A faecal microbiota signature with high specificity for pancreatic cancer

Upregulation of Lactobacillus spp. in gut microbiota as a novel mechanism for environmental eustress-induced anti-pancreatic cancer effects

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with limited effective treatment options. Emerging evidence links enriched environment (EE)-induced eustress to PDAC inhibition. However, the underlying mechanisms remain unclear. In this study, we explored the role of gut microbiota in PDAC-suppressive effects of EE. We demonstrated that depletion of gut microbiota with antibiotics abolished EE-induced tumor suppression, while fecal microbiota transplantation (FMT) from EE mice significantly inhibited tumor growth in both subcutaneous and orthotopic PDAC models housed in standard environment. 16S rRNA sequencing revealed that EE enhanced gut microbiota diversity and selectively enriched probiotic Lactobacillus, particularly L. reuteri. Treatment with L. reuteri significantly suppressed PDAC tumor growth and increased natural killer (NK) cell infiltration into the tumor microenvironment. Depletion of NK cells alleviated the anti-tumor effects of L. reuteri, underscoring the essential role of NK cell-mediated immunity in anti-tumor response. Clinical analysis of PDAC patients showed that higher fecal Lactobacillus abundance correlated with improved progression-free and overall survival, further supporting the therapeutic potential of L. reuteri in PDAC. Overall, this study identifies gut microbiota as a systemic regulator of PDAC under psychological stress. Supplementation of psychobiotic Lactobacillus may offer a novel therapeutic strategy for PDAC.

A novel framework for assessing causal effect of microbiome on health: long-term antibiotic usage as an instrument

Assessing causality is undoubtedly one of the key questions in microbiome studies for the upcoming years. Since randomized trials in human subjects are often unethical or difficult to pursue, analytical methods to derive causal effects from observational data deserve attention. As simple covariate adjustment is not likely to account for all potential confounders, the idea of instrumental variable (IV) analysis is worth exploiting. Here we propose a novel framework of antibiotic instrumental variable regression (AB-IVR) for estimating the causal relationships between microbiome and various diseases. We rely on the recent studies showing that antibiotic treatment has a cumulative long-term effect on the microbiome, resulting in individuals with higher antibiotic usage to have a more perturbed microbiome. We apply the AB-IVR method on the Estonian Biobank data and show that the microbiome has a causal role in numerous diseases including migraine, depression and irritable bowel syndrome. We show with a plethora of sensitivity analyses that the identified causal effects are robust and propose ways for further methodological developments.

From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction

Pancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, characterized by late-stage diagnosis and limited therapeutic options. Risk stratification has traditionally been performed using epidemiological studies and genetic analyses, through which key risk factors, including smoking, diabetes, chronic pancreatitis, and inherited predispositions, have been identified. However, the multifactorial nature of PDAC has often been insufficiently addressed by these methods, leading to limited precision in individualized risk assessments. Advances in artificial intelligence (AI) have been proposed as a transformative approach, allowing the integration of diverse datasets-spanning genetic, clinical, lifestyle, and imaging data into dynamic models capable of uncovering novel interactions and risk profiles. In this review, the evolution of PDAC risk stratification is explored, with classical epidemiological frameworks compared to AI-driven methodologies. Genetic insights, including genome-wide association studies and polygenic risk scores, are discussed, alongside AI models such as machine learning, radiomics, and deep learning. Strengths and limitations of these approaches are evaluated, with challenges in clinical translation, such as data scarcity, model interpretability, and external validation, addressed. Finally, future directions are proposed for combining classical and AI-driven methodologies to develop scalable, personalized predictive tools for PDAC, with the goal of improving early detection and patient outcomes.

The relationship of the microbiome, associated metabolites and the gut barrier with pancreatic cancer

Pancreatic cancers have high mortality and rising incidence rates which may be related to unhealthy western-type dietary and lifestyle patterns as well as increasing body weights and obesity rates. Recent data also suggest a role for the gut microbiome in the development of pancreatic cancer. Here, we review the experimental and observational evidence for the roles of the oral, gut and intratumoural microbiomes, impaired gut barrier function and exposure to inflammatory compounds as well as metabolic dysfunction as contributors to pancreatic disease with a focus on pancreatic ductal adenocarcinoma (PDAC) initiation and progression. We also highlight some emerging gut microbiome editing techniques currently being investigated in the context of pancreatic disease. Notably, while the gut microbiome is significantly altered in PDAC and its precursor diseases, its utility as a diagnostic and prognostic tool is hindered by a lack of reproducibility and the potential for reverse causality in case-control cohorts. Future research should emphasise longitudinal and mechanistic studies as well as integrating lifestyle exposure and multi-omics data to unravel complex host-microbiome interactions. This will allow for deeper aetiologic and mechanistic insights that can inform treatments and guide public health recommendations.

Biomarkers, omics and artificial intelligence for early detection of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is frequently diagnosed in its late stages when treatment options are limited. Unlike other common cancers, there are no population-wide screening programmes for PDAC. Thus, early disease detection, although urgently needed, remains elusive. Individuals in certain high-risk groups are, however, offered screening or surveillance. Here we explore advances in understanding high-risk groups for PDAC and efforts to implement biomarker-driven detection of PDAC in these groups. We review current approaches to early detection biomarker development and the use of artificial intelligence as applied to electronic health records (EHRs) and social media. Finally, we address the cost-effectiveness of applying biomarker strategies for early detection of PDAC.

Inducible, but not constitutive, pancreatic REG/Reg isoforms are regulated by intestinal microbiota and pancreatic diseases

The REG/Reg gene locus encodes a conserved family of potent antimicrobial but also pancreatitis-associated proteins. Here we investigated whether REG/Reg family members differ in their baseline expression levels and abilities to be regulated in the pancreas and gut upon perturbations. We found, in humans and mice, the pancreas and gut differed in REG/Reg isoform levels and preferences, with the duodenum most resembling the pancreas. Pancreatic acinar cells and intestinal enterocytes were the dominant REG producers. Intestinal symbiotic microbes regulated the expression of the same, select Reg members in gut and pancreas. These Reg members had the most STAT3-binding sites close to the transcription start sites and were partially IL-22 dependent. We thus categorized them as "inducible" and others as "constitutive". Indeed, in pancreatic ductal adenocarcinoma and pancreatitis models, only inducible Reg members were upregulated in the pancreas. While intestinal Reg expression remained unchanged upon pancreatic perturbation, pancreatitis altered the microbial composition of the duodenum and feces shortly after disease onset. Our study reveals differential usage and regulation of REG/Reg isoforms as a mechanism for tissue-specific innate immunity, highlights the intimate connection of pancreas and duodenum, and implies a gut-to-pancreas communication axis resulting in a coordinated Reg response.

Microbiota as a state-of-the-art approach in precision medicine for pancreatic cancer management: A comprehensive systematic review

Emerging evidence suggests that harnessing the microbiome holds promise for innovative diagnostic and therapeutic strategies in the management of pancreatic cancer (PC). This study aims to systematically summarize the microbial markers associated with PC and assess their potential application in clinical outcome. Forty-one studies were included to assess the associations between microbial markers and PC. Among these, 13 were developed prediction models related to the microbiome in which the highest diagnostic and prognostic model belong to blood and intratumor markers, respectively. Notably, findings that utilize microbiotas from various body sites were elucidated, demonstrating their importance as unique signatures in biomarker discovery for diverse clinical applications. This review provides unique perspectives on overcoming challenges in PC by highlighting potential microbial-related markers as non-invasive approaches. Further clinical studies should evaluate the utility and accuracy of key indicators in the microbiome as a personalized tool for managing PC.

