Gut microbiota changes and its potential relations with thyroid carcinoma

Effects of forages on the microbiota of crossed sheep on cold Plateau

Diet is an important component to influence microbiota, there are less data available about the microbiome of Suffolk cross with Tibetan (SCT) animals with different fodders. The current study was conducted for comparing the fungi microbiota in SCT sheep fed with different forages. Sequencing of ileum samples from sheep groups of AH (alfalfa and oat grass), BH (mixture of grass and concentrated feeds), CH (concentrated feed I), DH (concentrated feed II) and EH (concentrated feed III) achieved 3,171,271 raw and 2,719,649 filtered sequences. Concentrated feeds changed fungi microbiota in SCT sheep with three phyla and 47 genera significantly different among the groups. Genera include positive genus of Scytalidium and negative fungi of Sarocladium, Kazachstania, Gibberella, Scytalidium, Candida, Wickerhamomyces. The findings of our study will contribute to efficient feeding of SCT sheep at cold plateau areas.

Unveiling the Role of Gut Microbiota and Metabolites in Autoimmune Thyroid Diseases: Emerging Perspectives

Autoimmune thyroid diseases (AITDs) are among the most prevalent organ-specific autoimmune disorders, with thyroid hormones playing a pivotal role in the gastrointestinal system's structure and function. Emerging evidence suggests a link between AITDs and the gut microbiome, which is a diverse community of organisms that are essential for digestion, absorption, intestinal homeostasis, and immune defense. Recent studies using 16S rRNA and metagenomic sequencing of fecal samples from AITD patients have revealed a significant correlation between a gut microbiota imbalance and the severity of AITDs. Progress in animal models of autoimmune diseases has shown that intervention in the gut microbiota can significantly alter the disease severity. The gut microbiota influences T cell subgroup differentiation and modulates the pathological immune response to AITDs through mechanisms involving short-chain fatty acids (SCFAs), lipopolysaccharides (LPSs), and mucosal immunity. Conversely, thyroid hormones also influence gut function and microbiota composition. Thus, there is a bidirectional relationship between the thyroid and the gut ecosystem. This review explores the pathogenic mechanisms of the gut microbiota and its metabolites in AITDs, characterizes the gut microbiota in Graves' disease (GD) and Hashimoto's thyroiditis (HT), and examines the interactions between the gut microbiota, thyroid hormones, T cell differentiation, and trace elements. The review aims to enhance understanding of the gut microbiota-thyroid axis and proposes novel approaches to mitigate AITD severity through gut microbiota modulation.

Chinese expert consensus on standard technical specifications for a gut microecomics laboratory (Review)

The intestinal microbiota is a complex ecosystem that not only affects various physiological functions, such as metabolism, inflammation and the immune response, but also has an important effect on the development of tumors and response to treatment. The detection of intestinal flora enables the timely identification of disease-related flora abnormalities, which has significant implications for both disease prevention and treatment. In the field of basic and clinical research targeting gut microbiome, there is a need to recognize and understand the laboratory assays for gut microbiomics. Currently, there is no unified standard for the experimental procedure, quality management and report interpretation of intestinal microbiome assay technology. In order to clarify the process, the Tumor and Microecology Committee of China Anti-Cancer Association and the Tumor and Microecology Committee of Hubei Provincial Immunology Society organized relevant experts to discuss and put forward the standard technical specifications for gut microecomics laboratories, which provides a basis for further in-depth research in the field of intestinal microecomics.

Prenatal Gut Microbiota Predicts Temperament in Offspring at 1-2 Years

The purpose of this study was to explore whether prenatal gut microbiota (GM) and its functions predict the development of offspring temperament. A total of 53 mothers with a 1-year-old child and 41 mothers with a 2-year-old child were included in this study using a mother-infant cohort from central China. Maternal fecal samples collected during the third trimester were analyzed using 16S rRNA V3-V4 gene sequences. Temperament of the child was measured by self-reported data according to the primary caregiver. The effects of GM in mothers on offspring's temperament were evaluated using multiple linear regression models. The results demonstrated that the alpha diversity index Simpson of prenatal GM was positively associated with the activity level of offspring at 1 year (adj. P = .036). Bifidobacterium was positively associated with high-intensity pleasure characteristics of offspring at 1 year (adj. P = .031). Comparatively, the presence of Bifidobacterium found in the prenatal microbiome was associated with low-intensity pleasure characteristics in offspring at 2 years (adj. P = .031). There were many significant associations noted among the functional pathways of prenatal GM and temperament of offspring at 2 years. Our findings support the maternal-fetal GM axis in the setting of fetal-placental development with subsequent postnatal neurocognitive developmental outcomes, and suggest that early childhood temperament is in part associated with specific GM in the prenatal setting.

Uncovering a Causal Connection between Gut Microbiota and Six Thyroid Diseases: A Two-Sample Mendelian Randomization Study

BACKGROUND

Recent studies have established associations between the gut microbiota (GM) and thyroid diseases (TDs). However, their causal relationships remain elusive.

METHODS

To investigate this causality, we conducted a two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data from MiBioGen and FinnGen, with GM as the exposure and six TDs as outcomes.

RESULTS

We identified 32 microbial taxa linked to the risk of six TDs. The Clostridium innocuum group, Ruminiclostridium5, and Lachnoclostridium exhibited protective effects against nontoxic diffuse goiter (NDG). Conversely, an increased risk of NDG was associated with Ruminococcaceae UCG002, Alistipes, Methanobrevibacter, Marvinbryantia, and Ruminococcaceae UCG014. Bifidobacterium and Sutterella were protective against nontoxic multinodular goiter (NMG), while the Ruminococcus gauvreauii group and Rikenellaceae RC9 gut group heightened NMG risk. Protective effects against nontoxic single thyroid nodule (NSTN) were observed with Defluviitaleaceae UCG011, Ruminococcus1, and Ruminococcaceae UCG010, whereas increased risk was linked to Alistipes, the Ruminococcus gauvreauii group, and Lachnospiraceae UCG010. Ruminiclostridium9, Victivallis, and Butyricimonas offered protection against thyrotoxicosis with Graves' Disease (GD), while the Eubacterium rectale group, Desulfovibrio, Bifidobacterium, Collinsella, Oscillospira, and Catenibacterium were risk factors. For thyrotoxicosis with Plummer Disease (PD), protective taxa included Butyricimonas and Lachnospira, whereas Dorea, Eggerthella, Odoribacter, Lactobacillus, Intestinimonas, and Phascolarctobacterium increased risk. Lastly, Parasutterella was protective against thyrotoxicosis with toxic single thyroid nodule (TSTN), while increased risk was associated with Sutterella, Oscillibacter, and Clostridium sensu stricto1.

CONCLUSIONS

Our findings support a causal relationship between specific GM and TDs at the genetic level, laying the foundation for future research into potential mechanisms and the identification of novel therapeutic targets.

GNA15 facilitates the malignant development of thyroid carcinoma cells via the BTK-mediated MAPK signaling pathway

G protein subunit alpha 15 (GNA15) is recognized as an oncogene for some cancers, however, its role in thyroid carcinoma (TC) is elusive and is investigated in this study. Concretely, bioinformatics was employed to analyze the GNA15 expression profile in TC. The effect of GNA15 on TC cell functions was examined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), colony formation, and Transwell assays. Expressions of extracellular regulated protein kinase (ERK), c-Jun N-terminal kinase (JNK), and p38 were determined using Western blot. The involvement of Bruton tyrosine kinase (BTK) in the mechanism of GNA15 was investigated by BTK knockdown and rescue assay. GNA15 presented an overexpression pattern in TC samples, which facilitated the viability, proliferation, migration, and invasion of TC cells; GNA15 silencing led to converse results. Ratios of p-ERK/ERK, p-JNK/JNK, and p-p38/p38 were upregulated by GNA15 overexpression. The BTK deficiency weakened the aforementioned behaviors of TC cells and blocked the MAPK signaling pathway, however, these effects were counteracted by GNA15 overexpression. Collectively, GNA15 contributes to the malignant development of TC cells by binding to BTK and thus activating the MAPK signaling pathway.

Metabolomics combined with intestinal microbiota reveals the mechanism of compound Qilian tablets against diabetic retinopathy

Background

Diabetic retinopathy (DR) is one of the common chronic complications of diabetes mellitus, which has developed into the leading cause of irreversible visual impairment in adults worldwide. Compound Qilian tablets (CQLT) is a traditional Chinese medicine (TCM) developed for treating DR, but its mechanism is still unclear. This study explored the mechanism of action of CQLT in treating DR through metabolomics and intestinal microbiota.

