Specific Gut Microbiome and Serum Metabolome Changes in Lung Cancer Patients

16S rRNA sequencing reveals relationships among enrichment of oral microbiota in the lower respiratory tract and pulmonary nodules malignant progression

Micro-aspiration of oral microorganisms results in considerable enrichment within the lower respiratory tract (LRT), constituting an early event in lung cancer pathogenesis. To explore the correlation between malignant risk of pulmonary nodules (PNs) and oral commensals enrichment in LRT, oral saliva and bronchial alveolar lavage fluid samples from 22 low-risk PN patients, 17 intermediate-risk PN patients, and 11 high-risk PN patients were analyzed using 16S rRNA gene sequencing. Alpha and beta diversity analyses reveal minimal variation in oral microbial diversity and abundance among patients with different risks of PN. In contrast, a significant reduction in the diversity of LRT microbiota is observed in patients at high risk of PN. Based on multigroup comparative analysis of species differences and the linear discriminant analysis effect size method, Synergistes and Tannerella were identified as the dominant bacterial genera in the oral and LRT of high-risk PN patients, respectively. The study found that the LRT microbiota of PN patients seemed to originate from the oral, and the high enrichment of oral microbiota in the lower respiratory tract was most common in high-risk PN patients. The predominant bacterial genera present in the oral cavity and LRT of patients with PN were identified through abundance variance analysis. Eight key microbial genera were found in both the oral cavity and LRT: Streptococcus, Granulicatella, Porphyromonas, Bacillus, Neisseria, Alloprevotella, Prevotella, and Leptotrichia. Notably, receiver operating characteristic analysis identified Streptococcus, Granulicatella, and Leptotrichia as reliable biomarkers to differentiate high-risk PN. Spearman correlation analysis confirmed that the accumulation of oral microorganisms in the LRT played an important role in the process of PN cancerization. The co-occurrence network showed that the coexistence of Veillonella and Streptococcus in the oral and LRT may be involved in the occurrence of PN, while the LRT cluster of Rothia occurred in high-risk PN patients. Correlation analysis among species identified microbial communities predominantly composed of Veillonella, which may facilitate pulmonary carcinogenesis.

IMPORTANCE

This study is the first to elucidate the composition and interrelationships of oral and lower respiratory tract (LRT) microbiota in patients with pulmonary nodule (PN) across varying malignancy risk levels. We conducted an analysis to investigate the correlation between the malignant potential of PNs and the enrichment of oral microbiota within the LRT. Additionally, we explored the feasibility of utilizing oral-lower respiratory commensal microbiota as biomarkers to assess the benign and malignant nature of pulmonary nodules. This study aims to provide evidence supporting early diagnosis and intervention strategies for lung cancer.

Metabolomics based early warning model for acute kidney injury risk in patients exposed to diquat

Acute kidney injury (AKI) is one of the most important indications of severe clinical symptoms in patients with diquat poisoning and is closely related to poor prognosis. However, current studies have rarely focused on early warnings of diquat-related AKI, which is not conducive to the treatment of patients with early clinical diquat poisoning. In this study, untargeted plasma metabolomics was employed to reveal the differences between diquat-poisoned patients with and without AKI, as well as between patients and healthy volunteers. The results showed that 48 metabolites were significantly changed in the patients, among which 3-hydroxybutyrylcarnitine, SAICAR, dodecanoic acid, and tetrahydrofolyl-[Glu](2) could be used to effectively differentiate the above three groups. Based on the ratios of the first two metabolites and the ratios of the last two metabolites, a decision tree model for the early warning of diquat-induced AKI was established with an accuracy rate of 88.7 %. This model provides great support for accurate clinical diagnosis and intervention regarding the AKI risk of diquat-exposed patients.

Volatile organic compound exposure in relation to lung cancer: Insights into mechanisms of action through metabolomics

Volatile organic compounds (VOCs) have proven to be hazardous to the human respiratory system. However, the underlying biological mechanisms remain poorly understood. Therefore, targeted determination of eleven VOC metabolites (mVOCs) along with the nontargeted metabolomic analysis was performed on urine samples collected from lung cancer patients and healthy individuals. Nine mVOCs mainly derived from aldehydes, alkenes, amides, and aromatics were detected in > 90 % of the urine samples, suggesting that the participants were ubiquitously exposed to these typical VOCs. A molecular gatekeeper discovery workflow was employed to link the exposure biomarkers with correlated clusters of endogenous metabolites. As a result, multiple metabolic pathways, including amino acid metabolism, steroid hormone biosynthesis and metabolism, and fatty acid β-oxidation were connected with VOC exposure. Furthermore, 16 of 73 molecular gatekeepers were associated with lung cancer and pointed to a few disrupted metabolic pathways related to hydroxysteroids and acylcarnitine. The shift in molecular profiles was validated in rat model post VOC administration. Thereinto, the up-regulation of enzymes involved in acylcarnitine synthesis and transport in rat lung tissues highlighted that the mitochondrial dysfunction may be a potential carcinogenic mechanism. Our findings provide new insights into the mechanisms underlying lung cancer induced by VOC exposure.

Assessment of progression of pulmonary fibrosis based on metabonomics and analysis of intestinal microbiota

The main purpose of this study was to explore the changes of biomarkers in different developmental stages of bleomycin-induced pulmonary fibrosis (PF) in rats via comprehensive pathophysiology, UPLC-QTOF/MS metabonomic technology, and 16S rRNA gene sequencing of intestinal microbiota. The rats were randomly divided into normal control and 1-, 2- and 4-week model group. The rat model of PF was established by one-time intratracheal instillation of bleomycin. The levels of inflammatory and fibrosis-related factors such as hydroxyproline (HYP), type III procollagen (COL-III), type IV collagen (COL-IV), hyaluronidase (HA), laminin (LN), interleukin (IL)-1β, IL-6, malondialdehyde (MDA) increased and superoxide dismutase (SOD) decreased as the PF cycle progressed. In the 1-, 2- and 4-week model group, 2, 19 and 18 potential metabolic biomarkers and 3, 16 and 12 potential microbial biomarkers were detected, respectively, which were significantly correlated. Glycerophospholipid metabolism pathway was observed to be an important pathway affecting PF at 1, 2 and 4 weeks; arginine and proline metabolism pathways significantly affected PF at 2 weeks. Linoleic acid metabolism pathway exhibited clear metabolic abnormalities at 2 and 4 weeks of PF, and alpha-linolenic acid metabolism pathway significantly affected PF at 4 weeks.

Gut Microbiota, Circulating Metabolites and Risk of Endometriosis: A Two-Step Mendelian Randomization Study

Epidemiological studies and animal models have suggested a possible link between gut microbiota (GM), circulating metabolites, and endometriosis (EMs) pathogenesis. However, whether these associations are causal or merely due to confounding factors remains unclear. We conducted a two-sample and two-step Mendelian randomization (MR) study to elucidate the potential causal relationship between GM and EMs, and the mediating role of circulating metabolites. Our MR analysis revealed that higher abundances of class Negativicutes, and order Selenomonadales, as well as genera Dialister, Enterorhabdus, Eubacterium xylanophilum group, Methanobrevibacter were associated with an increased risk of EMs (Odds Ratio (OR) range: 1.0019-1.0037). Conversely, higher abundances of genera Coprococcus 1 and Senegalimassilia were linked to reduced risk of EMs (OR range: 0.9964-0.9967). Additionally, elevated levels of circulating metabolites such as 1-eicosatrienoyl-glycerophosphocholine and 1-oleoylglycerophosphocholine were found to be associated with heightened risk of EMs (OR range: 2.21-3.16), while higher concentrations of 3-phenylpropionate and dihomo-linolenate were protective (OR range: 0.285-0.535). Two-step MR analysis indicated that specific microbial taxa, notably genus Enterorhabdus and order Selenomonadales, might function as mediators linking circulating metabolites to the risk of EMs. Our findings suggest a probable causal relationship between GM, circulating metabolites, and EMs, indicating that GM may mediate the influence of circulating metabolites on the pathophysiology of EMs. These results offer new leads for future mechanistic studies and could inform clinical translational research.

The causality between gut microbiota and endometriosis: a bidirectional Mendelian randomization study

Background

Observational studies and animal experiments had suggested a potential relationship between gut microbiota abundance and pathogenesis of endometriosis (EMs), but the relevance of this relationship remains to be clarified.

Methods

We perform a two-sample bidirectional Mendelian randomization (MR) analysis to explore whether there is a causal correlation between the abundance of the gut microbiota and EMs and the direction of causality. Genome-wide association study (GWAS) data ukb-d-N80, finn-b-N14-EM, and MiBinGen were selected. Inverse variance weighted (IVW), weighted median, and MR Egger are selected for causal inference. The Cochran Q test, Egger intercept test, and leave-one-out analysis are performed for sensitivity analyses.

Results

In the primary outcome, we find that a higher abundance of class Negativicutes, genus Dialister, genus Enterorhabdus, genus Eubacterium xylanophilum group, genus Methanobrevibacter and order Selenomonadales predict a higher risk of EMs, and a higher abundance of genus Coprococcus and genus Senegalimassilia predict a lower risk of EMs. During verifiable outcomes, we find that a higher abundance of phylum Cyanobacteria, genus Ruminococcaceae UCG002, and genus Coprococcus 3 predict a higher risk of EMs, and a higher abundance of genus Flavonifracto, genus Bifidobacterium, and genus Rikenellaceae RC9 predict a lower risk of EMs. In primary reverse MR analysis, we find that EMs predict a lower abundance of the genus Eubacterium fissicatena group, genus Prevotella7, genus Butyricicoccus, family Lactobacillaceae, and a higher abundance of genus Ruminococcaceae UCG009. In verifiable reverse MR analysis, we find that EMs predict a lower abundance of the genus Ruminococcaceae UCG004 and a higher abundance of the genus Howardella.