The exposome and pancreatic cancer, lifestyle and environmental risk factors for PDAC

Pancreatic cancer (PC), particularly pancreatic ductal adenocarcinoma (PDAC), is a significant global health issue with high mortality rates. PDAC, though only 3 % of cancer diagnoses, causes 7 % of cancer deaths due to its severity and asymptomatic early stages. Risk factors include lifestyle choices, environmental exposures, and genetic predispositions. Conditions like new-onset type 2 diabetes and chronic pancreatitis also contribute significantly. Modifiable risk factors include smoking, alcohol consumption, non-alcoholic fatty pancreatic disease (NAFPD), and obesity. Smoking and heavy alcohol consumption increase PC risk, while NAFPD and obesity, particularly central adiposity, contribute through chronic inflammation and insulin resistance. Refined sugar and sugar-sweetened beverages (SSBs) are also linked to increased PC risk, especially among younger individuals. Hormonal treatments and medications like statins, aspirin, and metformin have mixed results on PC risk, with some showing protective effects. The gut microbiome influences PC through the gut-pancreas axis, with disruptions leading to inflammation and carcinogenesis. Exposure to toxic substances, including heavy metals and chemicals, is associated with increased PC risk. Glycome changes, such as abnormal glycosylation patterns, are significant in PDAC development and offer potential for early diagnosis. Interactions between environmental and genetic factors are crucial in PDAC susceptibility. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) linked to PDAC, but gene-environment interactions remain largely unexplored. Future research should focus on polygenic risk scores (PRS) and large-scale studies to better understand these interactions and their impact on PDAC risk.

Oral microbiome-derived biomarkers for non-invasive diagnosis of head and neck squamous cell carcinoma

Mounting evidence suggests that sustained microbial dysbiosis is associated with the development of multiple cancers, while the species-level bacterial taxa and metabolic dysfunction of oral microbiome in patients with head and neck squamous cell carcinoma (HNSCC) remains unclear. In this cross-sectional study, comprehensive metagenomic and 16S rRNA amplicon sequencing analyses of oral swab samples from 172 patients were performed. Unsupervised clustering algorithms of relative microbial abundance profiles revealed three distinctive microbiome clusters. Based on the metagenomic and 16S rRNA amplicon sequencing data, machine learning-based methods were used to construct the HNSCC diagnostic classifier, which exhibited high area under the curve values of 0.78-0.89. Our study provided the first exhaustive metagenomic and 16S rRNA amplicon sequencing analyses to date, revealing that microbial-metabolic dysbiosis is a potential risk factor for HNSCC progression and therefore providing a robust theoretical basis for potential diagnostic and therapeutic strategies for HNSCC patients.

[Generation X and millennials are at greater cancer risk than previous generations: Possible causes and implications]

The incidence of early-onset malignancy (EOM) diagnosed under the age of 50 has been increasing worldwide. In the USA, Generation X and the millennials are up to 2 times more likely to develop 17 of the 34 most common cancers than the baby boomers at any given age. Globally, the incidence of EOM increased by 79.1% between 1990 and 2019. Early-life exposure may be linked with EOM development and may forecast a greater disease burden in the future. Possible causes and consequences are discussed with regards to cancer prevention.

Gut microbiota in cancer initiation, development and therapy

Cancer has long been associated with genetic and environmental factors, but recent studies reveal the important role of gut microbiota in its initiation and progression. Around 13% of cancers are linked to infectious agents, highlighting the need to identify the specific microorganisms involved. Gut microbiota can either promote or inhibit cancer growth by influencing oncogenic signaling pathways and altering immune responses. Dysbiosis can lead to cancer, while certain probiotics and their metabolites may help reestablish micro-ecological balance and improve anti-tumor immune responses. Research into targeted approaches that enhance therapy with probiotics is promising. However, the effects of probiotics in humans are complex and not yet fully understood. Additionally, methods to counteract harmful bacteria are still in development. Early clinical trials also indicate that modifying gut microbiota may help manage side effects of cancer treatments. Ongoing research is crucial to understand better how gut microbiota can be used to improve cancer prevention and treatment outcomes.

A comprehensive multi-omics analysis uncovers the associations between gut microbiota and pancreatic cancer

Pancreatic cancer is one of the most lethal malignant neoplasms. Pancreatic cancer is related to gut microbiota, but the associations between its treatment and microbial abundance as well as genetic variations remain unclear. In this study, we collected fecal samples from 58 pancreatic cancer patients including 43 pancreatic ductal adenocarcinoma (PDAC) and 15 non-PDAC, and 40 healthy controls, and shotgun metagenomic sequencing and untargeted metabolome analysis were conducted. PDAC patients were divided into five groups according to treatment and tumor location, including treatment-naive (UT), chemotherapy (CT), surgery combined with chemotherapy (SCT), Head, and body/tail (Tail) groups. Multivariate association analysis revealed that both CT and SCT were associated with increased abundance of Lactobacillus gasseri and Streptococcus equinus. The microbial single nucleotide polymorphisms (SNPs) densities of Streptococcus salivarius, Streptococcus vestibularis and Streptococcus thermophilus were positively associated with CT, while Lachnospiraceae bacterium 2_1_58FAA was positively associated with Head group. Compared with Tail group, the Head group showed positive associations with opportunistic pathogens, such as Escherichia coli, Shigella sonnei and Shigella flexneri. We assembled 424 medium-quality non-redundant metagenome-assembled genomes (nrMAGs) and 276 high-quality nrMAGs. In CT group, indole-3-acetic acid, capsaicin, sinigrin, chenodeoxycholic acid, and glycerol-3-phosphate were increased, and the accuracy of the model based on fecal metabolites reached 0.77 in distinguishing healthy controls and patients. This study identifies the associations between pancreatic cancer treatment and gut microbiota as well as its metabolites, reveals bacterial SNPs are related to tumor location, and extends our knowledge of gut microbiota and pancreatic cancer.

Microbiome Landscape and Association with Response to Immune Checkpoint Inhibitors in Advanced Solid Tumors: A SCRUM-Japan MONSTAR-SCREEN Study

Although the gut microbiome is associated with cancer development and progression, little is known about the effects of the gut microbiome landscape and the efficacy of immune checkpoint inhibitors (ICI) across cancer types. We investigated the association between the microbiome, clinical features, and ICI efficacy across cancer types in a large nationwide screening project for solid tumors. Among 2,180 patients with advanced solid tumors enrolled in the SCRUM-Japan MONSTAR-SCREEN between October 2019 and September 2021, in the chemotherapy-naïve cohort (n = 817), a high prevalence of oral bacteria was observed in patients using proton pump inhibitors (PPI) and those with upper gastrointestinal cancers, particularly postoperative patients with gastric or pancreatic cancer. Among patients treated with ICIs (n = 333), a high abundance of sequence variants in the gut microbiome was not significantly associated with ICI efficacy across cancer types (HR = 0.94; 95% confidence interval, 0.73-1.21). However, high oral bacteria in feces significantly correlated with a shorter progression-free survival compared with low oral bacteria (median, 4.34 vs. 6.97 months; HR = 1.38; 95% confidence interval, 1.07-1.78). Notably, in patients using PPIs, a higher proportion of oral bacteria influenced progression-free survival outcomes of ICI treatment (median, 3.15 vs. 2.04 months; P = 0.08), unlike in PPI nonusers (median, 7.13 vs. 5.55 months; P = 0.74). This study of the gut microbiome has unveiled significant insights into its landscape and potential impact on ICI efficacy. It highlights that the abundance of oral bacteria in feces may play a critical role in diminishing ICI efficacy among patients using PPIs.

SIGNIFICANCE

As part of the MONSTAR-SCREEN, a prospective nationwide project for patients with solid tumors, we found that although gut microbiome diversity does not consistently predict ICI efficacy across cancer types, a high level of oral bacteria in the gut is linked to reduced ICI effectiveness, especially in patients using PPIs. These findings highlight the potential clinical impact of microbiome variations on cancer treatment outcomes.

Fecal profiling reveals a common microbial signature for pancreatic cancer in Finnish and Iranian cohorts

BACKGROUND

Pancreatic cancer (PC) presents a significant challenge in oncology because of its late-stage diagnosis and limited treatment options. The inadequacy of current screening methods has prompted investigations into stool-based assays and microbial classifiers as potential early detection markers. The gut microbiota composition of PC patients may be influenced by population differences, thereby impacting the accuracy of disease prediction. However, comprehensive profiling of the PC gut microbiota and analysis of these cofactors remain limited. Therefore, we analyzed the stool microbiota of 33 Finnish and 50 Iranian PC patients along with 35 Finnish and 34 Iranian healthy controls using 16S rRNA gene sequencing. We assessed similarities and differences of PC gut microbiota in both populations while considering sociocultural impacts and generated a statistical model for disease prediction based on microbial classifiers. Our aim was to expand the current understanding of the PC gut microbiota, discuss the impact of population differences, and contribute to the development of early PC diagnosis through microbial biomarkers.

