top of page

Colorectal cancer biomarkers and targets: a multi-omics review

Updated: Oct 22, 2023

For years, colorectal cancer has been one of the leading causes of cancer-related deaths worldwide, even though the disease is relatively slow growing and can often be removed via surgery and adjuvant therapy if caught early.

If caught early”. That’s right, the prognosis of the disease depends on which stage the patients are diagnosed. Treatment failures often happen as the disease progresses. As such, colorectal cancer research today is racing towards improving our understanding of the underlying mechanisms of colorectal cancer, to identify more effective colorectal cancer biomarkers for early detection of the disease and better therapeutic approaches.

Aiming to address that goal with a more comprehensive approach, we conducted a study combining different -omics datasets of colorectal cancer (Table 1) using our platform CDIAM Multi-Omics Studio. Interestingly, our study was able to identify some predominant signalling pathways, potential colorectal cancer biomarkers and therapeutic targets across multiple -omics experiments.

We are excited to share our findings in the paper below and summarize the key insights with this blog post.

Table 1. Summary of multi-omics CRC datasets

1. Major hallmarks for CRC progression: Dysregulation of cell cycle

We identified several significant pathways representing either positively or negatively affected biological processes in colorectal cancer (CRC). Interestingly, most shared significant pathways were found between bulk RNA and scRNA datasets. These pathways were involved in the cell cycle process: Polo-like kinase mediated events, NCI-PIDv2 FOXM1 transcription factor network (v2.0), NCI-PIDv2 PLK1 signalling events (v2.0), retinoblastoma gene in cancer and unwinding of DNA (Table 2). Indeed, previous studies also observed the overexpression of both PLK1 and FOXM1 in tumors including CRC, and the deletion or inactivation of retinoblastoma protein in CRC sample tissues (1, 2).

Table 2. Shared significant signaling pathways generated from up-regulated DEGs across all datasets

2. Highest scoring CRC targets: CES2, PPARD and CTNNB1

Next, we submitted the DEGs to the Pathway2Target (P2T) pipeline in CDIAM to identify potential CRC targets (7). We performed P2T separately for up- and down-regulated DEGs respectively as we wanted to identify targets with specific indications, i.e., to stimulate or to inhibit. Finally, we combined different target results using the Target Priority Pipeline (Figure 1).

From our P2T analysis, carboxylesterase 1 and 2 (CES1 and CES2) were ranked as the most potential targets for CRC (Table 3). Surprisingly, CES2 is mainly responsible for the conversion of CPT-11, a water-soluble carbamate prodrug derivative that is often used in combination with 5-fluorouracil, to a potent topoisomerase I inhibitor, SN-38, for the treatment of metastatic colon cancer (8-10). This indeed confirmed CES2 biological relevance in CRC, proposing its vital role in the efficiency of using CPT-11 to treat metastatic CRC.

Interestingly, we also found peroxisome proliferator–activated receptor–δ (PPARD) and β-catenin (CTNNB1) as the third- and fifth-highest scoring potential target for CRC, respectively. It has been long known that β-catenin is a functional effector molecule of Wnt signalling, the most representative signalling pathways and driver of CRC (11). In a recent study by Liu et al (2020), the relationship between PPARD and β-catenin was also highlighted in which the deletion of PPARD caused a reduction in β-catenin activation, consequently suppressing CRC, while the overexpression of PPARD induced an opposite result (12). As such, targeting both proteins could be highly beneficial for CRC patients.

Figure 1. Target Priority Pipeline to output the combined P2T results of up-regulated DEGs pathway enrichments.

Table 3. Rank and scores of each predicted targets generated from the Target Priority Pipeline of P2T workflow, generated from combined up-regulated pathway enrichments.

3. VEGFA as a potential colorectal cancer biomarker

From our Biomarker2Validate analysis of four -omics datasets (scRNA, bulkRNA, mutationRNA. and proteomics), vascular endothelial growth factor- A (VEGFA) was identified as the most robust colorectal cancer biomarker.

