Comparative proteomics and molecular mechanical analysis in CDA-II induced therapy of LCI-D20 hepatocellular carcinoma model. J Cancer Res Clin Oncol. 2009;135:591-602. [PMID: 18853186 DOI: 10.1007/s00432-008-0493-0]

A novel fatty acid metabolism-related gene prognostic signature and candidate drugs for patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the deadliest cancers. Fatty acid metabolism (FAM) is associated with the development and treatment of HCC. This study aimed to build a FAM-related gene model to assess the prognosis of HCC and provide guidance for individual treatment. RNA-sequencing data of patients with HCC from The Cancer Genome Atlas and Gene Expression Omnibus database (GSE14520) were extracted as the training and validation sets, respectively. A FAM-related gene predictive signature was built, and the performance of prognostic model was assessed. The immune infiltration and drug sensitivity were also evaluated. Quantitative real-time polymerase chain reaction and western blot were performed to evaluate the levels of the model genes. A 12-gene FAM-related risk signature was constructed; patients with a higher risk score had poorer prognosis than those with a lower risk score. Risk score was shown as an independent risk factor for overall survival of HCC, and the signature was further confirmed as an effective and accurate model. A nomogram was constructed, and it exhibited the good performance in the prognostic prediction. In addition, the immune cell infiltration and sensitivity to chemotherapy drugs were correlated with different risk levels. Finally, quantitative real-time polymerase chain reaction and western blot proved the changes of above genes. Differential expression of FAM-related genes can be used to predict response to immunotherapy and chemotherapy, and improve the clinical prognosis evaluation of patients with HCC, which provides new clues for further experimental exploration and verification on FAM-related genes in HCC.

Construction and experimental verification of user-friendly molecular subtypes mediated by immune-associated genes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) accounts for third most cancer death globally, and its prognosis continues to be poor even with many novel therapeutic approaches emerging. The advent of immunotherapy seems to offer new hope, but low response rates are an unresolved problem. To gain further knoeledge of the effect of immune-related genes in HCC, we examined the connection between immune-related genes and the immune microenvironment in HCC through the HCC transcriptome dataset. The study also aimed to construct and experimentally validate user-friendly molecular subtypes mediated by immune-related genes in HCC. The immune cell infiltration patterns differs in HCC adjacent non-disease tissues and cancerous tissues. Patients with HCC could be classified into 2 subtypes: subtype A and subtype B. Specifically, subtype A shows characteristics of a hot tumor, in which the infiltration of cells exhibiting antigens and the expression of other crucial factors associated with immune function are higher than in a cold tumor. In addition, we identified Hub genes for the different subtypes and constructed a prognostic prediction model based on six genes (KLRB1, KLF2, S100A9, MSC, ANXA5, and IMPDH1). Further experimental analysis of HCC samples exhibited that the expression levels of KLF2 and ANXA5 were associated with immune cell infiltration and expression of PD-L1 in cancer tissues. Our work suggests that the expression of immune-related genes has crucial effect on the tumor microenvironment and prognosis of HCC patients and may be associated with immunotherapeutic response, which provides new clues for the widespread and effective application of immunotherapy in HCC.

Predictive proteomic biomarkers for inflammatory bowel disease-associated cancer: Where are we now in the era of the next generation proteomics?

