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

Unravelling the prognostic and operative role of intratumoural microbiota in non-small cell lung cancer: Insights from 16S rRNA and RNA sequencing

BACKGROUND

Complex interrelationships between the microbiota and cancer have been identified by several studies. However, despite delineating microbial composition in non-small cell lung cancer (NSCLC), key pathogenic microbiota and their underlying mechanisms remain unclear.

METHODS

We performed 16S rRNA V3-V4 amplicon and transcriptome sequencing on cancerous and adjacent normal tissue samples from 30 patients with NSCLC, from which clinical characteristics and prognosis outcomes were collected. We used 16S rRNA sequencing to dissect microbial composition and perform prognosis correlations, and in conjunction with transcriptome sequencing, we determined potential mechanisms underpinning significant microbiota actions.

RESULTS

In comparing different sample types, we identified more pronounced beta diversity disparity between NSCLC, lung squamous cell carcinoma (LUSC) and corresponding paired normal tissues. Concurrently, LUSC and lung adenocarcinoma exhibited distinct microbial composition traits at genus levels. Subsequently, four phyla, five classes, nine orders, 17 families and 36 genera were filtered out and were related to prognosis outcomes. Intriguingly, a protective microbial cluster was identified encompassing nine genera associated with delayed disease recurrence, with functional analyses suggested that these microbiota predominantly exerted metabolism-related functions. Additionally, a harmful microbial cluster (HMC) was identified, including three genera. In this HMC and subsequent prognosis model analyses, harmful intratumoural microbiota were potentially implicated in infection, inflammation and immune regulation. Crucially, we identified a microbial genus, Peptococcus, which was as an independent, detrimental NSCLC prognostic factor and potentially impacted prognosis outcomes via tumour necrosis factor (TNF) signalling.

CONCLUSIONS

We identified a substantial connection between intratumoural microbiota and NSCLC prognosis outcomes. Protective microbiota primarily exerted metabolic functions, whereas harmful microbiota were mainly implicated in infection, inflammation and immune modulation. Furthermore, Peptococcus may be significant in adverse NSCLC prognoses and serve as a potential biomarker for patient management and cancer screening.

KEY POINTS

Four phyla, five classes, nine orders, 17 families and 36 genera have been found associated with NSCLC prognosis. We identified a protective microbial cluster associated with delayed recurrence and a harmful microbial cluster related to shorter survival and earlier recurrence. We identified Peptococcus as an independent, detrimental prognostic factor for NSCLC, potentially impacting prognosis via TNF signalling.

Gut microbiota and metabolites associated with immunotherapy efficacy in extensive-stage small cell lung cancer: a pilot study

Background

The gut microbiota and its associated metabolites play a critical role in shaping the systemic immune response and influencing the efficacy of immunotherapy. In this study, patients with extensive-stage small cell lung cancer (ES-SCLC) were included to explore the correlation between gut microbiota and metabolites and immunotherapy efficacy in patients with ES-SCLC.

Methods

Pre- and post-treatment, we collected stool samples from 49 ES-SCLC patients treated with an anti-programmed death-ligand 1 (PD-L1) antibody. We then applied 16S ribosomal RNA (rRNA) sequencing and liquid chromatography-mass spectrometry (LC-MS) non-targeted metabolomics technology. Subsequently, the gut microbiota and metabolites were identified and classified.

Results

The results showed no statistical difference in gut microbiota alpha and beta diversity between the responder (R) and non-responder (NR) patients at baseline. However, the alpha diversity of the R patients was significantly higher than that of the NR patients after treatment. There were also differences in the microbiome composition at the baseline and post-treatment. Notably, after treatment, Faecalibacterium, Clostridium_sensu_stricto_1, and [Ruminococcus]_torques were enriched in the R group, while Dubosiella, coriobacteriaceae_UCG-002 was enriched in the NR group. The non-targeted metabolomics results also indicated that short-chain fatty acids (SCFAs) were up-regulated in the R group after treatment. More, differential metabolites were enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including the PD-L1 expression and programmed death 1 (PD-1) checkpoint pathway in cancer.