Methods

Histopathologic examination of the pancreas and retina of Zucker diabetic fatty (ZDF) rats and immunohistochemistry were used to determine the expression levels of retinal nerve damage indicators ionized calcium binding adaptor molecule-1 (Iba-1) and glial fibrillary acidic protein (GFAP). Rat fecal samples were tested by LC-MS metabolomics to search for potential biomarkers and metabolic pathways for CQLT treatment of DR. Characteristic nucleic acid sequences of rat intestinal microbiota from each group were revealed using 16S rDNA technology to explore key microbes and related pathways for CQLT treatment of DR. At the same time, we investigated the effect of CQLT on the gluconeogenic pathway.

Results

After CQLT intervention, islet cell status was improved, Iba-1 and GFAP expression were significantly decreased, and abnormal retinal microvascular proliferation and exudation were ameliorated. Metabolomics results showed that CQLT reversed 20 differential metabolites that were abnormally altered in DR rats. Intestinal microbiota analysis showed that treatment with CQLT improved the abundance and diversity of intestinal flora. Functional annotation of metabolites and intestinal flora revealed that glycolysis/gluconeogenesis, alanine, aspartate and glutamate metabolism, starch and sucrose metabolism were the main pathways for CQLT in treating DR. According to the results of correlation analysis, there were significant correlations between Iba-1, GFAP, and intestinal microbiota and metabolites affected by CQLT. In addition, we found that CQLT effectively inhibited the gluconeogenesis process in diabetic mice.

Conclusion

In conclusion, CQLT could potentially reshape intestinal microbiota composition and regulate metabolite profiles to protect retinal morphology and function, thereby ameliorating the progression of DR.

Causal relationship between gut microbiota and thyroid nodules: a bidirectional two-sample Mendelian randomization study

Objective

Emerging evidence suggests alterations in gut microbiota (GM) composition following thyroid nodules (TNs) development, yet the causal relationship remains unclear. Utilizing Mendelian Randomization (MR), this study aims to elucidate the causal dynamics between GM and TNs.

Methods

Employing summary statistics from the MiBioGen consortium (n=18,340) and FinnGen consortium (1,634 TNs cases, 263,704 controls), we conducted univariable and multivariable MR analyses to explore the GM-TNs association. Techniques including inverse variance weighted, MR-Egger regression, weighted median, and MR-PRESSO were utilized for causal inference. Instrumental variable heterogeneity was assessed through Cochran's Q statistic and leave-one-out analysis. Reverse MR was applied for taxa showing significant forward MR associations, with multivariate adjustments for confounders.

Results

Our findings suggest that certain microbiota, identified as Ruminococcaceae_NK4A214_group (OR, 1.89; 95%CI, 0.47-7.64; p = 0.040), Senegalimassilia (OR, 1.72; 95%CI, 1.03-2.87; p =0.037), Lachnospiraceae (OR,0.64; 95%CI,0.41-0.99; p =0.045), exhibit a protective influence against TNs' development, indicated by negative causal associations. In contrast, microbiota categorized as Desulfovibrionales (OR, 0.63; 95%CI, 0.41-0.95; p =0.028), Prevotella_7 (OR, 0.79; 95%CI, 0.63-1.00; p =0.049), Faecalibacterium (OR, 0.66; 95%CI, 0.44-1.00; p =0.050), Desulfovibrionaceae (OR, 0.55; 95%CI, 0.35-0.86; p =0.008), Deltaproteobacteria (OR, 0.65; 95%CI, 0.43-0.97; p =0.036) are have a positive correlation with with TNs, suggesting they may serve as risk factors. Reverse MR analyses did not establish significant causal links. After comprehensive adjustment for confounders, taxa Desulfovibrionales (Order), Desulfovibrionaceae (Family), Deltaproteobacteria (Class) remain implicated as potential contributors to TNs' risk.

Discussion

This study substantiates a significant causal link between GM composition and TNs development, underscoring the thyroid-gut axis's relevance. The findings advocate for the integration of GM profiles in TNs' prevention and management, offering a foundation for future research in this domain.

Early and long-term responses of intestinal microbiota and metabolites to 131I treatment in differentiated thyroid cancer patients

BACKGROUND

Multiple high doses of 131I therapy in patients with differentiated thyroid cancer (DTC) might disrupt the balance of gut microbiota and metabolites. This study aimed to investigate the alterations of intestinal bacteria and metabolism over two courses of 131I therapy, explore the interactions, and construct diagnostic models reflecting enteric microecology based on 131I therapy.

METHODS

A total of 81 patients were recruited for the first 131I therapy (131I-1st), among whom 16 received a second course (131I-2nd) after half a year. Fecal samples were collected 1 day before (Pre-131I-1st/2nd) and 3 days after (Post-131I-1st/2nd) 131I therapy for microbiome (16S rRNA gene sequencing) and metabolomic (LC-MS/MS) analyses.

RESULTS

A total of six microbial genera and 11 fecal metabolites enriched in three pathways were identified to show significant differences between Pre-131I-1st and other groups throughout the two courses of 131I treatment. In the Post-131I-1st group, the beneficial bacteria Bifidobacterium, Lachnoclostridium, uncultured_bacterium_f_Lachnospiraceae, and Lachnospiraceae_UCG004 were abundant and the radiation-sensitive pathways of linoleic acid (LA), arachidonic acid, and tryptophan metabolism were inhibited compared with the Pre-131I-1st group. Compared with the Pre-131I-1st group, the Pre-131I-2nd group exhibited a reduced diversity of flora and differentially expressed metabolites, with a low abundance of beneficial bacteria and dysregulated radiation-sensitive pathways. However, less significant differences in microbiota and metabolites were found between the Pre/Post-131I-2nd groups compared with those between the Pre/Post-131I-1st groups. A complex co-occurrence was observed between 6 genera and 11 metabolites, with Lachnoclostridium, Lachnospiraceae_UCG004, Escherichia-Shigella, and LA-related metabolites contributing the most. Furthermore, combined diagnostic models of charactered bacteria and metabolites answered well in the early, long-term, and dose-dependent responses for 131I therapy.

CONCLUSIONS

Different stages of 131I therapy exert various effects on gut microecology, which play an essential role in regulating radiotoxicity and predicting the therapeutic response.

The relationship between the gut microbiota and thyroid disorders

Disorders of the thyroid gland are common, more prevalent in women than in men, and range from inflammatory to neoplastic lesions. Autoimmune thyroid diseases (AITD) affect 2-5% of the population, while thyroid cancer is the most frequent endocrine malignancy. Treatment for AITD is still restricted to management rather than prevention or cure. Progress has been made in identifying genetic variants that predispose to AITD and thyroid cancer, but the increasing prevalence of all thyroid disorders indicates that factors other than genes are involved. The gut microbiota, which begins to develop before birth, is highly sensitive to diet and the environment, providing a potential mechanism for non-communicable diseases to become communicable. Its functions extend beyond maintenance of gut integrity: the gut microbiota regulates the immune system, contributes to thyroid hormone metabolism and can generate or catabolize carcinogens, all of which are relevant to AITD and thyroid cancer. Observational and interventional studies in animal models support a role for the gut microbiota in AITD, which has been confirmed in some reports from human cohorts, although considerable geographic variation is apparent. Reports of a role for the microbiota in thyroid cancer are more limited, but evidence supports a relationship between gut dysbiosis and thyroid cancer.

Causal relationship between gut microbiota and differentiated thyroid cancer: a two-sample Mendelian randomization study

Background

The gut microbiota has been significantly associated with differentiated thyroid cancer (DTC). However, the causal relationship between the gut microbiota and DTC remains unexplored.

Methods

Genome-wide association study (GWAS) summary databases were utilized to select exposures and outcomes. The Mendelian randomization (MR) method was employed to investigate the causal relationship between the gut microbiota and DTC. A sensitivity analysis was performed to assess the reliability of the findings.

Results

Four bacterial traits were associated with the risk of DTC: Class Mollicutes [odds ratio (OR) = 10.953, 95% confidence interval (95% CI): 2.333-51.428, p = 0.002], Phylum Tenericutes (OR = 10.953, 95% CI: 2.333-51.428, p = 0.002), Genus Eggerthella (OR = 3.219, 95% CI: 1.033-10.024, p = 0.044), and Order Rhodospirillales (OR = 2.829, 95% CI: 1.096-7.299, p = 0.032). The large 95% CI range for the Class Mollicutes and the Phylum Tenericutes may be attributed to the small sample size. Additionally, four other bacterial traits were negatively associated with DTC: Genus Eubacterium fissicatena group (OR = 0.381, 95% CI: 0.148-0.979, p = 0.045), Genus Lachnospiraceae UCG008 (OR = 0.317, 95% CI: 0.125-0.801, p = 0.015), Genus Christensenellaceae R-7 group (OR = 0.134, 95% CI: 0.020-0.886, p = 0.037), and Genus Escherichia Shigella (OR = 0.170, 95% CI: 0.037-0.769, p = 0.021).

