Despite extensive investigations into the microbiome and metabolome changes associated with colon polyps and colorectal cancer (CRC), the microbiome and metabolome profiles of individuals with colonic polyposis, including those with (Gene-pos) and without (Gene-neg) a known genetic driver, remain comparatively unexplored. Using colon biopsies, polyps, and stool from patients with Gene-pos adenomatous polyposis (N = 9), Gene-neg adenomatous polyposis (N = 18), and serrated polyposis syndrome (SPS, N = 11), we demonstrated through 16S rRNA sequencing that the mucosa-associated microbiota in individuals with colonic polyposis is representative of the microbiota associated with small polyps, and that both Gene-pos and SPS cohorts exhibit differential microbiota populations relative to Gene-neg polyposis cohorts. Furthermore, we used these differential microbiota taxa to perform linear discriminant analysis to differentiate Gene-neg subjects from Gene-pos and from SPS subjects with an accuracy of 89% and 93% respectively. Stool metabolites were quantified via 1H NMR, revealing an increase in alanine in SPS subjects relative to non-polyposis subjects, and Partial Least Squares Discriminant Analysis (PLS-DA) analysis indicated that the proportion of leucine to tyrosine in fecal samples may be predictive of SPS. Use of these microbial and metabolomic signatures may allow for better diagnostric and risk-stratification tools for colonic polyposis patients and their families as well as promote development of microbiome-targeted approaches for polyp prevention.

Complex relationships between the human microbiome and cancer are increasingly recognized for cancer sites that harbor commensal microbial communities such as the gut, genitourinary tract, and skin. For organ sites that likely do not contain commensal microbiota, there is still a substantial capacity for the human-associated microbiota to influence disease etiology across the cancer spectrum. We propose such a relationship for prostate cancer, the most commonly diagnosed cancer in males in the United States. This review explores the current evidence for a role for the urinary and gut microbiota in prostate cancer risk, via both direct interactions (prostate infections) and long-distance interactions such as via the metabolism of procarcinogenic or anticarcinogenic dietary metabolites. We further explore a newly recognized role of the gut microbiota in mediating cancer treatment response or resistance either via production of androgens and/or procarcinogenic metabolites or via direct metabolism of anticancer drugs that are used to treat advanced disease. Overall, we present the current state of knowledge relating to how the human microbiome mediates prostate cancer risk, progression, and therapy response, as well as suggest future research directions for the field.

Periodontal disease affects individuals' quality of life across economic, social, and psychological dimensions. Without timely and appropriate treatment, it can lead to tooth loss. This disease is potentially associated with certain types of cancer. The aim of this study was to investigate the relationship between periodontal disease and the risk of breast cancer. This study examined 200 women with breast cancer and 200 healthy women over the age of 35. Age and gender were matched between the case and control groups. A questionnaire was completed for all participants, which included epidemiological indicators such as age, gender, smoking status, alcohol consumption, socio-economic and educational status, body mass index (BMI), family history of breast cancer, age at menarche, age at menopause, physical inactivity, current diseases, and past medical/dental history. Periodontal status indicators, including probing pocket depth (PPD), bleeding on probing (BOP), attachment loss (AL), and gingival index (GI), were also evaluated. Statistical analysis was performed using Chi-square tests, multivariate regression models, and SPSS software version 21. A p-value of < 0.05 was considered statistically significant for all tests. The study revealed that a family history of breast cancer, early menarche, late menopause, age at first pregnancy, BMI above 25 and higher GI were significantly associated with an increased risk of breast cancer. After running Step 1a of the regression model, it was found that family history of breast cancer, increased BMI and GI were significantly associated with the risk of breast cancer. However, no statistically significant differences were found regarding age, educational level, socio-economic status, smoking, BOP, and PPD in relation to breast cancer occurrence. Individuals with a positive family history of breast cancer, higher BMI, and elevated GI were significantly at greater risk of developing breast cancer.

The human microbiome, an intricate ecosystem of trillions of microbes residing across various body sites, significantly influences cancer, a leading cause of morbidity and mortality worldwide. Recent studies have illuminated the microbiome's pivotal role in cancer development, either through direct cellular interactions or by secreting bioactive compounds such as metabolites. Microbial metabolites contribute to cancer initiation through mechanisms such as DNA damage, epithelial barrier dysfunction, and chronic inflammation. Furthermore, microbial metabolites exert dual roles on cancer progression and response to therapy by modulating cellular metabolism, gene expression, and signaling pathways. Understanding these complex interactions is vital for devising new therapeutic strategies. This review highlights microbial metabolites as promising targets for cancer prevention and treatment, emphasizing their impact on therapy responses and underscoring the need for further research into their roles in metastasis and therapy resistance.

Cigarette smoke exposure (CSE) increases the risk for a plethora of cancers. Recent evidence indicates that the gut microbiome can influence cancer progression by immune system modulation. Since CSE alters the gut microbiome, we hypothesized that the gut microbiome serves as a causative link between smoking and cancer growth. Through a combination of syngeneic animal models and fecal microbiota transplantation studies, we established an essential role for smoke-induced dysbiosis in cancer growth. 16s rRNA sequencing and liquid chromatography-mass spectrometry indicated a unique CSE-associated microbial and metabolomic signature. Immunophenotyping of tumor specimens and experiments in Rag1-KO and CD8-KO demonstrated that smoke-induced tumor growth requires functional adaptive immunity. Finally, utilizing gut microbial ablation strategies with broad- and narrow-spectrum antibiotics, we demonstrated the reversal of phenotypic effects of CSE. Our study provides evidence for gut microbiome as an actionable target to mitigate CSE-induced tumor promotion.

