Relating the gut metagenome and metatranscriptome to immunotherapy responses in melanoma patients

Platycodon grandiflorum-derived extracellular vesicles suppress triple-negative breast cancer growth by reversing the immunosuppressive tumor microenvironment and modulating the gut microbiota

Despite the approval of several artificial nanotherapeutics for the treatment of triple-negative breast cancer (TNBC), significant challenges, including unsatisfactory therapeutic outcomes, severe side effects, and the high cost of large-scale production, still restrict their long-term application. In contrast, plant-derived extracellular vesicles (PEVs) exhibit promising potential in cancer therapy due to their negligible systemic toxicity, high bioavailability and cost- effectiveness. In this study, we developed an alternative strategy to inhibit TNBC via Platycodon grandiflorum (PG)-derived extracellular vesicles (PGEVs). The PGEVs were isolated by ultracentrifugation and sucrose gradient centrifugation method and contained adequate functional components such as proteins, lipids, RNAs and active molecules. PGEVs exhibited remarkable stability, tolerating acidic digestion and undergoing minimal changes in simulated gastrointestinal fluid. They were efficiently taken up by tumor cells and induced increased production of reactive oxygen species (ROS), leading to tumor cell proliferation inhibition and apoptosis, particularly in the TNBC cell line 4T1. Additionally, PGEVs facilitated the polarization of tumor-associated macrophages (TAMs) toward M1 phenotype and increased the secretion of pro-inflammatory cytokines. Further in vivo investigations revealed that PGEVs efficiently accumulated in 4T1 tumors and exerted significant therapeutic effects through boosting systemic anti-tumor immune responses and modulating the gut microbiota whether administered orally or intravenously (i.v.). In conclusion, these findings highlight PGEVs as a promising natural, biocompatible and efficient nanotherapeutic candidate for treating TNBC.

The gut microbiome and cancer response to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) are widely used for cancer immunotherapy, yet only a fraction of patients respond. Remarkably, gut bacteria impact the efficacy of ICIs in fighting tumors outside of the gut. Certain strains of commensal gut bacteria promote antitumor responses to ICIs in a variety of preclinical mouse tumor models. Patients with cancer who respond to ICIs have a different microbiome compared with that of patients who don't respond. Fecal microbiota transplants (FMTs) from patients into mice phenocopy the patient tumor responses: FMTs from responders promote response to ICIs, whereas FMTs from nonresponders do not promote a response. In patients, FMTs from patients who have had a complete response to ICIs can overcome resistance in patients who progress on treatment. However, the responses to FMTs are variable. Though emerging studies indicate that gut bacteria can promote antitumor immunity in the absence of ICIs, this Review will focus on studies that demonstrate relationships between the gut microbiome and response to ICIs. We will explore studies investigating which bacteria promote response to ICIs in preclinical models, which bacteria are associated with response in patients with cancer receiving ICIs, the mechanisms by which gut bacteria promote antitumor immunity, and how microbiome-based therapies can be translated to the clinic.

Interplay between gut microbial communities and metabolites modulates pan-cancer immunotherapy responses

Immune checkpoint blockade (ICB) therapy has revolutionized cancer treatment but remains effective in only a subset of patients. Emerging evidence suggests that the gut microbiome and its metabolites critically influence ICB efficacy. In this study, we performed a multi-omics analysis of fecal microbiomes and metabolomes from 165 patients undergoing anti-programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) therapy, identifying microbial and metabolic entities associated with treatment response. Integration of data from four public metagenomic datasets (n = 568) uncovered cross-cohort microbial and metabolic signatures, validated in an independent cohort (n = 138). An integrated predictive model incorporating these features demonstrated robust performance. Notably, we characterized five response-associated enterotypes, each linked to specific bacterial taxa and metabolites. Among these, the metabolite phenylacetylglutamine (PAGln) was negatively correlated with response and shown to attenuate anti-PD-1 efficacy in vivo. This study sheds light on the interplay among the gut microbiome, the gut metabolome, and immunotherapy response, identifying potential biomarkers to improve treatment outcomes.

Understanding the role of the gut microbiome in solid tumor responses to immune checkpoint inhibitors for personalized therapeutic strategies: a review

Immunotherapy, especially immune checkpoint inhibitor (ICI) therapy, has yielded remarkable outcomes for some patients with solid cancers, but others do not respond to these treatments. Recent research has identified the gut microbiota as a key modulator of immune responses, suggesting that its composition is closely linked to responses to ICI therapy in cancer treatment. As a result, the gut microbiome is gaining attention as a potential biomarker for predicting individual responses to ICI therapy and as a target for enhancing treatment efficacy. In this review, we discuss key findings from human observational studies assessing the effect of antibiotic use prior to ICI therapy on outcomes and identifying specific gut bacteria associated with favorable and unfavorable responses. Moreover, we review studies investigating the possibility of patient outcome prediction using machine learning models based on gut microbiome data before starting ICI therapy and clinical trials exploring whether gut microbiota modulation, for example via fecal microbiota transplantation or live biotherapeutic products, can improve results of ICI therapy in patients with cancer. We also briefly discuss the mechanisms through which the gut microbial-derived products influence immunotherapy effectiveness. Further research is necessary to fully understand the complex interactions between the host, gut microbiota, and immunotherapy and to develop personalized strategies that optimize responses to ICI therapy.

A conserved pilin from uncultured gut bacterial clade TANB77 enhances cancer immunotherapy

Immune checkpoint blockade (ICB) has become a standard anti-cancer treatment, offering durable clinical benefits. However, the limited response rate of ICB necessitates biomarkers to predict and modulate the efficacy of the therapy. The gut microbiome's influence on ICB efficacy is of particular interest due to its modifiability through various interventions. However, gut microbiome biomarkers for ICB response have been inconsistent across different studies. Here, we identify TANB77, an uncultured and distinct bacterial clade, as the most consistent responder-enriched taxon through meta-analysis of ten independent ICB recipient cohorts. Traditional taxonomy fails to distinguish TANB77 from unrelated taxa, leading to its oversight. Mice with higher gut TANB77 abundance, either naturally or through transplantation, show improved response to anti-PD-1 therapy. Additionally, mice injected with TANB77-derived pilin-like protein exhibit improved anti-PD-1 therapy response, providing in vivo evidence for the beneficial role of the pilin-like protein. These findings suggest that pilins from the TANB77 order may enhance responses to ICB therapy across diverse cohorts of cancer patients.

Circulating Cell-Free Microbial DNA Signatures and Plasma Soluble CD14 Level Are Associated with Clinical Outcomes of Anti-PD-1 Therapy in Advanced Melanoma Patients

An accumulating number of studies suggest the potential of circulating cell-free microbial DNA (cfmDNA) as a non-invasive biomarker in various diseases, including cancers. However, its value in the prediction or prognosis of clinical outcomes of immune checkpoint inhibitors (ICIs) is poorly explored. The circulating cfmDNA pool may also reflect the translocation of various microbial ligands to the circulatory system and may be associated with the increased release of soluble CD14 (sCD14) by myeloid cells. In the present study, blood samples were collected from advanced melanoma patients (n = 66) before and during the anti-PD-1 therapy (approximately 3 and 12 months after the start). Then, V3-V4 16S rRNA gene sequencing was performed to analyze the circulating cfmDNA extracted from plasma samples. Moreover, the concentration of plasma sCD14 was measured using ELISA. As a result, the differences in the circulating cfmDNA profiles were found between patients with favorable and unfavorable clinical outcomes of the anti-PD-1 and baseline signatures correlated with progression-free survival and overall survival. Moreover, there was a higher concentration of plasma sCD14 in patients with unfavorable clinical outcomes. High baseline sCD14 level and its increase during the therapy prognosticated worse survival outcomes. Taken together, this preliminary study indicates the potential of circulating cfmDNA signatures and plasma sCD14 levels as biomarkers of clinical outcomes of ICIs.

Associations of the gut microbiome with outcomes in cervical and endometrial cancer patients treated with pembrolizumab: Insights from the phase II PRIMMO trial

BACKGROUND

The phase II PRIMMO trial investigated a pembrolizumab-based regimen in patients with recurrent and/or metastatic cervical (CC) or endometrial (EC) carcinoma who had at least one prior line of systemic therapy. Here, exploratory studies of the gut microbiome (GM) are presented.

METHODS

The microbial composition of 77 longitudinal fecal samples obtained from 35 patients (CC, n = 15; EC, n = 20) was characterized using 16S rRNA gene sequencing. Analyses included assessment of alpha (Shannon index) and beta diversity (weighted UniFrac), unbiased hierarchical clustering, and linear discriminant analysis effect size. Correlative studies with demographics, disease characteristics, safety, efficacy, and immune monitoring data were performed.