RESULTS

Compared with healthy controls, PC patients presented reduced microbial diversity, with discernible microbial profiles influenced by factors such as ethnicity, demographics, and lifestyle. PC was marked by significantly higher abundances of facultative pathogens including Enterobacteriaceae, Enterococcaceae, and Fusobacteriaceae, and significantly lower abundances of beneficial bacteria. In particular, bacteria belonging to the Clostridia class, such as butyrate-producing Lachnospiraceae, Butyricicoccaceae, and Ruminococcaceae, were depleted. A microbial classifier for the prediction of pancreatic ductal adenocarcinoma (PDAC) was developed in the Iranian cohort and evaluated in the Finnish cohort, where it yielded a respectable AUC of 0.88 (95% CI 0.78, 0.97).

CONCLUSIONS

This study highlights the potential of gut microbes as biomarkers for noninvasive PC screening and the development of targeted therapies, emphasizing the need for further research to validate these findings in diverse populations. A comprehensive understanding of the role of the gut microbiome in PC could significantly enhance early detection efforts and improve patient outcomes.

Gut microbiota characteristics in neonatal respiratory distress syndrome and the therapeutic potential of probiotics in recovery

Background

Neonatal Respiratory Distress Syndrome (NRDS) is a common and severe respiratory disorder in neonates, particularly among preterm infants (PTIs), and is often associated with hypoxemia and multiple organ dysfunction. This study aims to investigate the gut microbiota characteristics in NRDS and the potential regulatory role of probiotics in restoring gut microbiota dysbiosis.

Methods

This study enrolled 55 PTIs diagnosed with NRDS and 26 preterm infants without NRDS. The NRDS group was classified into two groups based on treatment: an antibiotic-only group (TA group, N = 30) and an antibiotic plus probiotics group (TB group, N = 25). Fecal samples were collected within 48 h of birth and again after recovery, for 16S rRNA sequencing.

Results

The study revealed that the gut microbiota diversity in the NRDS group was significantly greater than in the non-NRDS group, and the microbiota composition in the NRDS group was closely associated with multiple clinical indicators, including Apgar score, pH, PaO2, and PaCO2. Notably, the abundance of bacteria such as Muribaculaceae Incertae Sedis, Rhodococcus, and Corynebacterium was significantly higher in the NRDS group, which may contribute to disease progression. ROC analysis suggested that gut microbiota could serve as potential biomarkers for diagnosing NRDS. Probiotic intervention notably restored the gut microbiota structure in the NRDS group, particularly by enhancing the abundance of beneficial genera such as Streptococcus, Bifidobacterium, and Clostridium. This intervention reduced the microbiota disparity between the NRDS group and normal one-month-old children, thereby slowing disease progression.

Conclusion

This study demonstrated that the NRDS displayed an increase in gut microbiota diversity and alterations in specific bacterial populations, both of which were closely correlated with clinical data. Probiotic treatment aids in restoring the disrupted gut microbiota in NRDS infants, promoting disease recovery, and providing new biomarkers and clinical strategies for managing NRDS.

From Microbiome to Malignancy: Unveiling the Gut Microbiome Dynamics in Pancreatic Carcinogenesis

Pancreatic cancer is a major cause of cancer-associated mortality globally, characterized by a poor prognosis and limited therapeutic response. The current approach for treating pancreatic cancer involves locoregional control with surgical resection and systemic therapy in the form of cytotoxic chemotherapy. However, despite standard-of-care treatment, the outcomes remain dismal. Emerging evidence suggests that the gut microbiota plays a significant role in pancreatic carcinogenesis through dysbiosis, chronic inflammation and immune modulation. Dysbiosis-driven alterations in the gut microbiota composition can disrupt intestinal homeostasis, promote systemic inflammation and create a tumor-permissive microenvironment in the pancreas. Moreover, the gut microbiota modulates the efficacy of systemic therapies, including chemotherapy and immunotherapy, by impacting drug metabolism and shaping the tumor immune landscape. This review is mainly focused on exploring the intricate interplay between the gut microbiota and pancreatic cancer, and also highlighting its dual role in carcinogenesis and the therapeutic response.

Tumor Metastasis: Mechanistic Insights and Therapeutic Intervention

Metastasis remains a leading cause of cancer‐related deaths, defined by a complex, multi‐step process in which tumor cells spread and form secondary growths in distant tissues. Despite substantial progress in understanding metastasis, the molecular mechanisms driving this process and the development of effective therapies remain incompletely understood. Elucidating the molecular pathways governing metastasis is essential for the discovery of innovative therapeutic targets. The rapid advancements in sequencing technologies and the expansion of biological databases have significantly deepened our understanding of the molecular drivers of metastasis and associated drug resistance. This review focuses on the molecular drivers of metastasis, particularly the roles of genetic mutations, epigenetic changes, and post‐translational modifications in metastasis progression. We also examine how the tumor microenvironment influences metastatic behavior and explore emerging therapeutic strategies, including targeted therapies and immunotherapies. Finally, we discuss future research directions, stressing the importance of novel treatment approaches and personalized strategies to overcome metastasis and improve patient outcomes. By integrating contemporary insights into the molecular basis of metastasis and therapeutic innovation, this review provides a comprehensive framework to guide future research and clinical advancements in metastatic cancer.

Oral and fecal microbiota as accurate non-invasive tools for detection of pancreatic cancer in the Chinese population

Pancreatic cancer (PCA), a leading cause of cancer-related deaths, has limited non-invasive diagnostic methods. We aimed to identify oral and fecal microbiome biomarkers and construct diagnostic classifiers. Oral and fecal samples from 97 PCA patients and 90 healthy controls underwent 16S rRNA sequencing. Samples were randomly divided into training and validation cohorts in a 7:3 ratio. Random forest models were constructed using training cohort and validated internally and externally in Chinese, Japanese, and Spanish populations. Results revealed significant dysbiosis of the oral and fecal microbiota of PCA patients. Most of the differential taxa shared between oral and fecal samples showed similar changes. Relative abundances of Streptococcus in oral samples, and of Bifidobacterium, Klebsiella and Akkermansia in fecal samples, were enriched in PCA. The fecal Firmicutes to Bacteroidota ratio was higher in PCA patient samples. Oral and fecal microbiome classifiers based on the top 20 contributing genera were constructed, and internal validation showed that the area under the curve (AUC) values were 0.963 and 0.890, respectively. The fecal microbiome classifier performed well in the external Chinese population, with an AUC of 0.878, but poorly in the Japanese and Spanish populations. Furthermore, fecal microbiomes could predict metastasis status in PCA patients, with an AUC of 0.804. In conclusion, oral and fecal microbiota were dysbiotic in PCA patients. Fecal microbiome classifier provides a feasible, non-invasive, and cost-effective tool with high precision for PCA screening in China; oral microbiome classifier requires further validation in external populations sampled with the same simple and convenient methods.

