Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy

Abstract

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Its complexity is influenced by various signal transduction networks that govern cellular proliferation, survival, differentiation, and apoptosis. The pathogenesis of CRC is a testament to the dysregulation of these signaling cascades, which culminates in the malignant transformation of colonic epithelium. This review aims to dissect the foundational signaling mechanisms implicated in CRC, to elucidate the generalized principles underpinning neoplastic evolution and progression. We discuss the molecular hallmarks of CRC, including the genomic, epigenomic and microbial features of CRC to highlight the role of signal transduction in the orchestration of the tumorigenic process. Concurrently, we review the advent of targeted and immune therapies in CRC, assessing their impact on the current clinical landscape. The development of these therapies has been informed by a deepening understanding of oncogenic signaling, leading to the identification of key nodes within these networks that can be exploited pharmacologically. Furthermore, we explore the potential of integrating AI to enhance the precision of therapeutic targeting and patient stratification, emphasizing their role in personalized medicine. In summary, our review captures the dynamic interplay between aberrant signaling in CRC pathogenesis and the concerted efforts to counteract these changes through targeted therapeutic strategies, ultimately aiming to pave the way for improved prognosis and personalized treatment modalities in colorectal cancer.

Fig. 1

Initiation and development of colorectal carcinogenesis. This Figure illustrates the initiation and development of colorectal carcinogenesis over various timeframes. It begins with a normal colonic epithelium, which can transform into a small adenoma over 30–60 years (initiation phase). This can progress to a large adenoma (promotion phase) and further develop into cancer (progression phase) within 10–20 years. Finally, the cancer can metastasize to other parts of the body within 0–5 years (metastasis phase)

Fig. 2

Schematic overview of the diverse signaling cascades implicated in colorectal carcinogenesis. This panel showcases various pathways, including the Wnt, IGF2, ErbB, TGF-β, Notch, Hedgehog, and TNFα pathways. It details how extracellular signals are transmitted through receptors and intracellular molecules to the nucleus, emphasizing the complexity and interconnectedness of these signaling networks in the development and progression of colorectal cancer

Fig. 3

Comprehensive schematic depicting the genetic architecture and heritability of colorectal cancer. This schematic illustrates the genetic factors involved in familial and sporadic colorectal cancer. It categorizes genes based on their association with specific signaling pathways: Wnt signaling pathway (blue), MAPK signaling pathway (green), DNA repair/fidelity of DNA replication (red), and TGF-β/BMP signaling pathway (purple). Familial cases include genes like APC-FAP, MSH6/MLH6, and SMAD2, while sporadic cases involve genes such as ATF1, SMAD7, and TPD52L3. This visual aids in understanding the complex genetic landscape contributing to colorectal cancer

Fig. 4

The landscape of epigenetic modulation in colorectal cancer signaling cascades. This figure illustrates the epigenetic mechanisms regulating gene expression in colorectal cancer, including DNA methylation, histone modifications, lncRNAs, and miRNAs. a DNA methylation affects gene expression through DNA methyltransferases (DNMT); b histone acetyltransferases (HAT) and histone deacetylases (HDAC) regulate chromatin states via specific histone marks (e.g., H3K27, H3K4, H3K9); c lncRNAs are involved in transcriptional activation and decoy mechanisms; d miRNAs, transcribed by RNA polymerase II and processed by Drosha and DGCR8, inhibit mRNA translation and promote degradation. These mechanisms together form the complex landscape of epigenetic regulation in colorectal cancer

Fig. 5

Interplay between colorectal cancer pathogenesis and the gut microbiota. This figure illustrates the interaction between various gut microbiota and the development of colorectal cancer. Specific bacteria, such as Fusobacterium nucleatum, Escherichia coli (pks+ strains), Bacteroides fragilis, Streptococcus gallolyticus, Enterococcus faecalis, Peptostreptococcus anaerobius, and Helicobacter pylori, produce factors that contribute to cancer pathogenesis. These factors include FadA adhesin, colibactin, B. fragilis toxin (BFT), extracellular superoxide, and cytotoxin-associated gene product (CagA), which lead to processes like Wnt/β-catenin signaling activation, NF-κB signaling activation, IL-8 secretion, IL-1β secretion, DNA damage, chromosomal instability, genotoxic stress, and inflammation. The Figure underscores the significant role of gut microbiota in influencing colorectal cancer pathways

Fig. 6

Therapeutic modulation of the gut microbiota in colorectal cancer management. This graph outlines prognostic/predictive biomarkers, CRC prevention modulation, and CRC treatment modulation

Fig. 7

Colorectal cancer: therapeutic targeting of oncogenic signaling cascades. This figure illustrates key oncogenic signaling pathways in colorectal cancer, focusing on receptor tyrosine kinases (RTKs) such as EGFR and HER2/HER3, and their downstream cascades. It highlights the targeted therapies Cetuximab and Osimertinib for EGFR, Trastuzumab and Neratinib for HER2/HER3, AMG510 for KRAS, Binimetinib for MEK1/2, as well as Alpelisib and Copanlisib, which target the PI3K pathway by inhibiting the PI3K p110α subunit. These inhibitors disrupt critical signaling cascades (Ras/Raf/MEK/ERK and PI3K/AKT/mTOR pathways) involved in cell proliferation, growth, and survival, demonstrating their potential effectiveness in treating colorectal cancer

Fig. 8

Immunotherapeutic strategies for CRC. This panel illustrates various immunotherapeutic strategies for colorectal cancer. The central circle highlights the different types of immunotherapy, including Vaccines, Oncolytic virus, Tumor-infiltrating lymphocytes, Dendritic cells/Mesenchymal cells, CAR cells, ADC, and Monoclonal antibodies. The inset on the left depicts the mechanism of action of T cells, highlighting the roles of Anti-CTLA4 and Anti-PD1 antibodies in targeting cancer cells

Fig. 9

Artificial Intelligence: a paradigm shift in colorectal cancer diagnosis, prognosis, and therapy. This graph underscores the application of Artificial Intelligence in colorectal cancer diagnosis, prognosis, and therapy. The diagram details AI’s role in radiography, endoscopy, and pathology for diagnosis. The prognosis section depicts AI analyzing clinical profiles, pathology reports, and omics data to create integrative survival models, which predict patient outcomes and guide personalized treatment plans for colorectal cancer. It also illustrates the process of using AI for treatment, from analyzing clinical samples and health data to identifying drug candidates and developing personalized treatment plans