RESULTS

Significant enrichment in multiple bacterial taxa was associated with the occurrence or resistance to severe treatment-related adverse events (overall or gastrointestinal toxicity specifically). Consistent differences in GM taxonomic composition before pembrolizumab initiation were observed between patients with favorable efficacy (e.g., enriched with Blautia genus) and those with poor efficacy (e.g., enriched with Enterobacteriaceae family and its higher-level taxa up to the phylum level, as well as Clostridium genus and its Clostridiaceae family). Two naturally occurring GM clusters with distinct bacterial compositions were identified. These clusters showed a more than four-fold differential risk for death (hazard ratio, 4.4 [95 % confidence interval, 1.9 to 10.3], P < 0.001) and were associated with interesting (but non-significant) trends in peripheral immune monitoring data.

CONCLUSION

Although exploratory, this study offers initial insights into the intricate interplay between the GM and clinical outcomes in patients with CC and EC treated with a pembrolizumab-based regimen.

TRIAL REGISTRATION

ClinicalTrials.gov (identifier NCT03192059) and EudraCT Registry (number 2016-001569-97).

Gut microbiota as a biomarker and modulator of anti-tumor immunotherapy outcomes

Although immune-checkpoint inhibitors (ICIs) have significantly improved cancer treatment, their effectiveness is limited by primary or acquired resistance in many patients. The gut microbiota, through its production of metabolites and regulation of immune cell functions, plays a vital role in maintaining immune balance and influencing the response to cancer immunotherapies. This review highlights evidence linking specific gut microbial characteristics to increased therapeutic efficacy in a variety of cancers, such as gastrointestinal cancers, melanoma, lung cancer, urinary system cancers, and reproductive system cancers, suggesting the gut microbiota's potential as a predictive biomarker for ICI responsiveness. It also explores the possibility of enhancing ICI effectiveness through fecal microbiota transplantation, probiotics, prebiotics, synbiotics, postbiotics, and dietary modifications. Moreover, the review underscores the need for extensive randomized controlled trials to confirm the gut microbiota's predictive value and to establish guidelines for microbiota-targeted interventions in immunotherapy. In summary, the article suggests that a balanced gut microbiota is key to maximizing immunotherapy benefits and calls for further research to optimize microbiota modulation strategies for cancer treatment. It advocates for a deeper comprehension of the complex interactions between gut microbiota, host immunity, and cancer therapy, aiming for more personalized and effective treatment options.

Metabolic pathways from the gut metatranscriptome are associated with COPD and respiratory function in lung cancer patients

Introduction

Changes in the human gut microbiome have been linked to various chronic diseases, including chronic obstructive pulmonary disease (COPD). While substantial knowledge is available on the genomic features of fecal communities, little is known about the microbiome's transcriptional activity. Here, we analyzed the metatranscriptomic (MTR) abundance of MetaCyc pathways, SuperPathways, and protein domain families (PFAM) represented by the gut microbiome in a cohort of non-small cell lung cancer (NSCLC) patients with- or without COPD comorbidity.

Methods

Fecal samples of 40 NSCLC patients with- or without COPD comorbidity were collected at the time of diagnosis. Data was preprocessed using the Metaphlan3/Humann3 pipeline and BioCyc© to identify metabolic SuperPathways. LEfSe analysis was conducted on Pathway- and PFAM abundance data to determine COPD- and non-COPD-related clusters.

Results

Key genera Streptococcus, Escherichia, Gemella, and Lactobacillus were significantly more active transcriptionally compared to their metagenomic presence. LEfSe analysis identified 11 MetaCyc pathways that were significantly overrepresented in patients with- and without COPD comorbidity. According to Spearman's rank correlation, Smoking PY showed a significant negative correlation with Glycolysis IV, Purine Ribonucleoside Degradation and Glycogen Biosynthesis I, and a significant positive correlation with Superpathway of Ac-CoA Biosynthesis and Glyoxylate cycle, whereas forced expiratory volume in the first second (FEV1) showed a significant negative correlation with Glycolysis IV and a significant positive correlation with Glycogen Biosynthesis I. Furthermore, COPD patients showed a significantly increased MTR abundance in ~60% of SuperPathways, indicating a universally increased MTR activity in this condition. FEV1 showed a significant correlation with SuperPathways Carbohydrate degradation, Glycan biosynthesis, and Glycolysis. Taxonomic analysis suggested a more prominent MTR activity from multiple Streptococcus species, Enterococcus (E.) faecalis, E. faecium and Escherichia (E.) coli than expected from their metagenomic abundance. Multiple protein domain families (PFAMs) were identified as more associated with COPD, E. faecium, E.coli, and Streptococcus salivarius, contributing the most to these PFAMs.

Conclusion

Metatranscriptome analysis identified COPD-related subsets of lung cancer with potential therapeutic relevance.

Gut metatranscriptomics based de novo assembly reveals microbial signatures predicting immunotherapy outcomes in non-small cell lung cancer

BACKGROUND

Advanced-stage non-small cell lung cancer (NSCLC) poses treatment challenges, with immune checkpoint inhibitors (ICIs) as the main therapy. Emerging evidence suggests the gut microbiome significantly influences ICI efficacy. This study explores the link between the gut microbiome and ICI outcomes in NSCLC patients, using metatranscriptomic (MTR) signatures.

METHODS

We utilized a de novo assembly-based MTR analysis on fecal samples from 29 NSCLC patients undergoing ICI therapy, segmented according to progression-free survival (PFS) into long (> 6 months) and short (≤ 6 months) PFS groups. Through RNA sequencing, we employed the Trinity pipeline for assembly, MMSeqs2 for taxonomic classification, DESeq2 for differential expression (DE) analysis. We constructed Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) machine learning (ML) algorithms and comprehensive microbial profiles.

RESULTS

We detected no significant differences concerning alpha-diversity, but we revealed a biologically relevant separation between the two patient groups in beta-diversity. Actinomycetota was significantly overrepresented in patients with short PFS (vs long PFS, 36.7% vs. 5.4%, p < 0.001), as was Euryarchaeota (1.3% vs. 0.002%, p = 0.009), while Bacillota showed higher prevalence in the long PFS group (66.2% vs. 42.3%, p = 0.007), when comparing the abundance of corresponding RNA reads. Among the 120 significant DEGs identified, cluster analysis clearly separated a large set of genes more active in patients with short PFS and a smaller set of genes more active in long PFS patients. Protein Domain Families (PFAMs) were analyzed to identify pathways enriched in patient groups. Pathways related to DNA synthesis and Translesion were more enriched in short PFS patients, while metabolism-related pathways were more enriched in long PFS patients. E. coli-derived PFAMs dominated in patients with long PFS. RF, SVM and XGBoost ML models all confirmed the predictive power of our selected RNA-based microbial signature, with ROC AUCs all greater than 0.84. Multivariate Cox regression tested with clinical confounders PD-L1 expression and chemotherapy history underscored the influence of n = 6 key RNA biomarkers on PFS.

CONCLUSION

According to ML models specific gut microbiome MTR signatures' associate with ICI treated NSCLC outcomes. Specific gene clusters and taxa MTR gene expression might differentiate long vs short PFS.

Viroid-like colonists of human microbiomes

Here, we describe "obelisks," a class of heritable RNA elements sharing several properties: (1) apparently circular RNA ∼1 kb genome assemblies, (2) predicted rod-like genome-wide secondary structures, and (3) open reading frames encoding a novel "Oblin" protein superfamily. A subset of obelisks includes a variant hammerhead self-cleaving ribozyme. Obelisks form their own phylogenetic group without detectable similarity to known biological agents. Surveying globally, we identified 29,959 distinct obelisks (clustered at 90% sequence identity) from diverse ecological niches. Obelisks are prevalent in human microbiomes, with detection in ∼7% (29/440) and ∼50% (17/32) of queried stool and oral metatranscriptomes, respectively. We establish Streptococcus sanguinis as a cellular host of a specific obelisk and find that this obelisk's maintenance is not essential for bacterial growth. Our observations identify obelisks as a class of diverse RNAs of yet-to-be-determined impact that have colonized and gone unnoticed in human and global microbiomes.

