Colorectal Tumour Mucosa Microbiome Is Enriched in Oral Pathogens and Defines Three Subtypes That Correlate with Markers of Tumour Progression

Tumor-associated microbiome features of metastatic colorectal cancer and clinical implications

Background

Colon microbiome composition contributes to the pathogenesis of colorectal cancer (CRC) and prognosis. We analyzed 16S rRNA sequencing data from tumor samples of patients with metastatic CRC and determined the clinical implications.

Materials and methods

We enrolled 133 patients with metastatic CRC at St. Vincent Hospital in Korea. The V3-V4 regions of the 16S rRNA gene from the tumor DNA were amplified, sequenced on an Illumina MiSeq, and analyzed using the DADA2 package.

Results

After excluding samples that retained <5% of the total reads after merging, 120 samples were analyzed. The median age of patients was 63 years (range, 34-82 years), and 76 patients (63.3%) were male. The primary cancer sites were the right colon (27.5%), left colon (30.8%), and rectum (41.7%). All subjects received 5-fluouracil-based systemic chemotherapy. After removing genera with <1% of the total reads in each patient, 523 genera were identified. Rectal origin, high CEA level (≥10 ng/mL), and presence of lung metastasis showed higher richness. Survival analysis revealed that the presence of Prevotella (p = 0.052), Fusobacterium (p = 0.002), Selenomonas (p<0.001), Fretibacterium (p = 0.001), Porphyromonas (p = 0.007), Peptostreptococcus (p = 0.002), and Leptotrichia (p = 0.003) were associated with short overall survival (OS, <24 months), while the presence of Sphingomonas was associated with long OS (p = 0.070). From the multivariate analysis, the presence of Selenomonas (hazard ratio [HR], 6.35; 95% confidence interval [CI], 2.38-16.97; p<0.001) was associated with poor prognosis along with high CEA level.

Conclusion

Tumor microbiome features may be useful prognostic biomarkers for metastatic CRC.

A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study

BACKGROUND & AIMS

Fecal tests currently used for colorectal cancer (CRC) screening show limited accuracy in detecting early tumors or precancerous lesions. In this respect, we comprehensively evaluated stool microRNA (miRNA) profiles as biomarkers for noninvasive CRC diagnosis.

METHODS

A total of 1273 small RNA sequencing experiments were performed in multiple biospecimens. In a cross-sectional study, miRNA profiles were investigated in fecal samples from an Italian and a Czech cohort (155 CRCs, 87 adenomas, 96 other intestinal diseases, 141 colonoscopy-negative controls). A predictive miRNA signature for cancer detection was defined by a machine learning strategy and tested in additional fecal samples from 141 CRC patients and 80 healthy volunteers. miRNA profiles were compared with those of 132 tumors/adenomas paired with adjacent mucosa, 210 plasma extracellular vesicle samples, and 185 fecal immunochemical test leftover samples.

RESULTS

Twenty-five miRNAs showed altered levels in the stool of CRC patients in both cohorts (adjusted P < .05). A 5-miRNA signature, including miR-149-3p, miR-607-5p, miR-1246, miR-4488, and miR-6777-5p, distinguished patients from control individuals (area under the curve [AUC], 0.86; 95% confidence interval [CI], 0.79-0.94) and was validated in an independent cohort (AUC, 0.96; 95% CI, 0.92-1.00). The signature classified control individuals from patients with low-/high-stage tumors and advanced adenomas (AUC, 0.82; 95% CI, 0.71-0.97). Tissue miRNA profiles mirrored those of stool samples, and fecal profiles of different gastrointestinal diseases highlighted miRNAs specifically dysregulated in CRC. miRNA profiles in fecal immunochemical test leftover samples showed good correlation with those of stool collected in preservative buffer, and their alterations could be detected in adenoma or CRC patients.

CONCLUSIONS

Our comprehensive fecal miRNome analysis identified a signature accurately discriminating cancer aimed at improving noninvasive diagnosis and screening strategies.