Conclusion

These findings contribute to our understanding of the pathological mechanisms underlying DTC and provide novel insights for the clinical treatment of DTC.

Causal relationship of genetically predicted gut microbiota with thyroid cancer: a bidirectional two-sample mendelian randomization study

Background

Previous investigations have demonstrated a correlation between the composition of gut microbiota and the development of thyroid cancer (TC). Nonetheless, there was no consensus on the causal effect of gut microbiota composition on TC risk. Therefore, the present study aimed to perform a bidirectional two-sample Mendelian randomization (MR) analysis to explore potential causal associations between gut microbiota and TC risk.

Methods

Utilizing data from the MiBioGen consortium's genome-wide association studies (GWAS) meta-analysis involving a sample size of 18,340, we identified instrumental variables for 211 gut microbiota taxa. The summary statistics for TC was from relevant large-scale GWAS conducted by the FinnGen consortium. In the first stage, the Inverse-variance weighted (IVW) method was used as the primary estimate method, and the stability of estimations was tested by a battery of sensitivity analyses. In the second stage, a reverse MR analysis was applied to determine whether reverse causality existed.

Results

According to the IVW method, we identified 9 genetically predicted gut microbiota that were causally correlated with TC risk. Among them, we observed a positive causal effect of Family Christensenellaceae (OR = 1.664, 95% CI: 1.103-2.511, P = 0.015), Family Victivallaceae (OR = 1.268, 95% CI: 1.009-1.594, P = 0.042), Genus Methanobrevibacter (OR = 1.505, 95% CI: 1.049-2.159, P = 0.027), Genus Ruminococcus2 (OR = 1.846, 95% CI: 1.261-2.704, P = 0.002), Genus Subdoligranulum (OR = 1.907, 95% CI: 1.165-3.121, P = 0.010), Phylum Verrucomicrobia (OR = 1.309, 95% CI: 1.027-1.668, P = 0.029) on TC risk, while Class Betaproteobacteria (OR = 0.522, 95% CI: 0.310-0.879, P = 0.015), Family Family XI (OR = 0.753, 95% CI: 0.577-0.983, P = 0.037), Genus Sutterella (OR = 0.596, 95% CI: 0.381-0.933, P = 0.024) might be correlated with a decreased risk of TC. Subsequently, various sensitivity analyses indicated no heterogeneity, directional pleiotropy or outliers. In addition, reverse analysis demonstrated a negative causal effect of TC risk on the abundance of the gut microbiota (Genus Ruminococcus2, OR = 0.947, 95% CI: 0.907-0.989, P = 0.014).

Conclusion

Genetic evidence suggested that bidirectional causal associations of specific bacteria taxa and the risk of TC, highlighting the association of the "gut-thyroid" axis. Further exploration of the potential microbiota-related mechanisms might have profound implications for public health in terms of the early prevention and treatment of TC.

Gluten-Free Diet Alters the Gut Microbiome in Women with Autoimmune Thyroiditis

The gut microbiome may contribute to the development of autoimmune diseases, such as autoimmune thyroiditis (AIT). Diet has a critical impact on the gut microbiome, and it has been shown that a gluten-free diet can negatively affect its composition. A gluten-free diet is popular among patients, and therefore the aim of this study was to check whether it affects thyroid function and gut microbiome composition in AIT. Thirty-one women with AIT complied with a gluten-free diet for 8 weeks. After the first 4 weeks, participants were divided into two groups: the first group received gluten in capsules and the other one-rice starch (placebo). Blood and stool samples were examined before diet (T0), after 4 weeks (T1) and after 8 weeks of diet (T2). The only significant difference in blood parameters was observed between T1 and T2 in the placebo group for the thyroid peroxidase antibody level. After the first 4 weeks, a significant increase in Desulfobacterota, Proteobacteria, Prevotella and Parasutterella and a significant decrease in Actinobacteriota, Coriobacteriaceae and Bifidobacterium were observed. The detected microbiome alterations may indicate increasing inflammation; however, further research is required, and for now, a gluten-free diet should be used cautiously in AIT.

Gut microbiota-derived short-chain fatty acids and depression: deep insight into biological mechanisms and potential applications

The gut microbiota is a complex and dynamic ecosystem known as the 'second brain'. Composing the microbiota-gut-brain axis, the gut microbiota and its metabolites regulate the central nervous system through neural, endocrine and immune pathways to ensure the normal functioning of the organism, tuning individuals' health and disease status. Short-chain fatty acids (SCFAs), the main bioactive metabolites of the gut microbiota, are involved in several neuropsychiatric disorders, including depression. SCFAs have essential effects on each component of the microbiota-gut-brain axis in depression. In the present review, the roles of major SCFAs (acetate, propionate and butyrate) in the pathophysiology of depression are summarised with respect to chronic cerebral hypoperfusion, neuroinflammation, host epigenome and neuroendocrine alterations. Concluding remarks on the biological mechanisms related to gut microbiota will hopefully address the clinical value of microbiota-related treatments for depression.

Exploring reciprocal causation: bidirectional mendelian randomization study of gut microbiota composition and thyroid cancer

BACKGROUND

While an association between gut microbiota composition and thyroid cancer (TC) has been observed, the directionality and causality of this relationship remain unclear.

METHODS

We conducted a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal effect between gut microbiota composition and TC. Gut microbiota data were derived from a diverse population encompassing various ethnicities (n = 18,340 samples), while TC data were sourced from an European population (n = 218,792 samples). Instrumental variables, represented by single nucleotide polymorphisms (SNPs), were employed to assess the causal relationship using multiple MR methods, including inverse-variance weighting (IVW), weighted median, weighted mode, MR-Egger, and simple mode. F-statistics and sensitivity analyses were performed to evaluate the robustness of the findings.

RESULTS

Our investigation identified a comprehensive set of 2934 instrumental variables significantly linked to gut microbiota composition (p < 1 × 10-5). The analysis illuminated notable candidates within the phylum Euryarchaeota, including families Christensenellaceae and Victivallaceae, and genera Methanobrevibacter, Ruminococcus2, and Subdoligranulum, which emerged as potential risk factors for TC. On the other hand, a protective influence against TC was attributed to class Betaproteobacteria, family FamilyXI, and genera Anaerofilum, Odoribacter, and Sutterella, alongside order Burkholderiales. Further enhancing our insights, the integration of 7 instrumental variables from TC data (p < 1 × 10-5) disclosed the regulatory potential of one family and five genera. Notably, the genus Coprobacter innocuum group (p = 0.012, OR = 0.944) exhibited the highest probability of regulation. Our meticulous analyses remained free from significant bias, heterogeneity, or horizontal pleiotropy concerns.

CONCLUSION

Through a bidirectional two-sample Mendelian randomization approach, we elucidated a potential bidirectional causal relationship between gut microbiota composition and TC. Specific microbial taxa were associated with an increased risk or conferred protection against TC. These findings advance our understanding of the complex interplay between the gut microbiota and TC pathogenesis, offering new insights into the therapeutic potential of modulating the gut microbiota for managing TC.

Clinical potential of microbiota in thyroid cancer therapy

Thyroid cancer is one of the most common tumors of the endocrine system because of its rapid and steady increase in incidence and prevalence. In recent years, a growing number of studies have identified a key role for the gut, thyroid tissue and oral microbiota in the regulation of metabolism and the immune system. A growing body of evidence has conclusively demonstrated that the microbiota influences tumor formation, prevention, diagnosis, and treatment. We provide extensive information in which oral, gut, and thyroid microbiota have an effect on thyroid cancer development in this review. In addition, we thoroughly discuss the various microbiota species, their potential functions, and the underlying mechanisms for thyroid cancer. The microbiome offers a unique opportunity to improve the effectiveness of immunotherapy and radioiodine therapy thyroid cancer by maintaining the right type of microbiota, and holds great promise for improving clinical outcomes and quality of life for thyroid cancer patients.

