PET imaging of somatostatin receptors
Somatostatin (SST) is a cyclic peptide consisting of 14 amino acids. This, and the extended form, somatostatin-28, are cleaved from the prohormone pro-somatostatin, which in turn, is cleaved from pre-pro-somatostatin. SST-14 is mainly produced and excreted in the central nervous system, pituitary, and pancreas, and SST-28 in epithelial cells of the gastrointestinal tract. Somatostatin-14 and somatostatin-28 bind to five somatostatin receptor subtypes, SSTR1-SSTR5. SSTR5 has higher affinity to SST-28 than to SST-14. Spliced variants for SSTR2 and SSTR5 have been found, with different subcellular localization. Somatostatin receptors belong to the G-protein coupled receptor (GCPR) family. SSTRs interact with each other and even with other GCPRs forming homo- and heterodimers (Møller et al., 2003). Signalling is also affected by SSTR internalization, recycling and degradation (Csaba et al, 2012).
SSTR1 is expressed in the brain, pancreatic β-cells, gastrointestinal (GI) tract, and several tumour types. SSTR2 is found in the brain, pancreatic α-cells, pituitary gland, GI tract, adrenal gland, spleen, and several tumour types, especially in neuroendocrine tumours (NETs). High level of SSTR2 gene expression occurs in proinflammatory M1 macrophages, but not in other macrophage phenotypes, and not in monocytes, T or B lymphocytes, NK cells, platelets, neutrophils, or endothelial cells (Tarkin et al., 2017). SSTR3 is expressed in the brain, GI tract, liver, spleen, and some tumour types. SSTR4 is found in GI tract, lungs, heart, and smaller amounts also in the brain. SSTR5 is expressed in the brain, pituitary gland, GI tract, some tumour types, and probably also in pancreatic α- and β-cells.
Somatostatin acts as a neurotransmitter (one of neuropeptides). SST suppresses the release of hormones, for example GH, TSH, prolactin, and ACTH in the pituitary, gastrin in the gastrointestinal tract, insulin and glucagon in the pancreas, and TRH and CRH in the hypothalamus. Somatostatin shows anti-inflammatory properties via actions on inflammatory cells, and it inhibits the proliferation of all cells, also tumour cells.
Cortistatin (CORT-17 and CORT-29 in humans) is a somatostatin-related peptide which also binds with high affinity to somatostatin receptors, but shows distinctive biological action by binding also to other receptors such as ghrelin receptor (GHS-R1a). Cortistatin is produced in the brain cortex, but also in peripheral tissues including pancreas and gastrointestinal tract, and inflammatory cells.
Several somatostatin analogues have been synthesized, including lanreotide (mainly for SSTR2), octreotide (mainly for SSTR2), pasireotide (all SSTRs except SSTR4), seglitide (SSTR2, SSTR4, SSTR5), somatoprim (SSTR2, SSTR4, SSTR5), and vapreotide (SSTR2 and SSTR5).
PET tracers for somatostatin receptors are mainly based on the octreotide, adding a chelator (usually DOTA) and the radioactive label (usually 68Ga or 64Cu). These include [68Ga]DOTANOC ([68Ga]DOTA-l-NaI3-octreotide), [68Ga]DOTATOC ([68Ga]DOTA-Tyr3-octreotide), [68Ga]DOTATATE ([68Ga]DOTA-Tyr3-octreotate), and [18F]SiTATE. [68Ga]DOTATATE has the highest affinity to SSTR2, which is also the most abundant of SSTR subtypes. [68Ga]DOTATOC and [68Ga]DOTANOC have affinity to both SSTR2 and SSTR5, and [68Ga]DOTANOC even to SSTR3 (Johnbeck et al., 2014). [18F]SiTATE is highly selective for SSTR2 with only minor affinity to the SSTR3 and SSTR4 and nearly no affinity to the SSTR subtype 1 and 5 (Wängler et al., 2022).
Most neuroendocrine tumours (NETs) express somatostatin receptors; therefore PET radioligands with variable specificity to somatostatin receptor subtypes have been introduced and used in diagnosing NETs. PET imaging using somatostatin analogues is becoming a new gold standard for NET and insulinoma imaging, replacing 111In-DTPA-pentetreotide (Octreoscan) scintigraphy (Johnbeck et al., 2014; Hope et al., 2018). [68Ga]DOTATOC and [68Ga]DOTATATE have been approved by the EMA and FDA.
In addition to cancer diagnosis and staging, PET imaging can also be used to develop somatostatin analogues for peptide receptor radionuclide therapy (PRRT). Whole-body PBPK models could be used to predict tissue distribution of PRRT ligands (Siebinga et al., 2021).
Labelled SST analogues may not be useful in imaging of brain tumours since the uptake is mostly associated with disrupted BBB, not the expression of somatostatin receptors (Kiviniemi et al., 2014 and 2015). Most glioblastomas do not express SSTR2, but most oligodendrogliomas have high SSTR2A expression (Kiviniemi et al., 2017).
Activated macrophages have been shown to overexpress SSTR1 and SSTR2 during their differentiation from monocytes. Also fibroplasts express SSTRs. In a small group of patients with idiopathic pulmonary fibrosis, [68Ga]DOTANOC uptake correlated with the extent of fibrosis (Ambrosini et al., 2010).
SSTR2 imaging could be used in the acute phase of sarcoidosis, but probably not in chronic phase where fibrotic tissue with low levels of SRRT2 is formed. [68Ga]DOTATATE was found to be less sensitive for detection of myocardial inflammation than [18F]FDG (Bravo et al., 2021). [68Ga]DOTANOC has good diagnostic accuracy in cardiac sarcoidosis (Gormsen et al., 2016). [68Ga]DOTATOC is superior to conventional 67Ga-SPECT in detecting sarcoidosis lesions in lymph nodes and muscles (Nobashi et al., 2016).
In mouse model of myocardial post-infarct inflammation, [68Ga]DOTATATE has very low uptake (SUV ∼0.10), and was inferior to [18F]FDG (Thackeray et al., 2015).
Somatostatin receptors are overexpressed in myocardial inflammation and in atherosclerotic plaques (Lapa et al., 2015). In a mouse model [68Ga]DOTANOC and [68Ga]DOTATATE were found to be better in detection of atherosclerotic plaques compared to [18F]FDR-NOC (Rinne et al., 2016). In atherosclerosis patients, [68Ga]DOTATATE discriminates high-risk versus low-risk coronary lesions better than [18F]FDG, and offers good image quality (Tarkin et al., 2017). Uptake in thoracic aorta correlates with cardiovascular risk factors (Lee et al., 2018).
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Updated at: 2022-12-07
Created at: 2015-09-16
Written by: Vesa Oikonen