Proteogenomic characterization and comprehensive integrative genomic analysis of human colorectal cancer liver metastasis

Abstract

Background: Proteogenomic characterization and integrative and comparative genomic analysis provide a functional context to annotate genomic abnormalities with prognostic value.

Methods: Here, we analyzed the proteomes and performed whole exome and transcriptome sequencing and single nucleotide polymorphism array profiling for 2 sets of triplet samples comprised of normal colorectal tissue, primary CRC tissue, and synchronous matched liver metastatic tissue.

Results: We identified 112 CNV-mRNA-protein correlated molecules, including up-regulated COL1A2 and BGN associated with prognosis, and four strongest hot spots (chromosomes X, 7, 16 and 1) driving global mRNA abundance variation in CRC liver metastasis. Two sites (DMRTB1R202H and PARP4V458I) were revealed to frequent mutate only in the liver metastatic cohort and displayed dysregulated protein abundance. Moreover, we confirmed that the mutated peptide number has potential prognosis value and somatic variants displayed increased protein abundance, including high MYH9 and CCT6A expression, with clinical significance.

Conclusions: Our proteogenomic characterization and integrative and comparative genomic analysis provides a new paradigm for understanding human colon and rectal cancer liver metastasis.

Trial registration: ClinicalTrials, NCT02917707. Registered 28 September 2016, https://ichgcp.net/clinical-trials-registry/NCT02917707 .

Keywords: CLM; CRC; Prognosis; Proteogenomics; SAAV.

Conflict of interest statement

Ethics approval and consent to participate

The study was examined and approved by the Ethics Committee of the Shanghai Tenth People’s Hospital, Tongji University School of Medicine (SHSY-IEC-PAP-16-24). Each participant provided their written informed consent to participate in this study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interest.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1

Mass-spectrometry-based proteomics workflow. Protein was extracted from fresh CRC and paired PN tissues and was used to generate tryptic digests. The resulting tryptic peptides were fractionated using off-line bRPLC Collected fractions were pooled and used with a Thermo Orbitrap-Velos MS instrument. Raw data were processed by Perseus software and then used for database and spectral library evaluation using the Andromeda peptide search engine. Identified peptides were assembled using Maxquant software. bRPLC, basic reverse-phase (high-pressure) liquid chromatography; CRC, colorectal cancer; PN paracarcinoma normal tissue

Fig. 2

Differentially expressed proteins identified from 2 triplet sets of PN, MT and LM tissues. a The cellular distribution is shown for 4198 proteins identified by mass spectrometry, with a false discovery rate of 1.0%. Correlation analysis of the expression of 4198 proteins from MT/LM vs. PN (b) and LM vs. MT (c) samples from mass-spectrometry analysis. d Numbers of differently expressed proteins (≥2-fold difference; P value ≤0.05). e KEGG pathway analysis of the 1386 differentially expressed proteins. f Gene Ontology using STRING online analysis software classified the 1386 differentially expressed proteins in CLM according to their biological process, cellular components and molecular functions

Fig. 3

RNA sequencing and mRNA-protein correlation analysis. a Hierarchical clustering for RNA-sequencing data of 8 samples. b Significantly changed genes among three groups (MT vs. PN, MT vs. NM, and LM vs. MT) from RNA-sequencing data of 8 samples. c KEGG pathway classification enrichment analysis of 2136 differentially expressed genes in CLM. d Significantly changed genes among two groups (MT vs. PN and MT vs. NM) from TCGA RNA-sequencing data. e 362 significantly changed genes showed significant mRNA-protein correlation, with a mean Spearman’s correlation coefficient of 0.55. Among these, 48 genes were enriched in metabolism pathways

Fig. 4

Effects of copy number alterations on mRNA and protein abundance. a Copy number alterations in 6 specimens from 2 patients, including 2 sets of primary MT, matched LM and PN, were identified by chromosome microarray analysis. Blue represents amplification, red represents deletion, and purple represents loss of heterozygosity. Red boxes indicate chromosomes that contain hot spots driving global mRNA variation abundance. b Chromosomal location of 321 regions (including 8424 genes) with significant focal amplification and 209 regions (including 2560 genes) with significant focal deletion in the LM or MT groups compared with the PN group. c Correlation analysis of the CNV-mRNA-protein abundance. The 1386 significantly changed proteins showed significant mRNA-protein correlation (multiple-test adjusted P < 0.01), with a mean Spearman’s correlation coefficient of 0.53 and CNV-protein correlation (multiple-test adjusted P < 0.05), with a mean Spearman’s correlation coefficient of 0.41. d Chromosomal location of 112 copy-number changed genes with positive CNV, mRNA and protein correlation

Fig. 5

Two genes display significant focal amplification and increased mRNA-protein abundance with clinical significance and biological function. a Significant focal amplification and increased mRNA-protein abundance of 4 CNV-mRNA-protein correlated molecules in the MT group compared to the PN group. b The association of the expression levels of 4 CNV-mRNA-protein correlated molecules with overall and disease-free survival by Kaplan-Meier survival analysis. c Western blot analyze for COL1A2 or BGN overexpression in CRC cell line SW480. Wound-healing assay (d) and migration abilities (e) of the parental and COL1A2 or BGN overexpressed SW480 cells

Fig. 6

Somatic coding mutations in paired normal colorectal samples, metastatic CRC and hepatic metastatic focus. a Mutation types in 6 specimens from 2 patients, including 2 sets of PN, primary MT, and synchronous matched LM. T > A transversions were the most common nucleotide substitution. b Distribution of SNVs in exonic, intronic, UTR and splicing regions based on our RNA-sequencing data. c Distribution of indels and non-synonymous SNVs in 6 samples from 2 patients, including 2 sets of PN, primary MT, and synchronous matched LM specimens. d Numbers of MT-specific, LM-specific and MT & LM-shared indels and nonsynonymous SNVs. Mutations involved in CLM including the TLL2A302S mutation, which was identified in both the MT and LM groups (e) and the KLF11D19N mutation, which was specific for the LM cohort (f). Two frequently mutated sites (DMRTB1R202H and PARP4V458I) in the MT cohorts were identified by SNP genotype analysis, with separate mutation rates of 5.26% (2/38) (g) and 17.5% (7/40) (h)

Fig. 7

Numbers of SAAVs in paired PN, NM or MT samples. a The proportion of mutated proteins and amino acids in CRC samples were calculated by comparing LC-MS/MS data for the standard protein library and SAAV library. b Numbers of SAAVs in 21 NM, 23MT and their PN colorectal tissues. Numbers of NM-specific (c), MT-specific (d) and NM & MT-shared SAAVs (e).The mutated pepides were identified by comparing LC-MS/MS data for the standard protein library and SAAV library

Fig. 8

Impact of SNVs on protein abundance. a Expression levels of 6 NM & MT-shared mutated proteins (including MYH9, HSPA9, HSP90AB1, ATP2A2, FABP5 and XPO1) in MT samples compared with NM or PN samples. b Expression levels of 7 MT-specific mutated proteins (including CCT6A, CAT, ACTN1, JUP, ARF4, FAM3D and HLA-B) in MT samples compared with NM or PN samples. c Mutation sites of 3 genes contained within the strongest mutational hot spots. d Univariate survival analysis of overall survival and disease-free survival based on MYH9 and CCT6A levels