Colon cancer (CC) is one of the most common cancers globally, which is associated with the gut microbiota intimately. In current research, exploring the complex interaction between microbiomes and CC is a hotspot. However, the information on microbiomes in most previous studies is based on fecal, which does not fully display the microbial environment of CC. Herein, we collected mucosal and tissue samples from both the tumor and normal regions of 19 CC patients and clarified the composition of mucosal microbiota by 16S rRNA and metagenomic sequencing. Additionally, RNA-Seq was also conducted to identify the different expression genes between tumor and normal tissue samples. We revealed significantly different microbial community structures and expression profiles to CC. Depending on correlation analysis, we demonstrated that 1,472 genes were significantly correlated with CC tumor microbiota. Our study reveals a significant enrichment of Campylobacter jejuni in the mucosa of CC, which correlates with bile secretion. Additionally, we observe a negative correlation between C. jejuni and immune cells CD4+ Tem and mast cells. Finally, we discovered that metabolic bacterial endosymbiont of Bathymodiolus sp., Bacillus wiedmannii, and Mycobacterium tuberculosis had a significant survival value for CC, which was ignored by previous research. Overall, our study expands the understanding of the complex interplay between microbiota and CC and provides new targets for the treatment of CC.

This study contributes to our understanding of the interaction between microbiota and colon cancer (CC). By examining mucosal and tissue samples rather than solely relying on fecal samples, we have uncovered previously unknown aspects of CC-associated microbiota. Our findings reveal distinct microbial community structures and gene expression profiles correlated with CC progression. Notably, the enrichment of Campylobacter jejuni in CC mucosa, linked to bile secretion, underscores potential mechanisms in CC pathogenesis. Additionally, observed correlations between microbial taxa and immune cell populations offer new avenues for immunotherapy research in CC. Importantly, this study introduces CC-associated microbiota with survival implications for CC, expanding therapeutic targets beyond conventional strategies. By elucidating these correlations, our study not only contributes to uncovering the potential role of gut microbiota in colon cancer but also establishes a foundation for mechanistic studies of gut microbiota in colon cancer, emphasizing the broader impact of microbiota research on cancer biology.

Genitourinary cancers account for 20% of cancer instances globally and pose a substantial burden. The microbiome, defined as the ecosystem of organisms that reside within and on the human body, seems to be closely related to multiple cancers. Research on the gut microbiome has yielded substantial insights into the interactions of this entity with the immune system and cancer therapeutic efficacy, whereas the urinary microbiome has been relatively less well-studied. Advances in next-generation sequencing technologies led to new discoveries in the urinary microbiome, which might aid in early detection, risk stratification and personalized treatment strategies in genitourinary cancers. Mechanistic investigations have also suggested a role for the urinary microbiome in modulating the tumour microenvironment and host immune response. For example, distinct urinary microbial signatures have been linked to bladder cancer occurrence and recurrence risk, with specific taxa associated with cytokine production and inflammation. Urinary microbiome signatures have also been explored as potential biomarkers for non-invasive cancer detection. However, challenges remain in standardizing methodologies, validating findings across studies, and establishing causative mechanisms. As investigations into the urinary microbiome continue to evolve, so does the potential for developing microbiome-modulating therapies and enhancing diagnostic capabilities to improve outcomes in patients with genitourinary cancers.

Accurate prediction of microbe-drug associations is essential for drug development and disease diagnosis. However, existing methods often struggle to capture complex nonlinear relationships, effectively model long-range dependencies, and distinguish subtle similarities between microbes and drugs. To address these challenges, this paper introduces a new model for microbe-drug association prediction, CLMT. The proposed model differs from previous approaches in three key ways. Firstly, unlike conventional GCN-based models, CLMT leverages a Graph Transformer network with an attention mechanism to model high-order dependencies in the microbe-drug interaction graph, enhancing its ability to capture long-range associations. Then, we introduce graph contrastive learning, generating multiple augmented views through node perturbation and edge dropout. By optimizing a contrastive loss, CLMT distinguishes subtle structural variations, making the learned embeddings more robust and generalizable. By integrating multi-view contrastive learning and Transformer-based encoding, CLMT effectively mitigates data sparsity issues, significantly outperforming existing methods. Experimental results on three publicly available datasets demonstrate that CLMT achieves state-of-the-art performance, particularly in handling sparse data and nonlinear microbe-drug interactions, confirming its effectiveness for real-world biomedical applications. On the MDAD, aBiofilm, and Drug Virus datasets, CLMT outperforms the previously best model in terms of Accuracy by 4.3%, 3.5%, and 2.8%, respectively.

Colorectal cancer (CRC) is a common malignancy requiring early screening to improve patient outcomes. Current screening methods such as colonoscopy and fecal occult blood tests have several limitations including high cost, poor specificity, invasiveness, and inconvenience. Recent research has identified specific bacterial communities associated with CRC, notably Parvimonas micra (P. micra), which serves as a biomarker for early screening and diagnosis owing to its accumulation in the malignant tissues and feces of CRC patients. Herein, we employed the whole-bacterium systematic evolution of ligands by the exponential enrichment (SELEX) method to isolate high-affinity aptamers against P. micra using 17 selection cycles. These aptamers were subsequently bound to Au@Fe3O4 nanoparticles, and the interaction of P. micra and aptamers inhibited the peroxidase-like activity of Au@Fe3O4 nanoparticles, thereby blocking the 3,3',5,5'-tetramethylbenzidine (TMB) chromogenic reaction and resulting in a measurable reduction in absorbance. This colorimetric detection strategy demonstrated a linear response across a range of 100-108 CFU/mL for P. micra with a limit of detection of 11 CFU/mL. Using a colorimetric aptasensor, we assessed the abundance of P. micra in clinical fecal samples and found significantly higher levels in the feces of CRC patients as compared to that of healthy individuals, which was consistent with the quantitative polymerase chain reaction results. This study therefore represents the first successful identification of an aptamer with high affinity and specificity for P. micra, leading to the development of a highly specific and sensitive aptasensor for its detection. The presented approach has a significant potential for CRC screening and diagnosis.

The gut microbiota has been strongly linked to gastrointestinal cancer, but the relationship between gut microbiota and esophageal cancer (EC) is still not fully understood. We conducted a 2-sample Mendelian randomization (MR) study to unveil the potential impact of intestinal microorganisms on EC in East Asian populations. In order to delve deeper into the potential causal relationship between gut microbiota and EC, we conducted a 2-sample MR analysis, utilizing 211 single nucleotide polymorphisms associated with gut microbiota, sourced from the largest genome-wide association study on gut microbiota, for our analysis. To estimate the causal relationship, we employed the inverse variance weighting method. In addition, to assess the potential influence of pleiotropy, we used MR-Egger regression in our analysis. Among the 10 specific bacterial taxa identified using the inverse variance weighting as being associated with the risk of EC, we observed a positive association between family Bacteroidaceae (P = .04), genus Bacteroides (P = .04), genus Bilophila (P = .02), genus Candidatus Soleaferrea (P = .02) and the EC, while family Victivallaceae (P = .03), genus Eubacterium coprostanoligenes (P = .01), genus Catenibacterium (P = .01), genus Coprococcus2 (P = .01), unknowngenus.id.959 (P = .02) and unknowngenus.id.1868 (P = .01) may be associated with a reduced risk of EC. Our MR analysis indicate a probable association between gut microbiota and the development and advancement of EC. These findings offer novel perspectives on the possible application of targeted gut bacteria for the prevention and management of EC.