VEGFA overexpression was previously observed in colorectal cancer specimens, especially in secondary metastases including liver or lymph node tissue, consistent with its critical role in tumor progression and angiogenesis (13-16). However, the expression of VEGF by itself has not been proven to be predictive of the tumor response to anti-VEGF therapy (17, 18). Instead, VEGF expression would be examined with other factors’ expression to serve as a better prognosis marker for CRC patients. Indeed, the high expression levels of VEGFA, VEGFA receptors, VEGFR1 (FLT1) and VEGFR2 (KDR), indicated a very poor CRC prognosis (19). The high levels of VEGFA and telomere repeat binding factor 2 (TRF2), regulated by the Wnt/β-catenin pathway, were demonstrated as a novel prognostic biomarker, identifying the subset of high-risk CRC patients that could benefit from other specific therapeutic regimens (20). Meanwhile, in another study examining clinical outcomes in metastatic CRC patients receiving regorafenib, an oral multi-kinase inhibitor used as salvage therapy for metastatic CRC, the decrease of baseline serum cytokine CCL5 levels and serum VEGF-A levels were found to be potential predictive markers for survival or treatment-specific toxicities in mCRC patients receiving regorafenib (21).

4. Increased crosstalk between immune cells and other cells in CRC

Consistent with the findings reported in the original paper, via CellphoneDB, significant up-regulation in the intercellular communication between immune cells such as macrophages, CD8+ T cells, Treg cells, Th17 cells as well as myofibroblasts, and other cells compared to normal mucosa was seen (Figure 3) (4).

Upon examining pairs of ligand-receptor interactions, we found that the top interactions, e.g., bone marrow stromal cell antigen 2 (BST2), CCL20-CCR6 and LILRB4, are known to modulate inflammatory processes in cancers and its expression was upregulated in CRC tissues compared to normal. He et al identified the crucial role of BST2 in communicating between CRC cells and tumor-associated macrophage 2 (TAM2s), one of tumor-infiltrating immune cells contributing to the crosstalk between cancer cells and the tumor micro-environment (22, 23). Similarly, LILRB4 is also expressed abundantly on TAMs and the deletion of LILRB4 or anti-LILRB4 antibody could improve T cells and TAMs immuneresponsiveness, increasing patients’ survival against tumor challenges (24).

Figure 3. Summary of up-regulated cell-cell communication between different cell types in CRC patients from GSE1322465. The top bar represents cell types that contain ligands, while the bottom bar represents cell types that contain receptors. The edge represents the number of significant interactions found between these cell types.


In this study, we provide a functional outlook on how the powerful workflows provided within the CDIAM multi-omics analysis software platform can facilitate multi-omics data integration analysis and interpretation. We successfully identified several important drug targets and colorectal cancer biomarkers that were consistent with previous CRC research findings, signifying that our computational workflow pipelines are reliable in terms of identifying pathways and biomarkers with clinical and pathological relevance. Still, additional future studies should be performed to validate our results.


1. G. J. Kohn, H. J. Schwartz, B. H. Ruebner, A. J. Wong, M. J. Lawson, Colonic retinoblastoma protein and proliferation in cancer and non-cancer patients. J Gastroenterol Hepatol 12, 198-203 (1997).

2. T. Parisi, R. T. Bronson, J. A. Lees, Inactivation of the retinoblastoma gene yields a mouse model of malignant colorectal cancer. Oncogene 34, 5890-5899 (2015).

3. Q.-L. Li et al., Genome-wide profiling in colorectal cancer identifies PHF19 and TBC1D16 as oncogenic super enhancers. Nat Comm 12, 6407 (2021).

4. H. O. Lee et al., Lineage-dependent gene expression programs influence the immune landscape of colorectal cancer. Nat Genet 52, 594-603 (2020).

5. B. Zhang et al., Proteogenomic characterization of human colon and rectal cancer. Nature 513, 382-387 (2014).

6. O. O. Coker et al., Altered gut metabolites and microbiota interactions are implicated in colorectal carcinogenesis and can be non-invasive diagnostic biomarkers. Microbiome 10, 35 (2022).

