) exhibits similar metrics to the DAKO assay but is only useful in serum and routine storage diminishes its accuracy. Current studies indicate that CgA is more effective as a biomarker for cardiac disease. Given the diverse limitations of CgA, NET biomarker focus has evolved toward measurement of multiple analytes, for example, transcripts. Multianalyte algorithmic analyses perform significantly better as diagnostic (>95%) and prognostic markers (>90%) than CgA (30–74 and ∼50%, respectively) since they delineate different aspects of the biological behavior of NETs, (e.g., proliferome and metabolome). Summary: CgA is neither a reliable nor robust NET biomarker. As a monoanalyte, it is restricted by poor metrics and has limited predictive value. Its current clinical utility appears optimal in cardiovascular disease. The significance of CgA in NET disease is diminishing as other analytical approaches, particularly transcript multianalyte assays or other strategies, evolve to supersede it.