Neoadjuvant vidutolimod and nivolumab in high-risk resectable melanoma: A prospective phase II trial

Intratumoral TLR9 agonists and anti-PD-1 produce clinical responses and broad immune activation. We conducted a single-arm study of neoadjuvant TLR9 agonist vidutolimod combined with anti-PD-1 nivolumab in high-risk resectable melanoma. In 31 evaluable patients, 55% major pathologic response (MPR) was observed, meeting primary endpoint. MPR was associated with necrosis, and melanophagocytosis with increased CD8+ tumor-infiltrating lymphocytes and plasmacytoid dendritic cells (pDCs) in the tumor microenvironment, and increased frequencies of Ki67+CD8+ T cells peripherally. MPRs had an enriched pre-treatment gene signature of myeloid cells, and response to therapy was associated with gene signatures of immune cells, pDCs, phagocytosis, and macrophage activation. MPRs gut microbiota were enriched for Gram-negative bacteria belonging to the Bacteroidaceae and Enterobacteriaceae families and the small subgroup of Gram-negative Firmicutes. Our findings support that combined vidutolimod and nivolumab stimulates a broad anti-tumor immune response and is associated with distinct baseline myeloid gene signature and gut microbiota. ClinicalTrials.gov identifier: NCT03618641.

A two-step, two-sample Mendelian randomization analysis investigating the interplay between gut microbiota, immune cells, and melanoma skin cancer

This study aims to rigorously explore the potential causal relationships among gut microbiota (GM), immune cells, and melanoma skin cancer among participants from Europe, where this disease exhibits significant prevalence and profound societal impact. Using the genome-wide association analysis database, a double-sample Mendelian randomization (MR) analysis was drawn upon to investigate GM, immune cells, and melanoma skin cancer. The inverse variance weighted approach was applied to estimate the causal connections among these variables. A two-step MR analysis was employed to quantitatively gauge the impact of immune cells mediated GM on melanoma skin cancer. To address potential sources of bias, such as pleiotropy and heterogeneity, multiple analytical techniques were integrated. The MR analysis pinpointed 6 GM taxa related to either an augmented or declined risk of late-stage melanoma skin cancer. In the same vein, 32 immune cell phenotypes were noticed as correlates with modified risk of melanoma skin cancer. Our study also implies that the probable association between GM and melanoma could be facilitated by 5 immune cell phenotypes. The findings of our study underline certain GM taxa and immune cells as potential influencers on the onset and development of melanoma skin cancer. Importantly, our results spotlight 5 immune cell phenotypes as potential agents mediating this association.

Effects of gut microbiota on immune checkpoint inhibitors in multi-cancer and as microbial biomarkers for predicting therapeutic response

BACKGROUND

Gut bacteria are related to immune checkpoint inhibitors (ICIs). However, there is inconsistency in ICI-associated species, while the role of non-bacterial microbes in immunotherapy remains elusive. Here, we evaluated the association of trans-kingdom microbes with ICIs by multi-cohort multi-cancer analyses.

METHODS

We retrieved fecal metagenomes from 1,359 ICI recipients with four different cancers (metastatic melanoma [MM], non-small cell lung carcinoma [NSCLC], renal cell cancer [RCC], and hepatocellular carcinoma) from 12 published datasets. Microbiota composition was analyzed using the Wilcoxon rank test. The performance of microbial biomarkers in predicting ICI response was assessed by random forest. Key responder-associated microbes were functionally examined in vitro and in mice.

FINDINGS

Trans-kingdom gut microbiota (bacteria, eukaryotes, viruses, and archaea) was significantly different between ICI responders and non-responders in multi-cancer. Bacteria (Faecalibacterium prausnitzii, Coprococcus comes) and eukaryotes (Nemania serpens, Hyphopichia pseudoburtonii) were consistently enriched in responders of ≥2 cancer types or from ≥3 cohorts, contrasting with the depleted bacterium Hungatella hathewayi. Responder-associated species in each cancer were revealed, such as F. prausnitzii in MM and 6 species in NSCLC. These signature species influenced ICI efficacy by modulating CD8+ T cell activity in vitro and in mice. Moreover, bacterial and eukaryotic biomarkers showed great performance in predicting ICI response in patients from discovery and two validation cohorts (MM: area under the receiver operating characteristic curve [AUROC] = 72.27%-80.19%; NSCLC: AUROC = 72.70%-87.98%; RCC: AUROC = 83.33%-89.58%).

CONCLUSIONS

This study identified trans-kingdom microbial signatures associated with ICI in multi-cancer and specific cancer types. Trans-kingdom microbial biomarkers are potential predictors of ICI response in patients with cancer.

FUNDING

Funding information is shown in the acknowledgments.

Recent Advances in Bacterium-Based Therapeutic Modalities for Melanoma Treatment

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.

Gut microbiome model predicts response to neoadjuvant immunotherapy plus chemoradiotherapy in rectal cancer

BACKGROUND

Accurate evaluation of the response to preoperative treatment enables the provision of a more appropriate personalized therapeutic schedule for locally advanced rectal cancer (LARC), which remains an enormous challenge, especially neoadjuvant immunotherapy plus chemoradiotherapy (nICRT).

METHODS

This prospective, multicenter cohort study enrolled patients with LARC from 6 centers who received nICRT. The dynamic variation in the gut microbiome during nICRT was evaluated. A species-level gut microbiome prediction (SPEED) model was developed and validated to predict the pathological complete response (pCR) to nICRT.

FINDINGS

A total of 50 patients were enrolled, 75 fecal samples were collected from 33 patients at different time points, and the pCR rate reached 42.4% (14/33). Lactobacillus and Eubacterium were observed to increase after nICRT. Additionally, significant differences in the gut microbiome were observed between responders and non-responders at baseline. Significantly higher abundances of Lachnospiraceae bacterium and Blautia wexlerae were found in responders, while Bacteroides, Prevotella, and Porphyromonas were found in non-responders. The SPEED model showcased a superior predictive performance with areas under the curve of 98.80% (95% confidence interval [CI]: 95.67%-100%) in the training cohort and 77.78% (95% CI: 65.42%-88.29%) in the validation cohort.

CONCLUSIONS

Programmed death 1 (PD-1) blockade plus concurrent long-course CRT showed a favorable pCR rate and is well tolerated in microsatellite-stable (MSS)/mismatch repair-proficient (pMMR) patients with LARC. The SPEED model can be used to predict the pCR to nICRT based on the baseline gut microbiome with high robustness and accuracy, thereby assisting clinical physicians in providing individualized management for patients with LARC.

FUNDING

This research was funded by the China National Natural Science Foundation (82202884).

Gut microbiota as a prognostic biomarker for unresectable hepatocellular carcinoma treated with anti-PD-1 therapy

Objective

To investigate the relationship between the gut microbiome and the response to anti-PD-1-based combination therapy in unresectable hepatocellular carcinoma (HCC). We aimed to identify potential non-invasive biomarkers and new strategies to modulate immunotherapy in HCC.

Methods

In this study, fresh stool samples and clinical data were collected from unresectable HCC patients treated with anti-PD-1-based combination therapy at the Cancer Hospital of the Chinese Academy of Medical Sciences between January 2020 and December 2021. The patients were divided into two groups based on their response to treatment: the treatment responder group (R group) and the treatment non-responder group (NR group). The composition and diversity of the gut microbiome were bioinformatically analyzed by using the Whole Genome Shotgun strategy, including taxonomic composition analysis, Alpha diversity analysis, Beta diversity analysis, and differentially enriched bacterial taxa analysis. Differentially enriched bacterial taxa between R and NR groups were identified based on the magnitude of the linear discriminant analysis effect size (LEfSe) and analyzed for their impact on the survival of the patient.

Results

A total of 45 eligible patients with unresectable HCC treated with anti-PD-1-based combination therapy participated in this study. The gut microbiological composition and Alpha diversity of patients were not statistically different, but there was a statistically significant difference in Beta diversity between the R and NR groups. (PERMANOVA tests, P = 0.006). We further identified 56 enriched bacterial taxa in the R group and 44 enriched bacterial taxa in the NR group based on the LEfSe analysis (LDA >2.66, P< 0.05). Patients with a high abundance of Collinsella genus, Ruminococcus_AM4211, and Ruminococcus_AF25_28AC had a longer median PFS and median OS compared to those with low abundance (P < 0.05). On the contrary, the median PFS and OS of patients with a high abundance of Bacteroides_AF20_13LB and Veillonella_atypica were significantly shorter than those of patients with low abundance (P < 0.05). The multivariate analysis showed that the abundance of Bacteroides_AF20_13LB and Ruminococcus_ AF25_28AC was independent related factors for PFS, and the abundance of Bacteroides_AF20_13LB was an independent related factor of OS.

Conclusion

The enrichment of specific gut microbiota affected clinical efficacy and survival benefits in HCC treated with anti-PD-1 therapy and may be a promising non-invasive gut microbial biomarker and a new strategy for modulating immunotherapy in HCC.

Immune Checkpoint Inhibitor Therapy for Metastatic Melanoma: What Should We Focus on to Improve the Clinical Outcomes?

