Differential analysis of two-dimension gel electrophoresis profiles from the normal-metaplasia-dysplasia-carcinoma tissue of human bronchial epithelium

Integrating genomics and proteomics-oriented biomarkers to comprehend lung cancer

BACKGROUND

Lung cancer is the leading cause of cancer deaths worldwide. Recent years have brought tremendous progress in the development of genomic and proteomic platforms to study lung cancer progression and biomarker identification.

OBJECTIVE

To evaluate and integrate potential innovations of 'omics' (e.g., genomics and proteomics) technologies in dissecting biomarkers for lung cancer.

METHODS

Omics technologies permit simultaneous monitoring of many hundreds or thousands of macro and small molecules, as well as functional monitoring of multiple pivotal cellular pathways. Discussion follows to explore the principal challenges in the development of cancer biomarkers integrating genomics with proteomics data sets with their functional counterparts in conjunction with clinical data.

RESULTS/CONCLUSION

Sets of genes and gene interactions affecting different subsets of cancers can be determined using genomics in lung cancer. Proteomic studies have generated numerous functional data sets of potential diagnostic, prognostic and therapeutic significance in lung cancer. It is likely that omics will take a central place in the understanding, diagnosis, monitoring and treatment of lung cancer. Here the potential benefits and pitfalls of these methodologies are reviewed for the faster discovery of therapeutically valuable biomarkers for lung cancer.

Mass spectrometry-based proteomics: the road to lung cancer biomarker discovery

Lung cancer is the leading cause of cancer death in men and women in Western nations, and is among the deadliest cancers with a 5-year survival rate of 15%. The high mortality caused by lung cancer is attributable to a late-stage diagnosis and the lack of effective treatments. So, it is crucial to identify new biomarkers that could function not only to detect lung cancer at an early stage but also to shed light on the molecular mechanisms that underlie cancer development and serve as the basis for the development of novel therapeutic strategies. Considering that DNA-based biomarkers for lung cancer showed inadequate sensitivity, specificity, and reproducibility, proteomics could represent a better tool for the identification of useful biomarkers and therapeutic targets for this cancer type. Among the proteomics technologies, the most powerful tool is mass spectrometry. In this review, we describe studies that use mass spectrometry-based proteomics technologies to analyze tumor proteins and peptides, which might represent new diagnostic, prognostic, and predictive markers for lung cancer. We focus in particular on those findings that hold promise to impact significantly on the clinical management of this disease.

Identification of isocitrate dehydrogenase 1 as a potential diagnostic and prognostic biomarker for non-small cell lung cancer by proteomic analysis

Lung cancer is the leading cause of cancer-related death in the world. To explore tumor biomarkers for clinical application, two-dimensional fluorescence difference gel electrophoresis and subsequent MALDI-TOF/TOF mass spectrometry were performed to identify proteins differentially expressed in 12 pairs of lung squamous cell tumors and their corresponding normal tissues. A total of 28 nonredundant proteins were identified with significant alteration in lung tumors. The up-regulation of isocitrate dehydrogenase 1 (IDH1), superoxide dismutase 2, 14-3-3ε, and receptor of activated protein kinase C1 and the down-regulation of peroxiredoxin 2 in tumors were validated by RT-PCR and Western blot analysis in independent 15 pairs of samples. Increased IDH1 expression was further verified by the immunohistochemical study in extended 73 squamous cell carcinoma and 64 adenocarcinoma clinical samples. A correlation between IDH1 expression and poor overall survival of non-small cell lung cancer (NSCLC) patients was observed. Furthermore, ELISA analysis showed that the plasma level of IDH1 was significantly elevated in NSCLC patients compared with benign lung disease patients and healthy individuals. In addition, knockdown of IDH1 by RNA interference suppressed the proliferation of NSCLC cell line and decreased the growth of xenograft tumors in vivo. These observations suggested that IDH1, as a protein promoting tumor growth, could be used as a plasma biomarker for diagnosis and a histochemical biomarker for prognosis prediction of NSCLC.

Effect of shRNA mediated down-regulation of Annexin A2 on biological behavior of human lung adencarcinoma cells A549

In the previous study, we found that Annexin A2 was significantly up-regulated in lung cancer and could induce related-antigen in lung cancer patients' serum. To further study the function of Annexin A2, the short hairpin RNA plasmid targeting Annexin A2 was constructed in vitro and transfected into human lung adencarcinoma A549 cells. Knocking down Annexin A2 expression by shRNA, the mRNA level of Annexin A2 was investigated by semi-quantitative RT-PCR. The expression of Annexin A2 protein was examined by Western Blotting and Immuocytochemistry. MTT assay and Transwell chamber model were used to evaluate proliferation and invasion of A549 cells in vitro. The concentration of matrix metalloproteinase-2 (MMP-2) and cathepsin B (CB) in the supernatant was evaluated by ELISA. At 48 h after transfection, the expression of Annexin A2 mRNA and protein was down-regulated significantly, respectively (p < 0.05).The proliferation and invasion capability of A549 cells also decreased significantly (p < 0.05). The concentration of MMP-2 and CB was down-regulated obviously, respectively (p < 0.05). This study implies that Annexin A2 might play an important role in the progression and invasion of human lung cancer cells, and could promote progression of lung cancer by regulating the expression of MMP-2 and CB.