Inflammatory Stimuli and Fecal Microbiota Transplantation Accelerate Pancreatic Carcinogenesis in Transgenic Mice, Accompanied by Changes in the Microbiota Composition

An association between gut microbiota and the development of pancreatic ductal adenocarcinoma (PDAC) has been previously described. To better understand the bacterial microbiota changes accompanying PDAC promotion and progression stimulated by inflammation and fecal microbiota transplantation (FMT), we investigated stool and pancreatic microbiota by 16s RNA-based metagenomic analysis in mice with inducible acinar transgenic expressions of KrasG12D, and age- and sex-matched control mice that were exposed to inflammatory stimuli and fecal microbiota obtained from mice with PDAC. Time- and inflammatory-dependent stool and pancreatic bacterial composition alterations and stool alpha microbiota diversity reduction were observed only in mice with a Kras mutation that developed advanced pancreatic changes. Stool Actinobacteriota abundance and pancreatic Actinobacteriota and Bifidobacterium abundances increased. In contrast, stool abundance of Firmicutes, Verrucomicrobiota, Spirochaetota, Desulfobacterota, Butyricicoccus, Roseburia, Lachnospiraceae A2, Lachnospiraceae unclassified, and Oscillospiraceae unclassified decreased, and pancreatic detection of Alloprevotella and Oscillospiraceae uncultured was not observed. Furthermore, FMT accelerated tumorigenesis, gradually decreased the stool alpha diversity, and changed the pancreatic and stool microbial composition in mice with a Kras mutation. Specifically, the abundance of Actinobacteriota, Bifidobacterium and Faecalibaculum increased, while the abundance of genera such as Lachnospiraceace A2 and ASF356, Desulfovibrionaceace uncultured, and Roseburia has decreased. In conclusion, pancreatic carcinogenesis in the presence of an oncogenic Kras mutation stimulated by chronic inflammation and FMT dynamically changes the stool and pancreas microbiota. In particular, a decrease in stool microbiota diversity and abundance of bacteria known to be involved in short-fatty acids production were observed. PDAC mouse model can be used for further research on microbiota-PDAC interactions and towards more personalized and effective cancer therapies.

Inflammation, microbiota, and pancreatic cancer

Pancreatic cancer (PC) is a malignancy of gastrointestinal tract threatening the life of people around the world. In spite of the advances in the treatment of PC, the overall survival of this disease in advanced stage is less than 12%. Moreover, PC cells have aggressive behaviour in proliferation and metastasis as well as capable of developing therapy resistance. Therefore, highlighting the underlying molecular mechanisms in PC pathogenesis can provide new insights for its treatment. In the present review, inflammation and related pathways as well as role of gut microbiome in the regulation of PC pathogenesis are highlighted. The various kinds of interleukins and chemokines are able to regulate angiogenesis, metastasis, proliferation, inflammation and therapy resistance in PC cells. Furthermore, a number of molecular pathways including NF-κB, TLRs and TGF-β demonstrate dysregulation in PC aggravating inflammation and tumorigenesis. Therapeutic regulation of these pathways can reverse inflammation and progression of PC. Both chronic and acute pancreatitis have been shown to be risk factors in the development of PC, further highlighting the role of inflammation. Finally, the composition of gut microbiota can be a risk factor for PC development through affecting pathways such as NF-κB to mediate inflammation.

Microbial dynamics of acute pancreatitis: integrating culture, sequencing, and bile impact on bacterial populations and gaseous metabolites

Background

Our study examined the composition of the intestinal microflora in a hospitalized patient with AP symptoms treated several months earlier for diverticulitis. The therapeutic intervention necessitated Hartmann's procedure, culminating in colostomy creation.

Aims

Employing a thorough microbiological analysis we attempted to demonstrate whether the microflora isolated from the peripancreatic fluid exhibited a stronger correlation with the contents of the stoma or with the rectal swab. Additionally, we sought to determine the association between later onset of AP and diverticulitis.

Methods

Following clinical materials from the patient in the initial phase of AP were collected: rectal swab, colostomy bag contents (in the publication referred to as stoma content/stool) and peripancreatic fluid. Microbiological analysis was performed, including classic culture methodology, NGS techniques, and genotyping methodologies. Furthermore, the effect of bile on the shift in the population of selected bacterial species was examined.

Results

The NGS technique confirmed greater consistency in bacteria percentage (phyla/family) between stoma content and peripancreatic fluid. In both samples, a clear dominance of the Proteobacteria phyla (over 75%) and the Enterobacteriaceae family was demonstrated. Moreover, NGS verified the presence of the Fusobacteriota phylum and Fusobacteriaceae family only in rectal swabs, which may indicate a link between this type of bacteria and the etiology of diverticulitis. We observed that Escherichia coli 33 isolated from stool exhibited active gaseous metabolite production (mainly hydrogen).

Conclusions

The abundant production of hydrogen may substantially impact enzymatic processes, inducing specific alterations in disulfide bonds and trypsin inactivation. Our investigation alludes to the conceivable active involvement of bile in effecting qualitative and quantitative modifications in the peripancreatic microbiota composition, establishing a correlation between released bile and bacterial generation of gaseous metabolites.

Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot study

Introduction

Many studies have reported the importance of the human microbiome in relationship to the overall health of its host. While recent studies have explored the microbiome's role in various types of cancer compared to healthy patients, this pilot study is the first to investigate differences in the skin microbiome composition among pancreatic adenocarcinoma patients, individuals with other cancers, and cancer-free controls.

Methods

The study characterizes the skin microbiome's potential associations with cancer status by analyzing skin swabs from the forehead and cheek of 58 participants using Next Generation Sequencing (NGS), differential abundance analysis, and machine learning techniques.

Results

The study results indicated that the cancer group displayed a significantly higher mean alpha diversity compared to the control group. Additionally, a machine learning classification model achieved a mean F1 Score of 0.943 in predicting cancer status, indicating measurable differentiation in the skin microbiome between the study groups. This differentiation is supported by differential abundance methods, including ANCOM-BC and MaAsLin2.

Discussion

This pilot study suggests that skin microbiome profiling could serve as a non-invasive biomarker for cancer detection and monitoring, which warrants a larger, longitudinal study to validate these results.

Gut microbes of the cecum versus the colon drive more severe lethality and multi-organ damage

Intestinal perforations lead to a high risk of sepsis-associated morbidity and multi-organ dysfunctions. A perforation allows intestinal contents (IC) to enter the peritoneal cavity, causing abdominal infections. Right- and left-sided perforations have different prognoses in humans, but the mechanisms associated with different cecum and colon perforations remain unclear. This study investigates how gut flora influences outcomes from perforations at different sites in mice. Using fecal-induced peritonitis mouse model, isolated IC from the cecum or colon was injected peritoneally at 2 mg/kg. Bacterial burden was quantified with quantitative PCR, and microbial communities were analyzed using 16S rRNA gene sequencing. Survival rates were monitored, and blood biochemical indices, histological changes, cytokines expression, immunological signaling and multiple-organ damage were assessed at 16 h post-injections. The results showed cecum IC developed more severe sepsis than colon IC, with shorter median survival time and greater multi-organ damage. Mice treated with cecum IC displayed elevated tissue damage markers in the liver, heart, and kidneys, contributing to worsened pathology. This was likely driven by systematic inflammatory cytokines production and lung inflammation. Mechanistically, cecum IC triggered stronger cGAS-STING and TBK1-NF-κB signaling, promoting systemic inflammation compared to the colon IC. Moreover, bacterial analysis demonstrated that cecum IC carry a higher bacterial burden than colon IC and exhibit a different microbial community. A detailed microbiome comparison revealed an increased abundance of potentially pathogenic bacteria in the cecum IC. These findings suggest that the site of intestinal perforation influences sepsis severity, with the cecum being associated with a higher bacterial burden and a relatively increased abundance of potentially pathogenic bacteria compared to the colon. Our findings first compared the lethality associated with the microbial composition of the cecum and colon, indicating the perforation site could help providers predict the severity of sepsis, thereby introducing a novel perspective to microbiology and sepsis research.

Recommendations, evidence and sustainability of screening for pancreatic cancer in high-risk individuals

Pancreatic cancer is a highly lethal malignancy and is predicted to become the second leading cause of cancer-related deaths by 2030. Early detection significantly improves outcomes, but general population screening remains infeasible due to the low prevalence of the disease and lack of specific biomarkers. This review evaluates current recommendations for pancreatic cancer surveillance in high-risk individuals, synthesises evidence from recent studies and explores the sustainability of current imaging-based surveillance programmes. Challenges such as overdiagnosis, economic feasibility and disparities in access highlight the need for targeted, cost-effective strategies. Collaborative initiatives and consortia are needed to advance biomarker research and refine risk stratification. By integrating evidence-based recommendations with sustainable approaches, this review outlines pathways to improve early detection and reduce mortality from pancreatic cancer.

