The human organism coexists with its microbiota in a symbiotic relationship. These polymicrobial communities are involved in many crucial functions, such as immunity, protection against pathogens, and metabolism of dietary compounds, thus maintaining homeostasis. The oral cavity and the colon, although distant anatomic regions, are both highly colonized by distinct microbiotas. However, studies indicate that oral bacteria are able to disseminate into the colon. This is mostly evident in conditions such as periodontitis, where specific bacteria, namely Fusobacterium nucrelatum and Porphyromonas gingivalis project a pathogenic profile. In the colon these bacteria can alter the composition of the residual microbiota, in the context of complex biofilms, resulting in intestinal dysbiosis. This orally-driven disruption promotes aberrant immune and inflammatory responses, eventually leading to colorectal cancer (CRC) tumorigenesis. Understanding the exact mechanisms of these interactions will yield future opportunities regarding prevention and treatment of CRC.

The intestinal microbiota consists of numerous microbial species that collectively interact with the host, playing a crucial role in health and disease. Colorectal cancer is well-known to be related to dysbiotic alterations in intestinal microbiota. It is evident that the microbiota is significantly affected by colorectal surgery in combination with the various perioperative interventions, mainly mechanical bowel preparation and antibiotic prophylaxis. The altered postoperative composition of intestinal microbiota could lead to an enhanced virulence, proliferation of pathogens, and diminishment of beneficial microorganisms resulting in severe complications including anastomotic leakage and surgical site infections. Moreover, the intestinal microbiota could be utilized as a possible biomarker in predicting long-term outcomes after surgical CRC treatment. Understanding the underlying mechanisms of these interactions will further support the establishment of genomic mapping of intestinal microbiota in the management of patients undergoing CRC surgery.

Gastrointestinal (GI) cancers, such as colorectal and gastric cancers, pose significant global health challenges due to their high rates of incidence and mortality. Even with advancements in treatment and early detection, many patients still face poor outcomes, highlighting the critical need for new biomarkers and therapeutic targets. Telomere length (TL) and telomerase activity (TA) have gained attention in this context. Telomeres, protective nucleotide sequences at chromosome ends, shorten with each cell division, leading to cellular aging. Telomerase, a ribonucleoprotein enzyme, counteracts this shortening by adding telomeric repeats, a process tightly regulated in normal cells but often dysregulated in cancer. This review critically evaluates the role of TL and TA in the pathogenesis of GI cancers, examining their potential as diagnostic, prognostic, and predictive biomarkers. It explores how alterations in telomere biology contribute to the initiation and progression of GI tumors and assesses the therapeutic implications of targeting telomerase. By integrating findings from diverse studies, this review aims to elucidate the intricate relationship between telomere dynamics and gastrointestinal carcinogenesis, offering insights into how TL and TA could be leveraged to enhance the early detection, treatment, and prognosis of GI cancers.

Intestinal dysbiosis is a major contributor to colorectal cancer (CRC) development, leading to bacterial translocation into the bloodstream. This study aimed to evaluate the presence of circulated bacterial DNA (cbDNA) in CRC patients (n = 75) and healthy individuals (n = 25). DNA extracted from peripheral blood was analyzed using PCR, with specific primers targeting 16S rRNA, Escherichia coli (E. coli), and Fusobacterium nucleatum (F. nucleatum). High 16S rRNA and E. coli detections were observed in all patients and controls. Only the detection of F. nucleatum was significantly higher in metastatic non-excised CRC, compared to controls (p < 0.001), non-metastatic excised CRC (p = 0.023), and metastatic excised CRC (p = 0.023). This effect was mainly attributed to the presence of the primary tumor (p = 0.006) but not the presence of distant metastases (p = 0.217). The association of cbDNA with other clinical parameters or co-morbidities was also evaluated, revealing a higher detection of E. coli in CRC patients with diabetes (p = 0.004). These results highlighted the importance of bacterial translocation in CRC patients and the potential role of F. nucleatum as an intratumoral oncomicrobe in CRC.

Gastrointestinal (GI) cancers, such as colorectal and gastric cancers, pose significant global health challenges due to their high rates of incidence and mortality. Even with advancements in treatment and early detection, many patients still face poor outcomes, highlighting the critical need for new biomarkers and therapeutic targets. Telomere length (TL) and telomerase activity (TA) have gained attention in this context. Telomeres, protective nucleotide sequences at chromo-some ends, shorten with each cell division, leading to cellular aging. Telomerase, a ribonucleoprotein enzyme, counteracts this shortening by adding telomeric repeats, a process tightly regulated in normal cells but often dysregulated in cancer. This review critically evaluates the role of TL and TA in the pathogenesis of GI cancers, examining their potential as diagnostic, prognostic, and predictive biomarkers. It explores how alterations in telomere biology contribute to the initiation and progression of GI tumors and assesses the therapeutic implications of targeting telomerase. By integrating findings from diverse studies, this review aims to elucidate the intricate relationship between telomere dynamics and gastrointestinal carcinogenesis, offering in-sights into how TL and TA could be leveraged to enhance the early detection, treatment, and prognosis of GI cancers.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, although advances in molecular profiling and artificial intelligence (AI) are now reshaping precision oncology in ways that promise better patient outcomes. This review synthesises contemporary evidence on next-generation biomarkers and AI applications in CRC across multi-omic data integration, liquid biopsy, computational pathology, radiomics and clinical implementation. Several findings stand out. Integrated multi-omic approaches combining genomics, transcriptomics, proteomics, metabolomics and microbiomics outperform single-omic biomarkers for predicting prognosis and treatment response. Machine learning (ML) and deep learning (DL) models achieve clinical-grade performance for molecular biomarker prediction directly from routine histopathology, with a pooled area under the receiver operating characteristic curve (AUROC) of 0.94 for microsatellite instability (MSI) detection. Circulating tumour DNA (ctDNA) monitoring enables minimal residual disease (MRD) detection and real-time treatment guidance, postoperative ctDNA status separating a two-year recurrence-free survival of 91.1% from 50.4%; randomised evidence further shows that ctDNA-guided management can safely reduce adjuvant chemotherapy use in stage II colon cancer. Radiomics and pathomics extract prognostically significant quantitative features from imaging and histopathology, permitting non-invasive tumour characterisation, while multimodal models integrating clinical, genomic, imaging and pathological data support individualised treatment selection. MSI-high (MSI-H) status predicts exceptional immunotherapy benefit, carrying an overall survival hazard ratio of 0.35 against chemotherapy. Considerable difficulties nonetheless persist: harmonising data across institutions, generalising models to diverse populations, algorithmic bias and regulatory frameworks suited to clinical AI. Priorities for the coming years are prospective validation of AI-guided treatment algorithms, integration of spatial transcriptomics and single-cell approaches, federated learning to support multi-institutional collaboration without compromising privacy, and standardised protocols for biomarker testing and interpretation.