Fecal microbial biomarkers combined with multi-target stool DNA test improve diagnostic accuracy for colorectal cancer

Innovative approaches in colorectal cancer screening: advances in detection methods and the role of artificial intelligence

Colorectal cancer (CRC) is the third most prevalent cancer globally and poses a significant health threat, making early detection crucial. This review paper explored emerging detection methods for early screening of CRC, including gut microbiota, metabolites, genetic markers, and artificial intelligence (AI)-based technologies. Current screening methods have their respective advantages and limitations, particularly in detecting precursors. First, the importance of the gut microbiome in CRC progression is discussed, highlighting how specific microbial alterations can serve as biomarkers for early detection, potentially enhancing diagnostic accuracy when combined with traditional screening methods. Next, research on metabolic reprogramming illustrates the relationship between metabolic changes and CRC, with studies developing metabolite-based detection models that show good sensitivity for early diagnosis. In terms of genetic markers, methylated DNA markers like SEPTIN9 have demonstrated high sensitivity, although further validation across diverse populations is necessary. Lastly, AI technology has shown immense potential in improving adenoma detection rates, significantly enhancing the quality of colonoscopic examinations through image recognition techniques. This review aims to provide a comprehensive perspective on new strategies for CRC screening, emphasizing the potential of noninvasive detection technologies and the prospects of AI and genomics in clinical applications. Despite several challenges, this review advocates for future large-scale prospective studies to validate the effectiveness and cost-effectiveness of these new screening methods while promoting the implementation of screening protocols tailored to individual characteristics.

Periodontitis Exacerbates Colorectal Cancer by Altering Gut Microbiota-Derived Metabolomics in Mice

AIM

The correlation between periodontitis and colorectal cancer (CRC) has drawn widespread attention. However, how periodontitis affects CRC progression remains unclear.

METHODS

C57BL/6 mice were used to establish experimental periodontitis and CRC model. Histological alterations of periodontium and colon were observed by hematoxylin and eosin staining. Micro-computed tomography (micro-CT) was applied to evaluate alveolar bone loss (ABL). Tumor growth was detected by immunofluorescence. Gut bacteria were analyzed using 16S rRNA sequencing. Gas chromatography-mass spectrometry (GC-MS) was performed to observe the alterations of gut microbial metabolites. The detection of associated pathways was carried out using quantitative real-time PCR (qRT-PCR).

RESULTS

Experimental periodontitis significantly induced increases in tumor number in mice with CRC. Double immunofluorescence for Ki67 and β-catenin, as well as Cyclin D1 and β-catenin, indicated that experimental periodontitis observably promoted tumor growth. 16S rRNA sequencing and untargeted metabolomics analysis displayed that experimental periodontitis altered gut microbial community and metabolite profiles in CRC mice. Notably, we found that experimental periodontitis dramatically increased the level of three oncometabolites (serotonin, adenosine, and spermine) in mice with CRC.

CONCLUSION

Alterations of gut microbial community and metabolites might be relevant in experimental periodontitis deteriorating CRC.

Gut Microbiome and Metabolite Characteristics Associated With Different Clinical Stages in Non-Small Cell Lung Cancer Patients

Objective

Our research has pinpointed the gut microbiome's role in the progression of various pathological types of non-small cell lung cancer (NSCLC). Nonetheless, the characteristics of the gut microbiome and its metabolites across different clinical stages of NSCLC are yet to be fully understood. The current study seeks to explore the distinctive gut flora and metabolite profiles of NSCLC patients across varying TNM stages.

Methods

The research team gathered stool samples from 52 patients diagnosed with non-small cell lung cancer (NSCLC) and 29 healthy individuals. Subsequently, they performed 16S rRNA gene amplification sequencing and untargeted gas/liquid chromatography-mass spectrometry metabolomics analysis.

Results

The study revealed that the alpha-diversity of the gut microbiome in NSCLC patients at different stages did not exhibit statistically significant differences. Notably, Lachnospira and Blautia were more abundant in healthy controls. The distribution of gut microbial species in patients with varying stages of NSCLC was uneven, with Bacteroides and Bacteroidaceae being most prevalent in stage T2, and Prevotella dominating in stage T4. Levels of Ruminococcus gnavus were notably elevated in stages N3 and M. The genus levels of Klebsiella, Parabacteroides, and Tannerellaceae were higher in stage II patients. Rodentibacter was the bacterium with increased levels in stage III NSCLC patients. Further metabolomics studies revealed significantly elevated levels of quinic acid and 3-hydroxybenzoic acid in the healthy control group. In contrast, Stage I+II non-small cell lung cancer (NSCLC) patients exhibited reduced levels of L-cystathionine. Notably, quinic acid, phthalic acid, and L-lactic acid were observed to be increased in Stage III+IV NSCLC patients.

