Mohamed Hassanein

The State of Molecular Biomarkers for the Early Detection of Lung Cancer

Using biomarkers to select the most at-risk population, to detect the disease while measurable and yet not clinically apparent has been the goal of many investigations. Recent advances in molecular strategies and analytic platforms, including genomics, epigenomics, proteomics, and metabolomics, have identified increasing numbers of potential biomarkers in the blood, urine, exhaled breath condensate, bronchial specimens, saliva, and sputum, but none have yet moved to the clinical setting. Therefore, there is a recognized gap between the promise and the product delivery in the cancer biomarker field. In this review, we define clinical contexts where risk and diagnostic biomarkers may have use in the management of lung cancer, identify the most relevant candidate biomarkers of early detection, provide their state of development, and finally discuss critical aspects of study design in molecular biomarkers for early detection of lung cancer. Cancer Prev Res; 5(8); 992–1006. ©2012 AACR.

Moesin expression is a marker of basal breast carcinomas.

Basal breast cancers (BBCs) have a high risk of metastasis, recurrence and death. Formal subtype definition relies on gene expression but can be approximated by protein expression. New markers are needed to help in the management of the basal subtype of breast cancer. In a previous transcriptional analysis of breast cell lines we found that Moesin expression was a potential basal marker. We show here that Moesin protein expression is a basal marker in breast tumors. In a tissue microarray (TMA) containing 547 sporadic breast cancers, of which 108 were profiled for gene expression, Moesin was expressed in 31% of all tumors and in 82% of the basal tumors. To confirm that Moesin expression remained associated with the basal phenotype in specific types of BBCs, we analyzed Moesin expression in 2 other TMAs containing 40 medullary breast cancers (MBCs) and 27 BRCA1‐associated breast cancers (BRCA1‐BCs), respectively. Moesin was strongly expressed in MBCs (87%; p = 2.4 × 10−5) and in BRCA1‐BCs (58%; p = 1.3 × 10−5) as compared with non‐MBCs and sporadic cases. Moesin‐expressing tumors display features of BBCs, such as high proliferation rate, hormone receptors negativity, expression of putative basal/myoepithelial markers (CAV1, CD10, CK5/6, CK14, EGFR, P53, P‐cadherin and SMA). Survival analysis showed a reduced specific survival and metastasis‐free survival in Moesin‐expressing tumors by log‐rank test (pSS = 0.014 and pMFS = 0.014). In multivariate analysis, Moesin expression was nearly an independent prognostic marker of poor outcome as shown by Cox proportional hazard model in patients without lymph node metastasis (p = 0.052, HR = 2.38, CI 95[0.99–5.69]).

In-depth Proteomic Analysis of Nonsmall Cell Lung Cancer to Discover Molecular Targets and Candidate Biomarkers

Advances in proteomic analysis of human samples are driving critical aspects of biomarker discovery and the identification of molecular pathways involved in disease etiology. Toward that end, in this report we are the first to use a standardized shotgun proteomic analysis method for in-depth tissue protein profiling of the two major subtypes of nonsmall cell lung cancer and normal lung tissues. We identified 3621 proteins from the analysis of pooled human samples of squamous cell carcinoma, adenocarcinoma, and control specimens. In addition to proteins previously shown to be implicated in lung cancer, we have identified new pathways and multiple new differentially expressed proteins of potential interest as therapeutic targets or diagnostic biomarkers, including some that were not identified by transcriptome profiling. Up-regulation of these proteins was confirmed by multiple reaction monitoring mass spectrometry. A subset of these proteins was found to be detectable and differentially present in the peripheral blood of cases and matched controls. Label-free shotgun proteomic analysis allows definition of lung tumor proteomes, identification of biomarker candidates, and potential targets for therapy.

Microenvironmental Independence Associated with Tumor Progression

Tumor-microenvironment interactions are increasingly recognized to influence tumor progression. To understand the competitive dynamics of tumor cells in diverse microenvironments, we experimentally parameterized a hybrid discrete-continuum mathematical model with phenotypic trait data from a set of related mammary cell lines with normal, transformed, or tumorigenic properties. Surprisingly, in a resource-rich microenvironment, with few limitations on proliferation or migration, transformed (but not tumorigenic) cells were most successful and outcompeted other cell types in heterogeneous tumor simulations. Conversely, constrained microenvironments with limitations on space and/or growth factors gave a selective advantage to phenotypes derived from tumorigenic cell lines. Analysis of the relative performance of each phenotype in constrained versus unconstrained microenvironments revealed that, although all cell types grew more slowly in resource-constrained microenvironments, the most aggressive cells were least affected by microenvironmental constraints. A game theory model testing the relationship between microenvironment resource availability and competitive cellular dynamics supports the concept that microenvironmental independence is an advantageous cellular trait in resource-limited microenvironments.