Conclusion

Our study implies a mutual causality between gut microbiota abundance and the pathogenesis of EMs, which may provide a novel direction for EMs diagnosis, prevention, and treatment, may promote future functional or clinical analysis.

Exploring multi-omics and clinical characteristics linked to accelerated biological aging in Asian women of reproductive age: insights from the S-PRESTO study

BACKGROUND

Phenotypic age (PhenoAge), a widely used marker of biological aging, has been shown to be a robust predictor of all-cause mortality and morbidity in different populations. Existing studies on biological aging have primarily focused on individual domains, resulting in a lack of a comprehensive understanding of the multi-systemic dysregulation that occurs in aging.

METHODS

PhenoAge was evaluated based on a linear combination of chronological age (CA) and 9 clinical biomarkers in 952 multi-ethnic Asian women of reproductive age. Phenotypic age acceleration (PhenoAgeAccel), an aging biomarker, represents PhenoAge after adjusting for CA. This study conducts an in-depth association analysis of PhenoAgeAccel with clinical, nutritional, lipidomic, gut microbiome, and genetic factors.

RESULTS

Higher adiposity, glycaemia, plasma saturated fatty acids, kynurenine pathway metabolites, GlycA, riboflavin, nicotinamide, and insulin-like growth factor binding proteins were positively associated with PhenoAgeAccel. Conversely, a healthier diet and higher levels of pyridoxal phosphate, all-trans retinol, betaine, tryptophan, glutamine, histidine, apolipoprotein B, and insulin-like growth factors were inversely associated with PhenoAgeAccel. Lipidomic analysis found 132 lipid species linked to PhenoAgeAccel, with PC(O-36:0) showing the strongest positive association and CE(24:5) demonstrating the strongest inverse association. A genome-wide association study identified rs9864994 as the top genetic variant (P = 5.69E-07) from the ZDHHC19 gene. Gut microbiome analysis revealed that Erysipelotrichaceae UCG-003 and Bacteroides vulgatus were inversely associated with PhenoAgeAccel. Integrative network analysis of aging-related factors underscored the intricate links among clinical, nutritional and lipidomic variables, such as positive associations between kynurenine pathway metabolites, amino acids, adiposity, and insulin resistance. Furthermore, potential mediation effects of blood biomarkers related to inflammation, immune response, and nutritional and energy metabolism were observed in the associations of diet, adiposity, genetic variants, and gut microbial species with PhenoAgeAccel.

CONCLUSIONS

Our findings provide a comprehensive analysis of aging-related factors across multiple platforms, delineating their complex interconnections. This study is the first to report novel signatures in lipidomics, gut microbiome and blood biomarkers specifically associated with PhenoAgeAccel. These insights are invaluable in understanding the molecular and metabolic mechanisms underlying biological aging and shed light on potential interventions to mitigate accelerated biological aging by targeting modifiable factors.

Study on the Differences in Fecal Metabolites and Microbial Diversity of Jiangshan Black-Bone Chickens with Different Earlobe Colors

The differences in earlobe color of Jiangshan black-bone chickens have been reported to be caused by the combined effects of melanin and collagen. In this study, we conducted LC-MS untargeted metabolomics and 16S rDNA diversity sequencing on the cecal contents of two types of earlobes: peacock green (Blue and Green group) and dark reddish-purple (Black group). The metabolomic sequencing identified a total of 747 differential metabolites (DMs), in which the metabolites were primarily enriched in tyrosine and tryptophan metabolism pathways between peacock green and dark reddish-purple earlobes. There were 15 different bacterial taxa among the three groups of earlobes at the genus level, and correlation analysis between metabolites and microbes revealed that the DMs between peacock green and dark reddish-purple earlobes were positively correlated with the different bacterial taxa. In short, there are differences in gut microbiota and metabolites between Jiangshan black-bone chickens with peacock green earlobes and those with dark reddish-purple earlobes. Our results suggest that the bacterial phyla Firmicutes and Bacteroidota may influence melanin synthesis by affecting tryptophan metabolism, induced by 5-Methoxyindoleacetate, and tyrosine metabolism, induced by maleylacetoacetic acid and maleic acid, leading to differences in earlobe color.

Alterations of Ceramides, Acylcarnitines, GlyceroLPLs, and Amines in NSCLC Tissues

Abnormal lipid metabolism plays an important role in cancer development. In this study, nontargeted lipidomic study on 230 tissue specimens from 79 nonsmall cell lung cancer (NSCLC) patients was conducted using ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS). Downregulation of sphingosine and medium-long-chain ceramides and short-medium-chain acylcarnitine, upregulation of long-chain acylcarnitine C20:0, and enhanced histamine methylation were revealed in NSCLC tissues. Compared with paired noncancerous tissues, adenocarcinoma (AC) tissues had significantly decreased levels of sphingosine, medium-long-chain ceramides (Cer d18:1/12:0 and Cer d16:1/14:0, Cer d18:0/16:0, Cer d18:1/16:0, Cer d18:2/16:0, Cer d18:2/18:0), short-medium-chain (C2-C16) acylcarnitines, LPC 20:0 and LPC 22:1, and significantly increased levels of the long-chain acylcarnitine C20:0, LPC 16:0, LPC P-16:0, LPC 20:1, LPC 20:2, glyceroPC, LPE 16:0, and LPE 18:2. In squamous cell carcinoma (SCC) tissues, sphingosine, Cer d18:2/16:0 and Cer d18:2/18:0, and short-medium-chain acylcarnitines had significantly lower levels, while long-chain acylcarnitines (C20:0, and C22:0 or C22:0 M), LPC 20:1, LPC 20:2, and N1,N12-diacetylspermine had significantly higher levels compared to controls. In AC and SCC tissues, the levels of LPG 18:0, LPG 18:1, and LPS 18:1 were significantly decreased, while the levels of ceramide-1-phosphate (C1P) d18:0/3:0 or LPE P-16:0, N1-acetylspermidine, and 1-methylhistamine were significantly increased than controls. Furthermore, an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model based on a 4-lipid panel was established, showing good discrimination ability between cancerous and noncancerous tissues.

Pathogenic mechanisms and latest therapeutic approaches for radiation-induced lung injury: A narrative review

The treatment of thoracic tumors with ionizing radiation can cause radiation-induced lung injury (RILI), which includes radiation pneumonitis and radiation-induced pulmonary fibrosis. Preventing RILI is crucial for controlling tumor growth and improving quality of life. However, the serious adverse effects of traditional RILI treatment methods remain a major obstacle, necessitating the development of novel treatment options that are both safe and effective. This review summarizes the molecular mechanisms of RILI and explores novel treatment options, including natural compounds, gene therapy, nanomaterials, and mesenchymal stem cells. These recent experimental approaches show potential as effective prevention and treatment options for RILI in clinical practice.

Impact of the Lung Microbiota on Development and Progression of Lung Cancer

The past several years have provided a more profound understanding of the role of microbial species in the lung. The respiratory tract is a delicate ecosystem of bacteria, fungi, parasites, and viruses. Detecting microbial DNA, pathogen-associated molecular patterns (PAMPs), and metabolites in sputum is poised to revolutionize the early diagnosis of lung cancer. The longitudinal monitoring of the lung microbiome holds the potential to predict treatment response and side effects, enabling more personalized and effective treatment options. However, most studies into the lung microbiota have been observational and have not adequately considered the impact of dietary intake and air pollutants. This gap makes it challenging to establish a direct causal relationship between environmental exposure, changes in the composition of the microbiota, lung carcinogenesis, and tumor progression. A holistic understanding of the lung microbiota that considers both diet and air pollutants may pave the way to improved prevention and management strategies for lung cancer.

Gut microbiota influence on lung cancer risk through blood metabolite mediation: from a comprehensive Mendelian randomization analysis and genetic analysis

Background

Gut microbiota (GM) and metabolic alterations play pivotal roles in lung cancer (LC) development and host genetic variations are known to contribute to LC susceptibility by modulating the GM. However, the causal links among GM, metabolite, host genes, and LC remain to be fully delineated.

Method

Through bidirectional MR analyses, we examined the causal links between GM and LC, and utilized two-step mediation analysis to identify potential mediating blood metabolite. We employed diverse MR methods, including inverse-variance-weighted (IVW), weighted median, MR-Egger, weighted mode, and simple mode, to ensure a robust examination of the data. MR-Egger intercept test, Radial MR, MR-PRESSO, Cochran Q test and Leave-one-out (LOO) analysis were used for sensitivity analyses. Analyses were adjusted for smoking, alcohol intake frequency and air pollution. Linkage disequilibrium score regression and Steiger test were used to probe genetic causality. The study also explored the association between specific host genes and the abundance of gut microbes in LC patients.

Results

The presence of Bacteroides clarus was associated with an increased risk of LC (odds ratio [OR] = 1.07, 95% confidence interval [CI]: 1.03-1.11, p = 0.012), whereas the Eubacteriaceae showed a protective effect (OR = 0.82, 95% CI: 0.75-0.89, p = 0.001). These findings remained robust after False Discovery Rate (FDR) correction. Our mediator screening identified 13 blood metabolites that significantly influence LC risk after FDR correction, underscoring cystine and propionylcarnitine in reducing LC risk, while linking specific lipids and hydroxy acids to an increased risk. Our two-step mediation analysis demonstrated that the association between the bacterial pathway of synthesis of guanosine ribonucleotides and LC was mediated by Fructosyllysine, with mediated proportions of 11.38% (p = 0.037). LDSC analysis confirmed the robustness of these associations. Our study unveiled significant host genes ROBO2 may influence the abundance of pathogenic gut microbes in LC patients. Metabolic pathway analysis revealed glutathione metabolism and glutamate metabolism are the pathways most enriched with significant metabolites related to LC.

