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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.

Background Invasive cervical cancer (ICC) is caused by high-risk human papillomavirus types (HR-HPVs) and is usually preceded by a long phase of intraepithelial neoplasia (CIN). Before invasion, (epi) genetic changes, potentially applicable as molecular markers within cervical screening, occur in HPV host cells. Epigenetic alterations, such as dysregulation of microRNA (miRNA) expression, are frequently observed in ICC. The mechanisms and role of miRNA dysregulation in cervical carcinogenesis are still largely unknown. Methods We provide an overview of the studies investigating miRNA expression in relation to ICC progression, highlighting their common outcomes and their weaknesses/strengths. To achieve this, we systematically searched through Pubmed database all articles between January 2010 and December 2017. Results From the 24 studies retrieved, miR-29a and miR-21 are the most frequently down- and up-regulated in ICC progression, respectively. Microarray-based studies show a small overlap, with miR-10a, miR-20b, miR-9, miR-16 and miR-106 found repeatedly dysregulated. miR-34a, miR-125 and miR-375 were also found dysregulated in cervical exfoliated cells in relation to cancer progression. Conclusions The pivotal role of miRNAs in ICC progression and initial development is becoming more and more relevant. Available studies are essentially based on convenience material, entailing possible selection bias, and frequently of small size: all these points still represent a limitation to a wide comprehension of miRNAs relevant for ICC. The targeted approach instead of a genome-wide investigation still precludes the identification of all the relevant miRNAs in the process. The implementation of deep sequencing on large scale population-based studies will help to discover and validate the relation between altered miRNA expression and CC progression for the identification of biomarkers. Optimally, once explored on a miRNome scale, small specific miRNA signatures maybe used in the context of screening.

Several studies have investigated links between the gut microbiome and colorectal cancer (CRC), but questions remain about the replicability of biomarkers across cohorts and populations. We performed a meta-analysis of five publicly available datasets and two new cohorts and validated the findings on two additional cohorts, considering in total 969 fecal metagenomes. Unlike microbiome shifts associated with gastrointestinal syndromes, the gut microbiome in CRC showed reproducibly higher richness than controls (P < 0.01), partially due to expansions of species typically derived from the oral cavity. Meta-analysis of the microbiome functional potential identified gluconeogenesis and the putrefaction and fermentation pathways as being associated with CRC, whereas the stachyose and starch degradation pathways were associated with controls. Predictive microbiome signatures for CRC trained on multiple datasets showed consistently high accuracy in datasets not considered for model training and independent validation cohorts (average area under the curve, 0.84). Pooled analysis of raw metagenomes showed that the choline trimethylamine-lyase gene was overabundant in CRC (P = 0.001), identifying a relationship between microbiome choline metabolism and CRC. The combined analysis of heterogeneous CRC cohorts thus identified reproducible microbiome biomarkers and accurate disease-predictive models that can form the basis for clinical prognostic tests and hypothesis-driven mechanistic studies.Multicohort analysis identifies microbial signatures of colorectal cancer in fecal microbiomes.

ObjectivesMicroRNA (miRNA) profiles have been evaluated in several biospecimens in relation to common diseases for which diet may have a considerable impact. We aimed at characterising how specific diets are associated with the miRNome in stool of vegans, vegetarians and omnivores and how this is reflected in the gut microbial composition, as this is still poorly explored.DesignWe performed small RNA and shotgun metagenomic sequencing in faecal samples and dietary recording from 120 healthy volunteers, equally distributed for the different diets and matched for sex and age.ResultsWe found 49 miRNAs differentially expressed among vegans, vegetarians and omnivores (adj. p <0.05) and confirmed trends of expression levels of such miRNAs in vegans and vegetarians compared with an independent cohort of 45 omnivores. Two miRNAs related to lipid metabolism, miR-636 and miR-4739, were inversely correlated to the non-omnivorous diet duration, independently of subject age. Seventeen miRNAs correlated (|rho|>0.22, adj. p <0.05) with the estimated intake of nutrients, particularly animal proteins, phosphorus and, interestingly, lipids. In omnivores, higher Prevotella and Roseburia and lower Bacteroides abundances than in vegans and vegetarians were observed. Lipid metabolism-related miR-425-3p and miR-638 expression levels were associated with increased abundances of microbial species, such as Roseburia sp. CAG 182 and Akkermansia muciniphila, specific of different diets. An integrated analysis identified 25 miRNAs, 25 taxa and 7 dietary nutrients that clearly discriminated (area under the receiver operating characteristic curve=0.89) the three diets.ConclusionStool miRNA profiles are associated with specific diets and support the role of lipids as a driver of epigenetic changes and host-microbial molecular interactions in the gut.