Immune checkpoint inhibitors (ICIs) have transformed cancer treatment by enhancing anti-tumour immune responses, demonstrating significant efficacy in various malignancies, including melanoma. However, over 50% of patients experience limited or no response to ICI therapy. Resistance to ICIs is influenced by a complex interplay of tumour intrinsic and extrinsic factors. This review summarizes current ICIs for melanoma and the factors involved in resistance to the treatment. We also discuss emerging evidence that the microbiota can impact ICI treatment outcomes by modulating tumour biology and anti-tumour immune function. Furthermore, microbiota profiles may offer a non-invasive method for predicting ICI response. Therefore, future research into microbiota manipulation could provide cost-effective strategies to enhance ICI efficacy and improve outcomes for melanoma patients.

Changes in the gut microbiota of esophageal carcinoma patients based on 16S rRNA gene sequencing: a systematic review and meta-analysis

Background

This study conducts a systematic review through meta-analysis, comparing the composition and diversity of the gut microbiome in patients with esophageal cancer and healthy individuals, and explores the relationship between risk factors and related factors of esophageal cancer.

Methods

According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), we comprehensively searched the databases of PubMed, Web of Science, Embase, Cochrane Library. In addition, we applied the R programming language version 4.0.3 and Stata 15.1 software for data analysis. We also implemented the Newcastle-Ottawa Scale (NOS), funnel plot analysis, Egger's test, and Begg's test to assess the risk of bias.

Results

In this study, a total of 328 studies were identified through the literature search. Among them, 117 duplicate studies were removed, and 202 studies were excluded based on inclusion and exclusion criteria. Finally, 9 studies were included in the analysis, involving a total of 216 patients with esophageal carcinoma and 352 healthy controls. Four studies provided Chao1 index for quantitative consolidation (ES = 637.41, 95% CI: 549.16 to 725.66, p = 0.000, I2 = 98.2%). Two studies [27, 29] reported ACE index (ES = 438.89, 95% CI: 362.42 to 515.35, p = 0.000, I2 = 97%). Seven studies [26,27,29,30,32] reported the Shannon index for quantitative consolidation (ES = 4.38, 95% CI: 3.95 to 4.81, p = 0.000, I2 = 99%). At the phylum level, the abundance of Bacteroidetes(ES = 37.8, 95% CI: 25.75 to 49.85, p = 0.000, I2 = 87.2%) and Proteobacteria(ES = 7.48, 95% CI: 5.02 to 8.85, p = 0.04, I2 = 2.4%) have statistical difference between ESCC and HC. There was no significant difference between ESCC and HC in the abundance of genera(p>0.05).

Conclusions

This observational meta-analysis revealed that changes in the GM were correlated with esophageal carcinoma, and variations in some advantageous GM might involve regional differences. Additionally, the study aims to facilitate early diagnosis of esophageal cancer and improve screening and diagnostic efficiency.

Microbiota composition effect on immunotherapy outcomes in colorectal cancer patients: A systematic review

BACKGROUND

Immune checkpoint inhibitors (ICIs) have emerged as an effective treatment for colorectal cancer (CRC). Studies indicate that the composition of gut microbiota could potentially serve as a biomarker for predicting the clinical effectiveness of immune checkpoint inhibitors.

METHODS

Following PRISMA guidelines, the review was conducted after registering the protocol with PROSPERO. A comprehensive literature search was carried out across five databases: PubMed, Scopus, Web of Science, Embase, and Cochrane Library. Assessment tools from the National Institutes of Health (NIH) were used to gauge the quality of the studies.

RESULTS

A total of 5,132 papers were identified, and three studies and one conference abstract published between 2017-2022 met the inclusion criteria and were summarized in a descriptive synthesis table. These four studies were in accord with the following findings, four main phyla, Firmicutes, Bacteroidata, Actinobacteria, and Verrucomicrobiota were associated with CRC patients' clinical response toward ICIs treatment. Ruminococcaceae was predominantly related to CRC patients responding to therapy, while the Micrococcaceae family was more common among the non-responders. Bacterial taxa such as Faecalibacterium and Prevotellaceae were associated with better responses to ICIs and could be predictive biomarkers. The signature of fecal microbiota with Akkermansia muciniphila and Eubacterium rectale enrichment, and Rothia mucilaginosa depletion could independently predict better response to ICIs in patients with CRC.

CONCLUSION

The findings have brought attention to the notable differences in terms of richness and composition of microbiota between patients who responded positively to the treatment and those who did not. Bacterial species and families, such as Faecalibacterium, Bifidobacterium, Lachnospiraceae, Akkermansia sp., Ruminococcaceae, and Prevotellaceae, have consistently surfaced as potential indicators of immunotherapeutic responses. Furthermore, this review also emphasizes the need for additional comprehensive, multi-center studies with larger sample sizes to validate reported microbiota and expand our understanding of the role of gut microbiota in CRC ICIs therapy. PROSPERO ID: CRD42021277691.

Faecalibaterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors

Gut microbiota impacts responses to immune checkpoint inhibitors (ICI). A high level of Faecalibacterium prausnitzii have been associated with a positive response to ICI in multiple cancer types. Here, based on fecal shotgun metagenomics data, we show in two independent cohorts of patients with non-small cell lung cancer and advanced melanoma that a high level of F. prausnitzii at baseline is positively associated with a better clinical response to ICI. In MCA205 tumor-bearing mice, administration of F. prausnitzii strain EXL01, already in clinical development for Inflammatory Bowel Disease, restores the anti-tumor response to ICI in the context of antibiotic-induced microbiota perturbation at clinical and tumor transcriptomics level. In vitro, EXL01 strain enhances T cell activation in the presence of ICI. Interestingly, oral administration of EXL01 strain did not induce any change in fecal microbiota diversity or composition, suggesting a direct effect on immune cells in the small intestine. F. prausnitzii strain EXL01 will be evaluated as an adjuvant to ICI in multiple cancers in the near future.

Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours

Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.

Prevotella copri transplantation promotes neurorehabilitation in a mouse model of traumatic brain injury

BACKGROUND

The gut microbiota plays a critical role in regulating brain function through the microbiome-gut-brain axis (MGBA). Dysbiosis of the gut microbiota is associated with neurological impairment in Traumatic brain injury (TBI) patients. Our previous study found that TBI results in a decrease in the abundance of Prevotella copri (P. copri). P. copri has been shown to have antioxidant effects in various diseases. Meanwhile, guanosine (GUO) is a metabolite of intestinal microbiota that can alleviate oxidative stress after TBI by activating the PI3K/Akt pathway. In this study, we investigated the effect of P. copri transplantation on TBI and its relationship with GUO-PI3K/Akt pathway.

METHODS

In this study, a controlled cortical impact (CCI) model was used to induce TBI in adult male C57BL/6J mice. Subsequently, P. copri was transplanted by intragastric gavage for 7 consecutive days. To investigate the effect of the GUO-PI3K/Akt pathway in P. copri transplantation therapy, guanosine (GUO) was administered 2 h after TBI for 7 consecutive days, and PI3K inhibitor (LY294002) was administered 30 min before TBI. Various techniques were used to assess the effects of these interventions, including quantitative PCR, neurological behavior tests, metabolite analysis, ELISA, Western blot analysis, immunofluorescence, Evans blue assays, transmission electron microscopy, FITC-dextran permeability assay, gastrointestinal transit assessment, and 16 S rDNA sequencing.

RESULTS

P. copri abundance was significantly reduced after TBI. P. copri transplantation alleviated motor and cognitive deficits tested by the NSS, Morris's water maze and open field test. P. copri transplantation attenuated oxidative stress and blood-brain barrier damage and reduced neuronal apoptosis after TBI. In addition, P. copri transplantation resulted in the reshaping of the intestinal flora, improved gastrointestinal motility and intestinal permeability. Metabolomics and ELISA analysis revealed a significant increase in GUO levels in feces, serum and injured brain after P. copri transplantation. Furthermore, the expression of p-PI3K and p-Akt was found to be increased after P. copri transplantation and GUO treatment. Notably, PI3K inhibitor LY294002 treatment attenuated the observed improvements.

CONCLUSIONS

We demonstrate for the first time that P. copri transplantation can improve GI functions and alter gut microbiota dysbiosis after TBI. Additionally, P. copri transplantation can ameliorate neurological deficits, possibly via the GUO-PI3K/Akt signaling pathway after TBI.

