Quantitative proteomic profiling of paired cancerous and normal colon epithelial cells isolated freshly from colorectal cancer patients

Abstract

Purpose: The heterogeneous structure in tumor tissues from colorectal cancer (CRC) patients excludes an informative comparison between tumors and adjacent normal tissues. Here, we develop and apply a strategy to compare paired cancerous (CEC) versus normal (NEC) epithelial cells enriched from patients and discover potential biomarkers and therapeutic targets for CRC.

Experimental design: CEC and NEC cells are respectively isolated from five different tumor and normal locations in the resected colon tissue from each patient (N = 12 patients) using an optimized epithelial cell adhesion molecule (EpCAM)-based enrichment approach. An ion current-based quantitative method is employed to perform comparative proteomic analysis for each patient.

Results: A total of 458 altered proteins that are common among >75% of patients are observed and selected for further investigation. Besides known findings such as deregulation of mitochondrial function, tricarboxylic acid cycle, and RNA post-transcriptional modification, functional analysis further revealed RAN signaling pathway, small nucleolar ribonucleoproteins (snoRNPs), and infection by RNA viruses are altered in CEC cells. A selection of the altered proteins of interest is validated by immunohistochemistry analyses.

Conclusion and clinical relevance: The informative comparison between matched CEC and NEC enhances our understanding of molecular mechanisms of CRC development and provides biomarker candidates and new pathways for therapeutic intervention.

Keywords: Biomarker discovery; Colorectal cancer; Ion current-based analysis; Tumor cell enrichment.

Fig. 1

(A) Flowchart of experimental design for paired comparative proteomics analysis of isolated colorectal tumor epithelial cells and normal cells in 12 CRC patients (N=120 in total). (B) Ion current-based (ICB) quantification achieved better performance than other popular label-free quantitative methods including emPAI, NSAF, and MS2-TIC. (C) Volcano plots illustrating the accuracy of quantification using the sham dataset (10 replicate analyses randomly separated into two groups, n=5 per group) analyzed by the ICB approach. No altered proteins were determined in the sham dataset using the cutoff thresholds for discovery (p≤0.05 and ≥1.5-fold change).

Fig 2

Robust and efficient isolation of epithelial cells from fresh human colon using the Ber-EP4 antibody-based method. Histological sections (10x) of normal (A) and tumor (B) tissues from CRC patient showed highly heterogeneous tissue components especially in tumor, leading to overwhelming biological noises if comparing proteomes at tissue level. The effective and quick isolation of intact, viable normal (C) and tumor (D) epithelial cells from the tissues (40x) enabled a fair and direct proteomics comparison.

Fig 3

Optimization of protein identification for samples from 12 CRC patients. (A) Number of target and decoy proteins identified for each patient; (B) Number of target and decoy proteins identified in common from multiple patients; (C) Number of target and decoy proteins for each patient after recovering proteins identified from a single peptide in some patients while maintaining a stringent FDR control. (D) Distribution of the number of target and decoy proteins identified in common among multiple patients with and without recovery of those proteins identified in some patients from only a single peptide.

Fig. 4

Protein quantification in 12 CRC patients. (A) Distribution of protein ratios quantified from each patient; box and whiskers (whiskers: 5–95 percentile) analysis for protein ratios from each patient. (B) Number and percentage of altered proteins in each patient dataset. (C) Distribution of peptide ratios assigned to increased proteins (left) and decreased proteins (right) observed in CEC versus NEC samples in a randomly-selected patient (#4). (D) Number of proteins with the same change trend (up- or down-regulated) among 12 CRC patients.

Fig. 5

Association of proteins altered in CRC epithelial cells with canonical pathways as a result of Ingenuity Pathway Analysis. (A) Top 15 pathways associated with protein alteration; (B) Proteins associated with suppressed oxidative phosphorylation pathway; (C) Altered tricarboxylic acid cycle in colorectal tumor cells.

Fig. 6

Dysregulated networks observed in colorectal cancer cells in this study. (A) Molecular transport; (B) Liver cancer; (C) Infection by RNA virus; (D) Organismal death; (E) Oxidation of lipid; (F) RNA post-transcription modification; (G) Immune response.

Fig. 7

Immunohistochemistry analysis of S100 A9 (A&D, 10x), CEACAM7 (B&E, 10x) and DPEP-1(C&F, 10x) in normal (top row) and colorectal cancer (bottom row) cells. Images were acquired with 10x magnification. The positive staining is brown.