Cancer proteome-expression database: Genome Medicine Database of Japan Proteomics

Cancer biomarker development and two-dimensional difference gel electrophoresis (2D-DIGE)

Cancer results from the accumulation of genomic alterations. As the genome is functionally translated to the proteome and regulates tumor cell behavior, proteomics studies are expected to further the current understanding of the molecular mechanisms underlying carcinogenesis and cancer progression. Biomarkers are potential tools to classify cancers for therapy, predict responses to treatments, and support treatment-related decision-making. Biomarker development has been actively pursued in oncology by proteomic approaches. Two-dimensional difference gel electrophoresis (2D-DIGE) is a proteomics technique based on two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In 2D-DIGE, protein samples are labeled with distinct fluorescent dyes before fractionation via 2D-PAGE. 2D-DIGE offers advantages to identify biomarker candidates, including reproducibility, high sensitivity, comprehensiveness, and high throughput. 2D-DIGE has contributed to the establishment of tissue biomarkers, which potentially facilitate precision medicine. 2D-DIGE is thus expected to yield major advancements in cancer biomarker identification and development.

Current status of proteomics of soft tissue sarcomas

INTRODUCTION

Proteomics has been used in soft tissue sarcoma (STS) research in the attempts to improve the understanding of the disease background and develop novel clinical applications. Using various proteomics modalities, aberrant regulations of numerous intriguing proteins were identified in STSs, and the possible utilities of identified proteins as biomarkers or therapeutic targets have been explored. STS is an exceptionally diverse group of malignant diseases with highly complex molecular backgrounds and, therefore, an overview of the achievements and prospects of STS proteomics could enhance our knowledge of the possibilities and limitations of cancer proteomics. Areas covered: This review examines all STSs that have been examined using proteomics modalities, discussing unique aspects, limitations, and possible improvements of individual reports. To contribute to the current progress in cancer treatment development using novel anti-cancer drugs, proteomics plays a central role in linking cutting-edge technologies, application of proteogenomics, patient-derived cancer models, and biobanking system. Expert commentary: Therefore, proteomic-based STS research will be developed as an interdisciplinary science. STS proteomics will be further developed based on the interaction of oncologists with basic researchers in various fields, aimed at obtaining an enhanced understanding of the biology of the disease and achieving superior clinical outcomes for patients.

Sagace: a web-based search engine for biomedical databases in Japan

BACKGROUND

In the big data era, biomedical research continues to generate a large amount of data, and the generated information is often stored in a database and made publicly available. Although combining data from multiple databases should accelerate further studies, the current number of life sciences databases is too large to grasp features and contents of each database.

FINDINGS

We have developed Sagace, a web-based search engine that enables users to retrieve information from a range of biological databases (such as gene expression profiles and proteomics data) and biological resource banks (such as mouse models of disease and cell lines). With Sagace, users can search more than 300 databases in Japan. Sagace offers features tailored to biomedical research, including manually tuned ranking, a faceted navigation to refine search results, and rich snippets constructed with retrieved metadata for each database entry.

CONCLUSIONS

Sagace will be valuable for experts who are involved in biomedical research and drug development in both academia and industry. Sagace is freely available at http://sagace.nibio.go.jp/en/.

Application of proteomics to soft tissue sarcomas

Soft tissue sarcomas are rare and account for less than 1% of all malignant cancers. Other than development of intensive therapies, the clinical outcome of patients with soft tissue sarcoma remains very poor, particularly when diagnosed at a late stage. Unique mutations have been associated with certain soft tissue sarcomas, but their etiologies remain unknown. The proteome is a functional translation of a genome, which directly regulates the malignant features of tumors. Thus, proteomics is a promising approach for investigating soft tissue sarcomas. Various proteomic approaches and clinical materials have been used to address clinical and biological issues, including biomarker development, molecular target identification, and study of disease mechanisms. Several cancer-associated proteins have been identified using conventional technologies such as 2D-PAGE, mass spectrometry, and array technology. The functional backgrounds of proteins identified were assessed extensively using in vitro experiments, thus supporting expression analysis. These observations demonstrate the applicability of proteomics to soft tissue sarcoma studies. However, the sample size in each study was insufficient to allow conclusive results. Given the low frequency of soft tissue sarcomas, multi-institutional collaborations are required to validate the results of proteomic approaches.

dbDEPC 2.0: updated database of differentially expressed proteins in human cancers

