Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer
TL;DR: The first metagenomic profiling study of CRC faecal microbiomes is presented to discover and validate microbial biomarkers in ethnically different cohorts, and to independently validate selected biomarkers using an affordable clinically relevant technology.
Abstract: Objective To evaluate the potential for diagnosing colorectal cancer (CRC) from faecal metagenomes. Design We performed metagenome-wide association studies on faecal samples from 74 patients with CRC and 54 controls from China, and validated the results in 16 patients and 24 controls from Denmark. We further validated the biomarkers in two published cohorts from France and Austria. Finally, we employed targeted quantitative PCR (qPCR) assays to evaluate diagnostic potential of selected biomarkers in an independent Chinese cohort of 47 patients and 109 controls. Results Besides confirming known associations of Fusobacterium nucleatum and Peptostreptococcus stomatis with CRC, we found significant associations with several species, including Parvimonas micra and Solobacterium moorei . We identified 20 microbial gene markers that differentiated CRC and control microbiomes, and validated 4 markers in the Danish cohort. In the French and Austrian cohorts, these four genes distinguished CRC metagenomes from controls with areas under the receiver-operating curve (AUC) of 0.72 and 0.77, respectively. qPCR measurements of two of these genes accurately classified patients with CRC in the independent Chinese cohort with AUC=0.84 and OR of 23. These genes were enriched in early-stage (I–II) patient microbiomes, highlighting the potential for using faecal metagenomic biomarkers for early diagnosis of CRC. Conclusions We present the first metagenomic profiling study of CRC faecal microbiomes to discover and validate microbial biomarkers in ethnically different cohorts, and to independently validate selected biomarkers using an affordable clinically relevant technology. Our study thus takes a step further towards affordable non-invasive early diagnostic biomarkers for CRC from faecal samples.
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TL;DR: The large majority of studies on the role of the microbiome in the pathogenesis of disease are correlative and preclinical; several have influenced clinical practice.
Abstract: The large majority of studies on the role of the microbiome in the pathogenesis of disease are correlative and preclinical; several have influenced clinical practice.
2,083 citations
University of Copenhagen1, Lund University2, Molecular Medicine Partnership Unit3, ETH Zurich4, Fudan University5, German Cancer Research Center6, University of Trento7, University of São Paulo8, European Institute of Oncology9, Japan Society for the Promotion of Science10, Tokyo Institute of Technology11, University of Tokyo12, Osaka University13, National Presto Industries14, City University of New York15, National Institutes of Health16, Huntsman Cancer Institute17, University of Southern Denmark18
TL;DR: A meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer identified a core set of 29 species significantly enriched in CRC metagenomes, establishing globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.
Abstract: Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10−5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics. Cross-study analysis defines fecal microbial species associated with colorectal cancer.
615 citations
TL;DR: Large-cohort multi-omics data indicate that shifts in the microbiome and metabolome occur from the very early stages of the development of colorectal cancer, which is of possible etiological and diagnostic importance.
Abstract: In most cases of sporadic colorectal cancers, tumorigenesis is a multistep process, involving genomic alterations in parallel with morphologic changes. In addition, accumulating evidence suggests that the human gut microbiome is linked to the development of colorectal cancer. Here we performed fecal metagenomic and metabolomic studies on samples from a large cohort of 616 participants who underwent colonoscopy to assess taxonomic and functional characteristics of gut microbiota and metabolites. Microbiome and metabolome shifts were apparent in cases of multiple polypoid adenomas and intramucosal carcinomas, in addition to more advanced lesions. We found two distinct patterns of microbiome elevations. First, the relative abundance of Fusobacterium nucleatum spp. was significantly (P < 0.005) elevated continuously from intramucosal carcinoma to more advanced stages. Second, Atopobium parvulum and Actinomyces odontolyticus, which co-occurred in intramucosal carcinomas, were significantly (P < 0.005) increased only in multiple polypoid adenomas and/or intramucosal carcinomas. Metabolome analyses showed that branched-chain amino acids and phenylalanine were significantly (P < 0.005) increased in intramucosal carcinomas and bile acids, including deoxycholate, were significantly (P < 0.005) elevated in multiple polypoid adenomas and/or intramucosal carcinomas. We identified metagenomic and metabolomic markers to discriminate cases of intramucosal carcinoma from the healthy controls. Our large-cohort multi-omics data indicate that shifts in the microbiome and metabolome occur from the very early stages of the development of colorectal cancer, which is of possible etiological and diagnostic importance. Colorectal cancer stages are associated with distinct microbial and metabolomic profiles that could shed light on cancer progression.
599 citations
TL;DR: The role of microorganisms in colorectal carcinogenesis, and the potential clinical translation of the gut microbiota as a biomarker for CRC diagnosis and prognosis are described, and as an approach for disease prevention and to improve therapy are described.
