Panomics reveals patient individuality as the major driver of colorectal cancer progression

Abstract

Background: Colorectal cancer (CRC) is one of the most prevalent cancers, with over one million new cases per year. Overall, prognosis of CRC largely depends on the disease stage and metastatic status. As precision oncology for patients with CRC continues to improve, this study aimed to integrate genomic, transcriptomic, and proteomic analyses to identify significant differences in expression during CRC progression using a unique set of paired patient samples while considering tumour heterogeneity.

Methods: We analysed fresh-frozen tissue samples prepared under strict cryogenic conditions of matched healthy colon mucosa, colorectal carcinoma, and liver metastasis from the same patients. Somatic mutations of known cancer-related genes were analysed using Illumina's TruSeq Amplicon Cancer Panel; the transcriptome was assessed comprehensively using Clariom D microarrays. The global proteome was evaluated by liquid chromatography-coupled mass spectrometry (LC‒MS/MS) and validated by two-dimensional difference in-gel electrophoresis. Subsequent unsupervised principal component clustering, statistical comparisons, and gene set enrichment analyses were calculated based on differential expression results.

Results: Although panomics revealed low RNA and protein expression of CA1, CLCA1, MATN2, AHCYL2, and FCGBP in malignant tissues compared to healthy colon mucosa, no differentially expressed RNA or protein targets were detected between tumour and metastatic tissues. Subsequent intra-patient comparisons revealed highly specific expression differences (e.g., SRSF3, OLFM4, and CEACAM5) associated with patient-specific transcriptomes and proteomes.

Conclusion: Our research results highlight the importance of inter- and intra-tumour heterogeneity as well as individual, patient-paired evaluations for clinical studies. In addition to changes among groups reflecting CRC progression, we identified significant expression differences between normal colon mucosa, primary tumour, and liver metastasis samples from individuals, which might accelerate implementation of precision oncology in the future.

Keywords: Biomarkers; Colorectal cancer; Metastasis; Panomics; Patient individuality; Tumour heterogeneity.

Fig. 1

Unsupervised principal component analysis (a) and volcano plots of differentially expressed genes between all three group comparisons for NM, T, and LM (b–d). The PCA plot displays all four individual patients (P1, blue; P2, yellow; P3, purple; P4, grey). The X- and y-axes show the first and second principal components, respectively. Volcano plots are presented with the fold-change of the corresponding comparison in logarithmic scale (x-axis) against the q-value (y-axis) of b tumour vs. normal mucosa, c metastasis vs. normal mucosa, and d metastasis vs. tumour comparisons. Significance thresholds (q-value < 0.01 and |log₂FC| threshold of > 2) are indicated by dashed lines. Genes passing these cut-offs were considered significant and coloured in yellow. Genes passing the q-value but not the log₂FC threshold are coloured in rose. Genes that were not significant but passed the log₂FC threshold are indicated in blue

Fig. 2

Unsupervised principal component analysis (a) and volcano plots of differentially expressed proteins between all three group comparisons for NM, T, and LM (b–d). The PCA plot displays all four individual patients (P1, blue; P2, yellow; P3, purple; P4, grey). The X- and y-axes show the first and second principal components, respectively. Volcano plots are presented with the fold-change of the corresponding comparison in logarithmic scale (x-axis) against the q-value (y-axis) of b tumour vs. normal mucosa, c metastasis vs. normal mucosa, and d metastasis vs. tumour comparisons. Significance thresholds (q-value < 0.01 and |log₂FC| threshold of > 2) are indicated by dashed lines. Proteins passing these cut-offs were considered significant and coloured in yellow. Proteins passing the q-value but not the log₂FC threshold are coloured in rose. Proteins that were not significant but passed the log₂FC cut-off are indicated in blue

Fig. 3

Overlap of the transcriptome and proteome data showing significantly expressed targets for NM vs. T (a) and NM vs. LM (b) group comparisons. NM, normal mucosa; T, tumour; LM, liver metastasis

Fig. 4

GAGE against HALLMARK gene sets using protein expression data for all two-group comparisons and all patients