Conclusion

Compared to the analysis of a single microbial dataset, this study provides deeper functional insights by incorporating comprehensive metabolomic profiling. This approach demonstrates that both the gut microbiome and associated metabolites are altered in NSCLC patients across different clinical stages. Our findings may offer novel perspectives on the pathogenesis of NSCLC at various TNM stages. Further research is warranted to validate and clinically apply these potential biomarkers.

Predicting the potential deterioration of Barrett's esophagus based on gut microbiota: a Mendelian randomization analysis

Esophageal adenocarcinoma (EAC) is one of the most malignant tumors in the digestive system. To make thing worse, the scarcity of treatment options is disheartening. However, if detected early, there is a possibility of reversing the condition. Unfortunately, there is still a lack of relevant early screening methods. Considering that Barrett's esophagus (BE), a precursor lesion of EAC, has been confirmed as the only known precursor of EAC. Analyzing which BE cases will progress to EAC and understanding the processes and mechanisms involved is of great significance for early screening of such patients. Considering the significant alterations in the gut microbiota of patients with BE and its potential role in the progression to EAC, this study aims to analyze the relationship between BE, EAC, and GM to identify potential diagnostic biomarkers and therapeutic targets. This study utilized comprehensive statistical data on gut microbiota from a large-scale genome-wide association meta-analysis conducted by the MiBioGen consortium (n = 18,340). Subsequently, we selected a set of single nucleotide polymorphisms (SNPs) that fell below the genome-wide significance threshold (1 × 10-5) as instrumental variables. To investigate the causal relationship between gut microbiota and BE and EAC, we employed various MR analysis methods, including Inverse Variance Weighting (IVW), MR-Egger regression, weighted median (WM), and weighted mean. Additionally, we assessed the level of pleiotropy, heterogeneity, and stability of genetic variations through MR-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis. Furthermore, we conducted reverse MR analysis to identify the causal relationships between gut microbiota and BE and EAC. The results from the Inverse Variance-Weighted (IVW) analysis indicate that Alistipes (P = 4.86 × 10-2), Lactobacillus (P = 2.11 × 10-2), Prevotella 7 (P = 4.28 × 10-2), and RuminococcaceaeUCG004 (P = 4.34 × 10-2) are risk factors for Barrett's esophagus (BE), while Flavonifractor (P = 8.81 × 10-3) and RuminococcaceaeUCG004 (P = 4.99 × 10-2) are risk factors for esophageal adenocarcinoma (EAC). On the other hand, certain gut microbiota genera appear to have a protective effect against both BE and EAC. These include Eubacterium (nodatum group) (P = 4.51 × 10-2), Holdemania (P = 1.22 × 10-2), and Lactococcus (P = 3.39 × 10-2) in the BE cohort, as well as Eubacterium (hallii group) (P = 4.07 × 10-2) and Actinomyces (P = 3.62 × 10-3) in the EAC cohort. According to the results of reverse MR analysis, no significant causal effects of BE and EAC on gut microbiota were observed. Furthermore, no significant heterogeneity or pleiotropy was detected in the instrumental variables. We have established a causal relationship between the gut microbiota and BE and EAC. This study holds profound significance for screening BE patients who may be at risk of deterioration, as it can provide them with timely medical interventions to reverse the condition.

Exploring Gut Microbiome Composition and Circulating Microbial DNA Fragments in Patients with Stage II/III Colorectal Cancer: A Comprehensive Analysis

BACKGROUND

Colorectal cancer (CRC) significantly contributes to cancer-related mortality, necessitating the exploration of prognostic factors beyond TNM staging. This study investigates the composition of the gut microbiome and microbial DNA fragments in stage II/III CRC.

METHODS

A cohort of 142 patients with stage II/III CRC and 91 healthy controls underwent comprehensive microbiome analysis. Fecal samples were collected for 16S rRNA sequencing, and blood samples were tested for the presence of microbial DNA fragments. De novo clustering analysis categorized individuals based on their microbial profiles. Alpha and beta diversity metrics were calculated, and taxonomic profiling was conducted.

