1.
Transcriptome and Proteome Analyses of TNFAIP8 Knockdown Cancer Cells Reveal New Insights into Molecular Determinants of Cell Survival and Tumor Progression.
Day, TF, Mewani, RR, Starr, J, Li, X, Chakravarty, D, Ressom, H, Zou, X, Eidelman, O, Pollard, HB, Srivastava, M, et al
Methods in molecular biology (Clifton, N.J.). 2017;:83-100
Abstract
Tumor necrosis factor-α-inducible protein 8 (TNFAIP8) is the first discovered oncogenic and an anti-apoptotic member of a conserved TNFAIP8 or TIPE family of proteins. TNFAIP8 mRNA is induced by NF-kB, and overexpression of TNFAIP8 has been correlated with poor prognosis in many cancers. Downregulation of TNFAIP8 expression has been associated with decreased pulmonary colonization of human tumor cells, and enhanced sensitivities of tumor xenografts to radiation and docetaxel. Here we have investigated the effects of depletion of TNFAIP8 on the mRNA, microRNA and protein expression profiles in prostate and breast cancers and melanoma. Depending on the tumor cell type, knockdown of TNFAIP8 was found to be associated with increased mRNA expression of several antiproliferative and apoptotic genes (e.g., IL-24, FAT3, LPHN2, EPHA3) and fatty acid oxidation gene ACADL, and decreased mRNA levels of oncogenes (e.g., NFAT5, MALAT1, MET, FOXA1, KRAS, S100P, OSTF1) and glutamate transporter gene SLC1A1. TNFAIP8 knockdown cells also exhibited decreased expression of multiple onco-proteins (e.g., PIK3CA, SRC, EGFR, IL5, ABL1, GAP43), and increased expression of the orphan nuclear receptor NR4A1 and alpha 1 adaptin subunit of the adaptor-related protein complex 2 AP2 critical to clathrin-mediated endocytosis. TNFAIP8-centric molecules were found to be predominately implicated in the hypoxia-inducible factor-1α (HIF-1α) signaling pathway, and cancer and development signaling networks. Thus TNFAIP8 seems to regulate the cell survival and cancer progression processes in a multifaceted manner. Future validation of the molecules identified in this study is likely to lead to new subset of molecules and functional determinants of cancer cell survival and progression.
2.
Accurate mass spectrometry based protein quantification via shared peptides.
Dost, B, Bandeira, N, Li, X, Shen, Z, Briggs, SP, Bafna, V
Journal of computational biology : a journal of computational molecular cell biology. 2012;(4):337-48
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Abstract
In mass spectrometry-based protein quantification, peptides that are shared across different protein sequences are often discarded as being uninformative with respect to each of the parent proteins. We investigate the use of shared peptides which are ubiquitous (~50% of peptides) in mass spectrometric data-sets for accurate protein identification and quantification. Different from existing approaches, we show how shared peptides can help compute the relative amounts of the proteins that contain them. Also, proteins with no unique peptide in the sample can still be analyzed for relative abundance. Our article uses shared peptides in protein quantification and makes use of combinatorial optimization to reduce the error in relative abundance measurements. We describe the topological and numerical properties required for robust estimates, and use them to improve our estimates for ill-conditioned systems. Extensive simulations validate our approach even in the presence of experimental error. We apply our method to a model of Arabidopsis thaliana root knot nematode infection, and investigate the differential role of several protein family members in mediating host response to the pathogen.