The relationship between thyroid and human-associated microbiota: A systematic review of reviews

In recent years, a growing number of studies have examined the relationship between thyroid pathophysiology and intestinal microbiota composition. The reciprocal influence between these two entities has been proven so extensive that some authors coined the term "gut-thyroid axis". However, since some papers reported conflicting results, several aspects of this correlation need to be clarified. This systematic review was conceived to achieve more robust information about: 1)the characteristics of gut microbiota composition in patients with the more common morphological, functional and autoimmune disorders of the thyroid; 2)the influence of gut microbial composition on micronutrients that are essential for the maintenance of thyroid homeostasis; 3)the effect of probiotics, prebiotics and synbiotics, some of the most popular over-the-counter products, on thyroid balance; 4)the opportunity to use specific dietary advice. The literature evaluation was made by three authors independently. A five steps strategy was a priori adopted. After duplicates removal, 1106 records were initially found and 38 reviews were finally included in the analysis. The systematic reviews of reviews found that: 1) some significant variations characterize the gut microbiota composition in patients with thyroid disorders. However, geographical clustering of most of the studies prevents drawing definitive conclusions on this topic; 2) the available knowledge about the effect of probiotics and synbiotics are not strong enough to suggest the routine use of these compounds in patients with thyroid disorders; 3) specific elimination nutrition should not be routine suggested to patients, which, instead have to be checked for possible micronutrients and vitamins deficiency, often owed to gastrointestinal autoimmune comorbidities.

Gut microbiota and its metabolites in non-small cell lung cancer and brain metastasis: from alteration to potential microbial markers and drug targets

Background

The elevated mortality rate associated with non-small-cell lung cancer (NSCLC) is a well-established global concern. Considerable attention has been directed toward exploring the association between gut microbiota and various malignant tumors. We herein investigated the associations between the intestinal microbiome and its metabolites, particularly short-chain fatty acids (SCFAs), in patients with NSCLC at different stages, including early and brain metastasis (BM) stages. The findings aim to offer a fresh perspective on the diagnosis and management of NSCLC.

Methods

Fecal samples were collected from 115 participants, comprising healthy controls (n = 35) and patients with treatment-naive NSCLC at the early stage (ELC, n = 40) and the BM stage (n = 40). Characterization of the intestinal microbiome and fecal SCFA levels was performed using 16S rRNA gene sequencing and gas chromatography.

Results

The microbial diversity in patients with NSCLC was found to be less abundant and uniform, particularly in the BM stage. Significant alterations in the community structure of the gut microbiota were observed in patients with NSCLC, with an increase in pathogens in Fusobacteria and Proteobacteria and a decrease in SCFA-producing bacteria in Firmicutes and Actinobacteria, particularly in the BM stage. Meanwhile, microbial communities displayed intricate associations in patients with NSCLC. A biomarker panel (Faecalibacterium, Bifidobacterium, Butyricicoccus, Klebsiella, Streptococcus, and Blautia) successfully distinguished patients in the ELC and BM stages from healthy controls (area under the curve: 0.884). The overall concentration of fecal SCFAs was significantly lower in patients with BM compared to patients with ELC and healthy controls. Subgroup analysis of acetate and butyrate yielded similar results. Moreover, multiple disrupted pathways in the NSCLC group were identified using the Kyoto Encyclopedia of Genes and Genomes annotation, including lipid metabolism and genetic information processing, specifically in the BM stage.

Conclusion

Compared with healthy controls, distinct host-microbe interactions were evident in different phases of patients with NSCLC. Furthermore, specific forms of the gut microbiome and SCFAs may serve as valuable biomarkers and therapeutic targets in the diagnosis and treatment of NSCLC.

Microbiota Implications in Endocrine-Related Diseases: From Development to Novel Therapeutic Approaches

This comprehensive review article delves into the critical role of the human microbiota in the development and management of endocrine-related diseases. We explore the complex interactions between the microbiota and the endocrine system, emphasizing the implications of microbiota dysbiosis for the onset and progression of various endocrine disorders. The review aims to synthesize current knowledge, highlighting recent advancements and the potential of novel therapeutic approaches targeting microbiota-endocrine interactions. Key topics include the impact of microbiota on hormone regulation, its role in endocrine pathologies, and the promising avenues of microbiota modulation through diet, probiotics, prebiotics, and fecal microbiota transplantation. We underscore the importance of this research in advancing personalized medicine, offering insights for more tailored and effective treatments for endocrine-related diseases.

Association Between Antibiotic Exposure and Thyroid Cancer: A Nationwide Cohort Study in South Korea

Background: Although recent studies have introduced antibiotics as a potential risk factor for thyroid cancer, further studies are necessary. We examined the association between long-term antibiotic usage and thyroid cancer risk. Methods: This nationwide cohort study investigated 9,804,481 individuals aged 20 years or older who participated in health screening (2005-2006) with follow-up ending on December 31, 2019, using the Korean National Health Insurance Service database. Multivariable Cox proportional hazards regression was used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for thyroid cancer risk according to the cumulative days of antibiotic prescription and the number of antibiotic classes, respectively. A 1:1 propensity score (PS) matching was also performed for analysis. Results: Compared with nonusers of antibiotics, participants prescribed ≥365 days of antibiotics showed an increased risk of thyroid cancer (aHR, 1.71; CI, 1.66-1.78) after adjusting for covariates including age, smoking status, comorbidities including thyroid-related diseases, and the number of head and neck computed tomography scans. Participants prescribed ≥365 days of antibiotics also had a significantly increased risk of thyroid cancer (aHR, 1.37; CI, 1.34-1.40) compared with participants prescribed 1-14 days of antibiotics. Association remained significant in the 1:1 PS-matched cohort. Moreover, compared with nonusers of antibiotics, the 5 or more antibiotic class user group had a higher thyroid cancer risk (aHR, 1.71; CI, 1.65-1.78). Conclusions: Long-term antibiotic prescriptions and an increasing number of antibiotic classes may be associated with a higher risk of thyroid cancer in a duration-dependent manner. The effects of long-term antibiotic exposure on thyroid cancer should be further investigated.

Microbiota in cancer: molecular mechanisms and therapeutic interventions

The diverse bacterial populations within the symbiotic microbiota play a pivotal role in both health and disease. Microbiota modulates critical aspects of tumor biology including cell proliferation, invasion, and metastasis. This regulation occurs through mechanisms like enhancing genomic damage, hindering gene repair, activating aberrant cell signaling pathways, influencing tumor cell metabolism, promoting revascularization, and remodeling the tumor immune microenvironment. These microbiota-mediated effects significantly impact overall survival and the recurrence of tumors after surgery by affecting the efficacy of chemoradiotherapy. Moreover, leveraging the microbiota for the development of biovectors, probiotics, prebiotics, and synbiotics, in addition to utilizing antibiotics, dietary adjustments, defensins, oncolytic virotherapy, and fecal microbiota transplantation, offers promising alternatives for cancer treatment. Nonetheless, due to the extensive and diverse nature of the microbiota, along with tumor heterogeneity, the molecular mechanisms underlying the role of microbiota in cancer remain a subject of intense debate. In this context, we refocus on various cancers, delving into the molecular signaling pathways associated with the microbiota and its derivatives, the reshaping of the tumor microenvironmental matrix, and the impact on tolerance to tumor treatments such as chemotherapy and radiotherapy. This exploration aims to shed light on novel perspectives and potential applications in the field.

Mendelian randomization suggests a causal relationship between gut dysbiosis and thyroid cancer

Background

Alterations in gut microbiota composition and function have been linked to the development and progression of thyroid cancer (TC). However, the exact nature of the causal relationship between them remains uncertain.

Methods

A bidirectional two-sample Mendelian randomization (TSMR) analysis was conducted to assess the causal connection between gut microbiota (18,340 individuals) and TC (6,699 cases combined with 1,613,655 controls) using data from a genome-wide association study (GWAS). The primary analysis used the inverse-variance weighted (IVW) method to estimate the causal effect, with supplementary approaches including the weighted median, weighted mode, simple mode, and MR-Egger. Heterogeneity and pleiotropy were assessed using the Cochrane Q test, MR-Egger intercept test, and MR-PRESSO global test. A reverse TSMR analysis was performed to explore reverse causality.