For their stability and detectability faecal microRNAs represent promising molecules with potential clinical interest as non-invasive diagnostic and prognostic biomarkers. However, there is no evidence on how stool miRNA profiles change according to an individual’s age, sex, and body mass index (BMI) or how lifestyle habits influence the expression levels of these molecules. We explored the relationship between the stool miRNA levels and common traits (sex, age, BMI, and menopausal status) or lifestyle habits (physical activity, smoking status, coffee, and alcohol consumption) as derived by a self-reported questionnaire, using small RNA-sequencing data of samples from 335 healthy subjects. We detected 151 differentially expressed miRNAs associated with one variable and 52 associated with at least two. Differences in miR-638 levels were associated with age, sex, BMI, and smoking status. The highest number of differentially expressed miRNAs was associated with BMI (n = 92) and smoking status (n = 84), with several miRNAs shared between them. Functional enrichment analyses revealed the involvement of the miRNA target genes in pathways coherent with the analysed variables. Our findings suggest that miRNA profiles in stool may reflect common traits and lifestyle habits and should be considered in relation to disease and association studies based on faecal miRNA expression.

Background Molecular techniques can complement conventional spermiogram analyses to provide new information on the fertilizing potential of spermatozoa and to identify early alterations due to environmental pollution. Methods Here, we present a multilevel molecular profiling by small RNA sequencing and sperm nuclear basic protein analysis of male germ cells from 33 healthy young subjects residing in low and high-polluted areas. Results Although sperm motility and sperm concentration were comparable between samples from the two sites, those from the high-pollution area had a higher concentration of immature/immune cells, a lower protamine/histone ratio, a reduced ability of sperm nuclear basic proteins to protect DNA from oxidative damage, and an altered copper/zinc ratio in sperm. Sperm levels of 32 microRNAs involved in intraflagellar transport, oxidative stress response, and spermatogenesis were different between the two areas. In parallel, a decrease of Piwi-interacting RNA levels was observed in samples from the high-polluted area. Conclusions This comprehensive analysis provides new insights into pollution-driven epigenetic alterations in sperm not detectable by spermiogram. Graphical Abstract

The characteristics of microbial small RNA transcription are largely unknown, while it is of primary importance for a better identification of molecules with functional activities in the gut niche under both healthy and disease conditions. By performing combined analyses of metagenomic and small RNA sequencing (sRNA-Seq) data, we characterized both the human and microbial small RNA contents of stool samples from healthy individuals and from patients with colorectal carcinoma or adenoma. With the integrative analyses of metagenomic and sRNA-Seq data, we identified a human and microbial small RNA signature which can be used to improve diagnosis of the disease. Our analysis of human and gut microbiome small RNA expression is relevant to generation of the first hypotheses about the potential molecular interactions occurring in the gut of CRC patients, and it can be the basis for further mechanistic studies and clinical tests. Dysbiotic configurations of the human gut microbiota have been linked to colorectal cancer (CRC). Human small noncoding RNAs are also implicated in CRC, and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis, but their role has been less extensively explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens from patients with CRC or with adenomas and from healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We observed considerable overlap and a correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. We identified a combined predictive signature composed of 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC samples separately from healthy and adenoma samples (area under the curve [AUC] = 0.87). In the present study, we report evidence that host-microbiome dysbiosis in CRC can also be observed by examination of altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more-accurate tools for diagnostic purposes. IMPORTANCE The characteristics of microbial small RNA transcription are largely unknown, while it is of primary importance for a better identification of molecules with functional activities in the gut niche under both healthy and disease conditions. By performing combined analyses of metagenomic and small RNA sequencing (sRNA-Seq) data, we characterized both the human and microbial small RNA contents of stool samples from healthy individuals and from patients with colorectal carcinoma or adenoma. With the integrative analyses of metagenomic and sRNA-Seq data, we identified a human and microbial small RNA signature which can be used to improve diagnosis of the disease. Our analysis of human and gut microbiome small RNA expression is relevant to generation of the first hypotheses about the potential molecular interactions occurring in the gut of CRC patients, and it can be the basis for further mechanistic studies and clinical tests.