Lung cancer proteomics, clinical and technological considerations

The overall survival of lung cancer patients is disappointingly low. This is due to several factors, including the lack of an effective screening strategy to detect tumors at a potentially curable early stage, a marked resistance of lung cancer cells to drug treatment and a still superficial knowledge about the multifactorial cellular networks that are activated or suppressed during cancer progression. Furthermore, the armamentarium of clinicians and researchers in the field does not yet include reliable biomarkers to predict tumor response to treatment and foresee the natural history of the disease. In the present situation, a potential breakthrough is presented by proteomics technologies with the potential to discover relevant biomarkers which can be accurately quantified in multiplexed assays. Proteomics field can also contribute greatly in the understanding of mechanisms in tumor progression and treatment response. In this review we will describe the work that is being done in the field of lung cancer proteomics, focusing on clinically relevant questions that need to be addressed and on the possible applications of novel technologies.

Pro-oxidative DEP chemicals induce heat shock proteins and an unfolding protein response in a bronchial epithelial cell line as determined by DIGE analysis

Ambient particulate matter (PM) induces adverse health effects through the ability of pro-oxidative chemicals to induce the production of oxygen radicals and oxidant injury. Utilizing a proteomics strategy involving 2-D DIGE, immunoblotting, and real-time PCR, we demonstrate that organic diesel exhaust particle (DEP) chemicals induce an unfolding protein response (UPR) and proinflammatory effects in the human bronchial epithelial cell line, BEAS-2B. DIGE and MS showed the induction of at least 14 proteins, among which heat shock protein 70 (HSP70), HSP40, TPR2, and T-complex protein 1 (zeta-subunit) are known to play a role in the UPR. Demonstrating increased HSP70 mRNA expression and nuclear translocation of HSF1, the key transcription factor responsible for HSP expression, further strengthened this notion. Immunoblotting demonstrated increased expression of ATF4, an ER stress-associated transcriptional enhancer responsible for differential protein translation under conditions of ER stress. Finally, the DEP extract induced the expression of IL-6 and IL-8 in the culture supernatant. The role of oxidative stress was demonstrated further by response subtraction in the presence of the thiol antioxidant, N-acetyl cysteine. Our data suggest that pro-oxidative DEP chemicals induce protein unfolding/misfolding that lead to UPR and proinflammatory effects in a cell type that is targeted by PM in the lung.

Proteomics in cancer

Proteomic studies have generated numerous datasets of potential diagnostic, prognostic, and therapeutic significance in human cancer. Two key technologies underpinning these studies in cancer tissue are two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Although surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF)-MS is the mainstay for serum or plasma analysis, other methods including isotope-coded affinity tag technology, reverse-phase protein arrays, and antibody microarrays are emerging as alternative proteomic technologies. Because there is little overlap between studies conducted with these approaches, confirmation of these advanced technologies remains an elusive goal. This problem is further exacerbated by lack of uniform patient inclusion and exclusion criteria, low patient numbers, poor supporting clinical data, absence of standardized sample preparation, and limited analytical reproducibility (in particular of 2D-PAGE). Despite these problems, there is little doubt that the proteomic approach has the potential to identify novel diagnostic biomarkers in cancer. In therapeutic proteomics, the challenge is significant due to the complexity systems under investigation (i.e., cells generate over 10(5) different polypeptides). However, the most significant contribution of therapeutic proteomics research is expected to derive not from single experiments, but from the synthesis and comparison of large datasets obtained under different conditions (e.g., normal, inflammation, cancer) and in different tissues and organs. Thus, standardized processes for storing and retrieving data obtained with different technologies by different research groups will have to be developed. Shifting the emphasis of cancer proteomics from technology development and data generation to careful study design, data organization, formatting, and mining is crucial to answer clinical questions in cancer research.

Proteomic analysis of cancer tissues: shedding light on carcinogenesis and possible biomarkers

Lung, gastric, colorectal, pancreatic, and esophageal cancers, as well as hepatocellular carcinoma (HCC), were the six most common and highly fatal cancers for Japanese men in Japan in 2003, while for women uterine cervical cancer could also be added to this list. To identify diagnostic or therapeutic biomarkers for these cancers, investigators are nowadays performing proteomic analyses of cancer tissues and cells, and revealing a large number of molecules which are diagnostic, prognostic and informative of carcinogenesis. From reports of proteomic analyses of cancerous tissues and noncancerous tissues sampled from HCC, and pancreatic, esophageal, gastric, colorectal, lung and uterine cervical cancers, we classified the proteins into digestive enzymes, growth factors, cell adhesion molecules, calcium-binding proteins, proteases, protease inhibitors, transporter proteins, structural molecules, apoptosis inhibitor, molecular chaperone, as well as proteins related to cell growth, cell differentiation, cell transformation, tumor invasion, carcinogen metabolism, and others. The aim of this study was to understand carcinogenesis of major cancers from a proteomics perspective using samples from cancer patients, and to elucidate their tumor biomarkers.