http://li.uscap.org/article/S0023683722002550/pdf

High-throughput proteomics: a methodological mini-review.

Altered expression and function of the transcription factor cyclic AMP response-binding protein (CREB) has been identified to play an important role in cancer and is associated with the overall survival and therapy response of tumor patients. This review focuses on the expression and activation of CREB under physiologic conditions and in tumors of distinct origin as well as the underlying mechanisms of CREB regulation by diverse stimuli and inhibitors. In addition, the clinical relevance of CREB is summarized, including its use as a prognostic and/or predictive marker as well as a therapeutic target.

/pdf/what-turns-creb-on-and-off-and-why-does-it-matter-3ncgh5hqgr.pdf

What turns CREB on? And off? And why does it matter?

In the past decades, several ground breaking discoveries in life science were made. The completion of sequencing the human genome certainly belongs to the key tasks successfully completed, representing a true milestone in the biomedicine. The accomplishment of the complete genome also brings along a new, even more challenging task for scientists: The characterization of the human proteome. Proteomics, the main tool for proteome research, is a relatively new and extremely dynamically evolving branch of science, focused on the evaluation of gene expression at proteome level. Due to the specific properties of proteins, current proteomics deals with different issues, such as protein identification, quantification, characterization of post-translational modification, structure and function elucidation, and description of possible interactions. This field incorporates technologies that can be applied to serum and tissue in order to extract important biological information in the form of biomarkers to aid clinicians and scientists in understanding the dynamic biology of their system of interest, such as a patient with cancer. The present review article provides a detail description of proteomics and its role in cancer research.

Proteomics: A new perspective for cancer

Genomic, proteomic, and other omic-based approaches are now broadly used in biomedical research to facilitate the understanding of disease mechanisms and identification of molecular targets and biomarkers for therapeutic and diagnostic development. While the Omics technologies and bioinformatics tools for analyzing Omics data are rapidly advancing, the functional analysis and interpretation of the data remain challenging due to the inherent nature of the generally long workflows of Omics experiments. We adopt a strategy that emphasizes the use of curated knowledge resources coupled with expert-guided examination and interpretation of Omics data for the selection of potential molecular targets. We describe a downstream workflow and procedures for functional analysis that focus on biological pathways, from which molecular targets can be derived and proposed for experimental validation.

/pdf/omics-based-molecular-target-and-biomarker-identification-9k3w88qvrh.pdf

Omics-Based Molecular Target and Biomarker Identification

The exploration of the molecular mechanisms and signaling pathways on lung cancer is very important for developing new strategies of diagnosis and treatment to this disease, such as finding valuable lung cancer markers and molecularly targeted therapies. Previously, a number of studies disclose that heat shock protein 90 (Hsp90) is upregulated in cancer cells, tissues and serum of lung cancer patients, and its upregulation intimately correlates with the occurrence, development and outcome of lung cancer. On the contrary, inhibition of Hsp90 can suppress cell proliferation, motility and metastasis of lung cancer and promote apoptosis of lung cancer cells via complex signaling pathways. In addition, a series of Hsp90 inhibitors have been investigated as effective molecular targeted therapy tactics fighting against lung cancer. This review, systematically summarizes the role of Hsp90 in lung cancer, the molecular mechanisms and development of anti-Hsp90 treatment in lung cancer.

/pdf/molecular-mechanism-and-targeted-therapy-of-hsp90-involved-r4u0p8aagk.pdf

Molecular mechanism and targeted therapy of Hsp90 involved in lung cancer: New discoveries and developments (Review).

Cancer is a multifaceted disease that results from dysregulated normal cellular signaling networks caused by genetic, genomic and epigenetic alterations at cell or tissue levels. Uncovering the underlying protein signaling network changes, including cell cycle gene networks in cancer, aids in understanding the molecular mechanism of carcinogenesis and identifies the characteristic signaling network signatures unique for different cancers and specific cancer subtypes. The identified signatures can be used for cancer diagnosis, prognosis, and personalized treatment. During the past several decades, the available technology to study signaling networks has significantly evolved to include such platforms as genomic microarray (expression array, SNP array, CGH array, etc.) and proteomic analysis, which globally assesses genetic, epigenetic, and proteomic alterations in cancer. In this review, we compared Pathway Array analysis with other proteomic approaches in analyzing protein network involved in cancer and its utility serving as cancer biomarkers in diagnosis, prognosis and therapeutic target identification. With the advent of bioinformatics, constructing high complexity signaling networks is possible. As the use of signaling network-based cancer diagnosis, prognosis and treatment is anticipated in the near future, medical and scientific communities should be prepared to apply these techniques to further enhance personalized medicine.

/pdf/proteomics-pathway-array-and-signaling-network-based-3tv8smefjb.pdf

Proteomics, pathway array and signaling network-based medicine in cancer

Background: Current histopathological classification and TNM staging have limited accuracy in predicting survival and stratifying patients for appropriate treatment. The goal of the study is to determine whether the expression pattern of functionally important regulatory proteins can add additional values for more accurate classification and prognostication of non-small lung cancer (NSCLC). Methods: The expression of 108 proteins and phosphoproteins in 30 paired NSCLC samples were assessed using Protein Pathway Array (PPA). The differentially expressed proteins were further confirmed using a tissue microarray (TMA) containing 94 NSCLC samples and were correlated with clinical data and survival. Results: Twelve of 108 proteins (p-CREB(Ser133), p-ERK1/2(Thr202/Tyr204), Cyclin B1, p-PDK1(Ser241), CDK4, CDK2, HSP90, CDC2p34, β-catenin, EGFR, XIAP and PCNA) were selected to build the predictor to classify normal and tumor samples with 97% accuracy. Five proteins (CDC2p34, HSP90, XIAP, CDK4 and CREB) were confirmed to be differentially expressed between NSCLC (n=94) and benign lung tumor (n=19). Over-expression of CDK4 and HSP90 in tumors correlated with a favorable overall survival in all NSCLC patients and the over-expression of p-CREB(Ser133) and CREB in NSCLC correlated with a favorable survival in smokers and those with squamous cell carcinoma, respectively. Finally, the four proteins (CDK4, HSP90, p-CREB and CREB) were used to calculate the risk score of each individual patient with NSCLC to predict survival. Conclusion: In summary, our data demonstrated a broad disturbance of functionally important regulatory proteins in NSCLC and some of these can be selected as clinically useful biomarkers for diagnosis, classification and prognosis.

Protein signature for non-small cell lung cancer prognosis.

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Proteomics, pathway array and signaling network-based medicine in cancer

Protein signature for non-small cell lung cancer prognosis.