Chromosome-centric Human Proteome Project (C-HPP): Chromosome 12

Abstract

Following an official announcement of the Chromosome-centric Human Proteome Project (C-HPP), the Chromosome 12 (Ch12) Consortium has been established by five representative teams from five Asian countries including Thailand (Siriraj Hospital, Mahidol University), Singapore (National University of Singapore), Taiwan (Academia Sinica), Hong Kong (The Chinese University of Hong Kong), and India (Institute of Bioinformatics). We have worked closely together to extensively and systematically analyze all missing and known proteins encoded by Ch12 for their tissue/cellular/subcellular localizations. The target organs/tissues/cells include kidney, brain, gastrointestinal tissues, blood/immune cells, and stem cells. In the later phase, post-translational modifications and functional significance of Ch12-encoded proteins as well as their associations with human diseases (i.e., immune diseases, metabolic disorders, and cancers) will be defined. We have collaborated with other chromosome teams, Human Kidney and Urine Proteome Project (HKUPP), AOHUPO Membrane Proteomics Initiative, and other existing HUPO initiatives in the Biology/Disease-Based Human Proteome Project (B/D-HPP) to delineate functional roles and medical implications of Ch12-encoded proteins. The data set to be obtained from this multicountry consortium will be an important piece of the jigsaw puzzle to fulfill the missions and goals of the C-HPP and the global Human Proteome Project (HPP).

Quantitative Proteomic Verification of Membrane Proteins as Potential Therapeutic Targets Located in the 11q13 Amplicon in Cancers

“…Using DNA amplification analysis, we identified a series of 11q13-amplified cell lines to identify the overexpressed plasma membrane proteins using a membrane-enriched proteomics approach. The broader amplicon was defined from 0.45 to 132.32 Mb on the chromosome arm of 11q13, and the “peak” of the amplicon was defined as 60.02 to 75.92 Mb . Within this peak were 16 genes: SHANK2, CTTN, PPFIA1, FADD, ANO1, FGF3, FGF4, FGF19, ORAOV1, CCND1, MYEOV, TPCN2, MRGPRF, IGHMBP2, MRPL21, and CPT1A.…”

“…6,7 The C-HPP project is also studying the association of every chromosome in the disease setting. 6,7 In this paper, we focused in on a specific region of chromosome 11 and its relation to cancer as well as the potential to develop targets as antibody− drug conjugates. We performed a focused study on targets within the amplicon that could be potential antibody therapeutic targets in cancer.…”

“…An in-depth profiling of the chromosome 11 is currently underway as part of the Chromosome-Centric Human Proteome Project (C-HPP). , We expect that the strategy of focusing on the 11q13-amplified region can be applied more broadly, which is in accordance with the aim of the C-HPP. , A natural follow-up to this study would be to integrate the RNA-seq data of these cell lines with the proteomics data to identify new splice variants, as has been shown in breast cancer . Transmembrane targets from these various lineages could be identified that are putative antibody–drug conjugate targets.…”

“…The broader amplicon was defined from 0.45 to 132.32 Mb on the chromosome arm of 11q13, and the "peak" of the amplicon was defined as 60.02 to 75.92 Mb. 6 Within this peak were 16 genes: SHANK2, CTTN, PPFIA1, FADD, ANO1, FGF3, FGF4, FGF19, ORAOV1, CCND1, MYEOV, TPCN2, MRGPRF, IGHMBP2, MRPL21, and CPT1A. We measured the copy number of both ANO1 and CCND1, which lie within the core of the amplicon peak.…”

Proteogenomics from a bioinformatics angle: A growing field

“…To manage the size of the search database, Woo et al () proposed a splice graph approach to compile size‐limited multiple RNAseq alignment databases. Other studies use annotation information from large‐scale studies to filter (e.g., based on GENCODE (Khatun et al, )) or use a chromosome‐centric approach (C‐HPP: Chromosome‐Centric Human Proteome project (Liu et al, ; Chaiyarit et al, ; Pinto et al, )). Sequence homology (Junqueira et al, ) or sequence tag overlap (Tanner et al, ; Castellana et al, , , ) are also often used to help reduce the database size.…”