Genetic causal relationship between gut microbiota and cutaneous melanoma: a two-sample Mendelian randomization study

Currently, numerous studies suggest a potential association between the gut microbiota and the progression of melanoma. Hence, our objective was to examine the genetic impact of the gut microbiota on melanoma through the utilization of the Mendelian randomization (MR) approach. This research employed Bacteroides, Streptococcus, Proteobacteria, and Lachnospiraceae as exposure variables and cutaneous melanoma (CM) as the outcome in a two-sample MR analysis. In this MR research, the primary analytical approach was the random-effects inverse-variance weighting (IVW) model. Complementary methods included weighted median, MR Egger, and basic and weighted models. We assessed both heterogeneity and horizontal pleiotropy in our study, scrutinizing whether the analysis results were affected by any individual SNP. The random-effects IVW outcomes indicated that Streptococcus, Bacteroides, Lachnospiraceae and Proteobacteria had no causal relationship with CM, with odds ratios of 1.001 [95% confidence interval (CI) = 0.998-1.004, P  = 0.444], 0.999 (95% CI = 0.996-1.002, P  = 0.692), 1.001 (95% CI = 0.998-1.003, P  = 0.306), and 0.999 (95% CI = 0.997-1.002, P  = 0.998), respectively. No analyses exhibited heterogeneity, horizontal pleiotropy, or deviations. Our research determined that Bacteroides, Streptococcus, Proteobacteria, and Lachnospiraceae do not induce CM at the genetic level. However, we cannot dismiss the possibility that these four gut microbiotas might influence CM through other mechanisms.

Systemic metabolic depletion of gut microbiome undermines responsiveness to melanoma immunotherapy

Immunotherapy has proven to be a boon for patients battling metastatic melanoma, significantly improving their clinical condition and overall quality of life. A compelling link between the composition of the gut microbiome and the efficacy of immunotherapy has been established in both animal models and human patients. However, the precise biological mechanisms by which gut microbes influence treatment outcomes remain poorly understood. Using a robust dataset of 680 fecal metagenomes from melanoma patients, a detailed catalog of metagenome-assembled genomes (MAGs) was constructed to explore the compositional and functional properties of the gut microbiome. Our study uncovered significant findings that deepen the understanding of the intricate relationship between gut microbes and the efficacy of melanoma immunotherapy. In particular, we discovered the specific metagenomic profile of patients with favorable treatment outcomes, characterized by a prevalence of MAGs with increased overall metabolic potential and proficiency in polysaccharide utilization, along with those responsible for cobalamin and amino acid production. Furthermore, our investigation of the biosynthetic pathways of short-chain fatty acids, known for their immunomodulatory role, revealed a differential abundance of these pathways among the specific MAGs. Among others, the cobalamin-dependent Wood-Ljungdahl pathway of acetate synthesis was directly associated with responsiveness to melanoma immunotherapy.

Gut microbiome is associated with recurrence-free survival in patients with resected Stage IIIB-D or Stage IV melanoma treated with immune checkpoint inhibitors

The gut microbiome (GMB) has been associated with outcomes of immune checkpoint blockade therapy in melanoma, but there is limited consensus on the specific taxa involved, particularly across different geographic regions. We analyzed pre-treatment stool samples from 674 melanoma patients participating in a phase-III trial of adjuvant nivolumab plus ipilimumab versus nivolumab, across three continents and five regions. Longitudinal analysis revealed that GMB was largely unchanged following treatment, offering promise for lasting GMB-based interventions. In region-specific and cross-region meta-analyses, we identified pre-treatment taxonomic markers associated with recurrence, including Eubacterium, Ruminococcus, Firmicutes, and Clostridium. Recurrence prediction by these markers was best achieved across regions by matching participants on GMB compositional similarity between the intra-regional discovery and external validation sets. AUCs for prediction ranged from 0.83-0.94 (depending on the initial discovery region) for patients closely matched on GMB composition (e.g., JSD ≤0.11). This evidence indicates that taxonomic markers for prediction of recurrence are generalizable across regions, for individuals of similar GMB composition.

Gut Bacteria Provide Genetic and Molecular Reporter Systems to Identify Specific Diseases

With genetic information gained from next-generation sequencing (NGS) and genome-wide association studies (GWAS), it is now possible to select for genes that encode reporter molecules that may be used to detect abnormalities such as alcohol-related liver disease (ARLD), cancer, cognitive impairment, multiple sclerosis (MS), diabesity, and ischemic stroke (IS). This, however, requires a thorough understanding of the gut-brain axis (GBA), the effect diets have on the selection of gut microbiota, conditions that influence the expression of microbial genes, and human physiology. Bacterial metabolites such as short-chain fatty acids (SCFAs) play a major role in gut homeostasis, maintain intestinal epithelial cells (IECs), and regulate the immune system, neurological, and endocrine functions. Changes in butyrate levels may serve as an early warning of colon cancer. Other cancer-reporting molecules are colibactin, a genotoxin produced by polyketide synthetase-positive Escherichia coli strains, and spermine oxidase (SMO). Increased butyrate levels are also associated with inflammation and impaired cognition. Dysbiosis may lead to increased production of oxidized low-density lipoproteins (OX-LDLs), known to restrict blood vessels and cause hypertension. Sudden changes in SCFA levels may also serve as a warning of IS. Early signs of ARLD may be detected by an increase in regenerating islet-derived 3 gamma (REG3G), which is associated with changes in the secretion of mucin-2 (Muc2). Pro-inflammatory molecules such as cytokines, interferons, and TNF may serve as early reporters of MS. Other examples of microbial enzymes and metabolites that may be used as reporters in the early detection of life-threatening diseases are reviewed.

Microbiome bacterial influencers of host immunity and response to immunotherapy

The gut microbiota influences anti-tumor immunity and can induce or inhibit response to immune checkpoint inhibitors (ICIs). Therefore, microbiome features are being studied as predictive/prognostic biomarkers of patient response to ICIs, and microbiome-based interventions are attractive adjuvant treatments in combination with ICIs. Specific gut-resident bacteria can influence the effectiveness of immunotherapy; however, the mechanism of action on how these bacteria affect anti-tumor immunity and response to ICIs is not fully understood. Nevertheless, early bacterial-based therapeutic strategies have demonstrated that targeting the gut microbiome through various methods can enhance the effectiveness of ICIs, resulting in improved clinical responses in patients with a diverse range of cancers. Therefore, understanding the microbiota-driven mechanisms of response to immunotherapy can augment the success of these interventions, particularly in patients with treatment-refractory cancers.

Modulating gut microbiome in cancer immunotherapy: Harnessing microbes to enhance treatment efficacy

Immunotherapy has emerged as a robust approach against cancer, yet its efficacy has varied among individuals, accompanied by the occurrence of immune-related adverse events. As a result, the efficacy of immunotherapy is far from satisfactory, and enormous efforts have been invested to develop strategies to improve patient outcomes. The gut microbiome is now well acknowledged for its critical role in immunotherapy, with better understanding on host-microbes interaction in the context of cancer treatment. Also, an increasing number of trials have been conducted to evaluate the potential and feasibility of microbiome-targeting approaches to enhance efficacy of cancer treatment in patients. Here, the role of the gut microbiome and metabolites (e.g., short-chain fatty acids, tryptophan metabolites) in immunotherapy and the underlying mechanisms are explored. The application of microbiome-targeting approaches that aim to improve immunotherapy efficacy (e.g., fecal microbiota transplantation, probiotics, dietary intervention) is also elaborated, with further discussion on current challenges and suggestions for future research.

A specific enterotype derived from gut microbiome of older individuals enables favorable responses to immune checkpoint blockade therapy

Immunotherapy has revolutionized cancer treatment, but inconsistent responses persist. Our study delves into the intriguing phenomenon of enhanced immunotherapy sensitivity in older individuals with cancers. Through a meta-analysis encompassing 25 small-to-mid-sized trials of immune checkpoint blockade (ICB), we demonstrate that older individuals exhibit heightened responsiveness to ICB therapy. To understand the underlying mechanism, we reanalyze single-cell RNA sequencing (scRNA-seq) data from multiple studies and unveil distinct upregulation of exhausted and cytotoxic T cell markers within the tumor microenvironment (TME) of older patients. Recognizing the potential role of gut microbiota in modulating the efficacy of immunotherapy, we identify an aging-enriched enterotype linked to improved immunotherapy outcomes in older patients. Fecal microbiota transplantation experiments in mice confirm the therapeutic potential of the aging-enriched enterotype, enhancing treatment sensitivity and reshaping the TME. Our discoveries confront the prevailing paradox and provide encouraging paths for tailoring cancer immunotherapy strategies according to an individual's gut microbiome profile.

Causal associations between gut microbiota and cutaneous melanoma: a Mendelian randomization study

Background

Cutaneous melanoma (CM) of the skin stands as the leading cause of mortality among skin cancer-related deaths. Despite the successes achieved with novel therapies such as immunotherapy and targeted therapy, their efficacy remains limited, necessitating further exploration of new treatment modalities. The gut microbiota and CM may be linked, as indicated by a growing body of preclinical and observational research. Nevertheless, the exact correlation between the intestinal microbiota and CM remains to be determined. Therefore, this study aims to assess the potential causal relationship between the gut microbiota and CM.