Conclusion

These findings underscore the importance of GM in the development of LC, with metabolites partly mediating this effect, and provide dietary and lifestyle recommendations for high-risk lung cancer populations.

Pharmacomicrobiomics in precision cancer therapy: bench to bedside

The burgeoning field of pharmacomicrobiomics offers promising insights into the intricate interplay between the microbiome and cancer, shaping responses to diverse treatment modalities. This review aims to analyze the molecular mechanisms underlying interactions between distinct microbiota types and cancer, as well as their influence on treatment outcomes. We explore how the microbiome impacts antitumor immunity, and response to chemotherapy, immunotherapy, and radiation therapy, unveiling its multifaceted roles in cancer progression and therapy resistance. Moreover, we discuss the challenges hindering the development of microbiome-based interventions in cancer therapy, including standardization, validation, and clinical translation. By synthesizing clinical evidence, we underscore the transformative potential of harnessing pharmacomicrobiomics in guiding cancer treatment decisions, paving the way for improved patient outcomes in clinical practice.

From bench to bedside: an interdisciplinary journey through the gut-lung axis with insights into lung cancer and immunotherapy

This comprehensive review undertakes a multidisciplinary exploration of the gut-lung axis, from the foundational aspects of anatomy, embryology, and histology, through the functional dynamics of pathophysiology, to implications for clinical science. The gut-lung axis, a bidirectional communication pathway, is central to understanding the interconnectedness of the gastrointestinal- and respiratory systems, both of which share embryological origins and engage in a continuous immunological crosstalk to maintain homeostasis and defend against external noxa. An essential component of this axis is the mucosa-associated lymphoid tissue system (MALT), which orchestrates immune responses across these distant sites. The review delves into the role of the gut microbiome in modulating these interactions, highlighting how microbial dysbiosis and increased gut permeability ("leaky gut") can precipitate systemic inflammation and exacerbate respiratory conditions. Moreover, we thoroughly present the implication of the axis in oncological practice, particularly in lung cancer development and response to cancer immunotherapies. Our work seeks not only to synthesize current knowledge across the spectrum of science related to the gut-lung axis but also to inspire future interdisciplinary research that bridges gaps between basic science and clinical application. Our ultimate goal was to underscore the importance of a holistic understanding of the gut-lung axis, advocating for an integrated approach to unravel its complexities in human health and disease.

Gut microbial metabolites in lung cancer development and immunotherapy: Novel insights into gut-lung axis

Metabolic derivatives of numerous microorganisms inhabiting the human gut can participate in regulating physiological activities and immune status of the lungs through the gut-lung axis. The current well-established microbial metabolites include short-chain fatty acids (SCFAs), tryptophan and its derivatives, polyamines (PAs), secondary bile acids (SBAs), etc. As the study continues to deepen, the critical function of microbial metabolites in the occurrence and treatment of lung cancer has gradually been revealed. Microbial derivates can enter the circulation system to modulate the immune microenvironment of lung cancer. Mechanistically, oncometabolites damage host DNA and promote the occurrence of lung cancer, while tumor-suppresive metabolites directly affect the immune system to combat the malignant properties of cancer cells and even show considerable application potential in improving the efficacy of lung cancer immunotherapy. Considering the crosstalk along the gut-lung axis, in-depth exploration of microbial metabolites in patients' feces or serum will provide novel guidance for lung cancer diagnosis and treatment selection strategies. In addition, targeted therapeutics on microbial metabolites are expected to overcome the bottleneck of lung cancer immunotherapy and alleviate adverse reactions, including fecal microbiota transplantation, microecological preparations, metabolite synthesis and drugs targeting metabolic pathways. In summary, this review provides novel insights and explanations on the intricate interplay between gut microbial metabolites and lung cancer development, and immunotherapy through the lens of the gut-lung axis, which further confirms the possible translational potential of the microbiome metabolome in lung cancer treatment.

Microbial and Metabolic Gut Profiling across Seven Malignancies Identifies Fecal Faecalibacillus intestinalis and Formic Acid as Commonly Altered in Cancer Patients

The key association between gut dysbiosis and cancer is already known. Here, we used whole-genome shotgun sequencing (WGS) and gas chromatography/mass spectrometry (GC/MS) to conduct metagenomic and metabolomic analyses to identify common and distinct taxonomic configurations among 40, 45, 71, 34, 50, 60, and 40 patients with colorectal cancer, stomach cancer, breast cancer, lung cancer, melanoma, lymphoid neoplasms and acute myeloid leukemia (AML), respectively, and compared the data with those from sex- and age-matched healthy controls (HC). α-diversity differed only between the lymphoid neoplasm and AML groups and their respective HC, while β-diversity differed between all groups and their HC. Of 203 unique species, 179 and 24 were under- and over-represented, respectively, in the case groups compared with HC. Of these, Faecalibacillus intestinalis was under-represented in each of the seven groups studied, Anaerostipes hadrus was under-represented in all but the stomach cancer group, and 22 species were under-represented in the remaining five case groups. There was a marked reduction in the gut microbiome cancer index in all case groups except the AML group. Of the short-chain fatty acids and amino acids tested, the relative concentration of formic acid was significantly higher in each of the case groups than in HC, and the abundance of seven species of Faecalibacterium correlated negatively with most amino acids and formic acid, and positively with the levels of acetic, propanoic, and butanoic acid. We found more differences than similarities between the studied malignancy groups, with large variations in diversity, taxonomic/metabolomic profiles, and functional assignments. While the results obtained may demonstrate trends rather than objective differences that correlate with different types of malignancy, the newly developed gut microbiota cancer index did distinguish most of the cancer cases from HC. We believe that these data are a promising step forward in the search for new diagnostic and predictive tests to assess intestinal dysbiosis among cancer patients.

Causal relationship between gut microbiota and pathological scars: a two-sample Mendelian randomization study

Background

Pathological scars, including keloids and hypertrophic scars, represent a significant dermatological challenge, and emerging evidence suggests a potential role for the gut microbiota in this process.

Methods

Utilizing a two-sample Mendelian randomization (MR) methodology, this study meticulously analyzed data from genome-wide association studies (GWASs) relevant to the gut microbiota, keloids, and hypertrophic scars. The integrity and reliability of the results were rigorously evaluated through sensitivity, heterogeneity, pleiotropy, and directionality analyses.

Results

By employing inverse variance weighted (IVW) method, our findings revealed a causal influence of five bacterial taxa on keloid formation: class Melainabacteria, class Negativicutes, order Selenomonadales, family XIII, and genus Coprococcus2. Seven gut microbiota have been identified as having causal relationships with hypertrophic scars: class Alphaproteobacteria, family Clostridiaceae1, family Desulfovibrionaceae, genus Eubacterium coprostanoligenes group, genus Eubacterium fissicatena group, genus Erysipelotrichaceae UCG003 and genus Subdoligranulum. Additional sensitivity analyses further validated the robustness of the associations above.

Conclusion

Overall, our MR analysis supports the hypothesis that gut microbiota is causally linked to pathological scar formation, providing pivotal insights for future mechanistic and clinical research in this domain.

Characterizations of multi-kingdom gut microbiota in immune checkpoint inhibitor-treated hepatocellular carcinoma

BACKGROUND

The association between gut bacteria and the response to immune checkpoint inhibitors (ICI) in hepatocellular carcinoma (HCC) has been studied; however, multi-kingdom gut microbiome alterations and interactions in ICI-treated HCC cohorts are not fully understood.

METHODS

From November 2018 to April 2022, patients receiving ICI treatment for advanced HCC were prospectively enrolled. Herein, we investigated the multi-kingdom microbiota characterization of the gut microbiome, mycobiome, and metabolome using metagenomic, ITS2, and metabolomic data sets of 80 patients with ICI-treated HCC.

RESULTS

Our findings demonstrated that bacteria and metabolites differed significantly between the durable clinical benefit (DCB) and non-durable clinical benefit (NDB) groups, whereas the differences were smaller for fungi. The overall diversity of bacteria and fungi before treatment was higher in the DCB group than in the NDB group, and the difference in diversity began to change with the use of immunotherapy after 6-8 weeks. We also explored the alterations of gut microbes in the DCB and NDB groups, established 18 bacterial species models as predictive biomarkers for predicting whether immunotherapy is of sustained benefit (area under the curve=75.63%), and screened two species of bacteria (Actinomyces_sp_ICM47, and Senegalimassilia_anaerobia) and one metabolite (galanthaminone) as prognostic biomarkers for predicting survival in patients with HCC treated with ICI.

CONCLUSIONS

In this study, the status and characterization of the multi-kingdom microbiota, including gut bacteria, fungi, and their metabolites, were described by multiomics sequencing for the first time in patients with HCC treated with ICI. Our findings demonstrate the potential of bacterial taxa as predictive biomarkers of ICI clinical efficacy, and bacteria and their metabolites as prognostic biomarkers.