Recent advances in genomic medicine have opened up the possibility of tailored medicine that may eventually replace traditional “one-size-fits all” approaches to the treatment of inflammatory bowel disease (IBD). In addition to exploring the interactions between hosts and microbes, referred to as the microbiome, a variety of strategies that can be tailored to an individual in the coming era of personalized medicine in the treatment of IBD are being investigated. These include prompt genomic screening of patients at risk of developing IBD, the utility of molecular discrimination of IBD subtypes among patients diagnosed with IBD, and the discovery of proteome biomarkers to diagnose or predict cancer risks. Host genetic factors influence the etiology of IBD, as do microbial ecosystems in the human bowel, which are not uniform, but instead represent many different microhabitats that can be influenced by diet and might affect processes essential to bowel metabolism. Further advances in basic research regarding intestinal inflammation may reveal new insights into the role of inflammatory mediators, referred to as the inflammasome, and the macromolecular complex of metabolites formed by intestinal bacteria. Collectively, knowledge of the inflammasome and metagenomics will lead to the development of biomarkers for IBD that target specific pathogenic mechanisms involved in the spontaneous progress of IBD. In this review article, our recent results regarding the discovery of potential proteomic biomarkers using a label-free quantification technique are introduced and on-going projects contributing to either the discrimination of IBD subtypes or to the prediction of cancer risks are accompanied by updated information from IBD biomarker research.

Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance

Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies, and patients have a dismal prognosis, with a <10% five-year survival rate. The identification of markers that can predict the potential for metastases will have a great effect in improving patient outcomes. In this study, we used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify proteins that are differentially expressed in metastatic and primary RCC. We identified 1256 non-redundant proteins, and 456 of these were quantified. Further analysis identified 29 proteins that were differentially expressed (12 overexpressed and 17 underexpressed) in metastatic and primary RCC. Dysregulated protein expressions of profilin-1 (Pfn1), 14-3-3 zeta/delta (14-3-3ζ), and galectin-1 (Gal-1) were verified on two independent sets of tissues by means of Western blot and immunohistochemical analysis. Hierarchical clustering analysis showed that the protein expression profile specific for metastatic RCC can distinguish between aggressive and non-aggressive RCC. Pathway analysis showed that dysregulated proteins are involved in cellular processes related to tumor progression and metastasis. Furthermore, preliminary analysis using a small set of tumors showed that increased expression of Pfn1 is associated with poor outcome and is a potential prognostic marker in RCC. In addition, 14-3-3ζ and Gal-1 also showed higher expression in tumors with poor prognosis than in those with good prognosis. Dysregulated proteins in metastatic RCC represent potential prognostic markers for kidney cancer patients, and a greater understanding of their involved biological pathways can serve as the foundation of the development of novel targeted therapies for metastatic RCC.

Nuclear translocation of β-catenin during mesenchymal stem cells differentiation into hepatocytes is associated with a tumoral phenotype

Wnt/β-catenin pathway controls biochemical processes related to cell differentiation. In committed cells the alteration of this pathway has been associated with tumors as hepatocellular carcinoma or hepatoblastoma. The present study evaluated the role of Wnt/β-catenin activation during human mesenchymal stem cells differentiation into hepatocytes. The differentiation to hepatocytes was achieved by the addition of two different conditioned media. In one of them, β-catenin nuclear translocation, up-regulation of genes related to the Wnt/β-catenin pathway, such as Lrp5 and Fzd3, as well as the oncogenes c-myc and p53 were observed. While in the other protocol there was a Wnt/β-catenin inactivation. Hepatocytes with nuclear translocation of β-catenin also had abnormal cellular proliferation, and expressed membrane proteins involved in hepatocellular carcinoma, metastatic behavior and cancer stem cells. Further, these cells had also increased auto-renewal capability as shown in spheroids formation assay. Comparison of both differentiation protocols by 2D-DIGE proteomic analysis revealed differential expression of 11 proteins with altered expression in hepatocellular carcinoma. Cathepsin B and D, adenine phosphoribosyltransferase, triosephosphate isomerase, inorganic pyrophosphatase, peptidyl-prolyl cis-trans isomerase A or lactate dehydrogenase β-chain were up-regulated only with the protocol associated with Wnt signaling activation while other proteins involved in tumor suppression, such as transgelin or tropomyosin β-chain were down-regulated in this protocol. In conclusion, our results suggest that activation of the Wnt/β-catenin pathway during human mesenchymal stem cells differentiation into hepatocytes is associated with a tumoral phenotype.