A large amount of differentially expressed proteins (DEPs) have been identified in various cancer proteomics experiments, curation and annotation of these proteins are important in deciphering their roles in oncogenesis and tumor progression, and may further help to discover potential protein biomarkers for clinical applications. In 2009, we published the first database of DEPs in human cancers (dbDEPCs). In this updated version of 2011, dbDEPC 2.0 has more than doubly expanded to over 4000 protein entries, curated from 331 experiments across 20 types of human cancers. This resource allows researchers to search whether their interested proteins have been reported changing in certain cancers, to compare their own proteomic discovery with previous studies, to picture selected protein expression heatmap across multiple cancers and to relate protein expression changes with aberrance in other genetic level. New important developments include addition of experiment design information, advanced filter tools for customer-specified analysis and a network analysis tool. We expect dbDEPC 2.0 to be a much more powerful tool than it was in its first release and can serve as reference to both proteomics and cancer researchers. dbDEPC 2.0 is available at http://lifecenter.sgst.cn/dbdepc/index.do.

Proteomic study identified HSP 70 kDa protein 1A as a possible therapeutic target, in combination with histone deacetylase inhibitors, for lymphoid neoplasms

Histone deacetylase inhibitors (HDACi) demonstrate possible anticancer activities in various malignancies including lymphoid neoplasms. However, the anticancer effects of HDACi are often limited, and combination therapy with other drugs has been undertaken to improve the outcome of patients. Here we conducted proteomic investigation of 33 lymphoid cell lines to identify novel therapeutic targets for enhancing the effects of HDACi. Using the proteomic data in our published 2D-DIGE database, we examined the proteins associated with resistance to valproic acid (VPA). The lymphoid neoplasm cell lines in the database were grouped according to their sensitivity to VPA treatment. A comparative proteomic study of the cell line groups resulted in the identification of 10 protein spots, whose intensity was associated with chemosensitivity. Among the identified proteins, HSPA1A showed higher expression in cell lines with resistance to VPA, and the results were validated by Western blotting. In vitro experiments demonstrated that treatment with KNK-437, an inhibitor of HSPA1A, enhanced the cytotoxic effects of VPA, as well as vorinostat, in the lymphoid neoplasm cell line. Treatment with KNK-437 facilitated the apoptotic effects of VPA. In conclusion, we identified HSPA1A as a possible therapeutic target, in combination with HDACi, for lymphoid neoplasms.

The grand challenge to decipher the cancer proteome

The quest to decipher protein alterations in cancer has spanned well over half a century. The vast dynamic range of protein abundance coupled with a plethora of isoforms and disease heterogeneity have been formidable challenges. Progress in cancer proteomics has substantially paralleled technological developments. Advances in analytical techniques and the implementation of strategies to de-complex the proteome into manageable components have allowed proteins across a wide dynamic range to be explored. The massive amounts of data that can currently be collected through proteomics allow the near-complete definition of cancer subproteomes, which reveals the alterations in signalling and developmental pathways. This allows the discovery of predictive biomarkers and the annotation of the cancer genome based on proteomic findings. There remains a considerable need for infrastructure development and the organized collaborative efforts to efficiently mine the cancer proteome.

Genome-wide germline analyses on cancer susceptibility and GeMDBJ database: Gastric cancer as an example

The power of an SNP-based genome-wide association study (GWAS) was first demonstrated in Japan using the JSNP database and is currently a major strategy adopted around the world for a number of common diseases including cancers. The hypothesis-free strategy can lead us to a novel hypothesis for carcinogenesis and may contribute to identifying a high risk group for research and, in the future, practice of personalized prevention. We performed a GWAS on diffuse-type gastric cancer and identified a significant association with SNPs in the PSCA (prostate stem cell antigen) gene. The association was validated by a Korean gastric case-control analysis. The PSCA protein is expressed predominantly in the stem cell/precursor-rich region of the gastric epithelium, which is considered as the origin of diffuse-type gastric cancer, and showed tumor suppressor-like characteristics. Individuals with a low PSCA promoter activity are susceptible to diffuse-type gastric cancer. By contrast, the polymorphism does not significantly predispose to intestinal-type gastric cancer, congruous to the hypothesis of the two distinct carcinogenesis pathways for the two major types of gastric cancer. In addition to publication on a specific gene, the sharing of GWAS data through a database on the web is expected to accelerate validation and discovery by other investigators. GeMDBJ (Genome Medicine Database of Japan), started in 2005 in Japan, is one of such attempts. Moreover, the advent of "next generation" sequencers may herald a new era in which the poorly explored domains of the genetic architecture of disease susceptibility may be unveiled.