The Causal Effect of Gut Microbiota and Plasma Metabolome on Lung Cancer and the Heterogeneity across Subtypes: A Mendelian Randomization Study

The causal effect and pathways of gut microbiota and plasma metabolome on lung cancer have been important topics for personalized medicine; however, the heterogeneity of lung cancer subtypes has not gained enough attention in previous studies. This study sought to employ a Mendelian randomization analysis to screen the specific gut microbiota and plasma metabolome, which may have a causal effect on lung cancer. We further extended our analysis to estimate the effects of these exposures on various pathological subtypes of lung cancer. Furthermore, a mediation analysis was performed to identify the potential pathway underlying the influence of microbiota and metabolites. Our study identified 13 taxa and 15 metabolites with a causal association with the overall risk of lung cancer. Furthermore, we found 8 taxa and 14 plasma metabolites with a causal effect on lung adenocarcinoma, 4 taxa and 10 metabolites with a causal effect on squamous cell lung carcinoma, and 7 taxa and 16 metabolites with a causal effect on SCLC. We also identified seven mediation pathways that could potentially elucidate the influence of these microbiota and metabolites on overall lung cancer or special subtypes. Our study highlighted the heterogeneity of the gut microbiome and plasma metabolome in a lung cancer subtype and elucidated the potential underlying mechanisms. This could pave the way for more personalized lung cancer prevention and treatment.

Effects of natural products on functional constipation: analysis of active ingredient and mechanism

Constipation is a prevalent clinical ailment of the gastrointestinal system, yet its pathogenesis remains ambiguous. Despite the availability of numerous treatment modalities, they are insufficient in resolving the issue for patients. This work conducted a comprehensive review of the existing literature pertaining to the utilization of natural products for the treatment of constipation, with a focus on the efficacy of natural products in treating constipation, and to provide a comprehensive summary of their underlying mechanisms of action. Upon conducting a thorough review of the extant literature, we found that natural products can effectively treat constipation as modern synthetic drugs and compounded drugs with acetylcholinesterase (AChE) effects, rich in fiber and mucus, and the effects of increasing the tension of the ileum and gastrointestinal tract muscle, mediating signaling pathways, cytokine, excitability of the smooth muscle of the gastrointestinal tract, and regulating the homeostasis of intestinal flora. However, there is a wide variety of natural products, and there are still relatively few studies; the composition of natural products is complex, and the mechanism of action of natural products cannot be clarified. In the future, we need to further improve the detailed mechanism of natural products for the treatment of constipation.

Microbiome and lung cancer: carcinogenic mechanisms, early cancer diagnosis, and promising microbial therapies

Microbiomes in the lung, gut, and oral cavity are correlated with lung cancer initiation and progression. While correlations have been preliminarily established in earlier studies, delving into microbe-mediated carcinogenic mechanisms will extend our understanding from correlation to causation. Building upon the causative relationships between microbiome and lung cancer, a novel concept of microbial biomarkers has emerged, mainly encompassing cancer-specific bacteria and circulating microbiome DNA. They might function as noninvasive liquid biopsy techniques for lung cancer early detection. Furthermore, potential microbial therapies have displayed initial efficacy in lung cancer treatment, providing multiple avenues for therapeutic intervention. Herein, we will discuss the molecular mechanisms and signaling pathways through which microbes influence lung cancer initiation and development. Additionally, we will summarize recent findings on microbial biomarkers as a member of tumor liquid biopsy techniques and provide an overview of the latest advances in various microbe-assisted/mediated therapeutic approaches for lung cancer.

A new perspective on gut-lung axis affected through resident microbiome and their implications on immune response in respiratory diseases

The highly diverse microbial ecosystem of the human body colonizes the gastrointestinal tract has a profound impact on the host's immune, metabolic, endocrine, and other physiological processes, which are all interconnected. Specifically, gut microbiota has been found to play a crucial role in facilitating the adaptation and initiation of immune regulatory response through the gastrointestinal tract affecting the other distal mucosal sites such as lungs. A tightly regulated lung-gut axis during respiratory ailments may influence the various molecular patterns that instructs priming the disease severity to dysregulate the normal function. This review provides a comprehensive summary of current research on gut microbiota dysbiosis in respiratory diseases including asthma, pneumonia, bronchopneumonia, COPD during infections and cancer. A complex-interaction among gut microbiome, associated metabolites, cytokines, and chemokines regulates the protective immune response activating the mucosal humoral and cellular response. This potential mechanism bridges the regulation patterns through the gut-lung axis. This paper aims to advance the understanding of the crosstalk of gut-lung microbiome during infection, could lead to strategize to modulate the gut microbiome as a treatment plan to improve bad prognosis in various respiratory diseases.

Detailed Characterization of the Lung-Gut Microbiome Axis Reveals the Link between PD-L1 and the Microbiome in Non-Small-Cell Lung Cancer Patients

Next-generation sequencing technologies have started a new era of respiratory tract research in recent years. Alterations in the respiratory microbiome between healthy and malignant conditions have been revealed. However, the composition of the microbiome varies among studies, even in similar medical conditions. Also, there is a lack of complete knowledge about lung-gut microbiome interactions in lung cancer patients. The aim of this study was to explore the lung-gut axis in non-small-cell lung cancer (NSCLC) patients and the associations between lung-gut axis microbiota and clinical parameters (CRP, NLR, LPS, CD8, and PD-L1). Lung tissue and fecal samples were used for bacterial 16S rRNA sequencing. The results revealed, for the first time, that the bacterial richness in lung tumor tissue gradually decreased with an increase in the level of PD-L1 expression (p < 0.05). An analysis of β-diversity indicated a significant positive correlation between the genera Romboutsia and Alistipes in both the lung tumor biopsies and stool samples from NSCLC patients (p < 0.05). Survival analysis showed that NSCLC patients with higher bacterial richness in their stool samples had prolonged overall survival (HR: 2.06, 95% CI: 1.025-4.17, p = 0.0426).

Exploring the relationship between intestinal microbiota and immune checkpoint inhibitors in the treatment of non-small cell lung cancer: insights from the "lung and large intestine stand in exterior-interior relationship" theory

Objective

This study is aim to discern the Traditional Chinese Medicine (TCM) syndrome classifications relevant to immunotherapy sensitive in non-small cell lung cancer (NSCLC) patients, and to delineate intestinal microbiota biomarkers and impact that wield influence over the efficacy of NSCLC immunotherapy, grounded in the TCM theory of "lung and large intestine stand in exterior-interior relationship."

Methods

The study cohort consisted of patients with advanced NSCLC who received treatment at the Oncology Department of Chengdu Fifth People's Hospital. These patients were categorized into distinct TCM syndrome types and subsequently administered immune checkpoint inhibitors (ICIs), specifically PD-1 inhibitors. Stool specimens were collected from patients both prior to and following treatment. To scrutinize the differences in microbial gene sequences and species of the intestinal microbiota, 16S rRNA amplicon sequencing technology was employed. Additionally, peripheral blood samples were collected, and the analysis encompassed the assessment of T lymphocyte subsets and myeloid suppressor cell subsets via flow cytometry. Subsequently, alterations in the immune microenvironment pre- and post-treatment were thoroughly analyzed.

Results

The predominant clinical manifestations of advanced NSCLC patients encompassed spleen-lung Qi deficiency syndrome and Qi-Yin deficiency syndrome. Notably, the latter exhibited enhanced responsiveness to ICIs with a discernible amelioration of the immune microenvironment. Following ICIs treatment, significant variations in microbial abundance were identified among the three strains: Clostridia, Lachnospiraceae, and Lachnospirales, with a mutual dependency relationship. In the subset of patients manifesting positive PD-L1 expression and enduring therapeutic benefits, the study recorded marked increases in the ratios of CD3+%, CD4+%, and CD4+/CD8+ within the T lymphocyte subsets. Conversely, reductions were observed in the ratios of CD8%, Treg/CD4+, M-MDSC/MDSC, and G-MDSC/MDSC.

Conclusion

The strains Clostridia, Lachnospiraceae, and Lachnospirales emerge as potential biomarkers denoting the composition of the intestinal microbiota in the NSCLC therapy. The immunotherapy efficacy of ICIs markedly accentuates in patients displaying durable treatment benefits and those expressing positive PD-L1.

Bones and guts - Why the microbiome matters

The importance of the gut microbiota in human health has become increasingly apparent in recent years, especially when the relationship between microbiota and host is no longer symbiotic. It has long been appreciated that gut dysbiosis can be detrimental to human health and is associated with numerous disease states. Only within the last decade, however, was the gut microbiota implicated in bone biology. Dubbed osteomicrobiology, this emerging field aims to understand the relationship between the gut microbiome and the bone microenvironment in both health and disease. Importantly, the key to one of the major clinical challenges facing both bone and cancer biologists: bone metastasis, may lie in the field of osteomicrobiology; however the link between gut bacteria and bone metastasis is only beginning to be explored. This review will discuss (i) osteomicrobiology as an emerging field, and (ii) the current understanding of osteomicrobiology in the context of cancer in bone.

The role of serum acylcarnitine profiling for the detection of multiple solid tumors in humans

Metabolic reprogramming is an essential hallmark of cancer. Several studies have reported the dysregulation of acylcarnitine (ACar) metabolism in tumor cells, suggesting that changes in the blood ACar may be related to tumor growth. Accordingly, this study aimed to understand the alteration of serum ACar profiles in various solid tumors and explore the potential of differential serum ACars as diagnostic biomarkers. A series of 69 relatively abundant ACars were identified via untargeted analysis. Then, targeted metabolomics was used to describe the metabolic alterations in ACars between normal controls and patients with six types of solid tumors. The results suggested that changes in ACars correlated with their carbon chain length and saturation. The six tumor types had highly similar ACar metabolic profiles, indicating similar fatty acid oxidation (FAO) metabolic pathways. Moreover, the receiver operating curve analysis of differential ACars showed that 16 ACars (C8-C14) had high diagnostic capability towards the studied solid tumors. Specifically, the area under the curve of ACar 10:2 isomer2 and ACar 12:2 isomer2 was greater than 0.95. In conclusion, the marked decrease in the levels of medium- and long-chain ACars (C8-C18) in the six solid tumors suggests that they may have similar FAO-based metabolic pathways, which could afford a common target for cancer therapy. Additionally, 16 ACars (C8-C14) were identified as potential biomarkers for diagnosing six types of solid tumors.