Results

This study identified seven microbial taxa with significant associations with TC. Specifically, the genus Butyrivibrio (OR: 1.127, 95% CI: 1.008-1.260, p = 0.036), Fusicatenibacter (OR: 1.313, 95% CI: 1.066-1.618, p = 0.011), Oscillospira (OR: 1.240, 95% CI: 1.001-1.536, p = 0.049), Ruminococcus2 (OR: 1.408, 95% CI: 1.158-1.711, p < 0.001), Terrisporobacter (OR: 1.241, 95% CI: 1.018-1.513, p = 0.032) were identified as risk factors for TC, while The genus Olsenella (OR: 0.882, 95% CI: 0.787-0.989, p = 0.031) and Ruminococcaceae UCG004 (OR: 0.719, 95% CI: 0.566-0.914, p = 0.007) were associated with reduced TC risk. The reverse MR analysis found no evidence of reverse causality and suggested that TC may lead to increased levels of the genus Holdemanella (β: 0.053, 95% CI: 0.012~0.094, p = 0.011) and decreased levels of the order Bacillales (β: -0.075, 95% CI: -0.143~-0.006, p = 0.033). No significant bias, heterogeneity, or pleiotropy was detected in this study.

Conclusion

This study suggests a potential causal relationship between gut microbiota and TC, providing new insights into the role of gut microbiota in TC. Further research is needed to explore the underlying biological mechanisms.

Interactive Association Between Gut Microbiota and Thyroid Cancer

CONTEXT

The association between the gut microbiota and thyroid cancer remains controversial.

OBJECTIVE

We aimed to systematically investigate the interactive causal relationships between the abundance and metabolism pathways of gut microbiota and thyroid cancer.

METHODS

We leveraged genome-wide association studies for the abundance of 211 microbiota taxa from the MiBioGen study (N = 18 340), 205 microbiota metabolism pathways from the Dutch Microbiome Project (N = 7738), and thyroid cancer from the Global Biobank Meta-analysis Initiative (N cases = 6699 and N participants = 1 620 354). We performed a bidirectional Mendelian randomization (MR) to investigate the causality from microbiota taxa and metabolism pathways to thyroid cancer and vice versa. We performed a systematic review of previous observational studies and compared MR results with observational findings.

RESULTS

Eight taxa and 12 metabolism pathways had causal effects on thyroid cancer, where RuminococcaceaeUCG004 genus (P = .001), Streptococcaceae family (P = .016), Olsenella genus (P = .029), ketogluconate metabolism pathway (P = .003), pentose phosphate pathway (P = .016), and L-arginine degradation II in the AST pathway (P = .0007) were supported by sensitivity analyses. Conversely, thyroid cancer had causal effects on 3 taxa and 2 metabolism pathways, where the Holdemanella genus (P = .015) was supported by sensitivity analyses. The Proteobacteria phylum, Streptococcaceae family, Ruminococcus2 genus, and Holdemanella genus were significantly associated with thyroid cancer in both the systematic review and MR, whereas the other 121 significant taxa in observational results were not supported by MR.

DISCUSSIONS

These findings implicated the potential role of host-microbiota crosstalk in thyroid cancer, while the discrepancy among observational studies calls for further investigations.

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.

Insight into the mechanism of Xiao-Chai-Hu-Tang alleviates irinotecan-induced diarrhea based on regulating the gut microbiota and inhibiting Gut β-GUS

BACKGROUND

Irinotecan (CPT-11, Camptosar@) is a first-line drug for metastatic colorectal cancer. CPT-11-induced diarrhea, which is closely related to the concentrations of β-glucuronidase (β-GUS) and SN-38 in the gut, largely limits its clinical application.

PURPOSE

Herein, Xiao-Chai-Hu-Tang (XCHT), a traditional Chinese formula, was applied to mitigate CPT-11-induced toxicity. This study initially explored the mechanism by which XCHT alleviated diarrhea, especially for β-GUS from the gut microbiota.

METHODS

First, we examined the levels of the proinflammatory cytokines and the anti-inflammatory cytokines in the intestine. Furthermore, we researched the community abundances of the gut microbiota in the CPT-11 and XCHT-treated mice based on 16S rRNA high-throughput sequencing technology. Meanwhile, the level of SN-38 and the concentrations of β-GUS in intestine were examined. We also resolved the 3D structure of β-GUS from gut microbiota by X-ray crystallography technology. Moreover, we used virtual screening, SPR analysis, and enzyme activity assays to confirm whether the main active ingredients from XCHT could selectively inhibit β-GUS.

RESULTS

In XCHT-treated mice, the levels of the proinflammatory cytokines decreased, the anti-inflammatory cytokines increased, and the community abundances of beneficial Firmicutes and Bacteroidota improved in the gut microbiota. We also found that the concentrations of β-GUS and the level of SN-38, the major ingredient that induces diarrhea in the gut, significantly decreased after coadministration of XCHT with CPT-11 in the intestine. Additionally, we revealed the structural differences of β-GUS from different gut microbiota. Finally, we found that EcGUS had good affinity with baicalein and meanwhile could be selectively inhibited by baicalein from XCHT.

CONCLUSIONS

Overall, XCHT could relieve the delayed diarrhea induced by CPT-11 through improving the abundance of beneficial gut microbiota and reduced inflammation. Furthermore, based on the three-dimensional structure, baicalein, especially, could be used as a candidate EcGUS inhibitor to alleviate CPT-11-induced diarrhea.

The role of intermittent fasting and the ketogenic diet in cancer disease: can they replace the Mediterranean diet?

The prevalence of cancer is rising globally, and it is the second leading cause of death. Nutrition has an important influence on the risk of developing cancer. Moreover, changes in the gut microbiota are connected to the risk of developing cancer and are critical for sustaining immunity. Various studies have shown that intermittent fasting, ketogenic diet, and the Mediterranean diet are effective therapies in changing the intestinal microbiota, the prevention of cancer, and the improvement of tolerance to treatment in cancer patients. Although there is not enough evidence to show that the ketogenic diet is effective in changing the intestinal microbiota in a manner that could prevent cancer, intermittent fasting and the Mediterranean diet could positively affect composition of intestinal microbiota against cancer. In addition, the ketogenic diet, intermittent fasting, and the Mediterranean diet have the potential to stimulate anticarcinogenic pathways, and they might increase cancer patients' quality of life according to scientific evidence. In this review, we represent and argue recent scientific data on relationship between intermittent fasting, the ketogenic diet, and the Mediterranean diet, intestinal microbiota, cancer prevention and cancer treatment.

Tumor Microbial Communities and Thyroid Cancer Development-The Protective Role of Antioxidant Nutrients: Application Strategies and Future Directions

Thyroid cancer (TC), the most frequent malignancy of the endocrine system, has recorded an increasing incidence in the last decades. The etiology of TC remains at least partly unknown and, among modifiable risk factors, the gut microbiota and dietary nutrients (vitamins, essential microelements, polyphenols, probiotics) have been recognized to not only influence thyroid function, but exert critical effects on TC development and progression. Recent discoveries on the existence of tumor microbiota also in the TC microenvironment provide further evidence for the essential role of tumor microorganisms in TC etiology and severity, as well as acting as prognostic markers and as a potential target of adjuvant care in the treatment of TC patients. Therefore, in this review, we summarize current knowledge on the relationship of the tumor microbiome with the clinical tumor characteristics and TC progression, also illustrating the molecular mechanisms underlying this association, and how antioxidant nutrients may be used as a novel strategy to both control gut health and reduce the risk for TC. Furthermore, we discuss how new technologies might be exploited for the development of new foods with high nutritional values, antioxidant capability, and even attractiveness to the individual in terms of sensory and emotional features.

Exploring blood metabolites and thyroid disorders: a bidirectional mendelian randomization study

Background

Human blood metabolites have demonstrated close associations with thyroid disorders in observational studies. However, it's essential to determine whether these correlations imply causation. Mendelian Randomization (MR) offers a promising approach to investigate these patterns.

Aims

The primary aim of our investigation is to establish causality between blood metabolites and three thyroid disorders: TC, GD, and HT.

Methods

We employed a two-sample bidirectional MR analysis approach to assess the relationships between 452 blood metabolites and the three aforementioned thyroid disorders. Causal links were estimated using the IVW method, with sensitivity analyses conducted via MR-Egger, Weighted Median, and MR-PRESSO. We assessed potential heterogeneity and pleiotropy using MR-Egger intercept and Cochran's Q statistic. Additionally, we conducted pathway analysis to identify potential metabolic pathways.

Results

We found 46 metabolites that showed suggestive associations with thyroid disease risk, especially Aspartate (ORIVW=7.41; 95%CI: 1.51-36.27; PIVW=0.013) and C-glycosyltryptophan (ORIVW=0.04; 95%CI: 0.00-0.29; PIVW=0.001) impacted TC, Kynurenine (ORIVW=2.69; 95%CI: 1.08-6.66; PIVW=0.032) and 4-androsten-3beta,17beta-diol disulfate 2 (ORIVW=0.78; 95%CI: 0.48-0.91; PIVW=0.024) significantly impacted GD, and Alpha-ketoglutarate (ORIVW=46.89; 95%CI: 4.65-473.28; PIVW=0.001) and X-14189-leucylalanine (ORIVW=0.31; 95%CI: 0.15-0.64 PIVW=0.001) significantly impacted HT. We also detected 23 metabolites influenced by TC and GD. Multiple metabolic pathways have been found to be involved in thyroid disease.