A systematic review of the relationship between gut microbiota and prevalence of pancreatic diseases

Acute pancreatitis (AP) represents one of the most common gastrointestinal (GI) diseases; it can manifest in varying degrees of severity, sometimes leading to a life-threatening condition for the patient. Pancreatic ductal adenocarcinoma (PDAC), due to its high malignancy and uncertain prognosis, is widely regarded as one of the most fatal diseases. The increasing prevalence of AP and PDAC represents a major burden on public health and the healthcare system worldwide. The aim of this systematic review was to discuss the current state of knowledge regarding the relationship between the gut microbiota and the incidence, prognosis, diagnosis and treatment of AP and PDAC. To identify studies that analyzed the relationship between the gut microbiota and the occurrence/development of pancreatic diseases or PDAC, the online databases PubMed, Scopus and Google Scholar were searched between November 2023 and January 2024. Finally, 14 publications met the inclusion criteria (1. were conducted exclusively in humans and/or animals; 2. original, published in English in peer-reviewed journals after 2019; 3. described the relationship between gut microbiota and the occurrence of AP or PDAC). The collected studies indicated significant changes in the gut microbiota of patients with AP and PDAC. Moreover, they highlighted the presence of a relationship between the gut microbiota and the occurrence, course, treatment efficiency and prognosis of the disease in question. Further research is needed to understand precisely the relationship between the gut microbiota and the occurrence of pancreatic diseases and whether it may be a starting point for the development of modern forms of therapy based on the use of prebiotics and/or diet to restore the normal composition of the intestinal bacteria.

Preventive effects of kefir on colon tumor development in Wistar rats: gut microbiota critical role

To clarify the effects of kefir in critical periods of development in adult diseases, we study the effects of kefir intake during early life on gut microbiota and prevention of colorectal carcinogenesis in adulthood. Lactating Wistar rats were divided into three groups: control (C), kefir lactation (KL), and kefir puberty (KP) groups. The C and KP groups received 1 mL of water/day; KL dams received kefir milk daily (108 CFU/mL) during lactation. After weaning (postnatal day 21), KP pups received kefir treatment until 60 days. At 67 days old, colorectal carcinogenesis was induced through intraperitoneal injection of 1, 2-dimethylhydrazine. The gut microbiota composition were analyzed by 16S rRNA gene sequencing and DESeq2 (differential abundance method), revealing significant differences in bacterial abundances between the kefir consumption periods. Maternal kefir intake strong anticancer power, suppressed tumors in adult offspring and reduced the relative risk of offspring tumor development. The gut microbiota in cecal samples of the KL group was enriched with Lactobacillus, Romboutsia, and Blautia. In contrast, control animals were enriched with Acinetobacter. The administration of kefir during critical periods of development, with emphasis on lactation, affected the gut microbial community structure to promote host benefits. Pearson analysis indicated positive correlation between tumor number with IL-1 levels. Therefore, the probiotic fermented food intake in early life may be effective as chemopreventive potential against colon tumor development, especially in lactation period.

Dysbiosis-NK Cell Crosstalk in Pancreatic Cancer: Toward a Unified Biomarker Signature for Improved Clinical Outcomes

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor prognosis, primarily due to its immunosuppressive tumor microenvironment (TME), which contributes to treatment resistance. Recent research shows that the microbiome, including microbial communities in the oral cavity, gut, bile duct, and intratumoral environments, plays a key role in PDAC development, with microbial imbalances (dysbiosis) promoting inflammation, cancer progression, therapy resistance, and treatment side effects. Microbial metabolites can also affect immune cells, especially natural killer (NK) cells, which are vital for tumor surveillance, therapy response and treatment-related side effects. Dysbiosis can affect NK cell function, leading to resistance and side effects. We propose that a combined biomarker approach, integrating microbiome composition and NK cell profiles, can help predict treatment resistance and side effects, enabling more personalized therapies. This review examines how dysbiosis contributes to NK cell dysfunction in PDAC and discusses strategies (e.g., antibiotics, probiotics, vaccines) to modulate the microbiome and enhance NK cell function. Targeting dysbiosis could modulate NK cell activity, improve the effectiveness of PDAC treatments, and reduce side effects. However, further research is needed to develop unified NK cell-microbiome interaction-based biomarkers for more precise and effective patient outcomes.

Discovery of robust and highly specific microbiome signatures of non-alcoholic fatty liver disease

BACKGROUND

The pathogenesis of non-alcoholic fatty liver disease (NAFLD) with a global prevalence of 30% is multifactorial and the involvement of gut bacteria has been recently proposed. However, finding robust bacterial signatures of NAFLD has been a great challenge, mainly due to its co-occurrence with other metabolic diseases.

RESULTS

Here, we collected public metagenomic data and integrated the taxonomy profiles with in silico generated community metabolic outputs, and detailed clinical data, of 1206 Chinese subjects w/wo metabolic diseases, including NAFLD (obese and lean), obesity, T2D, hypertension, and atherosclerosis. We identified highly specific microbiome signatures through building accurate machine learning models (accuracy = 0.845-0.917) for NAFLD with high portability (generalizable) and low prediction rate (specific) when applied to other metabolic diseases, as well as through a community approach involving differential co-abundance ecological networks. Moreover, using these signatures coupled with further mediation analysis and metabolic dependency modeling, we propose synergistic defined microbial consortia associated with NAFLD phenotype in overweight and lean individuals, respectively.

CONCLUSION

Our study reveals robust and highly specific NAFLD signatures and offers a more realistic microbiome-therapeutics approach over individual species for this complex disease. Video Abstract.

Effects of data transformation and model selection on feature importance in microbiome classification data

BACKGROUND

Accurate classification of host phenotypes from microbiome data is crucial for advancing microbiome-based therapies, with machine learning offering effective solutions. However, the complexity of the gut microbiome, data sparsity, compositionality, and population-specificity present significant challenges. Microbiome data transformations can alleviate some of the aforementioned challenges, but their usage in machine learning tasks has largely been unexplored.

RESULTS

Our analysis of over 8500 samples from 24 shotgun metagenomic datasets showed that it is possible to classify healthy and diseased individuals using microbiome data with minimal dependence on the choice of algorithm or transformation. Presence-absence transformations performed comparably to abundance-based transformations, and only a small subset of predictors is necessary for accurate classification. However, while different transformations resulted in comparable classification performance, the most important features varied significantly, which highlights the need to reevaluate machine learning-based biomarker detection.

CONCLUSIONS

Microbiome data transformations can significantly influence feature selection but have a limited effect on classification accuracy. Our findings suggest that while classification is robust across different transformations, the variation in feature selection necessitates caution when using machine learning for biomarker identification. This research provides valuable insights for applying machine learning to microbiome data and identifies important directions for future work.

Normal Gut Microbiomes in Diverse Populations: Clinical Implications

The human microbiome is a sensor and modulator of physiology and homeostasis. Remarkable tractability underpins the promise of therapeutic manipulation of the microbiome. However, the definition of a normal or healthy microbiome has been elusive. This is in part due to the underrepresentation of minority groups and major global regions in microbiome studies to date. We review studies of the microbiome in different populations and highlight a commonality among health-associated microbiome signatures along with major drivers of variation. We also provide an overview of microbiome-associated therapeutic interventions for some widespread, widely studied diseases. We discuss sources of bias and the challenges associated with defining population-specific microbiome reference bases. We propose a roadmap for defining normal microbiome references that can be used for population-customized microbiome therapeutics and diagnostics.

Exosome applications for the diagnosis and treatment of pancreatic ductal adenocarcinoma: An update (Review)

Pancreatic ductal adenocarcinoma (PDAC) is a malignant neoplasm that typically manifests with subtle clinical manifestations in its early stages and frequently eludes diagnosis until the advanced phases of the disease. The limited therapeutic options available for PDAC significantly contribute to its high mortality rate, highlighting the urgent need for novel biomarkers capable of effectively identifying early clinical manifestations and facilitating precise diagnosis. The pivotal role of cellular exosomes in both the pathogenesis and therapeutic interventions for PDAC has been underscored. Furthermore, researchers have acknowledged the potential of exosomes as targeted drug carriers against regulatory cells in treating PDAC. The present article aims to provide a comprehensive review encompassing recent advancements in utilizing exosomes for elucidating mechanisms underlying disease development, patterns of metastasis, diagnostic techniques and treatment strategies associated with PDAC.