RESULTS

Patients with CRC exhibited distinct microbial composition compared to controls. Beta diversity analysis confirmed CRC-specific microbial profiles. Taxonomic profiling revealed unique taxonomies in the patient cohort. De novo clustering separated individuals into distinct groups, with specific microbial DNA fragment detection associated with certain patient clusters.

CONCLUSIONS

The gut microbiota can differentiate patients with CRC from healthy individuals. Detecting microbial DNA fragments in the bloodstream may be linked to CRC prognosis. These findings suggest that the gut microbiome could serve as a prognostic factor in stage II/III CRC. Identifying specific microbial markers associated with CRC prognosis has potential clinical implications, including personalized treatment strategies and reduced healthcare costs. Further research is needed to validate these findings and uncover underlying mechanisms.

Causal associations between gut microbiota and cutaneous melanoma: a Mendelian randomization study

Background

Cutaneous melanoma (CM) of the skin stands as the leading cause of mortality among skin cancer-related deaths. Despite the successes achieved with novel therapies such as immunotherapy and targeted therapy, their efficacy remains limited, necessitating further exploration of new treatment modalities. The gut microbiota and CM may be linked, as indicated by a growing body of preclinical and observational research. Nevertheless, the exact correlation between the intestinal microbiota and CM remains to be determined. Therefore, this study aims to assess the potential causal relationship between the gut microbiota and CM.

Methods

The study utilized exposure data obtained from the MiBioGen consortium's microbiome GWAS, which included a total of 18,340 samples gathered from 24 population-based cohorts. Data at the summary level for CM were acquired from the UK Biobank investigation. The main analytical strategy utilized in this research was the inverse variance weighted (IVW) technique, supported by quality assurance measures like the weighted median model, MR-Egger, simple model, and weighted model approaches. The Cochran's Q test was used to evaluate heterogeneity. To ascertain potential pleiotropy, we employed both the MR-Egger regression and the MR-PRESSO test. Sensitivity analysis was conducted using the leave-one-out method.

Results

The study found that the class Bacteroidia (OR = 0.997, 95% CI: 0.995-0.999, p = 0.027), genus Parabacteroides (OR = 0.997, 95% CI: 0.994-0.999, p = 0.037), order Bacteroidales (OR = 0.997, 95% CI: 0.995-0.999, p = 0.027), and genus Veillonella (OR = 0.998, 95% CI: 0.996-0.999, p = 0.046) have protective effects on CM. On the order hand, the genus Blautia (OR = 1.003, 95% CI: 1-1.006, p = 0.001) and phylum Cyanobacteria (OR = 1.002, 95% CI: 1-1.004, p = 0.04) are identified as risk factors for CM.

Conclusion

We comprehensively assessed the potential causal relationship between the gut microbiota and CM and identified associations between six gut microbiota and CM. Among these, four gut microbiota were identified as protective factors for CM, while two gut microbiota were identified as risk factors for CM. This study effectively established a causal relationship between the gut microbiota and CM, thereby providing valuable insights into the mechanistic pathways through which the microbiota impacts the progression of CM.

Commensal Fecal Microbiota Profiles Associated with Initial Stages of Intestinal Mucosa Damage: A Pilot Study

Progressive intestinal mucosal damage occurs over years prior to colorectal cancer (CRC) development. The endoscopic screening of polyps and histopathological examination are used clinically to determine the risk and progression of mucosal lesions. We analyzed fecal microbiota compositions using 16S rRNA gene-based metataxonomic analyses and the levels of short-chain fatty acids (SCFAs) using gas chromatography in volunteers undergoing colonoscopy and histopathological analyses to determine the microbiota shifts occurring at the early stages of intestinal mucosa alterations. The results were compared between diagnosis groups (nonpathological controls and polyps), between samples from individuals with hyperplastic polyps or conventional adenomas, and between grades of dysplasia in conventional adenomas. Some microbial taxa from the Bacillota and Euryarchaeota phyla were the most affected when comparing the diagnosis and histopathological groups. Deeper microbiota alterations were found in the conventional adenomas than in the hyperplastic polyps. The Ruminococcus torques group was enriched in both the hyperplastic polyps and conventional adenomas, whereas the family Eggerthellaceae was enriched only in the hyperplastic polyps. The abundance of Prevotellaceae, Oscillospiraceae, Methanobacteriaceae, Streptococcaceae, Christensenellaceae, Erysipelotrichaceae, and Clostridiaceae shifted in conventional adenomas depending on the grade of dysplasia, without affecting the major SCFAs. Our results suggest a reorganization of microbial consortia involved in gut fermentative processes.