Label-free quantitative proteomics and N-terminal analysis of human metastatic lung cancer cells

Glial cell proteome using targeted quantitative methods for potential multi-diagnostic biomarkers

Glioblastoma is one of the most malignant primary brain cancer. Despite surgical resection with modern technology followed by chemo-radiation therapy with temozolomide, resistance to the treatment and recurrence is common due to its aggressive and infiltrating nature of the tumor with high proliferation index. The median survival time of the patients with glioblastomas is less than 15 months. Till now there has been no report of molecular target specific for glioblastomas. Early diagnosis and development of molecular target specific for glioblastomas are essential for longer survival of the patients with glioblastomas. Development of biomarkers specific for glioblastomas is most important for early diagnosis, estimation of the prognosis, and molecular target therapy of glioblastomas. To that end, in this study, we have conducted a comprehensive proteome study using primary cells and tissues from patients with glioblastoma. In the discovery stage, we have identified 7429 glioblastoma-specific proteins, where 476 proteins were quantitated using Tandem Mass Tag (TMT) method; 228 and 248 proteins showed up and down-regulated pattern, respectively. In the validation stage (20 selected target proteins), we developed quantitative targeted method (MRM: Multiple reaction monitoring) using stable isotope standards (SIS) peptide. In this study, five proteins (CCT3, PCMT1, TKT, TOMM34, UBA1) showed the significantly different protein levels (t-test: p value ≤ 0.05, AUC ≥ 0.7) between control and cancer groups and the result of multiplex assay using logistic regression showed the 5-marker panel showed better sensitivity (0.80 and 0.90), specificity (0.92 and 1.00), error rate (10 and 2%), and AUC value (0.94 and 0.98) than the best single marker (TOMM34) in primary cells and tissues, respectively. Although we acknowledge that the model requires further validation in a large sample size, the 5 protein marker panel can be used as baseline data for the discovery of novel biomarkers of the glioblastoma.

Functional proteomics based on protein microarray technology for biomedical research

This chapter traces a route through Proteomics from its origins to the present day. The different proteomics applications are discussed with a focus on microarray technology. Analytical microarrays, functional microarrays and reverse phase microarrays and their different applications are discussed. Several studies are mentioned where the great versatility of this approach is shown. Finally, the advantages and future challenges of microarray technology are outlined.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Advances in the application of proteomics in lung cancer

Although the incidence and mortality of lung cancer have decreased significantly in the past decade, it is still one of the leading causes of death, which greatly impairs people’s life and health. Proteomics is an emerging technology that involves the application of techniques for identifying and quantifying the overall proteins in cells, tissues and organisms, and can be combined with genomics, transcriptomics to form a multi-omics research model. By comparing the content of proteins between normal and tumor tissues, proteomics can be applied to different clinical aspects like diagnosis, treatment, and prognosis, especially the exploration of disease biomarkers and therapeutic targets. The applications of proteomics have promoted the research on lung cancer. To figure out potential applications of proteomics associated with lung cancer, we summarized the role of proteomics in studies about tumorigenesis, diagnosis, prognosis, treatment and resistance of lung cancer in this review, which will provide guidance for more rational application of proteomics and potential therapeutic strategies of lung cancer.

Proteomics and metabolomics approach in adult and pediatric glioma diagnostics

The diagnosis of glioma is mainly based on imaging methods that do not distinguish between stage and subtype prior to histopathological analysis. Patients with gliomas are generally diagnosed in the symptomatic stage of the disease. Additionally, healing scar tissue may be mistakenly identified based on magnetic resonance imaging (MRI) as a false positive tumor recurrence in postoperative patients. Current knowledge of molecular alterations underlying gliomagenesis and identification of tumoral biomarkers allow for their use as discriminators of the state of the organism. Moreover, a multiomics approach provides the greatest spectrum and the ability to track physiological changes and can serve as a minimally invasive method for diagnosing asymptomatic gliomas, preceding surgery and allowing for the initiation of prophylactic treatment. It is important to create a vast biomarker library for adults and pediatric patients due to their metabolic differences. This review focuses on the most promising proteomic, metabolomic and lipidomic glioma biomarkers, their pathways, the interactions, and correlations that can be considered characteristic of tumor grade or specific subtype.

Biomarker discovery in highly invasive lung cancer cell through proteomics approaches

Lung cancer is one of the leading causes of cancer-related death worldwide. The most common type of lung cancer is non-small cell lung cancer (NSCLC). When NSCLC is detected, patients are typically already in a metastatic stage. Metastasized cancer is a major obstacle of effective treatment and understanding the mechanisms underlying metastasis is critical to treat cancer. Herein, we selected an invasive subpopulation from the human lung cancer cell line A549 using the transwell system and named it as A549-I5. Invasive and migratory activities of this cell line were analysed using wound healing, invasion, and migration assays. In addition, epithelial-mesenchymal transition (EMT) markers, such as Snail 1, Twist, Vimentin, N-cadherin and E-cadherin, were assessed through immunoblotting. In comparison to A549 cells, the invasive A549-I5 lung cancer cells had enhanced invasiveness, motility and EMT marker expression. Proteomic analysis identified 83 significantly differentially expressed proteins in A549-I5 cells. These identified proteins were classified according to their cellular functions and most were involved in cytoskeleton, redox regulation, protein degradation and protein folding. In summary, our results provide potential diagnostic markers and therapeutic candidates for the treatment of NSCLC metastasis. SIGNIFICANCE OF THE STUDY: When NSCLC is detected, most patients are already in a metastatic stage. Herein, we selected an invasive subpopulation from a human lung cancer cell line which had increased EMT markers as well as high wound healing, invasion and migration abilities. Proteomic analysis identified numerous proteins associated with functions in cytoskeleton, redox regulation, protein degradation and protein folding that were differentially expressed in these cells. These results may provide potential diagnostic markers and therapeutic candidates for the treatment of NSCLC metastasis.

Comparative proteomic profiling of pancreatic ductal adenocarcinoma cell lines

Pancreatic cancer is one of the most fatal cancers and is associated with limited diagnostic and therapeutic modalities. Currently, gemcitabine is the only effective drug and represents the preferred first-line treatment for chemotherapy. However, a high level of intrinsic or acquired resistance of pancreatic cancer to gemcitabine can contribute to the failure of gemcitabine treatment. To investigate the underlying molecular mechanisms for gemcitabine resistance in pancreatic cancer, we performed label-free quantification of protein expression in intrinsic gemcitabine-resistant and - sensitive human pancreatic adenocarcinoma cell lines using our improved proteomic strategy, combined with filter-aided sample preparation, single-shot liquid chromatography-mass spectrometry, enhanced spectral counting, and a statistical method based on a power law global error model. We identified 1931 proteins and quantified 787 differentially expressed proteins in the BxPC3, PANC-1, and HPDE cell lines. Bioinformatics analysis identified 15 epithelial to mesenchymal transition (EMT) markers and 13 EMT-related proteins that were closely associated with drug resistance were differentially expressed. Interestingly, 8 of these proteins were involved in glutathione and cysteine/methionine metabolism. These results suggest that proteins related to the EMT and glutathione metabolism play important roles in the development of intrinsic gemcitabine resistance by pancreatic cancer cell lines.