Conclusions

These findings are anticipated to provide novel markers for predicting the efficacy of immune checkpoint inhibitors (ICIs) in patients with ES-SCLC, and offer new directions for further research on molecular mechanisms.

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

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

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

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

Alterations of gut microbiota and its metabolomics in children with 6PPDQ, PBDE, PCB, and metal(loid) exposure

The composition and metabolites of the gut microbiota can be altered by environmental pollutants. However, the effect of co-exposure to multiple pollutants on the human gut microbiota has not been sufficiently studied. In this study, gut microorganisms and their metabolites were compared between 33 children from Guiyu, an e-waste dismantling and recycling area, and 34 children from Haojiang, a healthy environment. The exposure level was assessed by estimating the daily intake (EDI) of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), 6PPD-quinone (6PPDQ), and metal(loid)s in kindergarten dust. Significant correlations were found between the EDIs of 6PPDQ, BDE28, PCB52, Ni, Cu, and the composition of gut microbiota and specific metabolites. The Bayesian kernel machine regression model showed negative correlations between the EDIs of five pollutants (6PPDQ, BDE28, PCB52, Ni, and Cu) and the composition of gut microbiota. The EDIs of these five pollutants were positively correlated with the levels of the metabolite 2,4-diaminobutyric acid, while negatively correlated with the levels of d-erythro-sphingosine and d-threitol. Our study suggests that exposure to 6PPDQ, BDE28, PCB52, Ni, and Cu in kindergarten dust is associated with alterations in the composition and metabolites of the gut microbiota. These alterations may be associated with children's health.

Microbes for lung cancer detection: feasibility and limitations

As the second most common cancer in the world, the development of lung cancer is closely related to factors such as heredity, environmental exposure, and lung microenvironment, etc. Early screening and diagnosis of lung cancer can be helpful for the treatment of patients. Currently, CT screening and histopathologic biopsy are widely used in the clinical detection of lung cancer, but they have many disadvantages such as false positives and invasive operations. Microbes are another genome of the human body, which has recently been shown to be closely related to chronic inflammatory, metabolic processes in the host. At the same time, they are important players in cancer development, progression, treatment, and prognosis. The use of microbes for cancer therapy has been extensively studied, however, the diagnostic role of microbes is still unclear. This review aims to summarize recent research on using microbes for lung cancer detection and present the current shortcomings of microbes in collection and detection. Finally, it also looks ahead to the clinical benefits that may accrue to patients in the future about screening and early detection.

Gut microbiome affects the response to immunotherapy in non-small cell lung cancer

BACKGROUND

Immunotherapy has revolutionized cancer treatment. Recent studies have suggested that the efficacy of immunotherapy can be further enhanced by the influence of gut microbiota. In this study, we aimed to investigate the impact of bacteria on the effectiveness of cancer immunotherapy by combining analysis of clinical samples with validation in animal models.

METHODS

In order to characterize the diversity and composition of microbiota and its relationship with response to immune checkpoint inhibitors (ICIs), 16S ribosomal RNA (rRNA) and GC-MS sequencing was performed on 71 stool samples from patients with advanced non-small cell lung cancer (NSCLC) prior to treatment with immune checkpoint blockade (ICB). Furthermore, fecal microbiota transplantation (FMT) was performed from different patients into mice and a subcutaneous tumor model established using the Lewis lung cancer cell line to evaluate the therapeutic effect of PD-1 on mice with varying gut microbiota.

RESULTS

The results demonstrated a significant association between elevated gut microbiota diversity and response to treatment with ICIs, p < 0.05. Faecalibacterium was markedly increased in the gut microbiota of responders (R), accompanied by increased short-chain fatty acid (SCFA) levels, especially butanoic acid, acetic acid and hexanoic acid, p < 0.05. Additionally, FMT from R and nonresponders (NR) could promote an anticancer effect and reduce the expression of Ki-67 cells in tumors in mice, p < 0.05. Moreover, R and NR FMT did not alter PD-L1 expression in the tumor tissues of mice, p > 0.05. The diversity of gut microbiota consistently correlated with an optimistic prognosis in NSCLC patients with immunotherapy, which could be functionally mediated by SCFAs.