Environmental insults and compensative responses: when microbiome meets cancer

Tumor microenvironment has recently been ascribed a new hallmark-the polymorphic microbiome. Accumulating evidence regarding the tissue specific territories of tumor-microbiome have opened new and interesting avenues. A pertinent question is regarding the functional consequence of the interface between host-microbiome and cancer. Given microbial communities have predominantly been explored through an ecological perspective, it is important that the foundational aspects of ecological stress and the fight to 'survive and thrive' are accounted for tumor-micro(b)environment as well. Building on existing evidence and classical microbial ecology, here we attempt to characterize the ecological stresses and the compensative responses of the microorganisms inside the tumor microenvironment. What insults would microbes experience inside the cancer jungle? How would they respond to these insults? How the interplay of stress and microbial quest for survival would influence the fate of tumor? This work asks these questions and tries to describe this underdiscussed ecological interface of the tumor and its microbiota. It is hoped that a larger scientific thought on the importance of microbial competition sensing vis-à-vis tumor-microenvironment would be stimulated.

Mucosal Microbiota from Colorectal Cancer, Adenoma and Normal Epithelium Reveals the Imprint of Fusobacterium nucleatum in Cancerogenesis

An increasing amount of evidence suggests the emerging role of the gut microbiota in the development of colorectal cancer (CRC). This study aimed to elucidate the architecture of microbial communities within normal and neoplastic colonic mucosa.

METHODS

Microbiota were analyzed by NGS and by an ensemble of metagenomics analysis tools in a total of 69 tissues from 9 patients with synchronous colorectal neoplasia and adenomas (27 specimens: 9 from normal tissues, 9 adenomas, and 9 tumours), 16 patients with only colonic adenomas (32 specimens: 16 from normal tissues and 16 adenomas), and from healthy subjects (10 specimens of normal mucosa).

RESULTS

Weak differences were observed in alpha and beta metrics among the synchronous tissues from CRC and controls. Through pairwise differential abundance analyses of sample groups, an increasing trend of Rikenellaceae, Pseudomonas and Fusobacterium, and decreasing trends of Staphylococcus, Actinobacillus and Gemmiger were observed in CRC, while Staphylococcus and Bifidobacterium were decreased in patients with only adenomas. At RT-qPCR analysis, Fusobacterium nucleatum was significantly enriched in all the tissues of subjects with synchronous colorectal neoplasia.

CONCLUSION

Our findings provide a comprehensive view of the human mucosa-associated gut microbiota, emphasizing global microbial diversity mostly in synchronous lesions and proving the constant presence of Fusobacterium nucleatum, with its ability to drive carcinogenesis.

Colon Cancer Microbiome Landscaping: Differences in Right- and Left-Sided Colon Cancer and a Tumor Microbiome-Ileal Microbiome Association

In the current era of precision oncology, it is widely acknowledged that CRC is a heterogeneous disease entity. Tumor location (right- or left-sided colon cancer or rectal cancer) is a crucial factor in determining disease progression as well as prognosis and influences disease management. In the last decade, numerous works have reported that the microbiome is an important element of CRC carcinogenesis, progression and therapy response. Owing to the heterogeneous nature of microbiomes, the findings of these studies were inconsistent. The majority of the studies combined colon cancer (CC) and rectal cancer (RC) samples as CRC for analysis. Furthermore, the small intestine, as the major site for immune surveillance in the gut, is understudied compared to the colon. Thus, the CRC heterogeneity puzzle is far from being solved, and more research is necessary for prospective trials that separately investigate CC and RC. Our prospective study aimed to map the colon cancer landscape using 16S rRNA amplicon sequencing in biopsy samples from the terminal ileum, healthy colon tissue, healthy rectal tissue and tumor tissue as well as in preoperative and postoperative stool samples of 41 patients. While fecal samples provide a good approximation of the average gut microbiome composition, mucosal biopsies allow for detecting subtle variations in local microbial communities. In particular, the small bowel microbiome has remained poorly characterized, mainly because of sampling difficulties. Our analysis revealed the following: (i) right- and left-sided colon cancers harbor distinct and diverse microbiomes, (ii) the tumor microbiome leads to a more consistent cancer-defined microbiome between locations and reveals a tumor microbiome-ileal microbiome association, (iii) the stool only partly reflects the microbiome landscape in patients with CC, and (iv) mechanical bowel preparation and perioperative antibiotics together with surgery result in major changes in the stool microbiome, characterized by a significant increase in the abundance of potentially pathogenic bacteria, such as Enterococcus. Collectively, our results provide new and valuable insights into the complex microbiome landscape in patients with colon cancer.

