title: Correlation of different markers (p53, EGF-R, c-erbB-2, Ki-67) expression in the diagnostic biopsies and the corresponding resected tumors in non-small cell lung cancer.
abstract: Substaging using molecular markers has been proposed to try to identify prognostic factors allowing to define groups of patients with lung cancer for whom specific therapy might be of benefit. The pre-operative assessment of these markers seems to be important specially in case of neoadjuvant chemotherapy. The aim of our study was to compare the expression of two potential prognostic factors (p53 and Ki-67) and two potential therapeutic targets (EGF-R and c-erbB-2) assessed on biopsy samples (B) of non-small cell lung cancer (NSCLC) with that of the corresponding resected tumor (RT). The expression of these biological markers was evaluated by immunohistochemistry on B and on the paired RT in 28 patients. The mean percentage of p53 positive cells was 28% in RT and 38% in B with 81% CR between B and RT and 19% FP on B. Considering RT results as standard, the positive (PPV) and negative predictive value (NPV) of the B were, respectively, 74 and 100%. The mean percentage of EGF-R positive cells was 11% in RT and 28% in B. With a cut-off of 1%, we found 85% concordant results (CR) between B and RT, 4% false negative (FN) and 11% false positive (FP) on B. The PPV and NPV values of the B were, respectively, 80 and 92%. The 8% B and 19% RT were considered as positive for c-erbB-2. We found 15% FN and 4% FP on B with 81% CR between B and RT for c-erbB-2. The NPV of the B was 83%. The mean percentage of Ki-67 positive cells was 32% in RT and 14% in B. We found 82% CR between B and RT, 14% FN and 4% FP on B. The PPV of the B was 96%. In conclusion, biopsies may provide reliable information about p53, EGF-R, c-erbB-2 and Ki-67 in lung carcinoma and could help to elaborate a therapeutic strategy.
authors.affiliation: Fonds National de la Recherche Scientifique, Belgium. ap.meert@bordet.be
authors.forename: Anne-Pascale
authors.initials: AP
authors.lastname: Meert
authors.forename: Benoit
authors.initials: B
authors.lastname: Martin
authors.forename: Jean-Marc
authors.initials: JM
authors.lastname: Verdebout
authors.forename: Marianne
authors.initials: M
authors.lastname: Paesmans
authors.forename: Thierry
authors.initials: T
authors.lastname: Berghmans
authors.forename: Vincent
authors.initials: V
authors.lastname: Ninane
authors.forename: Jean-Paul
authors.initials: JP
authors.lastname: Sculier
mesh_terms: D014408:Biomarkers, Tumor / Q000096:biosynthesis*; D001706:Biopsy; D002289:Carcinoma, Non-Small-Cell Lung / Q000378:metabolism* / Q000473:pathology / Q000601:surgery; D005260:Female; D018773:Genes, erbB-1 / Q000502:physiology; D018734:Genes, erbB-2 / Q000502:physiology; D006801:Humans; D019394:Ki-67 Antigen / Q000096:biosynthesis; D008168:Lung / Q000473:pathology* / Q000601:surgery; D008175:Lung Neoplasms / Q000378:metabolism* / Q000473:pathology / Q000601:surgery; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011013:Pneumonectomy; D011237:Predictive Value of Tests; D012372:ROC Curve; D016159:Tumor Suppressor Protein p53 / Q000096:biosynthesis
chemical_list: D014408:Biomarkers, Tumor; D019394:Ki-67 Antigen; D016159:Tumor Suppressor Protein p53