Microbiome and metabolome analysis in smoking and non-smoking pancreatic ductal adenocarcinoma patients

BACKGROUND

Smoking is a significant risk factor for pancreatic ductal adenocarcinoma (PDAC). This study aimed to investigate the effects of smoking on the pancreatic microbiome and metabolome in resectable and unresectable male PDAC patients.

METHODS

The pancreatic tissue samples were collected from resectable PDACs via surgery and unresectable PDACs via endoscopic ultrasound fine needle aspiration (EUS-FNA). Surgical samples obtained from 10 smoking and 6 non-smoking PDACs were measured by 16S ribosomal RNA (16S rRNA) gene sequencing and liquid chromatography-mass spectrometry (LC/MS). Fine needle aspiration (FNA) samples obtained from 20 smoking and 14 non-smoking PDACs were measured by 16S rRNA gene sequencing.

RESULTS

From resectable to unresectable patients, the dominant genus in the pancreas changed from Achromobacter to Delftia. Smoking further altered the abundance of specific bacteria, mainly manifested as an increase of Slackia in surgical tumor tissue of the smoking group, and an enrichment of Aggregatibacter and Peptococcus in FNA samples of the smoking group. In tumor tissue, smoking caused an enrichment of the cancer-promoting cAMP signaling pathway and L-lactic acid. In paracancerous tissue, smoking also induced a detrimental disturbance in the pancreatic microbiome and metabolome, including an enrichment of Veillonella, Novosphingobium, Deinococcus, and 3-hydroxybutanoic acid, and a reduction of linoleic acid. Besides, the cancer-promoting L-lactic acid was negatively correlated with Faecalibacterium in tumor tissue based on the correlation analysis.

CONCLUSION

There were differences in the pancreatic microbiome of PDAC patients at different stages, and smoking can further disrupt the pancreatic microbiome and metabolism in PDAC.

Difference in fecal and oral microbiota between pancreatic cancer and benign/low-grade malignant tumor patients

BACKGROUND

Significant gaps exist in understanding the gastrointestinal microbiota in patients with pancreatic cancer (PCA) versus benign or low-grade malignant pancreatic tumors (NPCA). This study aimed to analyze these microbiota characteristics and explore their potential use in distinguishing malignant pancreatic lesions.

METHODS

Between September 2020 and May 2024, fecal and oral samples were collected from 121 patients undergoing surgical resection or diagnostic biopsy of pancreatic lesions, including 75 patients with PCA and 46 patients with NPCA, and 16s rRNA sequencing was performed. Random forest models based using fecal and oral microbiota data were developed to diagnose PCA and NPCA, with performance assessed using the leave-one-out cross validation method.

RESULTS

The Shannon index and PCoA analysis revealed significant differences in oral microbiota composition between PCA and NPCA (p < 0.001 and p = 0.001, respectively). Fecal microbiome richness differed significantly (p = 0.02), though composition similarity was noted (p = 0.238). LEfSe identified 16 and 23 genera with significant differences in fecal and oral microbiomes, respectively. Random forest classifiers based on fecal and oral microbiota achieved areas under the curves (AUCs) of 89.4% and 96.3%, respectively, for distinguishing PCA and NPCA. In the mucinous tumor cohort, oral and fecal microbiome classifiers outperformed CA19-9, yielding AUCs of 83.0% and 85.2%, respectively.

CONCLUSION

Fecal and oral microbiota compositions were significantly different between PCA and NPCA patients. Random forest classifiers utilizing fecal and oral microbiota data effectively distinguish between benign or low-grade malignant and malignant pancreatic lesions.

The Past, Present, and Future of Biomarkers for the Early Diagnosis of Pancreatic Cancer

Pancreatic cancer is one of the most aggressive cancers with a very poor 5-year survival rate and reduced therapeutic options when diagnosed in an advanced stage. The dismal prognosis of pancreatic cancer has guided significant efforts to discover novel biomarkers in order to anticipate diagnosis, increasing the population of patients who can benefit from curative surgical treatment. CA 19-9 is the reference biomarker that supports the diagnosis and guides the response to treatments. However, it has significant limitations, a low specificity, and is inefficient as a screening tool. Several potential biomarkers have been discovered in the serum, urine, feces, and pancreatic juice of patients. However, most of this evidence needs further validation in larger cohorts. The advent of advanced omics sciences and liquid biopsy techniques has further enhanced this field of research. The aim of this review is to analyze the historical evolution of the research on novel biomarkers for the early diagnosis of pancreatic cancer, focusing on the current evidence for the most promising biomarkers from different body fluids and the novel trends in research, such as omics sciences and liquid biopsy, in order to favor the application of modern personalized medicine.

Anticarcinogenic effects of ursodeoxycholic acid in pancreatic adenocarcinoma cell models

Changes to the composition of the microbiome in neoplasia, is termed oncobiosis, may affect tumor behavior through the changes to the secretion of bacterial metabolites. In this study we show, that ursodeoxycholic acid (UDCA), a bacterial metabolite, has cytostatic properties in pancreatic adenocarcinoma cell (PDAC) models. UDCA in concentrations corresponding to the human serum reference range suppressed PDAC cell proliferation. UDCA inhibited the expression of epithelial mesenchymal transition (EMT)-related markers and invasion capacity of PDAC cells. UDCA treatment increased oxidative/nitrosative stress by reducing the expression of nuclear factor, erythroid 2-like 2 (NRF2), inducing inducible nitric oxide synthase (iNOS) and nitrotyrosine levels and enhancing lipid peroxidation. Furthermore, UDCA reduced the expression of cancer stem cell markers and the proportion of cancer stem cells. Suppression of oxidative stress by antioxidants, blunted the UDCA-induced reduction in cancer stemness. Finally, we showed that UDCA induced mitochondrial oxidative metabolism. UDCA did not modulate the effectiveness of chemotherapy agents used in the chemotherapy treatment of pancreatic adenocarcinoma. The antineoplastic effects of UDCA, observed here, may contribute to the induction of cytostasis in PDAC cell models by providing a more oxidative/nitrosative environment.

VIBES: A consensus subtyping of the vaginal microbiota reveals novel classification criteria

This study aimed to develop a robust classification scheme for stratifying patients based on vaginal microbiome. By employing consensus clustering analysis, we identified four distinct clusters using a cohort that includes individuals diagnosed with Bacterial Vaginosis (BV) as well as control participants, each characterized by unique patterns of microbiome species abundances. Notably, the consistent distribution of these clusters was observed across multiple external cohorts, such as SRA022855, SRA051298, PRJNA208535, PRJNA797778, and PRJNA302078 obtained from public repositories, demonstrating the generalizability of our findings. We further trained an elastic net model to predict these clusters, and its performance was evaluated in various external cohorts. Moreover, we developed VIBES, a user-friendly R package that encapsulates the model for convenient implementation and enables easy predictions on new data. Remarkably, we explored the applicability of this new classification scheme in providing valuable insights into disease progression, treatment response, and potential clinical outcomes in BV patients. Specifically, we demonstrated that the combined output of VIBES and VALENCIA scores could effectively predict the response to metronidazole antibiotic treatment in BV patients. Therefore, this study's outcomes contribute to our understanding of BV heterogeneity and lay the groundwork for personalized approaches to BV management and treatment selection.

Leveraging CAR macrophages targeting c-Met for precision immunotherapy in pancreatic cancer: insights from single-cell multi-omics

BACKGROUND

Pancreatic cancer is known for its poor prognosis and resistance to conventional therapies, largely due to the presence of cancer stem cells (CSCs) and aggressive angiogenesis. Effectively targeting these CSCs and associated angiogenic pathways is crucial for effective treatment. This study leverages single-cell multi-omics to explore a novel therapeutic approach involving Chimeric Antigen Receptor (CAR) macrophages engineered to target the c-Met protein on pancreatic CSCs.

