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The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Pro?ling 被引量:2
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作者 Johana A. Luna Coronell Khulan Sergelen +7 位作者 Philipp Hofe Istvan Gyurjan Stefanie Brezina Peter Hettegger Gernot Leeb Karl Mach Andrea Gsur Andreas Weinhausel 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2018年第1期73-84,共12页
Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated wi... Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, dif- ferential pathways were observed between the CRC and control samples. Furthermore, 103 DIR- AGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 "CRC genes." These data indicate that immunomies profiling on protein mieroarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology. 展开更多
关键词 Autoantibody tumorbiomarker Cancer immunology Colorectal cancer IMMUNOMICS Protein microarray
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Phenomic Imaging
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作者 Lizhen Lan Kai Feng +11 位作者 Yudan Wu Wenbo Zhang Ling Wei Huiting Che Le Xue Yidan Gao Ji Tao Shufang Qian Wenzhao Cao Jun Zhang Chengyan Wang Mei Tian 《Phenomics》 2023年第6期597-612,共16页
Human phenomics is defned as the comprehensive collection of observable phenotypes and characteristics infuenced by a complex interplay among factors at multiple scales.These factors include genes,epigenetics at the m... Human phenomics is defned as the comprehensive collection of observable phenotypes and characteristics infuenced by a complex interplay among factors at multiple scales.These factors include genes,epigenetics at the microscopic level,organs,microbiome at the mesoscopic level,and diet and environmental exposures at the macroscopic level.“Phenomic imaging”utilizes various imaging techniques to visualize and measure anatomical structures,biological functions,metabolic processes,and biochemical activities across diferent scales,both in vivo and ex vivo.Unlike conventional medical imaging focused on disease diagnosis,phenomic imaging captures both normal and abnormal traits,facilitating detailed correlations between macro-and micro-phenotypes.This approach plays a crucial role in deciphering phenomes.This review provides an overview of diferent phenomic imaging modalities and their applications in human phenomics.Additionally,it explores the associations between phenomic imaging and other omics disciplines,including genomics,transcriptomics,proteomics,immunomics,and metabolomics.By integrating phenomic imaging with other omics data,such as genomics and metabolomics,a comprehensive understanding of biological systems can be achieved.This integration paves the way for the development of new therapeutic approaches and diagnostic tools. 展开更多
关键词 PHENOMICS IMAGING GENOMICS TRANSCRIPTOMICS PROTEOMICS IMMUNOMICS Metabolomics
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