CONCLUSION

The findings of the present study indicated that the diversity of gut microbiota and SCFAs is related to the efficacy of immunotherapy. FMT can effectively delay tumor progression, and enhance the effect of immunotherapy, thus providing evidence for improving the efficacy of immunotherapy in NSCLC patients.

The implication of microbiome in lungs cancer: mechanisms and strategies of cancer growth, diagnosis and therapy

Available evidence illustrates that microbiome is a promising target for the study of growth, diagnosis and therapy of various types of cancer. Lung cancer is a leading cause of cancer death worldwide. The relationship of microbiota and their products with diverse pathologic conditions has been getting large attention. The novel research suggests that the microbiome plays an important role in the growth and progression of lung cancer. The lung microbiome plays a crucial role in maintaining mucosal immunity and synchronizing the stability between tolerance and inflammation. Alteration in microbiome is identified as a critical player in the progression of lung cancer and negatively impacts the patient. Studies suggest that healthy microbiome is essential for effective therapy. Various clinical trials and research are focusing on enhancing the treatment efficacy by altering the microbiome. The regulation of microbiota will provide innovative and promising treatment strategies for the maintenance of host homeostasis and the prevention of lung cancer in lung cancer patients. In the current review article, we presented the latest progress about the involvement of microbiome in the growth and diagnosis of lung cancer. Furthermore, we also assessed the therapeutic status of the microbiome for the management and treatment of lung cancer.

Developing technologies and areas of interest in lung cancer screening adjuncts

Lung cancer remains the leading cause of cancer mortality. Screening guidelines have been implemented in the past decade to aid in earlier detection of at-risk groups. Nevertheless, computed tomography (CT) scans, the principal screening modality in use today, are still low yield, with 3.6% of lung cancer confirmed amongst 39.1% of lesions detected over a 3-year period. They also carry relatively high false positive rates, between 9% and 27%, which can bear unnecessary financial and emotional costs to patients. As such, research efforts have been dedicated to the development of lung cancer screening adjuncts to improve detection reliability. We herein review several emerging technologies in this specific arena and their efficacy. These include plasma markers (microDNA, DNA methylation, and tumor-associated antibodies), breath/sputum biomarkers [volatile organic compounds (VOCs) and exhaled breath condensate (EBC)], proteomics, metabolomics, and machine learning, such as radiomics technology. We find that, across the board, they offer promising results in terms of non-invasive diagnostics, genetic sequencing for higher-risk individuals, and accessibility for a diverse cohort of patients. While these screening adjuncts are unlikely to completely replace the current standard of care at the moment, continued research into these technologies is crucial to improve and personalize the identification, treatment, and outcome of lung cancer patients in the near future.

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

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

Changes in Intestinal Flora and Serum Metabolites Pre- and Post-Antitumor Drug Therapy in Patients with Non-Small Cell Lung Cancer

OBJECTIVE

this study aimed to identify the relationships between gut microbiota, metabolism, and non-small cell lung cancer (NSCLC) treatment outcomes, which are presently unclear.

METHODS

in this single-center prospective cohort study, we investigated changes in the gut microbiota and serum metabolite profile in 60 patients with NSCLC after four cycles of anticancer therapy.

RESULTS

The microbial landscape of the gut exhibited a surge in Proteobacteria and Verrucomicrobiota populations, alongside a decline in Firmicutes, Actinobacteriota, and Bacteroidota. Furthermore, a significant shift in the prevalence of certain bacterial genera was noted, with an increase in Escherichia/Shigella and Klebsiella, contrasted by a reduction in Bifidobacterium. Metabolomic analysis uncovered significant changes in lipid abundances, with certain metabolic pathways markedly altered post-treatment. Correlation assessments identified strong links between certain gut microbial genera and serum metabolite concentrations. Despite these findings, a subgroup analysis delineating patient responses to therapy revealed no significant shifts in the gut microbiome's composition after four cycles of treatment.

CONCLUSIONS

This study emphasizes the critical role of gut microbiota changes in NSCLC patients during anticancer treatment. These insights pave the way for managing treatment complications and inform future research to improve patient care by understanding and addressing these microbiota changes.