METHODS

We employed single-cell RNA sequencing to analyze pancreatic cancer tissue, identifying c-Met as a key marker of CSCs. CAR macrophages were engineered using a lentiviral system to express a c-Met-specific receptor. The phagocytic efficiency of these CAR macrophages against pancreatic CSCs was assessed in vitro, along with their ability to inhibit angiogenesis. The in vivo efficacy of CAR macrophages was evaluated in a mouse model of pancreatic cancer.

RESULTS

CAR macrophages demonstrated high specificity for c-Met + CSCs, significantly enhancing phagocytosis and reducing the secretion of angiogenic factors such as VEGFA, FGF2, and ANGPT. In vivo, these macrophages significantly suppressed tumor growth and angiogenesis, prolonging survival in pancreatic cancer-bearing mice.

CONCLUSION

CAR macrophages targeting c-Met represent a promising therapeutic strategy for pancreatic cancer, offering targeted elimination of CSCs and disruption of tumor angiogenesis. This study highlights the potential of single-cell multi-omics in guiding the development of precision immunotherapies.

A core microbiome signature as an indicator of health

The gut microbiota is crucial for human health, functioning as a complex adaptive system akin to a vital organ. To identify core health-relevant gut microbes, we followed the systems biology tenet that stable relationships signify core components. By analyzing metagenomic datasets from a high-fiber dietary intervention in type 2 diabetes and 26 case-control studies across 15 diseases, we identified a set of stably correlated genome pairs within co-abundance networks perturbed by dietary interventions and diseases. These genomes formed a "two competing guilds" (TCGs) model, with one guild specialized in fiber fermentation and butyrate production and the other characterized by virulence and antibiotic resistance. Our random forest models successfully distinguished cases from controls across multiple diseases and predicted immunotherapy outcomes through the use of these genomes. Our guild-based approach, which is genome specific, database independent, and interaction focused, identifies a core microbiome signature that serves as a holistic health indicator and a potential common target for health enhancement.

Current status and prospect of gut and oral microbiome in pancreatic cancer: Clinical and translational perspectives

Pancreatic cancer is a highly lethal malignancy, and its diagnosis and treatment continue to pose significant challenges. Despite advancements in surgical and comprehensive treatment methods, the five-year survival rate remains below 12 %. With the rapid development of microbiome science, the gut and oral microbiota, which are readily accessible and can be sampled non-invasively, have emerged as a novel area of interest in pancreatic cancer research. Dysbiosis in these microbial communities can induce persistent inflammatory responses and affect the host's immune system, promoting cancer development and impacting the efficacy of treatments like chemotherapy and immunotherapy. This review provides an up-to-date overview of the roles of both gut and oral microbiota in the onset, progression, diagnosis, and treatment of pancreatic cancer. It analyzes the potential of utilizing these microbiomes as biomarkers and therapeutic targets from a clinical application perspective. Furthermore, it discusses future research directions aimed at harnessing these insights to advance the diagnosis and treatment strategies for pancreatic cancer. By focusing on the microbiome's role in clinical and translational medicine, this review offers insights into improving pancreatic cancer diagnosis and treatment outcomes.

The tumor immune microenvironment in resected treatment-naive pancreatic cancer patients with long-term survival

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide. Presently, only a fraction of patients undergo successful surgical resection, the most effective treatment. Enhancing treatment strategies necessitates a deep comprehension of the factors underlying extended survival after surgical resection in patients.

METHODS

This study aims to identify the important factors of PDAC patients' long-term survival with metatranscriptomics and multiplex immunofluorescence (IF) staining analyses. Specifically, differences in tumor immune microenvironment (TIME) were investigated between treatment-naïve PDAC short-term survivors (STS, overall survival <6 months) and long-term survivors (LTS, overall survival >5 years).

RESULTS

As a result, we detected 589 over-expressed genes, including HOXB9, CDA, and HOXB8, and 507 under-expressed genes, including AMY2B, SCARA5, and SLC2A2 in LTS. Most of the Reactome overbiological pathways enriched in our data were over-expressed in LTS, such as RHO GTPase Effectors and Cell Cycle Checkpoints. Eleven microbiomes significantly differed between LTS and STS, including Sphingopyxis and Capnocytophaga. Importantly, we demonstrate that the TIME profile with an increased abundance of memory B cells and the reduction of M0 and pro-tumoral M2 macrophages are associated with a good prognosis in PDAC.

CONCLUSIONS

In this study, we delved into the TIME with metatranscriptomics and IF staining analyses to understand the prerequisite of prolonged survival in PDAC patients. In LTS, several biological pathways were overexpressed, and specific microbiomes were identified. Furthermore, apparent differences in driven immune factors were found that provide valuable insights into developing new treatment strategies.

Machine learning algorithms and biomarkers identification for pancreatic cancer diagnosis using multi-omics data integration

PURPOSE

Pancreatic cancer is a lethal type of cancer with most of the cases being diagnosed in an advanced stage and poor prognosis. Developing new diagnostic and prognostic markers for pancreatic cancer can significantly improve early detection and patient outcomes. These biomarkers can potentially revolutionize medical practice by enabling personalized, more effective, targeted treatments, ultimately improving patient outcomes.

METHODS

The search strategy was developed following PRISMA guidelines. A comprehensive search was performed across four electronic databases: PubMed, Scopus, EMBASE, and Web of Science, covering all English publications up to September 2022. The Newcastle-Ottawa Scale (NOS) was utilized to assess bias, categorizing studies as "good," "fair," or "poor" quality based on their NOS scores. Descriptive statistics for all included studies were compiled and reviewed, along with the NOS scores for each study to indicate their quality assessment.

RESULTS

Our results showed that SVM and RF are the most widely used algorithms in machine learning and data analysis, particularly for biomarker identification. SVM, a supervised learning algorithm, is employed for both classification and regression by mapping data points in high-dimensional space to identify the optimal separating hyperplane between classes.

CONCLUSIONS

The application of machine-learning algorithms in the search for novel biomarkers in pancreatic cancer represents a significant advancement in the field. By harnessing the power of artificial intelligence, researchers are poised to make strides towards earlier detection and more effective treatment, ultimately improving patient outcomes in this challenging disease.

Genetically predicted gut bacteria, circulating bacteria-associated metabolites and pancreatic ductal adenocarcinoma: a Mendelian randomisation study

Pancreatic ductal adenocarcinoma (PDAC) has high mortality and rising incidence rates. Recent data indicate that the gut microbiome and associated metabolites may play a role in the development of PDAC. To complement and inform observational studies, we investigated associations of genetically predicted abundances of individual gut bacteria and genetically predicted circulating concentrations of microbiome-associated metabolites with PDAC using Mendelian randomisation (MR). Gut microbiome-associated metabolites were identified through a comprehensive search of Pubmed, Exposome Explorer and Human Metabolome Database. Single Nucleotide Polymorphisms (SNPs) associated by Genome-Wide Association Studies (GWAS) with circulating levels of 109 of these metabolites were collated from Pubmed and the GWAS catalogue. SNPs for 119 taxonomically defined gut genera were selected from a meta-analysis performed by the MiBioGen consortium. Two-sample MR was conducted using GWAS summary statistics from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including a total of 8,769 cases and 7,055 controls. Inverse variance-weighted MR analyses were performed along with sensitivity analyses to assess potential violations of MR assumptions. Nominally significant associations were noted for genetically predicted circulating concentrations of mannitol (odds ratio per standard deviation [ORSD] = 0.97; 95% confidence interval [CI]: 0.95-0.99, p = 0.006), methionine (ORSD= 0.97; 95%CI: 0.94-1.00, p = 0.031), stearic acid (ORSD= 0.93; 95%CI: 0.87-0.99, p = 0.027), carnitine = (ORSD=1.01; 95% CI: 1.00-1.03, p = 0.027), hippuric acid (ORSD= 1.02; 95%CI: 1.00-1.04, p = 0.038) and 3-methylhistidine (ORSD= 1.05; 95%CI: 1.01-1.10, p = 0.02). Two gut microbiome genera were associated with reduced PDAC risk; Clostridium sensu stricto 1 (OR: 0.88; 95%CI: 0.78-0.99, p = 0.027) and Romboutsia (OR: 0.87; 95%CI: 0.80-0.96, p = 0.004). These results, though based only on genetically predicted gut microbiome characteristics and circulating bacteria-related metabolite concentrations, provide evidence for causal associations with pancreatic carcinogenesis.

