Proteomic profiling identifies pathways dysregulated in non-small cell lung cancer and an inverse association of AMPK and adhesion pathways with recurrence

Abstract

Introduction: The identification of key pathways dysregulated in non-small cell lung cancer (NSCLC) is an important step toward understanding lung pathogenesis and developing new therapeutic approaches.

Methods: Toward this goal, reverse-phase protein lysate arrays (RPPA) were used to compare signaling pathways between NSCLC tumors and paired normal lung tissue from 46 patients and assess their association with clinical outcome.

Results: After RPPA quantification of 63 proteins and phosphoproteins, tissue pairs were randomized to a training set (n = 25 pairs) and test set (n = 21 pairs). In the training set, 15 protein markers were differentially expressed between tumors and normal lung (p ≤ 0.01), including markers in the PI3K/AKT and p38 MAPK signaling pathways (e.g., p70S6K, S6, p38, and phospho-p38), as well as caveolin-1 and β-catenin. A four-protein signature (p70S6K, cyclin B1, pSrc(Y527), and caveolin-1) independent of histology classified specimens as tumor versus normal with a predicted accuracy of 83%, sensitivity of 67%, and specificity of 100%. The signature was validated in the test set, correctly classifying all normal tissues and 14 of 21 tumor tissues. RPPA results were confirmed by immunohistochemistry for caveolin-1 and p70S6K. In tumors from patients with resected NSCLC, expression of proteins in the energy-sensing AMPK pathway (pLKB1, AMPK, p-Acetyl-CoA, pTSC2), adhesion, EGFR, and Rb signaling pathways was inversely associated with NSCLC recurrence.

Conclusions: These data provide evidence for dysregulation of several pathways including those involving energy sensing and adhesion that are potentially associated with NSCLC pathogenesis and disease recurrence.

FIGURE 1

Unsupervised hierarchical clustering identifies distinct protein expression patterns between normal lung and non-small cell lung cancer (NSCLC) tumors. Levels of 63 proteins and phosphoproteins were determined by reverse-phase protein lysate arrays in paired normal lung (blue) and NSCLC (red) samples from 46 patients. Unsupervised hierarchical clustering separated samples into two main groups based on differences in protein expression. One group contained a majority of the tumor samples (red), whereas the other contained mostly normal lung (blue), indicating major differences in protein expression between tumor and normal lung, even within an individual patient. Replicate proteins, such as p-p38(T180), pLKB1, and cyclin D1, clustered next to each other.

FIGURE 2

Identification of proteins differentially expressed between paired normal lung and non-small cell lung cancer tumor samples. A, Protein and phosphoprotein levels for 63 markers were compared between normal tissue (blue) and tumor tissue (red) from patients who underwent surgical resection of their tumors. Protein levels were compared between the two groups by t test and those with p value <0.005 (false discovery rate <1%) are shown. B, The ratio of phospho- to total protein levels are shown for Akt and FAK.

FIGURE 3

A four-marker proteomic signature discriminates tumor from normal lung tissue. A, The receiver operating characteristic curve shows good performance of the model to correctly classify tumor and normal tissues. B, Two-way hierarchical clustering of the normal (blue) and tumor (red) tissues from the training set shows that these tissues are well differentiated by levels of the four markers (p70S6K, cyclin B1, pSrc(Y527), and caveolin). C, Similarly, the four markers also separate normal (blue) from tumor (red) in the test set.