Methodology for biomarker discovery with reproducibility in microbiome data using machine learning

BACKGROUND

In recent years, human microbiome studies have received increasing attention as this field is considered a potential source for clinical applications. With the advancements in omics technologies and AI, research focused on the discovery for potential biomarkers in the human microbiome using machine learning tools has produced positive outcomes. Despite the promising results, several issues can still be found in these studies such as datasets with small number of samples, inconsistent results, lack of uniform processing and methodologies, and other additional factors lead to lack of reproducibility in biomedical research. In this work, we propose a methodology that combines the DADA2 pipeline for 16s rRNA sequences processing and the Recursive Ensemble Feature Selection (REFS) in multiple datasets to increase reproducibility and obtain robust and reliable results in biomedical research.

RESULTS

Three experiments were performed analyzing microbiome data from patients/cases in Inflammatory Bowel Disease (IBD), Autism Spectrum Disorder (ASD), and Type 2 Diabetes (T2D). In each experiment, we found a biomarker signature in one dataset and applied to 2 other as further validation. The effectiveness of the proposed methodology was compared with other feature selection methods such as K-Best with F-score and random selection as a base line. The Area Under the Curve (AUC) was employed as a measure of diagnostic accuracy and used as a metric for comparing the results of the proposed methodology with other feature selection methods. Additionally, we use the Matthews Correlation Coefficient (MCC) as a metric to evaluate the performance of the methodology as well as for comparison with other feature selection methods.

CONCLUSIONS

We developed a methodology for reproducible biomarker discovery for 16s rRNA microbiome sequence analysis, addressing the issues related with data dimensionality, inconsistent results and validation across independent datasets. The findings from the three experiments, across 9 different datasets, show that the proposed methodology achieved higher accuracy compared to other feature selection methods. This methodology is a first approach to increase reproducibility, to provide robust and reliable results.

Analyzing lung cancer risks in patients with impaired pulmonary function through characterization of gut microbiome and metabolites

BACKGROUND

Lung cancer (LC) is one of the most devastating diseases worldwide, there is growing studies confirm the role of impaired lung function in LC susceptibility. Moreover, gut microbiota dysbiosis is associated with LC severity. Whether alterations in gut microbiota and metabolites are associated with long-term lung dysfunction in LC patients remain unclear. Our study aimed to analyze the risk factors in LC patients with impaired pulmonary function based on the characteristics of the gut microbiome and metabolites.

METHODS

Fecal samples from 55 LC patients and 28 benign pulmonary nodules patients were collected. Pulmonary ventilation function was graded according to the American Thoracic Society/ European Respiratory Society (ATS/ERS) method. LC patients were divided into 3 groups, including 20 patients with normal lung ventilation, 23 patients with mild pulmonary ventilation dysfunction and 12 patients with moderate or above pulmonary ventilation dysfunction. The fecal samples were analyzed using 16 S rRNA gene amplicon sequencing and metabolomics.

RESULTS

The gut microbiome composition between LC patients and benign pulmonary nodules patients presented clearly differences based on Partial Least Squares Discriminant Analysis (PLS-DA). Pulmonary ventilation function was positively correlated with LC tumor stage, the richness and diversity of the gut microbiota in LC patients with moderate or above pulmonary ventilation dysfunction increased significantly, characterized by increased abundance of Subdoligranulum and Romboutsia. The metabolomics analysis revealed 69 differential metabolites, which were mainly enriched in beta-Alanine metabolism, styrene degradation and pyrimidine metabolism pathway. The area under the curve (AUC) combining the gut microbiome and metabolites was 90% (95% CI: 79-100%), indicating that the two species and four metabolites might regarded as biomarkers to assess the prediction of LC patients with impaired pulmonary function.

CONCLUSIONS

Our results showed that microbiome and metabolomics analyses provide important candidate to be used as clinically diagnostic biomarkers and therapeutic targets related to lung cancer with impaired pulmonary function.

Plasma metabolomic analysis of human hepatocellular carcinoma before and after transcatheter arterial chemoembolization

Introduction: Hepatocellular carcinoma (HCC) is the fourth most prevalent cancer in China. Transcatheter arterial chemoembolization (TACE) is a common interventional therapy for HCC. In this study, we aimed to explore specific metabolites that can accurately predict prognosis after TACE in patients with HCC. Methods: Patients with HCC and healthy volunteers (n = 20 each) were recruited to our study; plasma samples were collected from patients before and after TACE and from healthy volunteers. Plasma samples were subjected to untargeted ultra-high performance liquid chromatography-high resolution mass spectrometry metabolomics analysis, to identify metabolites significantly associated with the prognosis of patients with HCC after TACE. Results: Orthogonal filtered partial least squares discriminant analysis confirmed significant separation of the pre-TACE, post-TACE, and healthy groups, and 34 differential metabolites were identified between the pre-TACE and post-TACE groups. KEGG analysis revealed that phenylalanine, tyrosine, and tryptophan biosynthesis pathways and the phenylalanine metabolism pathway were potentially altered in HCC genesis and during TACE. Phenylalanine and tyrosine are involved in both pathways and were increased in the pre-TACE group relative to controls, with phenylalanine further increased in the post-TACE group. Receiver operating characteristic (ROC) curve analysis indicated that PC 36:4|PC 18:2_18:2 (area under the ROC curve (AUC) = 0.798) is a potential marker for assessment of prognosis in patients with HCC after TACE. Moreover, ROC curve analysis indicated that palmitoylcarnitine (AUC = 1) is a marker with potential value for HCC diagnosis. Conclusions: Limited studies had been conducted on the detection of metabolites in the plasma of HCC patients before and after TACE. PC 36:4|PC 18:2_18:2 is a potential marker for evaluation of the therapeutic effects of TACE. This finding may be beneficial for the treatment of patients with HCC after TACE.

Clinical Efficacy and Gut Microbiota Regulating-Related Effect of Si-Jun-Zi Decoction in Postoperative Non-Small Cell Lung Cancer Patients: A Prospective Observational Study

BACKGROUND

Postoperative non-small cell lung cancer (NSCLC) patients frequently encounter a deteriorated quality of life (QOL), disturbed immune response, and disordered homeostasis. Si-Jun-Zi Decoction (SJZD), a well-known traditional Chinese herbal formula, is frequently employed in clinical application for many years. Exploration is underway to investigate the potential therapeutic effect of SJZD for treating postoperative NSCLC.

OBJECTIVE

To assess the efficacy of SJZD on QOLs, hematological parameters, and regulations of gut microbiota in postoperative NSCLC patients.

METHODS

A prospective observational cohort study was conducted, enrolling 65 postoperative NSCLC patients between May 10, 2020 and March 15, 2021 in Yueyang Hospital, with 33 patients in SJZD group and 32 patients in control (CON) group. The SJZD group comprised of patients who received standard treatments and the SJZD decoction, while the CON group consisted of those only underwent standard treatments. The treatment period was 4 weeks. The primary outcome was QOL. The secondary outcomes involved serum immune cell and inflammation factor levels, safety, and alterations in gut microbiota.

RESULTS

SJZD group showed significant enhancements in cognitive functioning (P = .048) at week 1 and physical functioning (P = .019) at week 4. Lung cancer-specific symptoms included dyspnea (P = .001), coughing (P = .008), hemoptysis (P = .034), peripheral neuropathy (P = .019), and pain (arm or shoulder, P = .020, other parts, P = .019) eased significantly in the fourth week. Anemia indicators such as red blood cell count (P = .003 at week 1, P = .029 at week 4) and hemoglobin (P = .016 at week 1, P = .048 at week 4) were significantly elevated by SJZD. SJZD upregulated blood cell cluster differentiation (CD)3+ (P = .001 at week 1, P < .001 at week 4), CD3+CD4+ (P = .012 at week 1), CD3+CD8+ (P = .027 at week 1), CD19+ (P = .003 at week 4), increased anti-inflammatory interleukin (IL)-10 (P = .004 at week 1, P = .003 at week 4), and decreased pro-inflammatory IL-8 (P = .004 at week 1, p = .005 at week 4). Analysis of gut microbiota indicated that SJZD had a significant impact on increasing microbial abundance and diversity, enriching probiotic microbes, and regulating microbial biological functions.

CONCLUSIONS

SJZD appears to be an effective and safe treatment for postoperative NSCLC patients. As a preliminary observational study, this study provides a foundation for further research.

Untangling the web of intratumor microbiota in lung cancer

Microbes are pivotal in contemporary cancer research, influencing various biological behaviors in cancer. The previous notion that the lung was sterile has been destabilized by the discovery of microbiota in the lower airway and lung, even within tumor tissues. Advances of biotechnology enable the association between intratumor microbiota and lung cancer to be revealed. Nonetheless, the origin and tumorigenicity of intratumor microbiota in lung cancer still remain implicit. Additionally, accumulating evidence indicates that intratumor microbiota might serve as an emerging biomarker for cancer diagnosis, prognosis, and even a therapeutic target across multiple cancer types, including lung cancer. However, research on intratumor microbiota's role in lung cancer is still nascent and warrants more profound exploration. Herein, this paper provides an extensive review of recent advancements in the following fields, including 1) established and emerging biotechnologies utilized to study intratumor microbiota in lung cancer, 2) causation between intratumor microbiota and lung cancer from the perspectives of translocation, cancerogenesis and metastasis, 3) potential application of intratumor microbiota as a novel biomarker for lung cancer diagnosis and prognosis, and 4) promising lung cancer therapies via regulating intratumor microbiota. Moreover, this review addresses the limitations, challenges, and future prospects of studies focused on intratumor microbiota in lung cancer.