Methods

The study utilized exposure data obtained from the MiBioGen consortium's microbiome GWAS, which included a total of 18,340 samples gathered from 24 population-based cohorts. Data at the summary level for CM were acquired from the UK Biobank investigation. The main analytical strategy utilized in this research was the inverse variance weighted (IVW) technique, supported by quality assurance measures like the weighted median model, MR-Egger, simple model, and weighted model approaches. The Cochran's Q test was used to evaluate heterogeneity. To ascertain potential pleiotropy, we employed both the MR-Egger regression and the MR-PRESSO test. Sensitivity analysis was conducted using the leave-one-out method.

Results

The study found that the class Bacteroidia (OR = 0.997, 95% CI: 0.995-0.999, p = 0.027), genus Parabacteroides (OR = 0.997, 95% CI: 0.994-0.999, p = 0.037), order Bacteroidales (OR = 0.997, 95% CI: 0.995-0.999, p = 0.027), and genus Veillonella (OR = 0.998, 95% CI: 0.996-0.999, p = 0.046) have protective effects on CM. On the order hand, the genus Blautia (OR = 1.003, 95% CI: 1-1.006, p = 0.001) and phylum Cyanobacteria (OR = 1.002, 95% CI: 1-1.004, p = 0.04) are identified as risk factors for CM.

Conclusion

We comprehensively assessed the potential causal relationship between the gut microbiota and CM and identified associations between six gut microbiota and CM. Among these, four gut microbiota were identified as protective factors for CM, while two gut microbiota were identified as risk factors for CM. This study effectively established a causal relationship between the gut microbiota and CM, thereby providing valuable insights into the mechanistic pathways through which the microbiota impacts the progression of CM.

Exploring the regulatory mechanism of intestinal flora based on PD-1 receptor/ligand targeted cancer immunotherapy

Serving as a pivotal immunotherapeutic approach against tumors, anti-PD-1/PD-L1 therapy amplifies the immune cells' capability to eliminate tumors by obstructing the interaction between PD-1 and PD-L1. Research indicates that immune checkpoint inhibitors are effective when a patient's gut harbors unique beneficial bacteria. As such, it has further been revealed that the gut microbiome influences tumor development and the efficacy of cancer treatments, with metabolites produced by the microbiome playing a regulatory role in the antitumor efficacy of Immune checkpoint inhibitors(ICBs). This article discusses the mechanism of anti-PD-1 immunotherapy and the role of intestinal flora in immune regulation. This review focuses on the modulation of intestinal flora in the context of PD-1 immunotherapy, which may offer a new avenue for combination therapy in tumor immunotherapy.

Association between gut microbiota and pan-dermatological diseases: a bidirectional Mendelian randomization research

Background

Gut microbiota has been associated with dermatological problems in earlier observational studies. However, it is unclear whether gut microbiota has a causal function in dermatological diseases.

Methods

Thirteen dermatological diseases were the subject of bidirectional Mendelian randomization (MR) research aimed at identifying potential causal links between gut microbiota and these diseases. Summary statistics for the Genome-Wide Association Study (GWAS) of gut microbiota and dermatological diseases were obtained from public datasets. With the goal of evaluating the causal estimates, five acknowledged MR approaches were utilized along with multiple testing corrections, with inverse variance weighted (IVW) regression serving as the main methodology. Regarding the taxa that were causally linked with dermatological diseases in the forward MR analysis, reverse MR was performed. A series of sensitivity analyses were conducted to test the robustness of the causal estimates.

Results

The combined results of the five MR methods and sensitivity analysis showed 94 suggestive and five significant causal relationships. In particular, the genus Eubacterium_fissicatena_group increased the risk of developing psoriasis vulgaris (odds ratio [OR] = 1.32, pFDR = 4.36 × 10-3), family Bacteroidaceae (OR = 2.25, pFDR = 4.39 × 10-3), genus Allisonella (OR = 1.42, pFDR = 1.29 × 10-2), and genus Bacteroides (OR = 2.25, pFDR = 1.29 × 10-2) increased the risk of developing acne; and the genus Intestinibacter increased the risk of urticaria (OR = 1.30, pFDR = 9.13 × 10-3). A reverse MR study revealed insufficient evidence for a significant causal relationship. In addition, there was no discernible horizontal pleiotropy or heterogeneity.

Conclusion

This study provides novel insights into the causality of gut microbiota in dermatological diseases and therapeutic or preventive paradigms for cutaneous conditions.

Dissecting mechanisms of fecal microbiota transplantation efficacy in disease

Fecal microbiota transplantation (FMT) has emerged as an alternative or adjunct experimental therapy for microbiome-associated diseases following its success in the treatment of recurrent Clostridioides difficile infections (rCDIs). However, the mechanisms of action involved remain relatively unknown. The term 'dysbiosis' has been used to describe microbial imbalances in relation to disease, but this traditional definition fails to consider the complex cross-feeding networks that define the stability of the microbiome. Emerging research transitions toward the targeted restoration of microbial functional networks in treating different diseases. In this review, we explore potential mechanisms responsible for the efficacy of FMT and future therapeutic applications, while revisiting definitions of 'dysbiosis' in favor of functional network restoration in rCDI, inflammatory bowel diseases (IBDs), metabolic diseases, and cancer.

A gut microbial signature for combination immune checkpoint blockade across cancer types

Immune checkpoint blockade (ICB) targeting programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte protein 4 (CTLA-4) can induce remarkable, yet unpredictable, responses across a variety of cancers. Studies suggest that there is a relationship between a cancer patient's gut microbiota composition and clinical response to ICB; however, defining microbiome-based biomarkers that generalize across cohorts has been challenging. This may relate to previous efforts quantifying microbiota to species (or higher taxonomic rank) abundances, whereas microbial functions are often strain specific. Here, we performed deep shotgun metagenomic sequencing of baseline fecal samples from a unique, richly annotated phase 2 trial cohort of patients with diverse rare cancers treated with combination ICB (n = 106 discovery cohort). We demonstrate that strain-resolved microbial abundances improve machine learning predictions of ICB response and 12-month progression-free survival relative to models built using species-rank quantifications or comprehensive pretreatment clinical factors. Through a meta-analysis of gut metagenomes from a further six comparable studies (n = 364 validation cohort), we found cross-cancer (and cross-country) validity of strain-response signatures, but only when the training and test cohorts used concordant ICB regimens (anti-PD-1 monotherapy or combination anti-PD-1 plus anti-CTLA-4). This suggests that future development of gut microbiome diagnostics or therapeutics should be tailored according to ICB treatment regimen rather than according to cancer type.

Longitudinal gut microbiome changes in immune checkpoint blockade-treated advanced melanoma

Multiple clinical trials targeting the gut microbiome are being conducted to optimize treatment outcomes for immune checkpoint blockade (ICB). To improve the success of these interventions, understanding gut microbiome changes during ICB is urgently needed. Here through longitudinal microbiome profiling of 175 patients treated with ICB for advanced melanoma, we show that several microbial species-level genome bins (SGBs) and pathways exhibit distinct patterns from baseline in patients achieving progression-free survival (PFS) of 12 months or longer (PFS ≥12) versus patients with PFS shorter than 12 months (PFS <12). Out of 99 SGBs that could discriminate between these two groups, 20 were differentially abundant only at baseline, while 42 were differentially abundant only after treatment initiation. We identify five and four SGBs that had consistently higher abundances in patients with PFS ≥12 and <12 months, respectively. Constructing a log ratio of these SGBs, we find an association with overall survival. Finally, we find different microbial dynamics in different clinical contexts including the type of ICB regimen, development of immune-related adverse events and concomitant medication use. Insights into the longitudinal dynamics of the gut microbiome in association with host factors and treatment regimens will be critical for guiding rational microbiome-targeted therapies aimed at enhancing ICB efficacy.

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models

Every step in common microbiome profiling protocols has variable efficiency for each microbe. For example, different DNA extraction kits may have different efficiency for Gram-positive and -negative bacteria. These variable efficiencies, combined with technical variation, create strong processing biases, which impede the identification of signals that are reproducible across studies and the development of generalizable and biologically interpretable prediction models. "Batch-correction" methods have been used to alleviate these issues computationally with some success. However, many make strong parametric assumptions which do not necessarily apply to microbiome data or processing biases, or require the use of an outcome variable, which risks overfitting. Lastly and importantly, existing transformations used to correct microbiome data are largely non-interpretable, and could, for example, introduce values to features that were initially mostly zeros. Altogether, processing bias currently compromises our ability to glean robust and generalizable biological insights from microbiome data. Here, we present DEBIAS-M (Domain adaptation with phenotype Estimation and Batch Integration Across Studies of the Microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using benchmarks of HIV and colorectal cancer classification from gut microbiome data, and cervical neoplasia prediction from cervical microbiome data, we demonstrate that DEBIAS-M outperforms batch-correction methods commonly used in the field. Notably, we show that the inferred bias-correction factors are stable, interpretable, and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M allows for better modeling of microbiome data and identification of interpretable signals that are reproducible across studies.