7. T. M. Scott, S. Jensen, B. E. Pickett, A signaling pathway-driven bioinformatics pipeline for predicting therapeutics against emerging infectious diseases. F1000Res 10, 330 (2021).

8. R. Humerickhouse, K. Lohrbach, L. Li, W. F. Bosron, M. E. Dolan, Characterization of CPT-11 hydrolysis by human liver carboxylesterase isoforms hCE-1 and hCE-2. Cancer Res 60, 1189-1192 (2000).

9. W. J. Jansen et al., CPT-11 in human colon-cancer cell lines and xenografts: characterization of cellular sensitivity determinants. Int J Cancer70, 335-340 (1997).

10. J. van Ark-Otte et al., Determinants of CPT-11 and SN-38 activities in human lung cancer cells. Br J Cancer 77, 2171-2176 (1998).

11. Q.-W. Zhang et al., EGFL6 promotes cell proliferation in colorectal cancer via regulation of the WNT/β-catenin pathway. Mol. Cancer 58, 967-979 (2019).

12. Y. Liu et al., Pleiotropic effects of PPARD accelerate colorectal tumorigenesis, progression, and invasion. Cancer Res 79, 954-969 (2019).

13. M. L. George et al., VEGF-A, VEGF-C, and VEGF-D in colorectal cancer progression. Neoplasia3, 420-427 (2001).

14. T. André et al., Vegf, Vegf-B, Vegf-C and their receptors KDR, FLT-1 and FLT-4 during the neoplastic progression of human colonic mucosa. Int J Cancer 86, 174-181 (2000).

15. Y. Takahashi, Y. Kitadai, C. D. Bucana, K. R. Cleary, L. M. Ellis, Expression of vascular endothelial growth factor and its receptor, KDR, correlates with vascularity, metastasis, and proliferation of human colon cancer. Cancer Res 55, 3964-3968 (1995).

16. V. Garcia et al., Levels of VEGF-A mRNA in plasma from patients with colorectal carcinoma as possible surrogate marker of angiogenesis. J Cancer Res Clin Oncol134, 1165-1171 (2008).

17. K. Van der Jeught, H. C. Xu, Y. J. Li, X. B. Lu, G. Ji, Drug resistance and new therapies in colorectal cancer. World J Gastroenterol 24, 3834-3848 (2018).

18. Y. Aoyagi, H. Iinuma, A. Horiuchi, R. Shimada, T. Watanabe, Association of plasma VEGF-A, soluble VEGFR-1 and VEGFR-2 levels and clinical response and survival in advanced colorectal cancer patients receiving bevacizumab with modified FOLFOX6. Oncol Lett 1, 253-259 (2010).

19. S. D. Zhang, C. M. McCrudden, C. Meng, Y. Lin, H. F. Kwok, The significance of combining VEGFA, FLT1, and KDR expressions in colon cancer patient prognosis and predicting response to bevacizumab. Onco Targets Ther 8, 835-843 (2015).

20. R. Dinami et al., TRF2 and VEGF-A: an unknown relationship with prognostic impact on survival of colorectal cancer patients. J Exp Clin Cancer Res 39, 111 (2020).

21. M. Suenaga et al., Serum VEGF-A and CCL5 levels as candidate biomarkers for efficacy and toxicity of regorafenib in patients with metastatic colorectal cancer. Oncotarget7, 34811-34823 (2016).

22. J. Galon, D. Bruni, Tumor immunology and tumor evolution: intertwined histories. Immunity 52, 55-81 (2020).

23. X. He et al., BST2 induced macrophage M2 polarization to promote the progression of colorectal cancer. Int J Biol Sci 19, 331-345 (2023).

24. N. Sharma, O. T. Atolagbe, Z. Ge, J. P. Allison, LILRB4 suppresses immunity in solid tumors and is a potential target for immunotherapy. J Exp Med 218, (2021).


bottom of page