Epithelial insulin receptor expression – prognostic relevance in colorectal cancer
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Steffen M. Heckl1, Marie Pellinghaus1, Sandra Krüger2, Clara Bosselmann1, Franziska Wilhelm2, Hans-Michael Behrens2, Stefan Schreiber1 and Christoph Röcken2
1Department of Internal Medicine I, University Hospital Schleswig-Holstein, Kiel, Germany
2Department of Pathology, Christian-Albrechts-University, Kiel, Germany
Steffen M. Heckl, email: Steffen.Heckl@uksh.de
Keywords: colorectal cancer; insulin receptor; cancer risk factor; cancer prognosis; cancer therapeutic target
Received: May 15, 2018 Accepted: December 10, 2018 Published: December 25, 2018
Background: Metabolic reprogramming in cancer encompasses the insulin receptor (IR) as a player of energy homeostasis and proliferation. We aimed to characterize vascular (VIR) and epithelial (EIR) IR expression in CRC and correlate it with clinico-pathological parameters and survival.
Methods: 1580 primary CRCs were explored by immunohistochemistry for evaluation of VIR and EIR. Subgroup analyses included in situ hybridization for IR isoform A (IR-A) and DNA mismatch repair protein immunohistochemistry. Clinico-pathological and survival parameters were studied.
Results: High VIR was evident in 63.5% of all CRC samples and was associated with T-stage (P = 0.005). EIR was present in 72.2% and was associated with lower T-stages (P = 0.006) and UICC-stages (P < 0.001). EIR negativity was associated with increased metastasis (P = 0.028), nodal spread (P < 0.001), lymphatic invasion (P = 0.008) and a decreased tumor-specific (P = 0.011) and overall survival (P = 0.007; 95%–C.I.: 44.5–84.1). EIR negativity in UICC-stage II was associated with a significantly worse tumor-specific (P = 0.045) and overall (P = 0.043) survival. IR-A was expressed in CRC vessels and cells.
Conclusions: We demonstrate VIR to be frequent in CRC and characterize EIR negativity as an important prognostic risk factor. The association between EIR negativity and worse survival in UICC-stage II should be prospectively evaluated for an application in therapeutic algorithms.
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