Intestinal microbiota: A bridge between intermittent fasting and tumors

Intestinal microbiota and their metabolites are essential for maintaining intestinal health, regulating inflammatory responses, and enhancing the body's immune function. An increasing number of studies have shown that the intestinal microbiota is tightly tied to tumorigenesis and intervention effects. Intermittent fasting (IF) is a method of cyclic dietary restriction that can improve energy metabolism, prolong lifespan, and reduce the progression of various diseases, including tumors. IF can affect the energy metabolism of tumor cells, inhibit tumor cell growth, improve the function of immune cells, and promote an anti-tumor immune response. Interestingly, recent research has further revealed that the intestinal microbiota can be impacted by IF, in particular by changes in microbial composition and metabolism. These findings suggest the complexity of the IF as a promising tumor intervention strategy, which merits further study to better understand and encourage the development of clinical tumor intervention strategies. In this review, we aimed to outline the characteristics of the intestinal microbiota and its mechanisms in different tumors. Of note, we summarized the impact of IF on intestinal microbiota and discussed its potential association with tumor suppressive effects. Finally, we proposed some key scientific issues that need to be addressed and envision relevant research prospects, which might provide a theoretical basis and be helpful for the application of IF and intestinal microbiota as new strategies for clinical interventions in the future.

Integrated Macrogenomics and Metabolomics Explore Alterations and Correlation between Gut Microbiota and Serum Metabolites in Adult Epileptic Patients: A Pilot Study

Epilepsy (EP) is a complex brain disorder showing a lot of unknows reasons. Recent studies showed that gut microbiota can influence epilepsy via the brain-gut axis. Nevertheless, the mechanism by which gut microbiota affects adult epilepsy still remains unclear. In this study, fecal and serum samples were obtained from patients with epilepsy and normal controls. Using an integrated analysis, sequencing was performed by macrogenomics and high-throughput targeted metabolomics with various bioinformatics approaches. The macrogenomic sequencing revealed significant changes in microbial structure in patients suffering from epilepsy. For example, at the phylum level, the relative abundance of Actinobacteria, Bacteroidetes and Proteobacteria showed an increase in the patients with epilepsy, whereas that of Firmicutes decreased. In addition, the patients with epilepsy had significantly differential metabolite profiles compared to normal controls, and five clusters with 21 metabolites, mainly containing the upregulation of some fatty acids and downregulation of some amino acids. Tryptophan (AUC = 91.81, p < 0.0001), kynurenine (AUC = 79.09, p < 0.01) and 7Z,10Z,13Z,16Z-Docosatetraenoic acid (AUC = 80.95, p < 0.01) may be used as potential diagnostic markers for epilepsy. Differential serum metabolites have effects on tryptophan metabolism, iron death and other pathways. Furthermore, a multiomic joint analysis observed a statistically significant correlation between the differential flora and the differential serum metabolites. In our findings, a macrogenomic analysis revealed the presence of dysregulated intestinal flora species and function in adult epileptic patients. Deeper metabolomic analyses revealed differences in serum metabolites between patients with epilepsy and healthy populations. Meanwhile, the multiomic combination showed connection between the gut microbes and circulating metabolites in the EP patients, which may be potential therapeutic targets.

Monophasic Variant of Salmonella Typhimurium Infection Affects the Serum Metabolome in Swine

Salmonella is the most relevant foodborne zoonotic agent found in swine, and its presence in French herds is significant. Its carriage is asymptomatic, which makes it difficult to detect during rearing, thus increasing the risk of its presence on pork meat. Studies have shown that enteric infection in animals could be associated with changes in the serum metabolome composition, through the immune response or changes in the digestive microbiota composition. We hypothesized that these changes in the serum metabolome composition could be used as markers for the detection of asymptomatic animals infected by Salmonella. Using untargeted analysis by liquid chromatography coupled with mass spectrometry, we showed that significant differences in the composition of the serum metabolome could be detected between infected or noninfected animals both 1 and 21 days after experimental infection. This serum metabolome composition significantly changed during the 21 days postinfection in the infected animal groups, suggesting an evolution of the impact of infection with time. Despite this evolution, differences in the serum metabolome composition persisted between infected and noninfected animals 21 days after the initial infection. We also showed a possible difference between high-shedding and low-shedding animals 21 days postinfection. Finally, some of the variations in the metabolome were found to be significantly associated with variations of specific members of the fecal microbiota. Thus, excreting and asymptomatic animals, but also high-shedding animals, could be identified on the basis of their serum metabolome composition.

Gut microbiota disorder induces liver dysfunction in polycystic ovary syndrome rats' model by regulating metabolite rosmarinic acid

AIMS

The present study aims to investigate the impact of the gut microbiota and serum metabolites on the regulation of liver dysfunction in PCOS.

MATERIALS AND METHODS

PCOS rat models were established by treating Sprague Dawley (SD) rats with DHEA (an androgen, 60 mg/kg) and LET (a nonsteroidal aromatase inhibitor, 1 mg/kg) for 90 days. Hematoxylin and eosin staining (H&E), Western blotting, and radioimmunoassay were employed to test ovarian and liver functions. Gut microbiome and serum metabolites were assessed using 16S rRNA amplicon sequencing and non-targeted metabolomics, respectively. The association between gut microbiota and serum metabolites was examined using Spearman analysis. Finally, using HepG2 cells to investigate the function of the serum metabolite rosmarinic acid (RA).

KEY FINDINGS

Both Dehydroepiandrosterone (DHEA) and letrozole (LET) treatments induced a PCOS phenotype and liver dysfunction. However, LET resulted in more severe lipid accumulation and liver cell apoptosis than DHEA. 16S rRNA sequencing and non-targeted metabolomics analysis revealed significant differences in beta diversity and serum metabolite profiles among the three groups. Furthermore, among the significantly changed metabolites, RA was found to have a significant correlation with the levels of serum aspartate transaminase (AST) and lactate dehydrogenase (LDH) and could promote HepG2 cell apoptosis.

SIGNIFICANCE

Restoring gut microbiota, altering serum metabolites and/or decreasing RA may provide a new insight to treat this complication.

Potential effects of gut microbiota on host cancers: focus on immunity, DNA damage, cellular pathways, and anticancer therapy

The symbiotic bacteria that live in the human gut and the metabolites they produce have long influenced local and systemic physiological and pathological processes of the host. The gut microbiota are increasingly being recognized for its impact on a range of human diseases, including cancer, it may play a key role in the occurrence, progression, treatment, and prognosis of many types of cancer. Understanding the functional role of the gut microbiota in cancer is crucial for the development of the era of personalized medicine. Here, we review recent advances in research and summarize the important associations and clear experimental evidence for the role of the gut microbiota in a variety of human cancers, focus on the application and possible challenges associated with the gut microbiota in antitumor therapy. In conclusion, our research demonstrated the multifaceted mechanisms of gut microbiota affecting human cancer and provides directions and ideas for future clinical research.

Tracheal microbiome and metabolome profiling in iatrogenic subglottic tracheal stenosis

BACKGROUND

To study the role of microecology and metabolism in iatrogenic tracheal injury and cicatricial stenosis, we investigated the tracheal microbiome and metabolome in patients with tracheal stenosis after endotracheal intubation.

METHODS

We collected 16 protected specimen brush (PSB) and 8 broncho-alveolar lavage (BAL) samples from 8 iatrogenic subglottic tracheal stenosis patients, including 8 PSB samples from tracheal scar sites, 8 PSB samples from scar-free sites and 8 BAL samples, by lavaging the subsegmental bronchi of the right-middle lobe. Metagenomic sequencing was performed to characterize the microbiome profiling of 16 PSB and 8 BAL samples. Untargeted metabolomics was performed in 6 PSB samples (3 from tracheal scar PSB and 3 from tracheal scar-free PSB) using high-performance liquid chromatography‒mass spectrometry (LC‒MS).

RESULTS

At the species level, the top four bacterial species were Neisseria subflava, Streptococcus oralis, Capnocytophaga gingivals, and Haemophilus aegyptius. The alpha and beta diversity among tracheal scar PSB, scar-free PSB and BAL samples were compared, and no significant differences were found. Untargeted metabolomics was performed in 6 PSB samples using LC‒MS, and only one statistically significant metabolite, carnitine, was identified. Pathway enrichment analysis of carnitine revealed significant enrichment in fatty acid oxidation.

CONCLUSION

Our study found that carnitine levels in tracheal scar tissue were significantly lower than those in scar-free tissue, which might be a new target for the prevention and treatment of iatrogenic tracheal stenosis in the future.

Research progress on the effects of gut microbiome on lung damage induced by particulate matter exposure

Air pollution is one of the top five causes of death in the world and has become a research hotspot. In the past, the health effects of particulate matter (PM), the main component of air pollutants, were mainly focused on the respiratory and cardiovascular systems. However, in recent years, the intestinal damage caused by PM and its relationship with gut microbiome (GM) homeostasis, thereby affecting the composition and function of GM and bringing disease burden to the host lung through different mechanisms, have attracted more and more attention. Therefore, this paper reviews the latest research progress in the effect of PM on GM-induced lung damage and its possible interaction pathways and explores the potential immune inflammatory mechanism with the gut-lung axis as the hub in order to understand the current research situation and existing problems, and to provide new ideas for further research on the relationship between PM pollution, GM, and lung damage.

