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. 2018 Dec 21;17(1):177.
doi: 10.1186/s12943-018-0923-9.

Comparative proteogenomic analysis of right-sided colon cancer, left-sided colon cancer and rectal cancer reveals distinct mutational profiles

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Comparative proteogenomic analysis of right-sided colon cancer, left-sided colon cancer and rectal cancer reveals distinct mutational profiles

Robin Imperial et al. Mol Cancer. .

Abstract

Right-sided colon cancer (RCC) has worse prognosis compared to left-sided colon cancer (LCC) and rectal cancer. The reason for this difference in outcomes is not well understood. We performed comparative somatic and proteomic analyses of RCC, LCC and rectal cancers to understand the unique molecular features of each tumor sub-types. Utilizing a novel in silico clonal evolution algorithm, we identified common tumor-initiating events involving APC, KRAS and TP53 genes in RCC, LCC and rectal cancers. However, the individual role-played by each event, their order in tumor development and selection of downstream somatic alterations were distinct in all three anatomical locations. Some similarities were noted between LCC and rectal cancer. Hotspot mutation analysis identified a nonsense mutation, APC R1450* specific to RCC. In addition, we discovered new significantly mutated genes at each tumor location, Further in silico proteomic analysis, developed by our group, found distinct central or hub proteins with unique interactomes among each location. Our study revealed significant differences between RCC, LCC and rectal cancers not only at somatic but also at proteomic level that may have therapeutic relevance in these highly complex and heterogeneous tumors.

Keywords: Clonal evolution; Hotspot mutations; Left-sided colon cancer; Proteomics; Rectal cancers; Right-sided colon cancer.

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Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

Ashiq Masood Advisory board and speaker Bureau Bristol-Myers Squibb and Boehringer Ingelheim, Honorarium Biocept. Janakiraman Subramanian Advisory board - Astra Zeneca, Pfizer, Boehringer Ingelheim, Alexion, Paradigm, Bristol-Myers Squibb Speakers Bureau - Astra Zeneca, Boehringer Ingelheim, Lilly Research Support - Biocept and Paradigm. Arif Hussain Advisory board – Novartis, Bayer, Astra Zeneca, Consultant – Bristol-Myers-Squibb. All other authors declare that they have no competing interest.

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Figures

Fig. 1
Fig. 1
shows ensemble-level clonal evolution trajectories in colorectal cancer using CAPRI algorithm. The events of the model are connected by dashed lines where red dotted lines denote hard and orange denotes soft exclusivity. Algorithm uses both Bayesian information criterion ‘BIC’ and Akaike information criterion ‘AIC’ as a regularization. Non-parametric bootstrap scores (NPB) are shown in the figure with hypergeometric test p-value cutoff of < 0.05. Other relations including temporal priority, probability raising are shown in Fig. 1a, b, and c and reported data in Additional file 4. 1a) clonal evolution in RCC, 1b) clonal evolution in LCC and 1c) clonal evolution in rectal cancers
Fig. 2
Fig. 2
a shows the frequency of APC hotspot the R1450 residue in (i) right-sided colon cancers, (ii) left-sided colon cancers and (iii) rectal cancers in TCGA (left) and MSKCC (right) datasets. Y-axis represent total number of mutations at each residue. b shows the mutual exclusivity of APC R1450* (APC_1450) compared to other genes of β-Catenin destruction complex in RCC. “APC_MCR” represents other APC mutations within the MCR region that are not at the 1450 residue. The bar plot above the oncoplot represents total mutations in each sample
Fig. 3
Fig. 3
shows the hub genes and neighbors in the disease-related sub-networks obtained by the most successful KDE method (in terms of precision score) in a RCC, b LCC and c rectal cancers. The genes registered in DisGeNET and experimentally confirmed for the diseases are shown with colored and larger nodes. Among these, genes that are not colored but have a red frame have a PMID value of one (e.g. have one supporting publication). There is no entry in DisGeNET for the grey colored nodes. Also, the most associated top three biological pathways, to which each module is related, are given above or below the relevant module to annotate each module

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