Viroid-like colonists of human microbiomes

Here, we describe the "Obelisks," a previously unrecognised class of viroid-like elements that we first identified in human gut metatranscriptomic data. "Obelisks" share several properties: (i) apparently circular RNA ~1kb genome assemblies, (ii) predicted rod-like secondary structures encompassing the entire genome, and (iii) open reading frames coding for a novel protein superfamily, which we call the "Oblins". We find that Obelisks form their own distinct phylogenetic group with no detectable sequence or structural similarity to known biological agents. Further, Obelisks are prevalent in tested human microbiome metatranscriptomes with representatives detected in ~7% of analysed stool metatranscriptomes (29/440) and in ~50% of analysed oral metatranscriptomes (17/32). Obelisk compositions appear to differ between the anatomic sites and are capable of persisting in individuals, with continued presence over >300 days observed in one case. Large scale searches identified 29,959 Obelisks (clustered at 90% nucleotide identity), with examples from all seven continents and in diverse ecological niches. From this search, a subset of Obelisks are identified to code for Obelisk-specific variants of the hammerhead type-III self-cleaving ribozyme. Lastly, we identified one case of a bacterial species (Streptococcus sanguinis) in which a subset of defined laboratory strains harboured a specific Obelisk RNA population. As such, Obelisks comprise a class of diverse RNAs that have colonised, and gone unnoticed in, human, and global microbiomes.

Faecalibacterium prausnitzii as a potential Antiatherosclerotic microbe

BACKGROUND

The gut microbiota plays a crucial role in coronary artery disease (CAD) development, but limited attention has been given to the role of the microbiota in preventing this disease. This study aimed to identify key biomarkers using metagenomics and untargeted metabolomics and verify their associations with atherosclerosis.

METHODS

A total of 371 participants, including individuals with various CAD types and CAD-free controls, were enrolled. Subsequently, significant markers were identified in the stool samples through gut metagenomic sequencing and untargeted metabolomics. In vivo and in vitro experiments were performed to investigate the mechanisms underlying the association between these markers and atherosclerosis.

RESULTS

Faecal omics sequencing revealed that individuals with a substantial presence of Faecalibacterium prausnitzii had the lowest incidence of CAD across diverse CAD groups and control subjects. A random forest model confirmed the significant relationship between F. prausnitzii and CAD incidence. Notably, F. prausnitzii emerged as a robust, independent CAD predictor. Furthermore, our findings indicated the potential of the gut microbiota and gut metabolites to predict CAD occurrence and progression, potentially impacting amino acid and vitamin metabolism. F. prausnitzii mitigated inflammation and exhibited an antiatherosclerotic effect on ApoE-/- mice after gavage. This effect was attributed to reduced intestinal LPS synthesis and reinforced mechanical and mucosal barriers, leading to decreased plasma LPS levels and an antiatherosclerotic outcome.

CONCLUSIONS

Sequencing of the samples revealed a previously unknown link between specific gut microbiota and atherosclerosis. Treatment with F. prausnitzii may help prevent CAD by inhibiting atherosclerosis.

The role of intestinal flora on tumor immunotherapy: recent progress and treatment implications

Immunotherapy, specifically immune checkpoint inhibitors, has emerged as a promising approach for treating malignant tumors. The gut, housing approximately 70 % of the body's immune cells, is abundantly populated with gut bacteria that actively interact with the host's immune system. Different bacterial species within the intestinal flora are in a delicate equilibrium and mutually regulate each other. However, when this balance is disrupted, pathogenic microorganisms can dominate, adversely affecting the host's metabolism and immunity, ultimately promoting the development of disease. Emerging researches highlight the potential of interventions such as fecal microflora transplantation (FMT) to improve antitumor immune response and reduce the toxicity of immunotherapy. These remarkable findings suggest the major role of intestinal flora in the development of cancer immunotherapy and led us to the hypothesis that intestinal flora transplantation may be a new breakthrough in modifying immunotherapy side effects.

Predicting patient outcomes after treatment with immune checkpoint blockade: A review of biomarkers derived from diverse data modalities

Immune checkpoint blockade (ICB) therapy targeting cytotoxic T-lymphocyte-associated protein 4, programmed death 1, and programmed death ligand 1 has shown durable remission and clinical success across different cancer types. However, patient outcomes vary among disease indications. Studies have identified prognostic biomarkers associated with immunotherapy response and patient outcomes derived from diverse data types, including next-generation bulk and single-cell DNA, RNA, T cell and B cell receptor sequencing data, liquid biopsies, and clinical imaging. Owing to inter- and intra-tumor heterogeneity and the immune system's complexity, these biomarkers have diverse efficacy in clinical trials of ICB. Here, we review the genetic and genomic signatures and image features of ICB studies for pan-cancer applications and specific indications. We discuss the advantages and disadvantages of computational approaches for predicting immunotherapy effectiveness and patient outcomes. We also elucidate the challenges of immunotherapy prognostication and the discovery of novel immunotherapy targets.

Predictive Factors in Metastatic Melanoma Treated with Immune Checkpoint Inhibitors: From Clinical Practice to Future Perspective

The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.

Gut microbial structural variation associates with immune checkpoint inhibitor response

The gut microbiota may have an effect on the therapeutic resistance and toxicity of immune checkpoint inhibitors (ICIs). However, the associations between the highly variable genomes of gut bacteria and the effectiveness of ICIs remain unclear, despite the fact that merely a few gene mutations between similar bacterial strains may cause significant phenotypic variations. Here, using datasets from the gut microbiome of 996 patients from seven clinical trials, we systematically identify microbial genomic structural variants (SVs) using SGV-Finder. The associations between SVs and response, progression-free survival, overall survival, and immune-related adverse events are systematically explored by metagenome-wide association analysis and replicated in different cohorts. Associated SVs are located in multiple species, including Akkermansia muciniphila, Dorea formicigenerans, and Bacteroides caccae. We find genes that encode enzymes that participate in glucose metabolism be harbored in these associated regions. This work uncovers a nascent layer of gut microbiome heterogeneity that is correlated with hosts' prognosis following ICI treatment and represents an advance in our knowledge of the intricate relationships between microbiota and tumor immunotherapy.

Dissecting the role of the gut microbiome and fecal microbiota transplantation in radio- and immunotherapy treatment of colorectal cancer

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and poses a major burden on the human health worldwide. At the moment, treatment of CRC consists of surgery in combination with (neo)adjuvant chemotherapy and/or radiotherapy. More recently, immune checkpoint blockers (ICBs) have also been approved for CRC treatment. In addition, recent studies have shown that radiotherapy and ICBs act synergistically, with radiotherapy stimulating the immune system that is activated by ICBs. However, both treatments are also associated with severe toxicity and efficacy issues, which can lead to temporary or permanent discontinuation of these treatment programs. There's growing evidence pointing to the gut microbiome playing a role in these issues. Some microorganisms seem to contribute to radiotherapy-associated toxicity and hinder ICB efficacy, while others seem to reduce radiotherapy-associated toxicity or enhance ICB efficacy. Consequently, fecal microbiota transplantation (FMT) has been applied to reduce radio- and immunotherapy-related toxicity and enhance their efficacies. Here, we have reviewed the currently available preclinical and clinical data in CRC treatment, with a focus on how the gut microbiome influences radio- and immunotherapy toxicity and efficacy and if these treatments could benefit from FMT.

Multi-kingdom gut microbiota analyses define bacterial-fungal interplay and microbial markers of pan-cancer immunotherapy across cohorts

The effect of gut bacteria on the response to immune checkpoint inhibitors (ICIs) has been studied, but the relationship between fungi and ICI responses is not fully understood. Herein, 862 fecal metagenomes from 9 different cohorts were integrated for the identification of differentially abundant fungi and subsequent construction of random forest (RF) models to predict ICI responses. Fungal markers demonstrate excellent performance, with an average area under the curve (AUC) of 0.87. Their performance improves even further, reaching an average AUC of 0.89 when combined with bacterial markers. Higher enrichment of exhausted T cells is detected in responders, as predicted by fungal markers. Multi-kingdom network and functional analysis reveal that the fungus Schizosaccharomyces octosporus may ferment starch into short-chain fatty acids in responders. This study provides a fungal profile of the ICI response and the identification of multi-kingdom microbial markers with good performance that may improve the overall applicability of ICI therapy.

