Digital quantification of somatostatin receptor subtypes 2 and 5 in growth hormone–secreting pituitary tumors

Immunohistochemistry (IHC) of somatostatin receptor subtype 2 can predict response to first-generation somatostatin receptor ligands (fg-SRLs) in acromegaly. Recently, we validated an open-source digital image analysis (DIA) to quantify somatostatin receptor subtype 2 (SSTR2) expression. We aimed to validate the DIA also on somatostatin receptor subtype 5 (SSTR5) in a new cohort of growth hormone (GH)-secreting pituitary tumors, with IHC performed in a different laboratory, and to correlate fg-SRL response with SSTs expression. Somatostatin receptor subtype 2 and SSTR5 were assessed in 42 GH-secreting pituitary tumors, using a semiquantitative immunoreactivity score (IRS) and the DIA by use of the open-access software CellProfiler. The DIA calculates the staining intensity and the percentage of positive cells (%PC). We found a good correlation between IRS and DIA for both SSTR2 and SSTR5 (P < .001), demonstrating the reliability of the DIA in this setting. Response to fg-SRL treatment correlated with SSTR2, but not SSTR5, expression. Somatostatin receptor subtype 2 expression predicted response to fg-SRL. In particular, the identified cut-offs were IRS ≥ 5 (area under the curve [AUC] 0.763; sensitivity 77%; specificity 83%); intensity/area ≥0.106 (AUC 0.833; sensitivity 92%; specificity 83%); and %PC-DIA ≥63.7% (AUC 0.917; sensitivity 92%; specificity 83%). The SSTR2 %PC correlated with treatment response only when evaluated using the DIA, showing a better performance of this method.

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Publication Details

Journal
European Journal of Endocrinology
Published
2024-12-21
DOI
https://doi.org/10.1093/ejendo/lvae170
Citations
4
Primary Topic
Pituitary Gland Disorders and Treatments
Type
article
Field-Weighted Citation Impact
1.43

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article

Digital quantification of somatostatin receptor subtypes 2 and 5 in growth hormone–secreting pituitary tumors

Federica Nista, Leo J. Hofland, Angelo Milioto, Diego Ferone et al.
4 citations
European Journal of Endocrinology
Pituitary Gland Disorders and Treatments
1.43
article

Digital quantification of somatostatin receptor subtypes 2 and 5 in growth hormone–secreting pituitary tumors

Federica Nista, Leo J. Hofland, Angelo Milioto, Diego Ferone, Jessica Amarù, Anand M. Iyer, Marica Arvigo, Federico Gatto, Claudia Campana, Peter M. van Koetsveld
article en
4 citations

Abstract

Immunohistochemistry (IHC) of somatostatin receptor subtype 2 can predict response to first-generation somatostatin receptor ligands (fg-SRLs) in acromegaly. Recently, we validated an open-source digital image analysis (DIA) to quantify somatostatin receptor subtype 2 (SSTR2) expression. We aimed to validate the DIA also on somatostatin receptor subtype 5 (SSTR5) in a new cohort of growth hormone (GH)-secreting pituitary tumors, with IHC performed in a different laboratory, and to correlate fg-SRL response with SSTs expression. Somatostatin receptor subtype 2 and SSTR5 were assessed in 42 GH-secreting pituitary tumors, using a semiquantitative immunoreactivity score (IRS) and the DIA by use of the open-access software CellProfiler. The DIA calculates the staining intensity and the percentage of positive cells (%PC). We found a good correlation between IRS and DIA for both SSTR2 and SSTR5 (P < .001), demonstrating the reliability of the DIA in this setting. Response to fg-SRL treatment correlated with SSTR2, but not SSTR5, expression. Somatostatin receptor subtype 2 expression predicted response to fg-SRL. In particular, the identified cut-offs were IRS ≥ 5 (area under the curve [AUC] 0.763; sensitivity 77%; specificity 83%); intensity/area ≥0.106 (AUC 0.833; sensitivity 92%; specificity 83%); and %PC-DIA ≥63.7% (AUC 0.917; sensitivity 92%; specificity 83%). The SSTR2 %PC correlated with treatment response only when evaluated using the DIA, showing a better performance of this method.

European Journal of EndocrinologyVol. 192(1)
Erasmus MC (NL), Ospedale Policlinico San Martino (IT), University of Genoa (IT), Erasmus University Rotterdam (NL)
Pfizer, Ipsen
Good health and well-being
Openalex Percentile: Top 15%
Pituitary Gland Disorders and Treatments
1.43
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