An increasing number of studies indicate that the gut, cervical, and vaginal microbiota may play crucial roles in the development of cervical cancer (CC). However, the interactions between the microbiota and the host are yet unknown. To address this gap, a systematic review and meta-analysis were conducted to assess the microbiota alterations in a variety of body locations, including the gut and genital tract.

Electronic searches of PubMed, Embase, Web of Science, and the Cochrane Library were conducted to retrieve eligible papers published from January 1, 2014, to January 1, 2024 (PROSPERO: CRD42024554433). This study was restricted to English-language studies reporting on alpha diversity, beta diversity, and relative abundance, as well as on patients with CC whose microbiota had been analyzed via next-generation sequencing technologies. To assess the risk of bias (RoB), we utilized the Newcastle‒Ottawa Quality Assessment Scale (NOS) and the ROBINS-I tool. For the meta-analysis, we employed Review Manager 5.4.

Thirty-six eligible studies were included in this review. The Chao1 index (SMD = 0.96, [95% CI: 0.71, 1.21], I2 = 0%) and the Shannon index (SMD = 1.02, [95% CI: 0.53, 1.50], I2 = 85%) values from vaginal samples were significantly greater in patients than in the controls. In the cervical samples, the Shannon index value (SMD = 1.29, [95% CI: 0.61, 1.97], I2 = 93%) significantly increased, whereas the Chao1 index value did not significantly differ (SMD = 0.50, [95% CI: -0.46, 1.46], I2 = 89%). The Shannon index value (SMD = 0.25, [95% CI: -0.22, 0.72], I2 = 38%) did not significantly differ across the gut samples. The majority of studies (19/25) indicated that the patients and noncancer controls differed significantly in terms of beta diversity. Cancer-associated changes were observed, with a dramatic decrease in the Lactobacillus genus and significant increases in pathogenic bacteria, including the Anaerococcus, Peptostreptococcus, Porphyromonas, Prevotella, and Sneathia genera. Additionally, the impact of antineoplastic therapies on microbial diversity was inconsistently reported across several studies.

This systematic review elucidates the microbiota alterations associated with the prevalence of CC and its response to anti-tumor therapies, aiming to provide insights for future research directions and precision medicine strategies to enhance women's quality of life.

CRD42024554433.

Craniofacial microsomia (CFM) is the second most common congenital craniofacial deformity, presenting diverse clinical manifestations and treatments that may influence oral bacteria dysbiosis (OBD). However, research linking CFM to OBD is limited. Saliva samples were collected from 20 patients with CFM and 24 controls. We compared oral microflora and gene function using 16 S ribosomal RNA sequencing and metagenomics. We also evaluated the correlation between CFM clinical phenotypes and microbiota community structure. Patients with CFM demonstrated greater richness and evenness in their oral microflora. The dominant genera included several pathogenic species, such as Actinomyces, Fusobacterium, and Prevotella. Notably, the severity of CFM correlated positively with the abundance of Neisseria and Porphyromonas. Upregulated pathways were primarily linked to biotin and amino acid metabolism, such as Tryptophan metabolism and Lysine degradation, and further underscored the need for focused oral health interventions in this population. This study is the first to indicate that CFM patients exhibit unique oral bacterial dysbiosis, marked by a higher presence of opportunistic pathogens and increased pathways related to oral and systemic health. These findings highlight the importance of monitoring oral health in patients with CFM.

Gut microbiota is associated with endometrial cancer (EC); however, the causal relationship remains unexplored. This study attempted to explore the relationship between gut microbiota and EC using Mendelian randomization (MR) methods.

In this two-sample MR analysis, we used MiBioGen's gut microbiota data as the exposure and three datasets from European populations with EC as the outcome. The EC datasets included general EC, endometrioid histology, and non-endometrioid histology. Single nucleotide polymorphism (SNP) was used as the instrumental variable. Inverse variance weighted (IVW), multiplicative random effects IVW (MRE-IVW), Maximum likelihood (ML), MR Egger, MR-PRESSO, and the weighted median were used to perform MR analysis. Sensitivity analysis was conducted to assess the reliability of the results.

In this MR analysis of three EC datasets, specific gut microbiota were identified as potentially associated with different pathological types of EC. For general EC (ID: ebi-a-GCST006464), Family.Acidaminococcaceae (OR = 1.23, 95%CI: 1.02-1.48) and genus.Butyrivibrio (OR = 1.08, 95%CI: 1.01-1.16) were identified as risk factors, while genus.Ruminococcaceae UCG014 (OR = 0.82, 95%CI: 0.69-0.98) and genus.Turicibacter (OR = 0.84, 95%CI: 0.73-0.97) appeared to have protective effects. For endometrioid histology EC (ID: ebi-a-GCST006465), Family.Acidaminococcaceae (OR = 1.27, 95%CI: 1.01-1.59) and genus.Butyrivibrio (OR = 1.10, 95%CI: 1.01-1.19) were identified as risk factors, while several microbiota, including Family.Lactobacillaceae, genus.Coprococcus3, genus.Dorea, genus.Flavonifractor, genus.Lactobacillus, genus.Paraprevotella, and genus.Turicibacter, were identified as protective factors. For non-endometrioid histology EC (ID: ebi-a-GCST006466), Family.Rhodospirillaceae (OR = 1.41, 95%CI: 1.01-1.96) and genus.Peptococcus (OR = 1.43, 95%CI: 1.07-1.91) were identified as risk factors, while no significant protective factors were identified.