Computed Tomography-Based Quantitative Texture Analysis and Gut Microbial Community Signatures Predict Survival in Non-Small Cell Lung Cancer

This study aims to combine computed tomography (CT)-based texture analysis (QTA) and a microbiome-based biomarker signature to predict the overall survival (OS) of immune checkpoint inhibitor (ICI)-treated non-small cell lung cancer (NSCLC) patients by analyzing their CT scans (n = 129) and fecal microbiome (n = 58). One hundred and five continuous CT parameters were obtained, where principal component analysis (PCA) identified seven major components that explained 80% of the data variation. Shotgun metagenomics (MG) and ITS analysis were performed to reveal the abundance of bacterial and fungal species. The relative abundance of Bacteroides dorei and Parabacteroides distasonis was associated with long OS (>6 mo), whereas the bacteria Clostridium perfringens and Enterococcus faecium and the fungal taxa Cortinarius davemallochii, Helotiales, Chaetosphaeriales, and Tremellomycetes were associated with short OS (≤6 mo). Hymenoscyphus immutabilis and Clavulinopsis fusiformis were more abundant in patients with high (≥50%) PD-L1-expressing tumors, whereas Thelephoraceae and Lachnospiraceae bacterium were enriched in patients with ICI-related toxicities. An artificial intelligence (AI) approach based on extreme gradient boosting evaluated the associations between the outcomes and various clinicopathological parameters. AI identified MG signatures for patients with a favorable ICI response and high PD-L1 expression, with 84% and 79% accuracy, respectively. The combination of QTA parameters and MG had a positive predictive value of 90% for both therapeutic response and OS. According to our hypothesis, the QTA parameters and gut microbiome signatures can predict OS, the response to therapy, the PD-L1 expression, and toxicity in NSCLC patients treated with ICI, and a machine learning approach can combine these variables to create a reliable predictive model, as we suggest in this research.

The impact of the gut microbiome on tumor immunotherapy: from mechanism to application strategies

Immunotherapy is one of the fastest developing areas in the field of oncology. Many immunological treatment strategies for refractory tumors have been approved and marketed. Nevertheless, much clinical and preclinical experimental evidence has shown that the efficacy of immunotherapy in tumor treatment varies markedly among individuals. The commensal microbiome mainly colonizes the intestinal lumen in humans, is affected by a variety of factors and exhibits individual variation. Moreover, the gut is considered the largest immune organ of the body due to its influence on the immune system. In the last few decades, with the development of next-generation sequencing (NGS) techniques and in-depth research, the view that the gut microbiota intervenes in antitumor immunotherapy through the immune system has been gradually confirmed. Here, we review important studies published in recent years focusing on the influences of microbiota on immune system and the progression of malignancy. Furthermore, we discuss the mechanism by which microbiota affect tumor immunotherapy, including immune checkpoint blockade (ICB) and adoptive T-cell therapy (ACT), and strategies for modulating the microbial composition to facilitate the antitumor immune response. Finally, opportunity and some challenges are mentioned to enable a more systematic understanding of tumor treatment in the future and promote basic research and clinical application in related fields.

Modulation of gut microbiota: a novel approach to enhancing the effects of immune checkpoint inhibitors

Although immune checkpoint inhibitors (ICIs) have greatly improved the prognosis of some cancer patients, the majority still fail to respond adequately, and the available biomarkers cannot reliably predict drug efficacy. The gut microbiota has received widespread attention among the various intrinsic and extrinsic factors contributing to drug resistance. As an essential regulator of physiological function, the impact of gut microbiota on host immunity and response to cancer therapy is increasingly recognized. Several studies have demonstrated significant differences in gut microbiota between responders and nonresponders. The gut microbiota associated with better clinical outcomes is called 'favorable gut microbiota'. Significantly, interventions can alter the gut microbiota. By shifting the gut microbiota to the 'favorable' one through various modifications, preclinical and clinical studies have yielded more pronounced responses and better clinical outcomes when combined with ICIs treatment, providing novel approaches to improve the efficacy of cancer immunotherapy. These findings may be attributed to the effects of gut microbiota and its metabolites on the immune microenvironment and the systemic immune system, but the underlying mechanisms remain to be discovered. In this review, we summarize the clinical evidence that the gut microbiota is strongly associated with the outcomes of ICI treatment and describe the gut microbiota characteristics associated with better clinical outcomes. We then expand on the current prevalent modalities of gut microbiota regulation, provide a comprehensive overview of preclinical and clinical research advances in improving the therapeutic efficacy and prognosis of ICIs by modulating gut microbiota, and suggest fundamental questions we need to address and potential directions for future research expansion.

Gut Microbiome in Patients With Early-Stage and Late-Stage Melanoma

Importance

The gut microbiome modulates the immune system and responses to immunotherapy in patients with late-stage melanoma. It is unknown whether fecal microbiota profiles differ between healthy individuals and patients with melanoma or if microbiota profiles differ among patients with different stages of melanoma. Defining gut microbiota profiles in individuals without melanoma and those with early-stage and late-stage melanoma may reveal features associated with disease progression.

Objective

To characterize and compare gut microbiota profiles between healthy volunteers and patients with melanoma and between patients with early-stage and late-stage melanoma.

Design, Setting, and Participants

This single-site case-control study took place at an academic comprehensive cancer center. Fecal samples were collected from systemic treatment-naive patients with stage I to IV melanoma from June 1, 2015, to January 31, 2019, and from healthy volunteers from June 1, 2021, to January 31, 2022. Patients were followed up for disease recurrence until November 30, 2021.

Main Outcomes and Measures

Fecal microbiota was profiled by 16S ribosomal RNA sequencing. Clinical and pathologic characteristics, treatment, and disease recurrence were extracted from electronic medical records. Fecal microbiome diversity, taxonomic profiles and inferred functional profiles were compared between groups.

Results

A total of 228 participants were enrolled (126 men [55.3%]; median age, 59 [range, 21-90] years), including 49 volunteers without melanoma, 38 patients with early-stage melanoma (29 with stage I or melanoma in situ and 9 with stage II), and 141 with late-stage melanoma (66 with stage III and 75 with stage IV). Community differences were observed between patients with melanoma and volunteers. Patients with melanoma had a higher relative abundance of Fusobacterium compared with controls on univariate analysis (0.19% vs 0.003%; P < .001), but this association was attenuated when adjusted for covariates (log2 fold change of 5.18 vs controls; P = .09). Microbiomes were distinct between patients with early-stage and late-stage melanoma. Early-stage melanoma had a higher alpha diversity (Inverse Simpson Index 14.6 [IQR, 9.8-23.0] vs 10.8 [IQR, 7.2-16.8]; P = .003), and a higher abundance of the genus Roseburia on univariate analysis (2.4% vs 1.2%; P < .001) though statistical significance was lost with covariate adjustment (log2 fold change of 0.86 vs controls; P = .13). Multiple functional pathways were differentially enriched between groups. No associations were observed between the microbial taxa and disease recurrence in patients with stage III melanoma treated with adjuvant immunotherapy.

Conclusions and Relevance

The findings of this case-control study suggest that fecal microbiota profiles were significantly different among patients with melanoma and controls and between patients with early-stage and late-stage melanoma. Prospective investigations of the gut microbiome and changes that occur with disease progression may identify future microbial targets for intervention.

Inference of disease-associated microbial gene modules based on metagenomic and metatranscriptomic data

The identification of microbial characteristics associated with diseases is crucial for disease diagnosis and therapy. However, the presence of heterogeneity, high dimensionality, and large amounts of microbial data presents tremendous challenges in discovering key microbial features. In this paper, we present IDAM, a novel computational method for inferring disease-associated gene modules from metagenomic and metatranscriptomic data. This method integrates gene context conservation (uber-operons) and regulatory mechanisms (gene co-expression patterns) within a mathematical graph model to explore gene modules associated with specific diseases. It alleviates reliance on prior meta-data. We applied IDAM to publicly available datasets from inflammatory bowel disease, melanoma, type 1 diabetes mellitus, and irritable bowel syndrome. The results demonstrated the superior performance of IDAM in inferring disease-associated characteristics compared to existing popular tools. Furthermore, we showcased the high reproducibility of the gene modules inferred by IDAM using independent cohorts with inflammatory bowel disease. We believe that IDAM can be a highly advantageous method for exploring disease-associated microbial characteristics. The source code of IDAM is freely available at https://github.com/OSU-BMBL/IDAM, and the web server can be accessed at https://bmblx.bmi.osumc.edu/idam/.