Abstract: Colorectal cancer (CRC) accounts for about 10% of all new cancer cases globally. Located at close proximity to the colorectal epithelium, the gut microbiota comprises a large population of microorganisms that interact with host cells to regulate many physiological processes, such as energy harvest, metabolism and immune response. Sequencing studies have revealed microbial compositional and ecological changes in patients with CRC, whereas functional studies in animal models have pinpointed the roles of several bacteria in colorectal carcinogenesis, including Fusobacterium nucleatum and certain strains of Escherichia coli and Bacteroides fragilis. These findings give new opportunities to take advantage of our knowledge on the gut microbiota for clinical applications, such as gut microbiota analysis as screening, prognostic or predictive biomarkers, or modulating microorganisms to prevent cancer, augment therapies and reduce adverse effects of treatment. This Review aims to provide an overview and discussion of the gut microbiota in colorectal neoplasia, including relevant mechanisms in microbiota-related carcinogenesis, the potential of utilizing the microbiota as CRC biomarkers, and the prospect for modulating the microbiota for CRC prevention or treatment. These scientific findings will pave the way to clinically translate the use of gut microbiota for CRC in the near future.
549 citations
TL;DR: CRC-associated microbiota profiles differ from those in healthy subjects and are linked with distinct mucosal gene-expression profiles, which differ between distal and proximal cancers.
Abstract: Objective A signature that unifies the colorectal cancer (CRC) microbiota across multiple studies has not been identified. In addition to methodological variance, heterogeneity may be caused by both microbial and host response differences, which was addressed in this study. Design We prospectively studied the colonic microbiota and the expression of specific host response genes using faecal and mucosal samples (‘ON’ and ‘OFF’ the tumour, proximal and distal) from 59 patients undergoing surgery for CRC, 21 individuals with polyps and 56 healthy controls. Microbiota composition was determined by 16S rRNA amplicon sequencing; expression of host genes involved in CRC progression and immune response was quantified by real-time quantitative PCR. Results The microbiota of patients with CRC differed from that of controls, but alterations were not restricted to the cancerous tissue. Differences between distal and proximal cancers were detected and faecal microbiota only partially reflected mucosal microbiota in CRC. Patients with CRC can be stratified based on higher level structures of mucosal-associated bacterial co-abundance groups (CAGs) that resemble the previously formulated concept of enterotypes. Of these, Bacteroidetes Cluster 1 and Firmicutes Cluster 1 were in decreased abundance in CRC mucosa, whereas Bacteroidetes Cluster 2, Firmicutes Cluster 2, Pathogen Cluster and Prevotella Cluster showed increased abundance in CRC mucosa. CRC-associated CAGs were differentially correlated with the expression of host immunoinflammatory response genes. Conclusions CRC-associated microbiota profiles differ from those in healthy subjects and are linked with distinct mucosal gene-expression profiles. Compositional alterations in the microbiota are not restricted to cancerous tissue and differ between distal and proximal cancers.
541 citations
References
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TL;DR: The results for 20 world regions are presented, summarizing the global patterns for the eight most common cancers, and striking differences in the patterns of cancer from region to region are observed.
Abstract: Estimates of the worldwide incidence and mortality from 27 cancers in 2008 have been prepared for 182 countries as part of the GLOBOCAN series published by the International Agency for Research on Cancer. In this article, we present the results for 20 world regions, summarizing the global patterns for the eight most common cancers. Overall, an estimated 12.7 million new cancer cases and 7.6 million cancer deaths occur in 2008, with 56% of new cancer cases and 63% of the cancer deaths occurring in the less developed regions of the world. The most commonly diagnosed cancers worldwide are lung (1.61 million, 12.7% of the total), breast (1.38 million, 10.9%) and colorectal cancers (1.23 million, 9.7%). The most common causes of cancer death are lung cancer (1.38 million, 18.2% of the total), stomach cancer (738,000 deaths, 9.7%) and liver cancer (696,000 deaths, 9.2%). Cancer is neither rare anywhere in the world, nor mainly confined to high-resource countries. Striking differences in the patterns of cancer from region to region are observed.
21,040 citations
TL;DR: The Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals are described, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species.
Abstract: To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, ~150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively
9,268 citations
TL;DR: In this article, the maximal statistical dependency criterion based on mutual information (mRMR) was proposed to select good features according to the maximal dependency condition. But the problem of feature selection is not solved by directly implementing mRMR.
Abstract: Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we first derive an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection. Then, we present a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers). This allows us to select a compact set of superior features at very low cost. We perform extensive experimental comparison of our algorithm and other methods using three different classifiers (naive Bayes, support vector machine, and linear discriminate analysis) and four different data sets (handwritten digits, arrhythmia, NCI cancer cell lines, and lymphoma tissues). The results confirm that mRMR leads to promising improvement on feature selection and classification accuracy.
8,078 citations
TL;DR: A marked increase in the use of international datasets for more highly evidenced-based changes in staging, and the enhanced use of nonanatomic prognostic factors in defining the stage grouping are notable.
Abstract: The American Joint Committee on Cancer and the International Union for Cancer Control update the tumor-node-metastasis (TNM) cancer staging system periodically. The most recent revision is the 7th edition, effective for cancers diagnosed on or after January 1, 2010. This editorial summarizes the background of the current revision and outlines the major issues revised. Most notable are the marked increase in the use of international datasets for more highly evidenced-based changes in staging, and the enhanced use of nonanatomic prognostic factors in defining the stage grouping. The future of cancer staging lies in the use of enhanced registry data standards to support personalization of cancer care through cancer outcome prediction models and nomograms.
7,303 citations
05 Aug 2003
TL;DR: This work derives an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection, and presents a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers).
7,075 citations