This two-sample MR study has identified gut microbiota with potential causal relationships with EC, varying by pathological type. These findings provide new insights into the pathogenesis of EC and suggest directions for future research on diagnosis and treatment strategies.

This scholarly review comprehensively examines the connection between dietary habits, gut health, cancer prognosis, and genomic profiles. It emphasizes the crucial role of gut microbiota in mediating genomic changes and oncogenic processes through metabolic derivatives.It advocatеs for pеrsonalizеd nutrition stratеgiеs based on individual microbiomе and gеnomic profilеs and proposеs that customized diеtary intеrvеntions could play a crucial rolе in cancеr prеvеntion thеrapy. Thе article highlights thе influеncе of spеcific nutriеnts and such as diеtary fibеr and polyphеnols found in cеrtain foods and dеmonstrating thеir potеntial to altеr gеnе еxprеssions associatеd with inflammation and tumorigеnеsis. Thе rеviеw citеs rеcеnt studiеs that support thе idеa that diеtary modifications can influеncе gеnе rеgulation and thеrеby potеntially altеring cancеr progrеssion. Nevertheless, it calls for morе rigorous rеsеarch including longitudinal and randomizеd studies, to substantiatе thе еvidеncе nеcеssary for developing diеtary guidеlinеs tailorеd for cancеr patiеnts. Thе rеviеw еmphasizеs thе nееd for a multidisciplinary approach and highlight thе importancе of collaboration across thе fiеlds of nutrition gеnomics microbiology and oncology to improve cancеr trеatmеnts and patiеnt quality of lifе. It posits thе rеviеw as a cornеrstonе for a divеrsе audiеncе within thе scientific and mеdical communitimphasizing thе nеcеssity for ongoing rеsеarch in nutritional gеnomics which it dеpicts as a fiеld full of opportunitiеs to transform cancеr carе.

Endometrial cancer (EC) is a significant gynecological malignancy with increasing incidence worldwide. Emerging evidence highlights the role of the uterine microbiome in the pathogenesis of EC. This study aims to characterize the uterine microbiome in EC patients and identify potential microbial biomarkers, with a focus on Anaerococcus as a differentiating taxon.

The endocervical canal swabs from patients with EC (n=16) and non-cancerous patients (EM, n=13) were collected. The V3-V4 region of the 16S rRNA gene was sequenced using the Illumina platform. Bioinformatic analyses were performed with QIIME2, and statistical comparisons were conducted to assess differences in microbial composition and diversity. In vitro experiments were conducted to assess the functional impact of Anaerococcus on human uterine fibroblasts, including its ability to adhere to the human cells and induce oxidative stress.

The α-diversity metrics, including Shannon entropy and observed amplicon sequence variants (ASVs), revealed significantly higher microbial diversity in EC samples compared to EM. Anaerococcus was identified as a key taxon differentiating EC from EM groups, showing a higher relative abundance in EC samples. Functional predictions and in vitro assays indicated that Anaerococcus may contribute to carcinogenesis by inducing reactive oxygen species (ROS) production, and has the high ability to adhere to the human endometrial fibroblasts.

The study provides evidence of distinct microbial signatures in EC, with Anaerococcus emerging as a potential biomarker. The in vitro findings suggest its role in endometrial carcinogenesis, underscoring its potential as a target for future diagnostic and therapeutic applications.

Persistent infection with oncogenic human papillomavirus (HPV) types, such as HPV 16 or 18, is a major factor in cervical cancer development. However, only a small percentage of infected women develop cancer, indicating that other factors are involved. Emerging evidence links vaginal microbiota with HPV persistence and cancer progression. Alterations in microbial composition, function, and metabolic pathways may contribute to this process. Despite the potential of metagenomics to explore these interactions, studies on the vaginal microbiota's role in cervical cancer are limited. This review systematically examines the relationship between cervical microbiota, HPV, and cervical cancer by analyzing studies from PubMed, EBSCO, and Scopus. We highlight how microbial diversity influences HPV persistence and cancer progression, noting that healthy women typically have lower microbiota diversity and higher Lactobacillus abundance compared to HPV-infected women, who exhibit increased Gardenella, Prevotella, Sneathia, Megasphaera, Streptococcus, and Fusobacterium spp., associated with dysbiosis. We discuss how microbial diversity is associated with HPV persistence and cancer progression, noting that studies suggest healthy women typically have lower microbiota diversity and higher Lactobacillus abundance, while HPV-infected women exhibit increased Gardnerella, Prevotella, Sneathia, Megasphaera, Streptococcus, and Fusobacterium spp., indicative of dysbiosis. Potential markers such as Gardnerella and Prevotella have been identified as potential microbiome biomarkers associated with HPV infection and cervical cancer progression. The review also discusses microbiome-related gene expression changes in cervical cancer patients. However, further research is needed to validate these findings and explore additional microbiome alterations in cancer progression.

Predicting potential associations between microbes and drugs is crucial for advancing pharmaceutical research and development. In this manuscript, we introduced an innovative computational model named BANNMDA by integrating Bilinear Attention Networks(BAN) with the Nuclear Norm Minimization (NNM) to uncover hidden connections between microbes and drugs.

In BANNMDA, we initially constructed a heterogeneous microbe-drug network by combining multiple drug and microbe similarity metrics with known microbe-drug relationships. Subsequently, we applied both BAN and NNM to compute predicted scores of potential microbe-drug associations. Finally, we implemented 5-fold cross-validation frameworks to evaluate the prediction performance of BANNMDA.

The experimental results indicated that BANNMDA outperformed state-of-the-art competitive methods. We conducted case studies on well-known drugs such as the Amoxicillin and Ceftazidime, as well as on pathogens such as Bacillus cereus and Influenza A virus, to further evaluate the efficacy of BANNMDA, and experimental outcomes showed that there were 9 out of the top 10 predicted drugs, along with 8 and 9 out of the top 10 predicted microbes having been corroborated by relevant literatures. These findings underscored the capability of BANNMDA to achieve commendable predictive accuracy.