Combining p-values from various statistical methods for microbiome data

MOTIVATION

In the field of microbiome analysis, there exist various statistical methods that have been developed for identifying differentially expressed features, that account for the overdispersion and the high sparsity of microbiome data. However, due to the differences in statistical models or test formulations, it is quite often to have inconsistent significance results across statistical methods, that makes it difficult to determine the importance of microbiome taxa. Thus, it is practically important to have the integration of the result from all statistical methods to determine the importance of microbiome taxa. A standard meta-analysis is a powerful tool for integrative analysis and it provides a summary measure by combining p-values from various statistical methods. While there are many meta-analyses available, it is not easy to choose the best meta-analysis that is the most suitable for microbiome data.

RESULTS

In this study, we investigated which meta-analysis method most adequately represents the importance of microbiome taxa. We considered Fisher's method, minimum value of p method, Simes method, Stouffer's method, Kost method, and Cauchy combination test. Through simulation studies, we showed that Cauchy combination test provides the best combined value of p in the sense that it performed the best among the examined methods while controlling the type 1 error rates. Furthermore, it produced high rank similarity with the true ranks. Through the real data application of colorectal cancer microbiome data, we demonstrated that the most highly ranked microbiome taxa by Cauchy combination test have been reported to be associated with colorectal cancer.

Effects of gut microbiota on immune responses and immunotherapy in colorectal cancer

Accumulating evidence suggests that gut microbial dysbiosis is implicated in colorectal cancer (CRC) initiation and progression through interaction with host immune system. Given the intimate relationship between the gut microbiota and the antitumor immune responses, the microbiota has proven to be effective targets in modulating immunotherapy responses of preclinical CRC models. However, the proposed putative mechanisms of how these bacteria affect immune responses and immunotherapy efficacy remains obscure. In this review, we summarize recent findings of clinical gut microbial dysbiosis in CRC patients, the reciprocal interactions between gut microbiota and the innate and/or the adaptive immune system, as well as the effect of gut microbiota on immunotherapy response in CRC. Increased understanding of the gut microbiota-immune system interactions will benefit the rational application of microbiota to the clinical promising biomarker or therapeutic strategy as a cancer immunotherapy adjuvant.

Luminal and Tumor-Associated Gut Microbiome Features Linked to Precancerous Lesions Malignancy Risk: A Compositional Approach

Colorectal cancer is the third most commonly diagnosed cancer worldwide. Human gut microbiome plays important roles in protecting against it, as well as contributing to its onset and progression. Identification of specific bacterial taxa associated with early stages of colorectal cancer may help develop effective microbiome-based diagnostics. For precancerous lesions, links of their characteristics to luminal and tumor-associated microbiome composition are to be elucidated. Paired stool and tumor brush biopsy samples were collected from 50 patients with precancerous lesions and early forms of colon cancer; their microbial communities were profiled using high-throughput 16S rRNA sequencing. We showed that the microbiome differences between stool and biopsy samples can be to a high extent computationally corrected. Compositionality-aware statistical analysis of microbiome composition revealed its associations with the number of lesions, lesion type, location and malignization pathway. A major determinant of precancerous lesions malignancy risk-the number of lesions-was positively associated with the abundance of H2S-producing taxa. Our results contribute to the basis for developing early non-invasive colorectal cancer diagnostics via identifying microorganisms likely participating in early stages of cancer pathogenesis.