Targeting SLC1a5‐mediated glutamine dependence in non‐small cell lung cancer

We previously elucidated the pleotropic role of solute carrier family A1 member 5 (SLC1A5) as the primary transporter of glutamine (Gln), a modulator of cell growth and oxidative stress in non‐small cell lung cancer (NSCLC). The aim of our study was to evaluate SLC1A5 as a potential new therapeutic target and candidate biomarker predictive of survival and response to therapy. SLC1A5 targeting was examined in a panel of NSCLC and human bronchial cell lines by RNA interference and by a small molecular inhibitor, gamma‐l‐glutamyl‐p‐nitroanilide (GPNA). The effects of targeting SLC1A5 on cell growth, Gln uptake, ATP level, autophagy and cell death were examined. Inactivation of SLC1A5 genetically or pharmacologically decreased Gln consumption, inhibited cell growth, induced autophagy and apoptosis in a subgroup of NSCLC cell lines that overexpress SLC1A5. Targeting SLC1A5 function decreased tumor growth in NSCLC xenografts. A multivariate Cox proportional hazards analysis indicates that patients with increased SLC1A5 mRNA expression have significantly shorter overall survival (p = 0.01, HR = 1.24, 95% CI: 1.05–1.46), adjusted for age, gender, smoking history and disease stage. In an immunohistochemistry study on 207 NSCLC patients, SLC1A5 protein expression remained highly significant prognostic value in both univariate (p < 0.0001, HR = 1.45, 95% CI: 1.15–1.50) and multivariate analyses (p = 0.04, HR = 1.22, 95% CI: 1.01–1.31). These results position SLC1A5 as a new candidate prognostic biomarker for selective targeting of Gln‐dependent NSCLC.

Advances in Proteomic Strategies toward the Early Detection of Lung Cancer

Since the advent of the new proteomics era more than a decade ago, large-scale studies of protein profiling have been exploited to identify the distinctive molecular signatures in a wide array of biological systems spanning areas of basic biological research, various disease states, and biomarker discovery directed toward therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomics approaches, leading to enhancement of the depth and breadth of proteome coverage. Proteomic signatures specific for invasive lung cancer and preinvasive lesions have begun to emerge. In this review we provide a critical assessment of the state of recent advances in proteomic approaches and the biological lessons they have yielded, with specific emphasis on the discovery of biomarker signatures for the early detection of lung cancer.

The RNA binding protein FXR1 is a new driver in the 3q26-29 amplicon and predicts poor prognosis in human cancers

Significance Altered expression of RNA binding proteins might contribute to cancer development. This study reveals the functional implications and clinical relevance of FXR1, an RNA binding protein, in non-small cell lung cancer (NSCLC). Our results demonstrate that FXR1 promotes tumor progression by regulating two other oncogenes within the same chromosome 3q amplicon. To drive tumor progression, FXR1 forms a new complex with protein kinase C, iota, and posttranscriptionally stabilizes the expression of epithelial cell transforming 2. We show that increased FXR1 expression in NSCLC is a candidate biomarker predictive of poor survival and might represent a novel therapeutic target. In addition, FXR1 expression correlates with poor clinical outcome in multiple human cancers, suggesting broader implications of this RNA binding protein in cancer progression. Aberrant expression of RNA-binding proteins has profound implications for cellular physiology and the pathogenesis of human diseases such as cancer. We previously identified the Fragile X-Related 1 gene (FXR1) as one amplified candidate driver gene at 3q26-29 in lung squamous cell carcinoma (SCC). FXR1 is an autosomal paralog of Fragile X mental retardation 1 and has not been directly linked to human cancers. Here we demonstrate that FXR1 is a key regulator of tumor progression and its overexpression is critical for nonsmall cell lung cancer (NSCLC) cell growth in vitro and in vivo. We identified the mechanisms by which FXR1 executes its regulatory function by forming a novel complex with two other oncogenes, protein kinase C, iota and epithelial cell transforming 2, located in the same amplicon via distinct binding mechanisms. FXR1 expression is a candidate biomarker predictive of poor survival in multiple solid tumors including NSCLCs. Because FXR1 is overexpressed and associated with poor clinical outcomes in multiple cancers, these results have implications for other solid malignancies.