This editorial, inspired by a recent study published in the World Journal of Gastrointestinal Oncology, covers the research findings on microbiota changes in various diseases. In recurrent colorectal polyps, the abundances of Klebsiella, Parvimonas, and Clostridium increase, while those of Bifidobacterium and Lactobacillus decrease. This dysbiosis may promote the formation and recurrence of polyps. Similar microbial changes have also been observed in colorectal cancer, inflammatory bowel disease, autism spectrum disorder, and metabolic syndrome, indicating the role of increased pathogens and decreased probiotics in these conditions. Regulating the gut microbiota, particularly by increasing probiotic levels, may help prevent polyp recurrence and promote gut health. This microbial intervention strategy holds promise as an adjunctive treatment for patients with colorectal polyps.

The human body harbors a vast array of microorganisms. Changes in the microbial ecosystem can potentially lead to diseases, including cancer. Traditionally, research has focused more on the gut microbiota and its influence on cancer. However, with the advancement of sequencing technologies, scholars have discovered that microorganisms within kidney tissues are significant components of tumor tissues. Intratumoral microorganisms may affect tumor growth and development through certain mechanisms, influence the function of immune cells, or impact the effectiveness of chemotherapy or immunotherapy in patients. This paper reviews the latest progress in the research on intratumoral microorganisms in renal cancer (RCa). It summarizes the types and distribution characteristics of these microorganisms, discusses the close association between specific viral infections (such as HPV and EBV) and RCa, and highlights the role of microorganisms in the pathogenesis of RCa. This review provides new perspectives for understanding the pathogenic mechanisms of RCa, thereby offering potential clinical applications.

The human microbiota plays a crucial role in maintaining overall health and well-being. The gut microbiota has been implicated in developing and progressing various diseases, including cancer. This review highlights the related mechanisms and the compositions that influence cancer pathogenesis with a highlight on gastric cancer. We provide a comprehensive overview of the mechanisms by which the microbiome influences cancer development, progression, and response to treatment, with a focus on identifying potential biomarkers for early detection, prevention strategies, and novel therapeutic interventions that leverage microbiome modulation. This comprehensive review can guide future research and clinical practices in understanding and harnessing the microbiome to optimize gastric cancer therapies.

Gut bacterial metabolism of dietary flavonoids results in the production of a variety of phenolic acids, whose contributions to health remain poorly understood. Here, we show that supplementation with the commonly consumed flavonoid quercetin impacted gut microbiome composition and resulted in a significant reduction in atherosclerosis burden in conventionally raised (ConvR) Apolipoprotein E (ApoE) knockout (KO) mice but not in germ-free (GF) ApoE KO mice. Metabolomic analysis revealed that consumption of quercetin significantly increased plasma levels of benzoylglutamic acid, 3,4 dihydroxybenzoic acid (3,4-DHBA) and its sulfate-conjugated form in ConvR mice, but not in GF mice supplemented with the flavonoid. Levels of these metabolites were negatively associated with atherosclerosis burden. Furthermore, we show that 3,4-DHBA prevented lipopolysaccharide (LPS)-induced decrease in transendothelial electrical resistance (TEER). These results suggest that the effects of quercetin on atherosclerosis are influenced by gut microbes and are potentially mediated by bacterial metabolites derived from the flavonoid.

The advent of checkpoint immunotherapy has dramatically changed the outcomes for patients with cancer. However, a considerable number of patients have little or no response to therapy. We review recent findings on the connection between the gut microbiota and the immune system, exploring whether this link could enhance the effectiveness of immunotherapy.

Clinical studies have reported specific types of bacteria in larger quantities at baseline in responders than in non-responders, especially Akkermansia mucinifila, Ruminococcaceae, Faecalibacterium, and Lachnospiraceae. Following the consumption of a high-fiber diet, bacteria in the gut ferment dietary fiber to short-chain fatty acids (SCFAs), like acetate, propionate, and butyrate. Some of the SCFAs nurture intestinal epithelial cells, and some enter the bloodstream. Here SCFAs can activate DC8 + cytotoxic T-cells to induce cancer cell death. High fiber intake in the diet was associated with a reduced risk of progression or death during checkpoint immunotherapy. Recent findings demonstrate that high-fiber plant-based diets such as the Mediterranean Diet positively influence the gut microbiota whereas antibiotics and proton pump inhibitors can negatively influence outcomes of cancer immunotherapy by changing the gut microbiota. This narrative review provides evidence of an association between types of bacteria and their metabolites and favorable responses to checkpoint immunotherapy. Prospective clinical trials are needed to determine if diet interventions can improve treatment outcomes.

Microbiome and radiotherapy represent bidirectionally interacting entities. The human microbiome has emerged as a pivotal modulator of the efficacy and toxicity of radiotherapy; however, a reciprocal effect of radiotherapy on microbiome composition alterations has also been observed. This review explores the relationship between the microbiome and extracranial solid tumors, particularly focusing on the bidirectional impact of radiotherapy on organ-specific microbiome. This article aims to provide a systematic review on the radiotherapy-induced microbial alteration in-field as well as in distant microbiomes. In this review, particular focus is directed to the oral and gut microbiome, its role in the development and progression of cancer, and how it is altered throughout radiotherapy. This review concludes with recommendations for future research, such as exploring microbiome modification to optimize radiotherapy-induced toxicities or enhance its anti-cancer effects.

Gastric cancer (GC) incidence remains high worldwide, and the survival rate is poor. GC develops from atrophic gastritis (AG), associated with Helicobacter pylori (Hp) infection, passing through intestinal metaplasia and dysplasia steps. Since Hp eradication does not exclude GC development, further investigations are needed. New data suggest the possible role of unexplored gastric microbiota beyond Hp in the progression from AG to GC. Aimed to develop a score that could be used in clinical practice to stratify GC progression risk, here was investigate gastric microbiota in AG Hp-negative patients with or without high-grade dysplasia (HGD) or GC.

Consecutive patients undergoing upper endoscopy within an endoscopic follow-up for AG were considered. The antrum and corpus biopsies were used to assess the microbiota composition along the disease progression by sequencing the 16S ribosomal RNA gene. Statistical differences between HGD/GC and AG patients were included in a multivariate analysis.

HGD/GC patients had a higher percentage of Bacillus in the antrum and a low abundance of Rhizobiales, Weeksellaceae and Veillonella in the corpus. These data were used to calculate a multiparametric score (Resident Gastric Microbiota Dysbiosis Test, RGM-DT) to predict the risk of progression toward HGD/GC. The performance of RGM-DT in discriminating patients with HGD/GC showed a specificity of 88.9%.