Conclusion

Our MR findings suggest that the identified metabolites and pathways can serve as biomarkers for clinical thyroid disorder screening and prevention, while also providing new insights for future mechanistic exploration and drug target selection.

Changes in Gut Microbiota and Metabolites in Papillary Thyroid Carcinoma Patients Following Radioactive Iodine Therapy

Purpose

Radioactive iodine therapy is administered through oral route, which is accumulated and absorbed in the intestine. However, its effects on the intestine remain unclear. In this study, we investigated the changes in the gut microbiota and metabolites following radioactive iodine therapy.

Patients and Methods

A total of 76 stool samples from the same 38 patients were collected at the start of radioactive iodine therapy and three days following the therapy. Stool microbiota and metabolites were detected using 16S rRNA gene sequencing and liquid chromatography-mass spectrometry.

Results

Enterobacteriales, Enterobacteriaceae and Escherichia-Shigella were elevated in most patients (27/38) following the therapy. The levels of 2-hydroxyundec-7-enoylcarnitine were significantly lower, whereas those of 5-dehydroavenasterol, butylisopropylamine, and salsoline-1-carboxylate were higher following the therapy. The relative abundance of Escherichia-Shigella was negatively correlated with 2-hydroxyundec-7-enoylcarnitine level (r2 = -0.661, P = 0.009). Functional pathways were predicted to be involved in amino acid and lipid metabolism following the therapy. Particularly, phenylalanine, linoleic acid, sphingolipid, purine, and alpha-linolenic acid metabolism were the main metabolic pathways.

Conclusion

Gut microbiota was disturbed following radioactive iodine therapy, with increased Escherichia-Shigella. Processes associated with energy production seems to be impacted following the therapy, with significantly decreased 2-hydroxyundec-7-enoylcarnitine level. Meanwhile, some metabolites and functional pathways may have a positive effect on intestinal homeostasis, and may be related to the repair and promotion of gut recovery following the therapy. This study provides a basic foundation to explore how radioactive iodine affects gut microbiota and metabolites, and how gut function is regulated in response to radioactive iodine therapy.

Mediterranean diet and olive oil, microbiota, and obesity-related cancers. From mechanisms to prevention

Olive oil (OO) is the main source of added fat in the Mediterranean diet (MD). It is a mix of bioactive compounds, including monounsaturated fatty acids, phytosterols, simple phenols, secoiridoids, flavonoids, and terpenoids. There is a growing body of evidence that MD and OO improve obesity-related factors. In addition, obesity has been associated with an increased risk for several cancers: endometrial, oesophageal adenocarcinoma, renal, pancreatic, hepatocellular, gastric cardia, meningioma, multiple myeloma, colorectal, postmenopausal breast, ovarian, gallbladder, and thyroid cancer. However, the epidemiological evidence linking MD and OO with these obesity-related cancers, and their potential mechanisms of action, especially those involving the gut microbiota, are not clearly described or understood. The goals of this review are 1) to update the current epidemiological knowledge on the associations between MD and OO consumption and obesity-related cancers, 2) to identify the gut microbiota mechanisms involved in obesity-related cancers, and 3) to report the effects of MD and OO on these mechanisms.

Exploring the oral-gut microbiota during thyroid cancer: Factors affecting the thyroid functions and cancer development

Thyroid cancer (TC) is categorized into papillary, follicular, medullary, and anaplastic. The TC is increasing in several countries, including China, the United States, the United Kingdom, Canada, France, Australia, Germany, Japan, Spain, and Italy. Thus, this review comprehensively covers the factors that affect thyroid gland function, TC types, risk factors, and symptoms. Lifestyle factors (such as nutrient consumption and smoking) and pollutants (such as chemicals and heavy metals) increased the thyroid-stimulating hormone (TSH) levels which are directly related to TC prevalence. The conventional and recent TC treatments are also highlighted. The role of the oral and gut microbiota as well as the application of probiotics on TC are also discussed. The variations in the composition of oral and gut microbes influence the thyroid function indirectly through alteration in metabolites (such as short-chain fatty acids) that are eminent for cellular energy metabolism. Maintenance of healthy gut and oral microbiota can help in regulating thyroid function by regulating iodine uptake. Oral or gut microbial dysbiosis can be considered as an early diagnosis factor or TC marker. High TSH during TC can increase the oral microbial diversity while disrupting the high ratio of Firmicutes and Bacteroidetes in the gut. Supplementation of probiotics as an adjuvant in TC treatment is beneficial. However, needs more extensive research to explore the direct effect of probiotics on thyroid function.

Polycystic ovary syndrome and thyroid disorder: a comprehensive narrative review of the literature

Background

Published data on the relationship between polycystic ovary syndrome (PCOS) and thyroid dysfunction are sparse and confusing.

Objective

To comprehensively review data available in the literature regarding the relationship between PCOS and the thyroid function, and its abnormalities.

Methods

Nine main areas of interest were identified and analyzed according to the available evidence: 1) Evaluation of thyroid function for PCOS diagnosis; 2) Epidemiology data on thyroid function/disorders in patients with PCOS, and vice versa; 3) Experimental data supporting the relationship between thyroid function/disorders and PCOS; 4) Effects of thyroid function/disorders on PCOS features, and vice versa; 5) Effect of thyroid alterations on the cardiometabolic risk in women with PCOS; 6) Effect of thyroid abnormalities on reproductive outcomes in women with PCOS; 7) Relationship between thyroid function/abnormalities in patients with PCOS who are undergoing fertility treatment; 8) Effect of treatments for thyroid diseases on PCOS; and 9) Effect of treatments for PCOS on thyroid function. An extensive literature search for specific keywords was performed for articles published from 1970 to March 2023 using PubMed and Web of Science. Data were reported in a narrative fashion.

Results

PCOS is a diagnosis of exclusion for which diagnosis is possible only after excluding disorders that mimic the PCOS phenotype, including thyroid dysfunctions. However, the tests and the cutoff values used for this are not specified. Many experimental and clinical data suggest a relationship between perturbations of the thyroid function and PCOS. Direct and unequivocal evidence on the effects of thyroid function/disorders on PCOS features are lacking. High thyroid-stimulating hormone levels and subclinical hypothyroidism may be associated with significant worsening of several intermediate endpoints of cardiometabolic risk in women with PCOS. Thyroid abnormalities may worsen reproductive outcomes, especially in patients undergoing fertility treatment. To date, there are no data demonstrating the efficacy of thyroid medications on fertility and cardiometabolic risk in women with PCOS. Lifestyle modification changes, metformin, and vitamin D seem to improve thyroid function in the general population.

Conclusion

PCOS and thyroid disorders are closely related, and their coexistence may identify patients with a higher reproductive and metabolic risk. Regular screening for thyroid function and thyroid-specific autoantibodies in women with PCOS, particularly before and during pregnancy, is highly recommended.

Faecalibacterium prausnitzii in Differentiated Thyroid Cancer Patients Treated with Radioiodine

BACKGROUND

Faecalibacterium prausnitzii, one of the most important bacteria of the human gut microbiota, produces butyrate (a short-chain fatty acid). Short-chain fatty acids are known to influence thyroid physiology and thyroid cancer's response to treatment. We aimed to analyze the relative abundance of Faecalibacterium prausnitzii on the gut microbiota of differentiated thyroid cancer patients compared to controls and its variation after radioiodine therapy (RAIT).

METHODS

Fecal samples were collected from 37 patients diagnosed with differentiated thyroid cancer before and after radioiodine therapy and from 10 volunteers. The abundance of F. prausnitzii was determined using shotgun metagenomics.

RESULTS

Our study found that the relative abundance of F. prausnitzii is significantly reduced in thyroid cancer patients compared to volunteers. We also found that there was a mixed response to RAIT, with an increase in the relative and absolute abundances of this bacterium in most patients.

CONCLUSIONS

Our study confirms that thyroid cancer patients present a dysbiotic gut microbiota, with a reduction in F. prausnitzii's relative abundance. In our study, radioiodine did not negatively affect F. prausnitzii, quite the opposite, suggesting that this bacterium might play a role in resolving radiation aggression issues.