Dysbiosis of vaginal and cervical microbiome is associated with uterine fibroids

Dysbiosis of the female reproductive tract is closely associated with gynecologic diseases. Here, we aim to explore the association between dysbiosis in the genital tract and uterine fibroids (UFs) to further provide new insights into UF etiology. We present an observational study to profile vaginal and cervical microbiome from 29 women with UFs and 38 healthy women, and 125 samples were obtained and sequenced. By comparing the microbial profiles between different parts of the reproductive tract, there is no significant difference in microbial diversity between healthy subjects and UF patients. However, alpha diversity of UF patients was negatively correlated with the number of fibroids. Increased Firmicutes were observed in both the cervical and vaginal microbiome of UF patients at the phylum level. In differential analysis of relative abundance, some genera were shown to be significantly enriched (e.g., Erysipelatoclostridium, Mucispirillum, and Finegoldia) and depleted (e.g., Erysipelotrichaceae UCG-003 and Sporolactobacillus) in UF patients. Furthermore, the microbial co-occurrence networks of UF patients showed lower connectivity and complexity, suggesting reduced interactions and stability of the cervical and vaginal microbiota in UF patients. In summary, our findings revealed the perturbation of microbiome in the presence of UFs and a distinct pattern of characteristic vaginal and cervical microbiome involved in UFs, offering new options to further improve prevention and management strategies.

Comparative polar and lipid plasma metabolomics differentiate KSHV infection and disease states

BACKGROUND

Kaposi sarcoma (KS) is a neoplastic disease etiologically associated with infection by the Kaposi sarcoma-associated herpesvirus (KSHV). KS manifests primarily as cutaneous lesions in individuals due to either age (classical KS), HIV infection (epidemic KS), or tissue rejection preventatives in transplantation (iatrogenic KS) but can also occur in individuals, predominantly in sub-Saharan Africa (SSA), lacking any obvious immune suppression (endemic KS). The high endemicity of KSHV and human immunodeficiency virus-1 (HIV) co-infection in Africa results in KS being one of the top 5 cancers there. As with most viral cancers, infection with KSHV alone is insufficient to induce tumorigenesis. Indeed, KSHV infection of primary human endothelial cell cultures, even at high levels, is rarely associated with long-term culture, transformation, or growth deregulation, yet infection in vivo is sustained for life. Investigations of immune mediators that distinguish KSHV infection, KSHV/HIV co-infection, and symptomatic KS disease have yet to reveal consistent correlates of protection against or progression to KS. In addition to viral infection, it is plausible that pathogenesis also requires an immunological and metabolic environment permissive to the abnormal endothelial cell growth evident in KS tumors. In this study, we explored whether plasma metabolomes could differentiate asymptomatic KSHV-infected individuals with or without HIV co-infection and symptomatic KS from each other.

METHODS

To investigate how metabolic changes may correlate with co-infections and tumorigenesis, plasma samples derived from KSHV seropositive sub-Saharan African subjects in three groups, (A) asymptomatic (lacking neoplastic disease) with KSHV infection only, (B) asymptomatic co-infected with KSHV and HIV, and (C) symptomatic with clinically diagnosed KS, were subjected to analysis of lipid and polar metabolite profiles RESULTS: Polar and nonpolar plasma metabolic differentials were evident in both comparisons. Integration of the metabolic findings with our previously reported KS transcriptomics data suggests dysregulation of amino acid/urea cycle and purine metabolic pathways, in concert with viral infection in KS disease progression.

CONCLUSIONS

This study is, to our knowledge, the first to report human plasma metabolic differentials between in vivo KSHV infection and co-infection with HIV, as well as differentials between co-infection and epidemic KS.

Distinct global metabolomic profiles of the model organism Caenorhabditis elegans during interactions with Staphylococcus aureus and Salmonella enterica Serovar Typhi

The interactive network of hosts with pathogenic microbes is still questionable. It has been hypothesized and reported that the host shows altered regulatory mechanisms for different pathogens. Several studies using transcriptomics and proteomics revealed the altered pathways and sequential regulations displayed by the host during bacterial interactions. Still, there is a gap in understanding the triggering molecule at transcriptomic and proteomic levels due to the lack of the knowledge of the interactive metabolites produced during their interactions. In this study, the global metabolomic approach was performed in the nematode model organism Caenorhabditis elegans upon exposure to a Gram-negative bacteria, Salmonella enterica Serovar Typhi, and a Gram-positive bacteria, Staphylococcus aureus, and the whole metabolome was categorized as endo-metabolome (internally produced) and exo-metabolome (externally releasing). The extracted metabolites were subjected to liquid chromatography mass spectrometry (ESI-LC/qToF-MS/MS). In total 5578, 4554 and 4046 endo-metabolites and 4451, 3625 and 1281 exo-metabolites were identified in C. elegans when exposed to E. coli OP50, S. Typhi and S. aureus, respectively. Both the multivariate and univariate analyses were performed. The variation in endo- and exo-metabolome during candidate bacterial interactions was observed. The results indicated that, during S. aureus interaction, the exclusively enriched metabolites were significantly involved in alpha-linoleic acid metabolism. Similarly, the exclusively enriched metabolites during the interaction of S. Typhi were significantly involved in the phosphatidylinositol signalling system. The whole metabolomic profile presented here will build the scope to understand the role of metabolites and the respective pathways in host response during the early period of bacterial infections.

The traditional Chinese medicine and non-small cell lung cancer: from a gut microbiome perspective

Non-small cell lung cancer (NSCLC) is one of the most serious diseases affecting human health today, and current research is focusing on gut flora. There is a correlation between intestinal flora imbalance and lung cancer, but the specific mechanism is not clear. Based on the "lung and large intestine being interior-exteriorly related" and the "lung-intestinal axis" theory. Here, based on the theoretical comparisons of Chinese and western medicine, we summarized the regulation of intestinal flora in NSCLC by active ingredients of traditional Chinese medicine and Chinese herbal compounds and their intervention effects, which is conducive to providing new strategies and ideas for clinical prevention and treatment of NSCLC.

Association Studies on Gut and Lung Microbiomes in Patients with Lung Adenocarcinoma

Lung adenocarcinoma (LADC) is a prevalent type of lung cancer that is associated with lung and gut microbiota. However, the interactions between these microbiota and cancer development remain unclear. In this study, a microbiome study was performed on paired fecal and bronchoalveolar lavage fluid (BALF) samples from 42 patients with LADC and 64 healthy controls using 16S rRNA gene amplicon and shotgun metagenome sequencing, aiming to correlate the lung and gut microbiota with LADC. Patients with LADC had reduced α-diversity in the gut microbiome and altered β-diversity compared with healthy controls, and the abundances of Flavonifractor, Eggerthella, and Clostridium were higher in the gut microbiome of LADC patients. The increased abundance of microbial species, such as Flavonifractor plautii, was associated with advanced-stage LADC and a higher metastasis rate. Phylogenetically, Haemophilus parainfluenzae was the most frequently shared taxon in the lung and gut microbiota of LADC patients. Gut microbiome functional pathways involving leucine, propanoate, and fatty acids were associated with LADC progression. In conclusion, the low diversity of the gut microbiota and the presence of H. parainfluenzae in gut and lung microbiota were linked to LADC development, while an increased abundance of F. plautii and the enriched metabolic pathways could be associated with the progression of LADC.

Applying multi-omics toward tumor microbiome research

Rather than a "short-term tenant," the tumor microbiome has been shown to play a vital role as a "permanent resident," affecting carcinogenesis, cancer development, metastasis, and cancer therapies. As the tumor microbiome has great potential to become a target for the early diagnosis and treatment of cancer, recent research on the relevance of the tumor microbiota has attracted a wide range of attention from various scientific fields, resulting in remarkable progress that benefits from the development of interdisciplinary technologies. However, there are still a great variety of challenges in this emerging area, such as the low biomass of intratumoral bacteria and unculturable character of some microbial species. Due to the complexity of tumor microbiome research (e.g., the heterogeneity of tumor microenvironment), new methods with high spatial and temporal resolution are urgently needed. Among these developing methods, multi-omics technologies (combinations of genomics, transcriptomics, proteomics, and metabolomics) are powerful approaches that can facilitate the understanding of the tumor microbiome on different levels of the central dogma. Therefore, multi-omics (especially single-cell omics) will make enormous impacts on the future studies of the interplay between microbes and tumor microenvironment. In this review, we have systematically summarized the advances in multi-omics and their existing and potential applications in tumor microbiome research, thus providing an omics toolbox for investigators to reference in the future.

16S rDNA sequencing combined with metabolomics profiling with multi-index scoring method reveals the mechanism of salt-processed Semen Cuscuta in Bushen Antai mixture on kidney yang deficiency syndrome

Kidney yang deficiency syndrome (KYDS) is a classic syndrome of traditional Chinese medicine (TCM). The salt-processed product of Semen Cuscuta (YP) is the monarch drug in Bushen Antai Mixture (BAM), can improve the reproductive dysfunction caused by KYDS, and the effect is better than that of raw products of Semen Cuscuta (SP). However, its mechanism is not completely clear yet. In this study, an integrated strategy combining untargeted metabolomics with microbiology was used to explore the mechanism of YP in the BAM improving KYDS. 16S rDNA gene sequencing showed that BAM containing YP (Y-BAM) had a significantly better regulatory effect on Desulfobacterota and Desulfovibrionaceae_unclassified than BAM containing SP (S-BAM). Untargeted metabolomics studies showed that Y-BAM significantly regulated 4 metabolites and 4 metabolic pathways. In addition, multi-index analysis showed that the effect of Y-BAM on arachidonic acid metabolism, tyrosine metabolism, purine metabolism, fructose and mannose metabolism and total metabolism was closer to that of the control group compared to S-BAM. The analysis of serum biochemical indexes showed that Y-BAM had more significant regulating effect on the levels of luteinizing hormone (LH), follicle stimulating hormone (FSH), testosterone (T) and superoxide dismutase (SOD) in serum of KYDS rats compared to S-BAM. Spearman correlation analysis showed that there was a significant correlation between intestinal microorganisms and metabolites and serum biochemical indexes. For example, Desulfovibrionaceae_unclassified was positively correlated with arachidonic acid, and negatively correlated with SOD and LH. This study suggests that YP may enhance the regulation of intestinal flora and endogenous metabolism of KYDS, so that BAM shows a better therapeutic effect on KYDS, which also reasonably explains why BAM uses Semen Cuscuta stir-baked with salt solution.

