Gene expression profiling reveals GC and CEACAM1 as new tools in the diagnosis of lung carcinoids

Research output: Contribution to journalArticle

Abstract

Background: Classification of lung carcinoids into typical and atypical is a diagnostic challenge since no immunohistochemical tools are available to support pathologists in distinguishing between the two subtypes. A differential diagnosis is essential for clinicians to correctly discuss therapy, prognosis and follow-up with patients. Indeed, the distinction between the two typical and atypical subtypes on biopsies/cytological specimens is still unfeasible and sometimes limited also after radical surgeries. By comparing the gene expression profile of typical (TC) and atypical carcinoids (AC), we intended to find genes specifically expressed in one of the two subtypes that could be used as diagnostic markers. Methods: Expression profiling, with Affymetrix arrays, was performed on six typical and seven atypical samples. Data were validated on an independent cohort of 29 tumours, by means of quantitative PCR and immunohistochemistry (IHC). Results: High-throughput gene expression profiling was successfully used to identify a gene signature specific for atypical lung carcinoids. Among the 273 upregulated genes in the atypical vs typical subtype, GC (vitamin D-binding protein) and CEACAM1 (carcinoembryonic antigen family member) emerged as potent diagnostic markers. Quantitative PCR and IHC on a validation set of 17 ACs and 12 TCs confirmed their reproducibility and feasibility. Conclusions: GC and CEACAM1 can distinguish between TC and AC, defining an IHC assay potentially useful for routine cytological and histochemical diagnostic procedures. The high sensitivity and reproducibility of this new diagnostic algorithm strongly support a further validation on a wider sample size.

Original languageEnglish
Pages (from-to)1244-1249
Number of pages6
JournalBritish Journal of Cancer
Volume110
Issue number5
DOIs
Publication statusPublished - Mar 4 2014

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Keywords

  • CEACAM1
  • Diagnostic algorithm
  • GC
  • Gene expression profile
  • Lung carcinoid

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

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