Protein expression predicts postop NSCLC recurrence, survival

By Sara Freeman, medwireNews Reporter

US-based researchers have identified a panel of 12 proteins that may help predict overall survival (OS) and the risk of recurrence in patients treated with surgery for non-small-cell lung cancer (NSCLC).

Waun Hong (University of Texas MD Anderson Cancer Center, Houston) and associates used immunohistochemistry (IHC) to determine the expression of 21 proteins previously linked to the development of lung cancer, in preclinical studies of NSCLC tissue resected between 2002 and 2005.

The majority of the 370 patients involved had stage I disease (63%) and adenocarcinoma (61%), with 36% given adjuvant chemotherapy or radiation and 15% neoadjuvant therapies. At a median follow up of 5.3 years, there were 209 cases of recurrence or death and 160 deaths. The median relapse-free survival (RFS) was 4.1 years and median OS was 6.4 years.

In multivariate analysis, three proteins were found to be significant predictors of shorter RFS after adjusting for age and stage. These were positive membrane insulin receptor expression (hazard ratio [HR]=1.44), cytoplasmic chemokine (C-X-C motif) receptor 2 (CXCR2), levels above the median value (HR=1.36) and elevated insulin-like growth factor 1 receptor (HR=1.52 per 100 increase).

By contrast, four proteins were associated with longer RFS, namely positive cytoplasmic pAMPK [phosphoadenosine monophosphate-activated protein kinase], positive cytoplasmic pmTOR [phospho-mammalian target of rapamycin], positive cytoplasmic EpCAM [epithelial cell adhesion molecule] and elevated membrane CASK [calcium/calmodulin-dependent serine protein kinase], with HRs of 0.65, 0.70, 0.71 and 0.68 per 100 increase, respectively.

After adjusting for age, stage and five biomarkers, longer OS was predicted by positive cytoplasmic pAMPK (HR=0.70), pmTOR (HR=0.66) and EpCAM (HR=0.65) expression, whereas shorter OS was linked to increased expression of cytoplasmic CXCR2 (HR=1.57) and higher nuclear flap structure-specific endonuclease-1 (HR=1.42).

“Based on our results we have identified some important biomarker associations and begun early development on a risk model,” Hong et al report in Clinical Cancer Research.

This model includes all histological subtypes and clinical factors as well as the proteins studied, which are involved in various processes such as cell adhesion and extracellular matrix interactions, DNA replication and repair, inflammation, growth and metabolism, and growth and effector pathways.

The researchers conclude: “By gaining a better understanding of the biology of lung carcinogenesis, we hope to use this knowledge to accurately assess risk and personalize chemoprevention strategies following lung cancer resection.”

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