Colorectal cancer (CRC) is the third most common cancer worldwide and the leading cause of cancer-related deaths. Recently, several studies have demonstrated that gut microbiota can alter CRC susceptibility and progression by modulating mechanisms such as inflammation and DNA damage, and by producing metabolites involved in tumor progression or suppression. Dysbiosis of gut microbiota has been observed in patients with CRC, with a decrease in commensal bacterial species (butyrate-producing bacteria) and an enrichment of detrimental bacterial populations (pro-inflammatory opportunistic pathogens). CRC is characterized by altered production of bacterial metabolites directly involved in cancer metabolism including short-chain fatty acids and polyamines. Emerging evidence suggests that diet has an important impact on the risk of CRC development. The intake of high-fiber diets and the supplementation of diet with polyunsaturated fatty acids, polyphenols and probiotics, which are known to regulate gut microbiota, could be not only a potential mechanism for the reduction of CRC risk in a primary prevention setting, but may also be important to enhance the response to cancer therapy when used as adjuvant to conventional treatment for CRC. Therefore, a personalized modulation of the pattern of gut microbiome by diet may be a promising approach to prevent the development and progression of CRC and to improve the efficacy of antitumoral therapy.
Obesity is considered an important factor that increases the risk of colorectal cancer (CRC). So far, the association of gut microbiota with both obesity and cancer has been described independently. Nevertheless, a specific obesity-related microbial profile linked to CRC development has not been identified. The aim of this study was to determine the gut microbiota composition in fecal samples from CRC patients with (OB-CRC) and without obesity (L-CRC) compared to the microbiota profile present in non-obese healthy controls (L-HC), in order to unravel the possible relationship between gut microbiota and microbial-derived metabolite trimethylamine N-oxide (TMAO), the inflammatory status, and the intestinal permeability in the context of obesity-associated CRC. The presence of obesity does not induce significant changes in the diversity and richness of intestinal bacteria of CRC patients. Nevertheless, OB-CRC patients display a specific gut microbiota profile characterized by a reduction in butyrate-producing bacteria and an overabundance of opportunistic pathogens, which in turn could be responsible, at least in part, for the higher levels of proinflammatory cytokine IL-1β, the deleterious bacterial metabolite TMAO, and gut permeability found in these patients. These results suggest a possible role of obesity-related gut microbiota in the development of CRC, which could give new clues for the design of new diagnostic tools for CRC prevention.
Emerging evidence has suggested that dysbiosis of the gut microbiota may influence the drug efficacy of colorectal cancer (CRC) patients during cancer treatment by modulating drug metabolism and the host immune response. Moreover, gut microbiota can produce metabolites that may influence tumor proliferation and therapy responsiveness. In this study we have investigated the potential contribution of the gut microbiota and microbial-derived metabolites such as short chain fatty acids and polyamines to neoadjuvant radiochemotherapy (RCT) outcome in CRC patients. First, we established a profile for healthy gut microbiota by comparing the microbial diversity and composition between CRC patients and healthy controls. Second, our metagenomic analysis revealed that the gut microbiota composition of CRC patients was relatively stable over treatment time with neoadjuvant RCT. Nevertheless, treated patients who achieved clinical benefits from RTC (responders, R) had significantly higher microbial diversity and richness compared to non-responder patients (NR). Importantly, the fecal microbiota of the R was enriched in butyrate-producing bacteria and had significantly higher levels of acetic, butyric, isobutyric, and hexanoic acids than NR. In addition, NR patients exhibited higher serum levels of spermine and acetyl polyamines (oncometabolites related to CRC) as well as zonulin (gut permeability marker), and their gut microbiota was abundant in pro-inflammatory species. Finally, we identified a baseline consortium of five bacterial species that could potentially predict CRC treatment outcome. Overall, our results suggest that the gut microbiota may have an important role in the response to cancer therapies in CRC patients.
18 March 2021 in Clinical and Translational Oncology
New biomarkers are needed for the prognosis of advanced colorectal cancer, which remains incurable by conventional treatments. O6-methylguanine DNA methyltransferase (MGMT) methylation and protein expression have been related to colorectal cancer treatment failure and tumor progression. Moreover, the presence in these tumors of cancer stem cells, which are characterized by CD133 expression, has been associated with chemoresistance, radioresistance, metastasis, and local recurrence. The objective of this study was to determine the prognostic value of CD133 and MGMT and their possible interaction in colorectal cancer patients.
1 November 2013 in Reports of Practical Oncology and Radiotherapy
IMRT provides highly conformal dose distributions creating non uniform spatial intensity using different segments in the beam. Different retrospective studies have shown a high capability of IMRT to treat tumours close to the base of skull. Prospective studies have shown a decrease in xerostomia compared with conventional 3D conformal treatment (3DCRT). Modulation of intensity is performed by the movement of the multileaf collimator (MLC) that can deliver the radiation in different ways, such as static field segments, dynamic field segments and rotational delivery (arc therapy and tomotherapy). There are slight differences among the different techniques in terms of homogeneity, dose conformity and treatment delivery time. The best method to deliver IMRT will depend on multiple factors such as deliverability, practicality, user training and plan quality.