Development of High-Throughput Quantitative Assays for Glucose Uptake in Cancer Cell Lines

PurposeMetabolism, and especially glucose uptake, is a key quantitative cell trait that is closely linked to cancer initiation and progression. Therefore, developing high-throughput assays for measuring glucose uptake in cancer cells would be enviable for simultaneous comparisons of multiple cell lines and microenvironmental conditions. This study was designed with two specific aims in mind: the first was to develop and validate a high-throughput screening method for quantitative assessment of glucose uptake in “normal” and tumor cells using the fluorescent 2-deoxyglucose analog 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxyglucose (2-NBDG), and the second was to develop an image-based, quantitative, single-cell assay for measuring glucose uptake using the same probe to dissect the full spectrum of metabolic variability within populations of tumor cells in vitro in higher resolution.ProcedureThe kinetics of population-based glucose uptake was evaluated for MCF10A mammary epithelial and CA1d breast cancer cell lines, using 2-NBDG and a fluorometric microplate reader. Glucose uptake for the same cell lines was also examined at the single-cell level using high-content automated microscopy coupled with semi-automated cell-cytometric image analysis approaches. Statistical treatments were also implemented to analyze intra-population variability.ResultsOur results demonstrate that the high-throughput fluorometric assay using 2-NBDG is a reliable method to assess population-level kinetics of glucose uptake in cell lines in vitro. Similarly, single-cell image-based assays and analyses of 2-NBDG fluorescence proved an effective and accurate means for assessing glucose uptake, which revealed that breast tumor cell lines display intra-population variability that is modulated by growth conditions.ConclusionsThese studies indicate that 2-NBDG can be used to aid in the high-throughput analysis of the influence of chemotherapeutics on glucose uptake in cancer cells.

Acyl-Coenzyme A–Binding Protein Regulates Beta-Oxidation Required for Growth and Survival of Non–Small Cell Lung Cancer

We identified acyl-coenzyme A–binding protein (ACBP) as part of a proteomic signature predicting the risk of having lung cancer. Because ACBP is known to regulate β-oxidation, which in turn controls cellular proliferation, we hypothesized that ACBP contributes to regulation of cellular proliferation and survival of non–small cell lung cancer (NSCLC) by modulating β-oxidation. We used matrix-assisted laser desorption/ionization-imaging mass spectrometry (MALDI-IMS) and immunohistochemistry (IHC) to confirm the tissue localization of ABCP in pre-invasive and invasive NSCLCs. We correlated ACBP gene expression levels in NSCLCs with clinical outcomes. In loss-of-function studies, we tested the effect of the downregulation of ACBP on cellular proliferation and apoptosis in normal bronchial and NSCLC cell lines. Using tritiated-palmitate (3H-palmitate), we measured β-oxidation levels and tested the effect of etomoxir, a β-oxidation inhibitor, on proliferation and apoptosis. MALDI-IMS and IHC analysis confirmed that ACBP is overexpressed in pre-invasive and invasive lung cancers. High ACBP gene expression levels in NSCLCs correlated with worse survival (HR = 1.73). We observed a 40% decrease in β-oxidation and concordant decreases in proliferation and increases in apoptosis in ACBP-depleted NSCLC cells as compared with bronchial airway epithelial cells. Inhibition of β-oxidation by etomoxir in ACBP-overexpressing cells produced dose-dependent decrease in proliferation and increase in apoptosis (P = 0.01 and P < 0.001, respectively). These data suggest a role for ACBP in controlling lung cancer progression by regulating β-oxidation. Cancer Prev Res; 7(7); 748–57. ©2014 AACR.

Discovery of New Membrane-Associated Proteins Overexpressed in Small-Cell Lung Cancer

Introduction: Small-cell lung cancer (SCLC) is the most aggressive subtype of lung cancer, with no early detection strategy or targeted therapy currently available. We hypothesized that difference gel electrophoresis (DIGE) may identify membrane-associated proteins (MAPs) specific to SCLC, advance our understanding of SCLC biology, and discover new biomarkers of SCLC. Methods: MAP lysates were prepared from three SCLCs, three non–small-cell lung cancers, and three immortalized normal bronchial epithelial cell lines and coanalyzed by DIGE. Subsequent protein identification was performed by mass spectrometry. Proteins were submitted to Ingenuity Pathway Analysis. Candidate biomarkers were validated by Western blotting (WB) and immunohistochemistry (IHC). Results: Principal component analysis on the global DIGE data set demonstrated that the four replicates derived from each of the nine cell lines clustered closely, as did samples within the same histological group. One hundred thirty-seven proteins were differentially expressed in SCLC compared with non–small-cell lung cancer and immortalized normal bronchial epithelial cells. These proteins were overrepresented in cellular/tissue morphology networks. Dihydropyrimidinase-related protein 2, guanine nucleotide–binding protein alpha-q, laminin receptor 1, pontin, and stathmin 1 were selected as candidate biomarkers among MAPs overexpressed in SCLC. Overexpression of all candidates but RSSA in SCLC was verified by WB and/or IHC on tissue microarrays. These proteins were significantly associated with SCLC histology and survival in univariables analyses. Conclusion: DIGE analysis of a membrane-associated subproteome discovered overexpression of dihydropyrimidinase-related protein 2, guanine nucleotide–binding protein alpha-q, RUVB1, and stathmin 1 in SCLC. Results were verified by WB and/or IHC in primary tumors, suggesting that investigating their functional relevance in SCLC progression is warranted. Association with survival requires further validation in larger clinical data sets.