The microbiome-based risk prediction model for GC could clarify the role of gastric microbiota as a cancer risk biomarker to be used in clinical practice. The proposed test might be used to personalize follow-up program thanks to a better cancer risk stratification.

As a key component of tumor microenvironment, the microbiota has gradually played a key role in cancer research. Particularly in colorectal cancer, the specific population of microbiota within the tumor shows a strong association with the tumor type. Although the existence and potential role of microbiota in tumors have been recognized, the specific associations between the microbiota and tumor tissue and the mechanism of action still need to be further explored. This paper reviews the discovery, origin, and emerging role of the intratumor microbiota in the immune microenvironment and systematically outlines the oncogenic and metastasis-promoting strategies of the intratumor microbiota. Moreover, it comprehensively and holistically evaluates therapeutic strategies and prognostic performance on the basis of the intratumor microbiota, with the goal of providing strong support for future research and clinical practice.

Introduction: Nutritional metabolomics provides a comprehensive overview of the biochemical processes that are induced by dietary intake through the measurement of metabolite profiles in biological samples. However, there is a lack of deep phenotypic analysis that shows how dietary interventions influence the metabolic state across multiple physiologic sites. Dietary amino acids have emerged as important nutrients for physiology and pathophysiology given their ability to impact cell metabolism. Methods: The aim of the current study is to evaluate the effect of modulating amino acids in diet on the metabolome and microbiome of mice. Here, we report a comprehensive metabolite profiling across serum, liver, and feces, in addition to gut microbial analyses, following a reduction in either total dietary protein or diet-derived non-essential amino acids in mice. Results: We observed both distinct and overlapping patterns in the metabolic profile changes across the three sample types, with the strongest signals observed in liver and serum. Although amino acids and related molecules were the most commonly and strongly altered group of metabolites, additional small molecule changes included those related to glycolysis and the tricarboxylic acid cycle. Microbial profiling of feces showed significant differences in the abundance of select species across groups of mice. Conclusions: Our results demonstrate how changes in dietary amino acids influence the metabolic profiles across organ systems and the utility of metabolomic profiling for assessing diet-induced alterations in metabolism.

In the contemporary field of life sciences, researchers have gradually recognized the critical role of microbes in maintaining human health. However, traditional biological experimental methods for validating the association between microbes and diseases are both time-consuming and costly. Therefore, developing effective computational methods to predict potential associations between microbes and diseases is an important and urgent task. In this study, we propose a novel computational framework, called GCATCMDA, for forecasting potential associations between microbes and diseases. Firstly, we construct Gaussian kernel similarity networks for microbes and diseases using known microbe-disease association data. Then, we design a feature encoder that combines graph convolutional network and graph attention mechanism to learn the node features of networks, and propose a feature dual-fusion module to effectively integrate node features from each layer's output. Next, we apply the feature encoder separately to the microbe similarity network, disease similarity network, and microbe-disease association network, and enhance the consistency of features for the same nodes across different association networks through contrastive learning. Finally, we pass the microbe and disease features into an inner product decoder to obtain the association scores between them. Experimental results demonstrate that the GCATCMDA model achieves superior predictive performance compared to previous methods. Furthermore, case studies confirm that GCATCMDA is an effective tool for predicting microbe-disease associations in real situations.

The association between gut microbiota (GM) and breast cancer (BC) has been studied. Nevertheless, the causal relationship between them and the potential mediating factors have not been clearly defined. Therefore, in this study, Mendelian randomization analysis (MR) was employed to explore the causal relationship between 473 GM and BC, as well as the mediating effect of potential immune cells. In this investigation, we availed ourselves of the publicly accessible summary statistics from the genome-wide association study to undertake two-sample and reverse Mendelian randomization analyses on GM and BC, with the intention of clarifying the causal association between GM and BC. Subsequently, through the application of the two-step Mendelian randomization analysis, it was revealed that the relationship between GM and BC was mediated by immune cells. The stability of the research outcomes was verified via sensitivity analysis. Mendelian randomization analysis elucidated the protective impacts of 8 genera on BC (such as Phylum Actinobacteriota, Species Bacteroides A plebeius A, Species Bifidobacterium adolescentis, Species CAG-841 sp002479075, Family Fibrobacteraceae, Order Fibrobacterales, Class Fibrobacteria, and Species Phascolarctobacterium sp003150755). Additionally, there are 23 immune cell traits related to BC. Our research findings showed that the species Megamonas funiformis was associated with an increased risk of BC, and 11.20% of this effect was mediated by CD38 on IgD+ CD24-. Likewise, HLA DR on CD33br HLA DR+ CD14- mediated the causal relationship between Species Prevotellamassilia and BC, having a mediating ratio of 7.89%. This study clarifies a potential causal relationship between GM, immune cells, and BC and provides genetic evidence for this causal connection. It offers research directions for the subsequent prevention and treatment of BC through the interaction between GM and immune cells, and provides a reference for future mechanistic and clinical studies in this field.

Host microbes are increasingly recognized as key components in various types of cancer, although their exact impact remains unclear. This study investigated the functional significance of Staphylococcus aureus (S. aureus) in breast cancer tumorigenesis and progression. We found that S. aureus invasion resulted in a compromised DNA damage response process, as evidenced by the absence of G1-phase arrest and apoptosis in breast cells in the background of double strand breaks production and the activation of the ataxia-telangiectasia mutated (ATM)-p53 signaling pathway. The high-throughput mRNA sequencing, bioinformatics analysis and pharmacological studies revealed that S. aureus facilitates breast cell metastasis through the innate immune pathway, particularly in cancer cells. During metastasis, S. aureus initially induced the expression of RIG-I-like receptors (RIG-I in normal breast cells, RIG-I and MDA5 in breast cancer cells), which in turn activated NF-κB p65 expression. We further showed that NF-κB p65 activated the CCL5-CCR5 pathway, contributing to breast cell metastasis. Our study provides novel evidence that the innate immune system, triggered by bacterial infection, plays a role in bacterial-driven cancer metastasis.