Role of the gut microbiota in anticancer therapy: from molecular mechanisms to clinical applications

In the past period, due to the rapid development of next-generation sequencing technology, accumulating evidence has clarified the complex role of the human microbiota in the development of cancer and the therapeutic response. More importantly, available evidence seems to indicate that modulating the composition of the gut microbiota to improve the efficacy of anti-cancer drugs may be feasible. However, intricate complexities exist, and a deep and comprehensive understanding of how the human microbiota interacts with cancer is critical to realize its full potential in cancer treatment. The purpose of this review is to summarize the initial clues on molecular mechanisms regarding the mutual effects between the gut microbiota and cancer development, and to highlight the relationship between gut microbes and the efficacy of immunotherapy, chemotherapy, radiation therapy and cancer surgery, which may provide insights into the formulation of individualized therapeutic strategies for cancer management. In addition, the current and emerging microbial interventions for cancer therapy as well as their clinical applications are summarized. Although many challenges remain for now, the great importance and full potential of the gut microbiota cannot be overstated for the development of individualized anti-cancer strategies, and it is necessary to explore a holistic approach that incorporates microbial modulation therapy in cancer.

Dysbiosis of the gut microbiome in elderly patients with hepatocellular carcinoma

Fecal samples from participants aged 60-80 were collected and sequenced by a high-throughput second-generation sequencer to explore the structural composition of gut microbiota in elderly patients with hepatocellular carcinoma(HCC). Comparison of gut microbiota between patients with hepatocellular carcinoma and healthy controls, α diversity and β diversity were statistically different. At the genus level, compared with the normal group, the abundance of A Blautia, Fusicatenibacter, Anaerostipes, Lachnospiraceae_ND3007_group, CAG-56, Eggerthella, Lachnospiraceae_FCS020_group and Olsenella were decreased significantly in the LC group. In contrast, the abundance of Escherichia-Shigella, Fusobacterium, Megasphaera, Veillonella, Tyzzerella_4, Prevotella_2 and Cronobacter increased significantly. The KEGG and COG pathway analyses showed that the dysbiosis of gut bacteria in primary liver carcinoma is associated with several pathways, including amino acid metabolism, replication and repair, nucleotide metabolism, cell motility, cell growth and death, and transcription. Age is negatively associated with the abundance of Bifidobacterium. Lachnospiraceae_ ND3007_ group, [Eubacterium]_hallii_group, Blautia, Fuscatenibacter and Anaerostipes are negatively correlated with ALT, AST and GGT levels (p < 0.05), respectively. Alpha-fetoprotein (AFP) is positively associated with the abundance of Erysipelatoclostridium, Magasphaera, Prevotella 2, Escherichia-Shigella, Streptococcus and [Eubacterium]_eligens_group (p < 0.05), respectively. A random forest model showed that the genera Eggerthella, Anaerostipes, and Lachnospiraceae_ ND3007_ group demonstrated the best predictive capacity. The area under the Receiver Operating Characteristic Curve of Eggerthella, Anaerostipes and Lachnospiraceae_ ND3007_ group are 0.791, 0.766 and 0.730, respectively. These data are derived from the first known gut microbiome study in elderly patients with hepatocellular carcinoma. Potentially, specific microbiota can be used as a characteristic index for screening, diagnosis, and prognosis of gut microbiota changes in elderly patients with hepatocellular carcinoma and even as a therapeutic clinical target.

Artificial intelligence-enabled microbiome-based diagnosis models for a broad spectrum of cancer types

Microbiome-based diagnosis of cancer is an increasingly important supplement for the genomics approach in cancer diagnosis, yet current models for microbiome-based diagnosis of cancer face difficulties in generality: not only diagnosis models could not be adapted from one cancer to another, but models built based on microbes from tissues could not be adapted for diagnosis based on microbes from blood. Therefore, a microbiome-based model suitable for a broad spectrum of cancer types is urgently needed. Here we have introduced DeepMicroCancer, a diagnosis model using artificial intelligence techniques for a broad spectrum of cancer types. Built based on the random forest models it has enabled superior performances on more than twenty types of cancers' tissue samples. And by using the transfer learning techniques, improved accuracies could be obtained, especially for cancer types with only a few samples, which could satisfy the requirement in clinical scenarios. Moreover, transfer learning techniques have enabled high diagnosis accuracy that could also be achieved for blood samples. These results indicated that certain sets of microbes could, if excavated using advanced artificial techniques, reveal the intricate differences among cancers and healthy individuals. Collectively, DeepMicroCancer has provided a new venue for accurate diagnosis of cancer based on tissue and blood materials, which could potentially be used in clinics.

Gut microbiota is associated with response to 131I therapy in patients with papillary thyroid carcinoma

PURPOSE

Radioactive iodine (¹³¹I) therapy is a conventional post-surgery treatment widely used for papillary thyroid carcinoma (PTC). Since ¹³¹I is orally administered, we hypothesize that it may affect gut microbiome. This study aims to investigate alterations of intestinal microbiome caused by ¹³¹I therapy in PTC patients and explore its association with response to ¹³¹I therapy.

METHODS

Fecal samples of 60 PTC patients pre- and post-¹³¹I therapy were collected to characterize the ¹³¹I therapy-induced gut microbiota alterations using 16S rRNA gene sequencing. According to the inclusion criteria, sequence data of 40 out of the 60 patients, divided into excellent response (ER) group and non-excellent response (NER) group, were recruited to investigate the possible connection between gut microbiota and response to ¹³¹I therapy. Multivariate binary logistic regression was employed to construct a predictive model for response to ¹³¹I therapy.

RESULTS

Microbial richness, diversity, and composition were tremendously altered by ¹³¹I therapy. A significant decline of Firmicutes to Bacteroides (F/B) ratio was observed post-¹³¹I therapy. ¹³¹I therapy also led to changes of gut microbiome-related metabolic pathways. Discrepancies in β diversity were found between ER and NER groups both pre- and post-¹³¹I therapy. Furthermore, a predictive model for response to ¹³¹I therapy with a p value of 0.003 and an overall percentage correct of 80.0% was established, with three variables including lymph node metastasis, relative abundance of g_Bifidobacterium and g_Dorea. Among them, g_Dorea was identified to be an in independent predictor of response to ¹³¹I therapy (p = 0.04).

CONCLUSION

For the first time, the present study demonstrates the gut microbial dysbiosis caused by ¹³¹I therapy in post-surgery PTC patients and reveals a previously undefined role of gut microbiome as predictor for ¹³¹I ablation response. G_Dorea and g_Bifidobacterium may be potential targets for clinical intervention to improve response to ¹³¹I in post-operative PTC patients.

TRIAL REGISTRATION

ChiCTR2100048000. Registered 28 June 2021.

Diagnosis and functional prediction of microbial markers in tumor tissues of sporadic colorectal cancer patients associated with the MLH1 protein phenotype

Objective

Most patients with sporadic colorectal cancer (SCRC) develop microsatellite instability because of defects in mismatch repair (MMR). Moreover, the gut microbiome plays a vital role in the pathogenesis of SCRC. In this study, we assessed the microbial composition and diversity of SCRC tumors with varying MutL protein homolog 1 (MLH1) status, and the effects of functional genes related to bacterial markers and clinical diagnostic prediction.

Methods

The tumor microbial diversity and composition were profiled using high-throughput sequencing of the 16S ribosomal RNA (rRNA) gene V4 region. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) software and BugBase tool were used to predict the functional roles of the microbiome. We aimed to construct a high-accuracy model to detect and evaluate the area under the receiver operating characteristic curve with candidate biomarkers.

Results

The study included 23 patients with negative/defective MLH1 (DM group) and 22 patients with positive/intact MLH1 (IM group). Estimation of alpha diversity indices showed that the Shannon index (p = 0.049) was significantly higher in the DM group than in the controls, while the Simpson index (p = 0.025) was significantly lower. At the genus level, we observed a significant difference in beta diversity in the DM group versus the IM group. Moreover, the abundance of Lachnoclostridium spp. and Coprococcus spp. was significantly more enriched in the DM group than in the IM group (q < 0.01 vs. q < 0.001). When predicting metagenomes, there were 18 Kyoto Encyclopedia of Genes and Genomes pathways and one BugBase function difference in both groups (all q < 0.05). On the basis of the model of diagnostic prediction, we built a simplified optimal model through stepwise selection, consisting of the top two bacterial candidate markers (area under the curve = 0.93).

Conclusion

In conclusion, the genera Lachnoclostridium and Coprococcus as key species may be crucial biomarkers for non-invasive diagnostic prediction of DM in patients with SCRC in the future.