Characteristics of Gut Microbiome in the Murine Model of Pancreatic Cancer with Damp-Heat Syndrome

PURPOSE

Murine models of pancreatic cancer with damp-heat syndrome were established based on two methods to explore the differences in the composition of intestinal flora and to seek characteristic genera with potential for model evaluation.

METHODS

In our study, thirty-four C57BL/6J male mice were randomly divided into a control group (Con), a model group (Mod), a classic damp-heat syndrome group (CDHS), and a climate-chamber group (CC). CDHS and CC groups were fed with a high-fat diet and glucose water, while the CDHS group was given 2.4 g/kg alcohol by gavage for 10 days, and the CC group was placed in a climatic chamber with a set temperature of (32 ± 1) °C and humidity of (92 ± 2)% for 10 days. The Mod group, CDHS group, and CC group underwent tumor-building experiments on day 11. Tumorigenicity was then assessed twice a week. After 4 weeks, feces, colon tissue, and tumor tissue were taken from the mice and were tested, and the mice were euthanized afterwards.

RESULTS

Mice in the CDHS and CC groups showed symptoms similar to the clinical damp-heat syndrome observed in traditional Chinese medicine (TCM), and exhibited a worse general condition and more rapid tumor growth trend than those in the Mod group. The pathological examination indicated that inflammation was prevalent in the CDHS and CC groups. Both groups had a disrupted intestinal barrier and an overgrowth of pathogenic bacteria such as c_Gammaproteobacteria, o_Enterobacteriales, and g_Bacteroides. Their microbiota composition showed greater diversity.

CONCLUSIONS

Intestinal flora may have a promising future in the discovery of indicators for evaluating a model of damp-heat syndrome in pancreatic cancer.

Inflammatory Processes: Key Mediators of Oncogenesis and Progression in Pancreatic Ductal Adenocarcinoma (PDAC)

Associations between inflammation and cancer were first discovered approximately 160 years ago by Rudolf Virchow, who observed that tumors were infiltrated with inflammatory cells, and defined inflammation as a pathological condition. Inflammation has now emerged as one of the key mediators in oncogenesis and tumor progression, including pancreatic ductal adenocarcinoma (PDAC). However, the role of inflammatory processes in cancers is complicated and controversial, and the detailed regulatory mechanisms are still unclear. This review elucidates the dynamic interplay between inflammation and immune regulation, microenvironment alteration, metabolic reprogramming, and microbiome risk factors in PDAC, committing to exploring a deeper understanding of the role of crucial inflammatory pathways and molecules for providing insights into therapeutic strategies.

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).

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

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

The microbial composition of pancreatic ductal adenocarcinoma: a systematic review of 16S rRNA gene sequencing

BACKGROUND

Pancreatic cancer, specifically pancreatic ductal adenocarcinoma (PDAC), continues to pose a significant clinical and scientific challenge. The most significant finding of recent years is that PDAC tumours harbour their specific microbiome, which differs amongst tumour entities and is distinct from healthy tissue. This review aims to evaluate and summarise all PDAC studies that have used the next-generation technique, 16S rRNA gene amplicon sequencing within each bodily compartment. As well as establishing a causal relationship between PDAC and the microbiome.

MATERIALS AND METHODS

This systematic review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. A comprehensive search strategy was designed, and 1727 studies were analysed.

RESULTS

In total, 38 studies were selected for qualitative analysis and summarised significant PDAC bacterial signatures. Despite the growing amount of data provided, we are not able to state a universal 16S rRNA gene microbial signature that can be used for PDAC screening. This is most certainly due to the heterogeneity of the presentation of results, lack of available datasets, and the intrinsic selection bias between studies.

CONCLUSION

Several key studies have begun to shed light on causality and the influence the microbiome constituents and their produced metabolites could play in tumorigenesis and influencing outcomes. The challenge in this field is to shape the available microbial data into targetable signatures. Making sequenced data readily available is critical, coupled with the coordinated standardisation of data and the need for consensus guidelines in studies investigating the microbiome in PDAC.

Pancreatic Cancer Screening among High-risk Individuals

Pancreatic ductal adenocarcinoma (PDAC) continues to remain one of the leading causes of cancer-related death. Unlike other malignancies where universal screening is recommended, the same cannot be said for PDAC. The purpose of this study is to review which patients are at high risk of developing PDAC and therefore candidates for screening, methods/frequency of screening, and risk for these groups of patients.

Elucidating the genotoxicity of Fusobacterium nucleatum-secreted mutagens in colorectal cancer carcinogenesis

BACKGROUND

Fusobacterium nucleatum (F. nucleatum) is one of the key tumorigenic bacteria in colorectal cancer (CRC), yet how F. nucleatum is involved in colorectal cancer carcinogenesis remains unknown.

RESULTS

In the present study, we carried out PathSeq analysis on RNA sequencing data from the 430 primary colon adenocarcinomas in TCGA database to assess the relationship between patients' survival and F. nucleatum abundance. Among patients with cecum and ascending colon tumors, we found that F. nucleatum transcriptome abundance is positively correlated with mutation load. We further demonstrated that patients with both high tumoral abundance of F. nucleatum and high mutation load exhibited poorer survival and DNA damage. We furthermore determined that F. nucleatum-conditioned medium (Fn. CM) induces DNA damage in both in vitro and in vivo studies. In addition, two F. nucleatum-secreted mutagens, namely DL-homocystine and allantoic acid, were identified to lead to DNA damage.

CONCLUSIONS

Our finding delineates the genotoxicity of F.nucleatum-secreted mutagens, which provides a basis for further work to investigate the role of F. nucleatum in the pathogenicity of CRC.

Gut microbiome changes associated with chronic pancreatitis and pancreatic cancer: a systematic review and meta-analysis

BACKGROUND

The study of changes in the microbiome in chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) holds significant potential for developing noninvasive diagnostic tools as well as innovative interventions to alter the progression of diseases. This systematic review and meta-analysis aimed to analyze in detail the taxonomic and functional characteristics of the gut microbiome in patients with CP and PDAC.

METHODS

Two researchers conducted a systematic search across public databases to gather all published research up to June 2023. Diversity and gut microbiota composition are the main outcomes the authors focus on.

RESULTS

This meta-analysis included 14 studies, involving a total of 1511 individuals in the PDAC ( n =285), CP ( n =342), and control ( n =649) groups. Our results show a significant difference in the composition of gut microbiota between PDAC/CP patients compared to healthy controls (HC), as evidenced by a slight decrease in α-diversity, including Shannon (SMD=-0.33; P =0.002 and SMD=-0.59; P <0.001, respectively) and a statistically significant β-diversity ( P <0.05). The pooled results showed that at the phylum level, the proportion of Firmicutes was lower in PDAC and CP patients than in HC patients. At the genus level, more than two studies demonstrated that four genera were significantly increased in PDAC patients compared to HC (e.g. Escherichia-Shigella and Veillonella ). CP patients had an increase in four genera (e.g. Escherichia-Shigella and Klebsiella ) and a decrease in eight genera (e.g. Coprococcus and Bifidobacterium ) compared to HC. Functional/metabolomics results from various studies also showed differences between PDAC/CP patients and HC. In addition, this study found no significant differences in gut microbiota between PDAC and CP patients.

CONCLUSIONS

Current evidence suggests changes in gut microbiota is associated with PDAC/CP, commonly reflected by a reduction in beneficial species and an increase in the pathogenic species. Further studies are needed to confirm these findings and explore therapeutic possibilities.