As next-generation sequencing technologies advance rapidly and the cost of metagenomic sequencing continues to decrease, researchers now face an unprecedented volume of microbiome data. This surge has stimulated the development of scalable microbiome data analysis methods and necessitated the incorporation of phylogenetic information into microbiome analysis for improved accuracy. Tools for constructing phylogenetic trees from 16S rRNA sequencing data are well-established, as the highly conserved regions of the 16S gene are limited, simplifying the identification of marker genes. In contrast, metagenomic and whole genome shotgun (WGS) sequencing involve sequencing from random fragments of the entire gene, making identification of consistent marker genes challenging owing to the vast diversity of genomic regions, resulting in a scarcity of robust tools for constructing phylogenetic trees. Although bacterial sequence tree construction tools exist for upstream bioinformatics, many downstream researchers-those integrating these trees into statistical models or machine learning-are either unaware of these tools or find them difficult to use due to the steep learning curve of processing raw sequences. This is compounded by the fact that public datasets often lack phylogenetic trees, providing only abundance tables and taxonomic classifications. To address this, we present a comprehensive review of phylogenetic tree construction techniques for microbiome data (16S rRNA or whole-genome shotgun sequencing). We outline the strengths and limitations of current methods, offering expert insights and step-by-step guidance to make these tools more accessible and widely applicable in quantitative microbiome data analysis.

Gut microbiota plays a prominent role in regulation of host nutrientmetabolism, drug and xenobiotics metabolism, immunomodulation and defense against pathogens. It synthesizes numerous metabolites thatmaintain the homeostasis of host. Any disbalance in the normalmicrobiota of gut can lead to pathological conditions includinginflammation and tumorigenesis. In the past few decades, theimportance of gut microbiota and its implication in various diseases, including cancer has been a prime focus in the field of research. Itplays a dual role in tumorigenesis, where it can accelerate as wellas inhibit the process. Various evidences validate the effects of gutmicrobiota in development and progression of malignancies, wheremanipulation of gut microbiota by probiotics, prebiotics, dietarymodifications and faecal microbiota transfer play a significant role.In this review, we focus on the current understanding of theinterrelationship between gut microbiota, immune system and cancer,the mechanisms by which they play dual role in promotion andinhibition of tumorigenesis. We have also discussed the role ofcertain bacteria with probiotic characteristics which can be used tomodulate the outcome of the various anti-cancer therapies under theinfluence of the alteration in the composition of gut microbiota.Future research primarily focusing on the microbiota as a communitywhich affect and modulate the treatment for cancer would benoteworthy in the field of oncology. This necessitates acomprehensive knowledge of the roles of individual as well asconsortium of microbiota in relation to physiology and response ofthe host.

This systematic review aims to investigate the microbial basis underlying the association between oral microbiota and colorectal cancer. A comprehensive search was conducted across four databases, encompassing potentially relevant studies published up to April 2024 related to the PECO question: "Is there a differentiation in oral microbial composition between adult patients diagnosed with colorectal cancer compared to healthy patients?". The Newcastle-Ottawa Scale was used to evaluate the quality of the studies included. The level of evidence was assessed through the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) tool. Sixteen studies fulfilled the eligibility criteria. Based on low to moderate evidence profile, high levels of certain subspecies within Firmicutes (such as Streptococcus anginosus, Peptostreptococcus stomatis, S. koreensis, and S. gallolyticus), Prevotella intermedia, Fusobacterium nucleatum, and Neisseria oralis were found to be associated with colorectal cancer. Conversely, certain bacteria (e.g., Lachnospiraceae, F. periodonticum, and P. melaninogenica) could exert a symbiotic protective effect against colorectal cancer. Based on existing evidence, it appears that variations in oral microbiota composition exist among individuals with and without colorectal cancer. However, further research is necessary to determine the mechanisms of oral dysbiosis in colorectal carcinogenesis.

Microbiota is present in the human tissue microenvironment and closely related to tumorigenesis and treatment. However, the landscape of tissue microbiome and its relationship with tumors remain less understood. In this study, we re-analyzed the omics data from the 7104 samples (94 projects for 15 cancers) in the NCBI database to obtain microbial profiles. After normalization and decontamination processing, we established classification models to distinguish between different tumors and tumor with adjacent normal tissues. The models had excellent performances, indicating that tissue microbiome had significant tumor specificity. Moreover, a series of key bacteria and bacteria-gene association pairs were screened out based on bioinformatic analysis, such as the tumor-promoting bacteria Fusobacterium, the tumor-suppressing bacteria Actinomyces, and the significant Rhodopseudomonas-COL1A1 association pair. In addition, we created a visual website, PTTM (http://198.46.152.196:7080/), for users to query and download the results. The identified key bacteria and association pairs provide candidate targets for further exploration of the molecular mechanisms of microbial action on tumorigenesis and the development of cancer therapy.

Metabolic alterations, a hallmark of cancer, enable tumor cells to adapt to their environment by modulating glucose, lipid, and amino acid metabolism, which fuels rapid growth and contributes to treatment resistance. In primary breast cancer, metabolic shifts such as the Warburg effect and enhanced lipid synthesis are closely linked to chemotherapy failure. Similarly, metastatic lesions often display distinct metabolic profiles that not only sustain tumor growth but also confer resistance to targeted therapies and immunotherapies. The review emphasizes two major aspects: the mechanisms driving metabolic resistance in both primary and metastatic breast cancer, and how the unique metabolic environments in metastatic sites further complicate treatment. By targeting distinct metabolic vulnerabilities at both the primary and metastatic stages, new strategies could improve the efficacy of existing therapies and provide better outcomes for breast cancer patients.

As a complicated and heterogeneous condition, breast cancer (BC) has posed a tremendous public health challenge across the world. Recent studies have uncovered the crucial effect of human microbiota on various perspectives of health and disease, which include cancer. The oral-gut microbiome axis, particularly, have been implicated in the occurrence and development of colorectal cancer through their intricate interactions with host immune system and modulation of systemic inflammation. However, the research concerning the impact of oral-gut microbiome axis on BC remains scarce. This study focused on comprehensively reviewing and summarizing the latest ideas about the potential bidirectional relation of the gut with oral microbiota in BC, emphasizing their potential impact on tumorigenesis, treatment response, and overall patient outcomes. This review can reveal the prospect of tumor microecology and propose a novel viewpoint that the oral-gut microbiome axis can be a breakthrough point in future BC studies.