Combined analysis of gut microbiome and serum metabolomics reveals novel biomarkers in patients with early-stage non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the predominant form of lung cancer and is one of the most fatal cancers worldwide. Recently, the International Association for the Study of Lung Cancer (IASLC) proposed a novel grading system based on the predominant and high-grade histological patterns for invasive pulmonary adenocarcinoma (IPA). To improve outcomes for NSCLC patients, we combined serum metabolomics and fecal microbiology to screen biomarkers in patients with early-stage NSCLC and identified characteristic microbial profiles in patients with different grades of IPA. 26 genera and 123 metabolites were significantly altered in the early-stage NSCLC patients. Agathobacter, Blautia, Clostridium, and Muribaculacea were more abundant in the early-stage NSCLC patients compared with healthy controls. For the different grades of IPA, the characteristic microorganisms are as follows: Blautia and Marinobacter in IPA grade type 1; Dorea in IPA grade type 2; and Agathobacter in IPA grade type 3. In the metabolome results, the early-stage NSCLC group mainly included higher levels of sphingolipids (D-erythro-sphingosine 1-phosphate, palmitoyl sphingomyelin), fatty acyl (Avocadyne 1-acetate, 12(S)-HETE, 20-Carboxy-Leukotriene B4, Thromboxane B3, 6-Keto-prostaglandin f1alpha, Sebacic acid, Tetradecanedioic acid) and glycerophospholipids (LPC 20:2, LPC 18:0, LPC 18:4, LPE 20:2, LPC 20:1, LPC 16:1, LPC 20:0, LPA 18:2, LPC 17:1, LPC 17:2, LPC 19:0). Dysregulation of pathways, such as sphingolipid metabolism and sphingolipid signaling pathway may become an emerging therapeutic strategy for early-NSCLC. Correlation analysis showed that gut microbiota and serum metabolic profiles were closely related, while Muribaculacea and Clostridium were the core genera. These findings provide new biomarkers for the diagnosis of early-stage NSCLC and the precise grading assessment of prognostic-related IPAs, which are of clinical importance and warrant further investigation of the underlying molecular mechanisms.

Label-free LC-MS/MS proteomics analyses reveal CLIC1 as a predictive biomarker for bladder cancer staging and prognosis

Introduction

Bladder cancer (BC) is a significant carcinoma of the urinary system that has a high incidence of morbidity and death owing to the challenges in accurately identifying people with early-stage BC and the lack of effective treatment options for those with advanced BC. Thus, there is a need to define new markers of prognosis and prediction.

Methods

In this study, we have performed a comprehensive proteomics experiment by label-free quantitative proteomics to compare the proteome changes in the serum of normal people and bladder cancer patients-the successful quantification of 2064 Quantifiable proteins in total. A quantitative analysis was conducted to determine the extent of changes in protein species' relative intensity and reproducibility. There were 43 upregulated proteins and 36 downregulated proteins discovered in non-muscle invasive bladder cancer and normal individuals. Sixty-four of these proteins were elevated, and 51 were downregulated in muscle-invasive and non-muscle-invasive bladder cancer, respectively. Functional roles of differentially expressed proteins were annotated using Gene Ontology (GO) and Clusters of Orthologous Groups of Proteins (COG). To analyze the functions and pathways enriched by differentially expressed proteins, GO enrichment analysis, protein domain analysis, and KEGG pathway analysis were performed. The proteome differences were examined and visualized using radar plots, heat maps, bubble plots, and Venn diagrams.

Results

As a result of combining the Venn diagram with protein-protein interactions (PPIs), Chloride intracellular channel 1 (CLIC1) was identified as the primary protein. Using the Gene Set Cancer Analysis (GSCA) website, the influence of CLIC1 on immune infiltration was analyzed. A negative correlation between CD8 naive and CLIC1 levels was found. For validation, immunohistochemical (IHC), qPCR, and western blotting (WB) were performed.Further, we found that CLIC1 was associated with a poor prognosis of bladder cancer in survival analysis.

Discussion

Our research screened CLIC1 as a tumor-promoting protein in bladder cancer for the first time using serum mass spectrometry. And CLIC1 associated with tumor stage, and immune infiltrate. The prognostic biomarker and therapeutic target CLIC1 may be new for bladder cancer patients.

Global research trends between gut microbiota and lung cancer from 2011 to 2022: A bibliometric and visualization analysis

Background

An increasing number of studies have found that the gut microbiota was related to the occurrence and development of lung cancer. Nonetheless, publication trends and research hotspots in this field remain unknown. The study aimed to perform a bibliometric analysis to systematically identify publication trends and research hotspots in the field of gut microbiota and lung cancer research within a 12-year panorama.

Methods

Publications related to the gut microbiota and lung cancer between 1 January 2011 and 25 October 2022 were retrieved from the Web of Science Core Collection (WoSCC) database. The online analytic tool of the WoSCC was used to analyze various bibliometric parameters. The bibliometrics website, CiteSpace, and VOSviewer were used to identify research trends and hotspots.

Results

A total of 375 publications related to the gut microbiota and lung cancer were extracted from WoSCC and identified for analysis. The number of annual publications has grown rapidly since 2018 and reached a peak in 2022. China was the most prolific country in this field, with 120 publications, followed by the United States (114), with the highest H-index of 31. Additionally, France ranked the highest with an average of 133 citations, while the leading institution and journal were the Unicancer and the International Journal of Molecular Sciences, respectively. Interestingly, Routy Bertrand was the most prolific author and also the most cited author in terms of H-index and citations. Reference and keyword burst detection indicated that the research hotspots mainly included 1) the gut microbiota directly affects the efficacy of immunotherapy for lung cancer, 2) the application of different gut bacteria on lung cancer, and 3) the mechanism of the gut microbiota on lung cancer.

Conclusion

The findings of this study revealed the general publication trends and evolving research hotspots in the field of gut microbiota and lung cancer at a global level. The research hotspots focused on the clinical application of the gut microbiota combined with immunotherapy in lung cancer and its mechanism. The findings of this study provide new perspectives on the field, which may shed light on a beneficial impact on further etiological studies, diagnosis, and treatment for lung cancer.

New Insights into the Relationship between Gut Microbiota and Radiotherapy for Cancer

Cancer is the second most common cause of death among humans in the world, and the threat that it presents to human health is becoming more and more serious. The mechanisms of cancer development have not yet been fully elucidated, and new therapies are changing with each passing day. Evidence from the literature has validated the finding that the composition and modification of gut microbiota play an important role in the development of many different types of cancer. The results also demonstrate that there is a bidirectional interaction between the gut microbiota and radiotherapy treatments for cancer. In a nutshell, the modifications of the gut microbiota caused by radiotherapy have an effect on tumor radiosensitivity and, as a result, affect the efficacy of radiotherapy and show a certain radiation toxicity, which leads to numerous side effects. What is of new research significance is that the "gut-organ axis" formed by the gut microbiota may be one of the most interesting potential mechanisms, although the relevant research is still very limited. In this review, we combine new insights into the relationship between the gut microbiota, cancer, and radiotherapy. Based on our current comprehensive understanding of this relationship, we give an overview of the new cancer treatments based on the gut microbiota.

Prediction model of poorly differentiated colorectal cancer (CRC) based on gut bacteria

BACKGROUND

The mortality of colorectal cancer is high, the malignant degree of poorly differentiated colorectal cancer is high, and the prognosis is poor.

OBJECTIVE

To screen the characteristic intestinal microbiota of poorly differentiated intestinal cancer.

METHODS

Fecal samples were collected from 124 patients with moderately differentiated CRC and 123 patients with poorly differentiated CRC, and the bacterial 16S rRNA V1-V4 region of the fecal samples was sequenced. Alpha diversity analysis was performed on fecal samples to assess the diversity and abundance of flora. The RDP classifier Bayesian algorithm was used to analyze the community structure. Linear discriminant analysis and Student's t test were used to screen the differences in flora. The PICRUSt1 method was used to predict the bacterial function, and six machine learning models, including logistic regression, random forest, neural network, support vector machine, CatBoost and gradient boosting decision tree, were used to construct a prediction model for the poor differentiation of colorectal cancer.

RESULTS

There was no significant difference in fecal flora alpha diversity between moderately and poorly differentiated colorectal cancer (P > 0.05). The bacteria that accounted for a large proportion of patients with poorly differentiated and moderately differentiated colorectal cancer were Blautia, Escherichia-Shigella, Streptococcus, Lactobacillus, and Bacteroides. At the genus level, there were nine bacteria with high abundance in the poorly differentiated group, including Bifidobacterium, norank_f__Oscillospiraceae, Eisenbergiella, etc. There were six bacteria with high abundance in the moderately differentiated group, including Megamonas, Erysipelotrichaceae_UCG-003, Actinomyces, etc. The RF model had the highest prediction accuracy (100.00% correct). The bacteria that had the greatest variable importance in the model were Pseudoramibacter, Megamonas and Bifidobacterium.

CONCLUSION

The degree of pathological differentiation of colorectal cancer was related to gut flora, and poorly differentiated colorectal cancer had some different bacterial flora, and intestinal bacteria can be used as biomarkers for predicting poorly differentiated CRC.