Effect of Bining decoction on gouty nephropathy: a network pharmacology analysis and preliminary validation of gut microbiota in a mouse model

Background

To use network pharmacology and gut microbiota sequencing to investigate the probable mechanism of Bining decoction (BN) in the treatment of gouty nephropathy (GN).

Methods

Firstly, the mechanism of therapeutic effects of BN on GN were collected by integrating network pharmacology. Secondly, the treatment effects of BN against GN in 30 Institute of Cancer Research (ICR) mice were evaluated by performing biochemical tests [uric acid, blood urea nitrogen, and creatinine (UA, BUN, and Cr)] and evaluating the renal weight index. Finally, 16S rRNA sequencing was utilized for elucidating the therapeutical effect of BN in GN.

Results

The results of gut microbiota sequencing analysis showed the abundance of Faecalibaculum, Romboutsia, Bifidobacterium, Bacteroides, Odoribacter, Lachnospiraceae NK4A136 group, unclassified_f__Lachnospiraceae, Roseburia, norank_f__Lachnospiraceae, Lactobacillus, Dubosiella, norank_f__Muribaculaceae, and Turicibacter in the BN group had a significant changed between-group comparisons. Using a network pharmacology-related database, 413 active components of BN were identified, as well as 1,085 GN-associated targets. The 118 targets of disease targets and component targets were mapped, of which the top 10 genes were selected. The Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that 157 pathways were enriched, which was partially consistent with the metabolic pathways of gut microbiota sequencing analysis.

Conclusions

Combining 16S rRNA gene sequencing and network pharmacology analysis, similar signaling pathways were followed: "Pathways in cancer" and "Adipocytokine signaling pathway". The results reveal that BN increases the abundance of Turicibacter, regulates the expression of JAK2 in the JAK/STAT pathway, increases the beneficial bacteria Turicibacter associated with intestinal butyric acid, which could enhance the intestinal barrier, and exert anti-inflammatory effects.

Effect of low-dose radiation on thyroid function and the gut microbiota

BACKGROUND

The thyroid-gut axis has a great influence on the maintenance of human health; however, we know very little about the effects of low-dose ionizing radiation (LDR) on thyroid hormone levels and gut microbiota composition.

AIM

To investigate the potential effects of low-dose X-ray radiation to male C57BL/6J mice.

METHODS

Peripheral blood was collected for enzyme-linked immunosorbent assay (ELISA), and stool samples were taken for 16S ribosomal RNA (rRNA) gene sequencing after irradiation.

RESULTS

We found that LDR caused changes in thyroid stimulating hormone (TSH) levels in the irradiated mice, suggesting a dose-dependent response in thyroid function to ionizing radiation. No changes in the diversity and richness of the gut microbiota were observed in the LDR-exposed group in comparison to the controls. The abundance of Moraxellaceae and Enterobacteriaceae decreased in the LDR-exposed groups compared with the controls, and the Lachnospiraceae abundance increased in a dose-dependent manner in the radiated groups. And the abundances of uncultured_bacterium_g_Acinetobacter, uncultured_bacterium_ o_Mollicutes_RF39, uncultured_bacterium_g_Citrobacter, and uncultured_ bacterium_g_Lactococcus decreased in the radiated groups at the genus level, which showed a correlation with radiation exposure and diagnostic efficacy. Analysis of functional metabolic pathways revealed that biological metabolism was predicted to have an effect on functional activities, such as nucleotide metabolism, carbohydrate metabolism, and glycan biosynthesis and metabolism. Furthermore, Kyoto Encyclopedia of Genes and Genomes pathway annotation also suggested that changes in the gut microbiota were related to processing functions, including translation, replication and repair.

CONCLUSION

LDR can change thyroid function and the gut microbiota, and changes in the abundances of bacteria are correlated with the radiation dose.

Interaction of Gut Microbiota with Endocrine Homeostasis and Thyroid Cancer

The gut microbiota plays a crucial role in healthy individuals as well as in patients with thyroid diseases, including thyroid cancer. Although the prognosis of differentiated thyroid cancer is predictable, that of some poorly differentiated, medullary, and anaplastic thyroid cancers remains unpromising. As the interaction between the gut microbiota and thyroid cancer has been gradually revealed in recent years, the thyroid gland, a crucial endocrine organ, is shown to have a complex connection with the body's metabolism and is involved in inflammation, autoimmunity, or cancer progression. Dysbiosis of the gut microbiota and its metabolites can influence changes in hormone levels and susceptibility to thyroid cancer through multiple pathways. In this review, we focus on the interactions of the gut microbiota with thyroid function diseases and thyroid cancer. In addition, we also discuss some potential new strategies for the prevention and treatment of thyroid disease and thyroid cancer. Our aim is to provide some possible clinical applications of gut microbiota markers for early diagnosis, treatment, and postoperative management of thyroid cancer. These findings were used to establish a better multi-disciplinary treatment and prevention management strategy and to individualize the treatment of patients in relation to their gut microbiota composition and pathological characteristics.

Diagnostic and Therapeutic Uses of the Microbiome in the Field of Oncology

Cancer is a leading cause of death worldwide and it can affect almost every part of the human body. Effective screening and early diagnosis of cancers is extremely difficult due to the multifactorial etiology of the disease and delayed presentation of the patients. The available treatments are usually not specific to the affected organ system, leading to intolerable systemic side effects and early withdrawal from therapies. In vivo and in vitro studies have revealed an association of specific microbiome signatures with individual cancers. The cancer-related human microbiome has also been shown to affect the response of tissues to chemotherapy, immunotherapy, and radiation. This is an excellent opportunity for us to design specific screening markers using the microbiome to prevent cancers and diagnose them early. We can also develop precise treatments that can target cancer-affected specific organ systems and probably use a lesser dose of chemotherapy or radiation for the same effect. This prevents adverse effects and early cessation of treatments. However, we need further studies to exactly clarify and characterize these associations. In this review article, we focus on the association of the microbiome with individual cancers and highlight its future role in cancer screenings, diagnosis, prognosis, and treatments.

The relationships between the gut microbiota and its metabolites with thyroid diseases

Emerging studies have provided a preliminary understanding of the thyroid-gut axis, indicating that intestinal microbiota and its metabolites may act directly or indirectly on the thyroid by influencing intestinal microelements uptake, iodothyronine conversion and storage, and immune regulation, providing new insights into the pathogenesis of thyroid disorders and clinical management strategies. However, the research on gut microbiota and thyroid has only presented the tip of the iceberg. More robust clinical data and basic experiments are still required to elucidate the specific relationships and mechanisms in the future. Here we will characterize the associations between the microbiota and thyroid diseases to evaluate their potential implications in the pathophysiology and open up scientific avenues for future precision studies of the thyroid-gut axis.

Alterations of Gut Microbiome and Metabolite Profiles Associated With Anabatic Lipid Dysmetabolism in Thyroid Cancer

BACKGROUND

Currently, the high morbidity of individuals with thyroid cancer (TC) is an increasing health care burden worldwide. The aim of our study was to investigate the relationship among the gut microbiota community, metabolites, and the development of differentiated thyroid cancer.

METHODS

16S rRNA gene sequencing and an integrated LC-MS-based metabolomics approach were performed to obtain the components and characteristics of fecal microbiota and metabolites from 50 patients with TC and 58 healthy controls (HCs).

RESULTS

The diversity and richness of the gut microbiota in the TC patients were markedly decreased. The composition of the gut microbiota was significantly altered, and the Bacteroides enterotype was the dominant enterotype in TC patients. Additionally, the diagnostic validity of the combined model (three genera and eight metabolites) and the metabolite model (six metabolites) were markedly higher than that of the microbial model (seven genera) for distinguishing TC patients from HCs. LEfSe analysis demonstrated that genera (g_Christensenellaceae_R-7_group, g_Eubacterium_coprostanoligenes_group) and metabolites [27-hydroxycholesterol (27HC), cholesterol] closely related to lipid metabolism were greatly reduced in the TC group. In addition, a clinical serum indicator (total cholesterol) and metabolites (27HC and cholesterol) had the strongest influence on the sample distribution. Furthermore, functional pathways related to steroid biosynthesis and lipid digestion were inhibited in the TC group. In the microbiota-metabolite network, 27HC was significantly related to metabolism-related microorganisms (g_Christensenellaceae_R-7_group).

CONCLUSIONS

Our research explored the characteristics of the gut microecology of patients with TC. The findings of this study will help to discover risk factors that affect the occurrence and development of TC in the intestinal microecology.