Diet has a strong influence on many physiological processes, which in turn have important implications on a variety of pathological conditions. In this respect, microRNAs (miRNAs), a class of small non-coding RNAs playing a relevant epigenetic role in controlling gene expression, may represent mediators between the dietary intake and the healthy status. Despite great advances in the field of nutri-epigenomics, it remains unclear how miRNA expression is modulated by the diet and, specifically, the intake of specific nutrients. We investigated the whole circulating miRNome by small RNA-sequencing performed on plasma samples of 120 healthy volunteers with different dietary habits (vegans, vegetarians, and omnivores). Dietary intakes of specific nutrients were estimated for each subject from the information reported in the food-frequency questionnaire previously validated in the EPIC study. We focused hereby on the intake of 23 natural compounds (NCs) of the classes of lipids, micro-elements, and vitamins. We identified 78 significant correlations (rho > 0.300, p -value < 0.05) among the estimated daily intake of 13 NCs and the expression levels of 58 plasma miRNAs. Overall, vitamin D, sodium, and vitamin E correlated with the largest number of miRNAs. All the identified correlations were consistent among the three dietary groups and 22 of them were confirmed as significant ( p -value < 0.05) by age-, gender-, and body-mass index-adjusted Generalized Linear regression Model analysis. miR-23a-3p expression levels were related with different NCs including a significant positive correlation with sodium (rho = 0.377) and significant negative correlations with lipid-related NCs and vitamin E. Conversely, the estimated intake of vitamin D was negatively correlated with the expression of the highest number of circulating miRNAs, particularly miR-1277-5p (rho = −0.393) and miR-144-3p (rho = −0.393). Functional analysis of the targets of sodium intake-correlated miRNAs highlighted terms related to cardiac development. A similar approach on targets of those miRNAs correlated with vitamin D intake showed an enrichment in genes involved in hormone metabolisms, while the response to chronic inflammation was among the top enriched processes involving targets of miRNAs negatively related with vitamin E intake. Our findings show that nutrients through the habitual diet influence circulating miRNA profiles and highlight that this aspect must be considered in the nutri-epigenomic research.

Background Bladder cancer (BC) has the highest per-patient cost of all cancer types. Hence, we aim to develop a non-invasive, point-of-care tool for the diagnostic and molecular stratification of patients with BC based on combined microRNAs (miRNAs) and surface-enhanced Raman spectroscopy (SERS) profiling of urine. Methods Next-generation sequencing of the whole miRNome and SERS profiling were performed on urine samples collected from 15 patients with BC and 16 control subjects (CTRLs). A retrospective cohort (BC = 66 and CTRL = 50) and RT-qPCR were used to confirm the selected differently expressed miRNAs. Diagnostic accuracy was assessed using machine learning algorithms (logistic regression, naïve Bayes, and random forest), which were trained to discriminate between BC and CTRL, using as input either miRNAs, SERS, or both. The molecular stratification of BC based on miRNA and SERS profiling was performed to discriminate between high-grade and low-grade tumors and between luminal and basal types. Results Combining SERS data with three differentially expressed miRNAs (miR-34a-5p, miR-205-3p, miR-210-3p) yielded an Area Under the Curve (AUC) of 0.92 ± 0.06 in discriminating between BC and CTRL, an accuracy which was superior either to miRNAs (AUC = 0.84 ± 0.03) or SERS data (AUC = 0.84 ± 0.05) individually. When evaluating the classification accuracy for luminal and basal BC, the combination of miRNAs and SERS profiling averaged an AUC of 0.95 ± 0.03 across the three machine learning algorithms, again better than miRNA (AUC = 0.89 ± 0.04) or SERS (AUC = 0.92 ± 0.05) individually, although SERS alone performed better in terms of classification accuracy. Conclusion miRNA profiling synergizes with SERS profiling for point-of-care diagnostic and molecular stratification of BC. By combining the two liquid biopsy methods, a clinically relevant tool that can aid BC patients is envisaged.

Fecal microRNAs represent promising molecules with potential clinical interest as non-invasive diagnostic and prognostic biomarkers. Colorectal cancer (CRC) screening based on the fecal immunochemical test (FIT) is an effective tool for prevention of cancer development. However, due to the poor sensitivity of FIT especially for premalignant lesions, there is a need for implementation of complementary tests. Improving the identification of individuals who would benefit from further investigation with colonoscopy using molecular analysis, such as miRNA profiling of FIT samples, would be ideal due to their widespread use. In the present study, we assessed the feasibility of applying small RNA sequencing to measure human miRNAs in FIT leftover buffer in samples from two European screening populations. We showed robust detection of miRNAs with profiles similar to those obtained from specimens sampled using the established protocol of RNA stabilizing buffers, or in long-term archived samples. Detected miRNAs exhibited differential abundances for CRC, advanced adenoma, and control samples that were consistent for FIT and RNA-stabilizing buffers. Interestingly, the sequencing data also allowed for concomitant evaluation of small RNA-based microbial profiles. We demonstrated that it is possible to explore the human miRNome in FIT leftover samples across populations and envision that the analysis of small RNA biomarkers can complement the FIT in large scale screening settings.