Gut-lung axis: role of the gut microbiota in non-small cell lung cancer immunotherapy

Immunotherapy for non-small cell lung cancer (NSCLC) has advanced considerably over the past two decades. In particular, immune checkpoint inhibitors are widely used for treating NSCLC. However, the overall cure and survival rates of patients with NSCLC remain low. Therefore, continuous investigation into complementary treatments is necessary to expand the clinical advantages of immunotherapy to a larger cohort of patients with NSCLC. Recently, the distinctive role of the gut microbiota (GM) in the initiation, progression, and dissemination of cancer has attracted increasing attention. Emerging evidence indicates a close relationship between the gut and lungs, known as the gut-lung axis (GLA). In this review, we aim to provide a comprehensive summary of the current knowledge regarding the connection between the GM and the outcomes of immunotherapy in NSCLC, with particular focus on the recent understanding of GLA. Overall, promising GM-based therapeutic strategies have been observed to improve the effectiveness or reduce the toxicity of immunotherapy in patients with NSCLC, thus advancing the utilization of microbiota precision medicine.

Crotonis Fructus-induced gut microbiota and serum metabolic disorders in rats

Crotonis Fructus (CF), a poisonous traditional laxative, has been used to treat constipation, edema, ascites, and inflammation for more than 2000 years. However, CF possesses toxicity and its toxic mechanism is still unclear. Thus, this research explored the deleterious impacts and underlying mechanisms of CF by evaluating alterations in gut microbiota composition and metabolites. High-throughput sequencing was employed on the 16S rDNA gene to explore the intestinal flora. The untargeted metabolomics method was utilized for evaluating serum metabolomics analysis. The results showed that CF could induce obvious hepatic and gastrointestinal damage by histopathologic morphology of the liver, stomach, duodenum, and colon. According to 16S rDNA sequencing, CF can cause gut microbiota disturbance in rats, and the abundance of opportunistic pathogens such as Clostridia_UCG_014_unclassified increased significantly, while the levels of beneficial bacterial Lactobacillus remarkably declined after CF treatment. Additionally, metabolomics analysis demonstrated that CF may induce toxicity by disrupting the glycerophospholipid metabolism pathway and metabolites such as phosphatidylcholine and phosphatidylethanolamine. Moreover, a correlation study revealed the link between intestinal flora, serum metabolites, and toxicity-related biochemical markers. The results provide a new idea for the research and clinical application of toxic traditional medicine. KEY POINTS: • Crotonis Fructus could affect the gut flora and serum metabolic disruption in SD rats. • Crotonis Fructus could promote the proliferation of harmful bacteria and inhibit beneficial bacteria. • Glycerophospholipid metabolism was disturbed by Crotonis Fructus.

Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer

Lung cancer is referred to as the second most common cancer worldwide and is mainly associated with complex diagnostics and the absence of personalized therapy. Metabolomics may provide significant insights into the improvement of lung cancer diagnostics through identification of the specific biomarkers or biomarker panels that characterize the pathological state of the patient. We performed targeted metabolomic profiling of plasma samples from individuals with non-small cell lung cancer (NSLC, n = 100) and individuals without any cancer or chronic pathologies (n = 100) to identify the relationship between plasma endogenous metabolites and NSLC by means of modern comprehensive bioinformatics tools, including univariate analysis, multivariate analysis, partial correlation network analysis and machine learning. Through the comparison of metabolomic profiles of patients with NSCLC and noncancer individuals, we identified significant alterations in the concentration levels of metabolites mainly related to tryptophan metabolism, the TCA cycle, the urea cycle and lipid metabolism. Additionally, partial correlation network analysis revealed new ratios of the metabolites that significantly distinguished the considered groups of participants. Using the identified significantly altered metabolites and their ratios, we developed a machine learning classification model with an ROC AUC value equal to 0.96. The developed machine learning lung cancer model may serve as a prototype of the approach for the in-time diagnostics of lung cancer that in the future may be introduced in routine clinical use. Overall, we have demonstrated that the combination of metabolomics and up-to-date bioinformatics can be used as a potential tool for proper diagnostics of patients with NSCLC.