Serum biomarkers for assessing histology and outcomes in patients with metastatic lung cancer

Emil Lou, Melissa Johnson, Camelia Sima, Rita Gonzalez-Espinoza, Martin Fleisher, Mark G. Kris, Christopher G. Azzoli

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

BACKGROUND: Serum biomarkers are not in routine clinical use for diagnosis, prognosis, or treatment selection in lung cancer. OBJECTIVE: We examined serum protein biomarkers from patients with metastatic lung cancer to determine whether they correlate with progression-free survival (PFS), overall survival (OS), or histologic subtype. METHODS: Serum samples were collected prior to chemotherapy from 153 patients with metastatic lung cancer treated at Memorial Sloan-Kettering Cancer Center. Serum biomarkers were selected for ELISA testing based on their availability in a CLIA-certified clinical laboratory: ProGRP, SCC-Ag, NSE, CYFRA 21-1, TIMP1, and HE4. Pretreatment biomarker levels were correlated with outcome using proportional hazards analysis and tumor histology using logistic regression analysis. RESULTS: Univariate analysis indicated that only higher levels of CYFRA 21-1 were significantly associated with worsened PFS (HR 1.3, 95% CI 1.1 - 1.5, p< 0.01) and OS (HR 1.4, 95% CI 1.2-1.7, p< 0.001). Multivariate analysis of NSE, CYFRA 21-1, and TIMP1 indicated that CYFRA 21-1 remained independently associated with lower OS (HR 1.3, 95% CI 1.1-1.6, p< 0.01). Univariate analysis indicated that ProGRP (OR 3.3, 95% CI 1.7-6.5, p< 0.001) and NSE (OR 4.8, 95% CI 2.6-8.8, p< 0.0001) had the highest probabilities of differentiating SCLC from NSCLC. Multivariate analysis of these two markers demonstrated that they predicted SCLC histology with 94% accuracy. Univariate analysis showed that only SCCL-Ag distinguished squamous cell histology from adenocarcinoma (OR 4.4, 95% CI 1.7-11.5, p< 0.01). CONCLUSIONS: Serum CYFRA 21-1 may be useful in predicting patient survival, and serum ProGRP, NSE 21-1, and SCCL-Ag may be helpful in distinguishing between lung cancer sub-types.

Original languageEnglish (US)
Pages (from-to)207-214
Number of pages8
JournalCancer Biomarkers
Volume14
Issue number4
DOIs
StatePublished - Jan 1 2014

Keywords

  • CYFRA 21-1
  • Lung cancer
  • SCCL-Ag
  • biomarker panel
  • biomarkers

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