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ITRAQ-based quantitative proteomic analysis of Yamanaka factors reprogrammed breast cancer cells.

ABSTRACT: Cancer cells had been developed to be reprogrammed into embryonic stem like cells by induced pluripotent stem cells (iPSCs) technology, however, the tumor differentiation/dedifferentiation mechanisms had not yet been analyzed on a genome-wide scale. Here, we inserted the four stem cell transcription factor genes OCT4, SOX2, C-MYC and KLF4 into MCF cells (MCFs), represented a female breast cancer cell type, and obtained iPSCs (Mcfips) in about 3 weeks. By using the LC MS/MS iTRAQ technology, we analyzed the proteomic changes between MCFs and Mcfips. Of identified 4,616 proteins totally, 247 and 142 differentially expressed (DE) proteins were found in Mcfips compared with human induce pluripotent stem cells (Hips) and MCFs, respectively. 35 co-up and 10 co-down regulated proteins were recognized in DE proteins. Above DE proteins were categorized with GO functional classification annotation and KEGG metabolic pathway analysis into biological processes. In the protein interaction network, we found 37 and 39 hubs interacted with more than one protein in Mcfips comparing to Hips, in addition, 25 and 9 hubs were identified in Mcfips comparing to MCFs. Importantly, the mitochondria, ribosome and tumor suppressor proteins were found to be core regulators of tumor reprogramming, which might contribute to understand the mechanisms in relation to the occurrences and progression of a tumor. Thus, our study provided a valuable data for exploring the possibility to normalize the malignant phenotype.

SUBMITTER: Wang K

PROVIDER: S-EPMC5470971 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background:Neuroticism is a core personality trait and a major risk factor for several mental and physical diseases, particularly in females, who score higher on neuroticism than men, on average. However, a better understanding of the expression profiles of proteins in the circulating blood of different neurotic female populations may help elucidate the intrinsic mechanism of neurotic personality and aid prevention strategies on mental and physical diseases associated with neuroticism. Methods:In our study, female subjects were screened for inclusion by the Eysenck Personality Questionnaire (EPQ), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI) scales and routine physical examination. Subjects who passed the examination and volunteered to participate were grouped by neuroticism using EPQ scores (0 and 1?=?low neuroticism group; >?5?=?high neuroticism group). Proteins in serum samples of the two neuroticism groups were identified using isobaric tags for relative and absolute quantification (iTRAQ) technology. Results:A total of 410 proteins exhibited significant differences between high and low neuroticism, 236 proteins were significantly upregulated and 174 proteins were significantly downregulated. Combine the results of GO and KEGG enrichment analysis of differences proteins between high and low neuroticism with the PPI network, it could be observed that the Alpha-synuclein (SNCA), ATP7A protein (ATP7A), Guanine nucleotide-binding protein G(I)/G(S)/G(O) subunit gamma-2 (GNG2), cyclin-dependent kinase 6 (CDK6), myeloperoxidase (MPO), azurocidin (AZU1), Histone H2B type 1-H (HIST1H2BH), Integrin alpha-M (ITGAM) and Matrix metalloproteinase-9 (MMP9) might participate in the intrinsic mechanism of neuroticism by regulating response to catecholamine stimulus, catecholamine metabolic process, limbic system development and transcriptional misregulation in cancer pathway. Conclusions:Our study revealed the characteristics of the neurotic personality proteome, which might be intrinsic mechanism of the neurotic population.

Project description:Breast cancer is the most common malignancy in females, with metastasis of this type of cancer frequently proving lethal. However, there are still no effective biomarkers to predict breast cancer metastasis. The aim of the present study was, therefore, to analyze breast cancer metastasis-associated proteins and evaluate the association between protein S100-A8 and the prognosis of breast cancer. The isobaric tags for relative and absolute quantitation (iTRAQ) proteomic technique was used to analyze the differential expression of proteins between fresh primary breast tumor (PBT) tissue and fresh paired metastatic lymph nodes (PMLN) tissue. Subsequently, immunohistochemical staining was used to locate and assess the expression of protein S100-A8 in benign breast disease (n=15), primary breast cancer with (n=109) or without (n=83) metastasis, and in paired metastatic lymph nodes (n=109) formalin fixed paraffin embedded (FFPE) tissue. Staining scores were evaluated and the association between protein S100-A8 expression levels and the clinicopathological characteristics of 192 patients with breast cancer were evaluated using the ?2 test. Kaplan-Meier and Cox hazards regression analyses were utilized to investigate the association between the expression of protein S100-A8 and the prognosis of patients with breast cancer. A total of 4,837 proteins were identified using the iTRAQ proteomic technique. Among these proteins, 643 differentially expressed proteins were revealed. Protein S100-A8 expression levels were identified to differ between PBT and PMLN tissues. Immunohistochemical staining suggested a significant difference between NMBT and PMLN (P=0.002), and also between PBT and PMLN (P<0.001). Cox hazards regression model analyses suggested that histological grade (P=0.031) and nodal status (P=0.001) were risk factors for lymph nodes metastasis of breast cancer. Kaplan-Meier analyses revealed no significant relationship between protein S100-A8 expression level and overall survival rate of patients with breast cancer. In conclusion, by using the iTRAQ proteomic technique and immunohistochemistry staining, it was identified that protein S100-A8 may be associated with lymph nodes metastasis of breast cancer and be a marker for progression of breast cancer.

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ITRAQ-based quantitative proteomic analysis of Yamanaka factors reprogrammed breast cancer cells.

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