Sulfur microbial diet (SMD) is a dietary pattern closely related to the intestinal load of sulfur-metabolizing microbes in humans. Diet and microbes may play an important role in the carcinogenesis of esophagus. However, epidemiological studies on SMD and esophageal cancer (EC) risk are scarce. Here, we evaluated this association based on a large American cohort.

In the cohort of the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, a SMD score was calculated to evaluate participants' compliance of SMD pattern, with higher scores presenting greater adherence. Cox hazards regression model was used to explore the association between the SMD score and the incidence of EC, esophageal squamous cell carcinoma (ESCC), and esophageal adenocarcinoma (EA). Subgroup analyses were conducted to figure out potential modifiers interacting with SMD on EC. Sensitivity analyses were used to testify the robustness of our main result.

Among 101,752 participants, 154 EC cases, consisted of 41 ESCC cases and 97 EA cases, were identified with mean follow-up of 8.9 years. In the fully adjusted model, the highest versus the lowest quartiles of the SMD score were found to be associated with an increased risk of EC and ESCC (EC: HRQ4 vs. Q1: 1.64; 95% CI: 1.05, 2.56; P = 0.016 for trend; ESCC: HRQ4 vs. Q1: 2.37; 95% CI: 1.02, 5.47; P = 0.031 for trend), while not significantly associated with increases risk of EA (HRQ4 vs. Q1: 1.41; P = 0.144 for trend). The main result remained through a series of sensitivity analyses. Subgroup analyses showed a stronger association between SMD and EC in participants with no regular consumption of aspirin (HRQ4 vs. Q1: 1.90; 95% CI: 1.04, 3.47) than in those using aspirin regularly (HRQ4 vs. Q1: 1.37; 95% CI: 0.71, 2.66) (P = 0.008 for interaction).

Adherence to the SMD pattern may be associated with increased risks of EC and ESCC, particularly for EC in individuals who do not regularly consume aspirin.

Melanoma is one of the most severe skin cancer indications with rapid progression and a high risk of metastasis. However, despite the accumulated advances in melanoma treatment including adjuvant radiation, chemotherapy, and immunotherapy, the overall melanoma treatment efficacy in the clinics is still not satisfactory. Interestingly, bacterial therapeutics have demonstrated unique properties for tumor-related therapeutic applications, such as tumor-targeted motility, tailorable cytotoxicity, and immunomodulatory capacity of the tumor microenvironment, which have emerged as a promising platform for melanoma therapy. Indeed, the recent advances in genetic engineering and nanotechnologies have boosted the application potential of bacterium-based therapeutics for treating melanoma by further enhancing their tumor-homing, cell-killing, drug delivery, and immunostimulatory capacities. This review provides a comprehensive summary of the state-of-the-art bacterium-based anti-melanoma modalities, which are categorized according to their unique functional merits, including tumor-specific cytotoxins, tumor-targeted drug delivery platforms, and immune-stimulatory agents. Furthermore, a perspective is provided discussing the potential challenges and breakthroughs in this area. The insights in this review may facilitate the development of more advanced bacterium-based therapeutic modalities for improved melanoma treatment efficacy.

The microbiota is defined as the microorganisms in a particular environment. Conversely, the term microbiome is less firmly defined and is used to reference the habitat.

To identify the association between the microbiome and the penile cancer EVIDENCE ACQUISITION: We performed this scoping review according to the recommendations of the Joanna Briggs Institute. We found five articles that fulfilled the inclusion criteria. We focused on oncogenesis and factors that alter the penile microbiome. We were not limited to language or setting. We searched MEDLINE (Ovid), Embase, Cochrane Central Register of Controlled Trials (CENTRAL), and LILACS from inception to the present day.

We found nine studies describing multiple factors that could disturb the microbiome, such as sexual behavior, anatomic alterations including circumcision, and inflammatory factors: lichen sclerosus, poor genital hygiene, compromised immune system, smoking, and HPV infection.

Overall, knowledge of the composition of the penile microbiota and its role in penile cancer oncogenesis is minimal.

Future studies should focus on the relationship between the microbiome and penile cancer to broaden this field of knowledge.

Models for microbial interactions attempt to understand and predict the steady state network of inter-species relationships in a community, e.g. competition for shared metabolites, and cooperation through cross-feeding. Flux balance analysis (FBA) is an approach that was introduced to model the interaction of a particular microbial species with its environment. This approach has been extended to analyzing interactions in a community of microbes; however, these approaches have two important drawbacks: first, one has to numerically solve a differential equation to identify the steady state, and second, there are no methods available to analyze the stability of the steady state. We propose a game theory based community FBA model wherein species compete to maximize their individual growth rate, and the state of the community is given by the resulting Nash equilibrium. We develop a computationally efficient method for directly computing the steady state biomasses and fluxes without solving a differential equation. We also develop a method to determine the stability of a steady state to perturbations in the biomasses and to invasion by new species. We report the results of applying our proposed framework to a small community of four E. coli mutants that compete for externally supplied glucose, as well as cooperate since the mutants are auxotrophic for metabolites exported by other mutants, and a more realistic model for a gut microbiome consisting of nine species.

The microbiota at different sites in the body is closely related to disease. The intake of probiotics is an effective strategy to alleviate diseases and be adjuvant in their treatment. However, probiotics may suffer from harsh environments and colonization resistance, making it difficult to maintain a sufficient number of live probiotics to reach the target sites and exert their original probiotic effects. Encapsulation of probiotics is an effective strategy. Therefore, probiotic delivery systems, as effective methods, have been continuously developed and innovated to ensure that probiotics are effectively delivered to the targeted site. In this review, initially, the design of probiotic delivery systems is reviewed from four aspects: probiotic characteristics, processing technologies, cell-derived wall materials, and interactions between wall materials. Subsequently, the review focuses on the effects of probiotic delivery systems that target four main microbial colonization sites: the oral cavity, skin, intestine, and vagina, as well as disease sites such as tumors. Finally, this review also discusses the safety concerns of probiotic delivery systems in the treatment of disease and the challenges and limitations of implementing this method in clinical studies. It is necessary to conduct more clinical studies to evaluate the effectiveness of different probiotic delivery systems in the treatment of diseases.