Pancreatic cystic neoplasms (PCNs) carry variable malignant potential, requiring precise clinical management. However, the heterogeneity and progression of PCNs remain poorly understood. This study analyzed the microbiome, metabolome, and ionome profiles of cyst fluids from 188 patients, including 165 with PCNs and 23 with other cyst types, using PacBio full-length 16S/ITS sequencing, LC-MS/MS, and ICP-MS. Bioinformatic analyses were performed, and metabolic enzyme and endoplasmic reticulum (ER) stress-related gene expression were examined using the PAAD TCGA dataset. PCNs were classified into distinct histopathological subtypes, including mucinous cystic lesions (MCLs) and serous cystic lesions (SCLs). MCLs demonstrated lower microbial diversity compared to SCLs, indicating microbial instability. Streptococcus and Staphylococcus were identified as key taxa in intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs), respectively. MCLs exhibited metabolic shifts towards lipid metabolism, while IPMNs showed distinct metabolic profiles potentially reflecting inflammation-related metabolic reprogramming. Ionic diversity varied among subtypes, with MCLs showing reduced diversity and IPMNs presenting broader ionic profiles. Palmitic acid (PA), a metabolite linked to Streptococcus, may contribute to pro-inflammatory metabolic alterations in IPMN. Our preliminary experiments demonstrated that co-culturing Streptococcus orails (S. orails) with ASAN-PaCa cells promoted their proliferation, accompanied by an elevation of PA levels in the supernatant. This integrative microbiome-metabolome-ionome analysis highlights histopathological heterogeneity among PCNs. While mechanistic associations remain to be fully defined, mucinous lesions may be more susceptible to microbe-driven metabolic disruption, with Streptococcus-associated lipid alterations as a potential contributing factor.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most deadly malignancies with a highly immunosuppressive tumor immune microenvironment (TIME) that hinders effective therapy. PDAC is characterized by significant heterogeneity in immune cell composition, spatial distribution and activation states, which impacts tumor progression and treatment response. Tumour-infiltrating lymphocytes (TILs), including CD4+ T-helper cells, CD8+ cytotoxic T-cells and FOXP3+ regulatory T-cells, play a key role in immune regulation, yet PDAC is largely an immunologically "cold" tumour with limited effector T-cell infiltration. The surrounding cellular microenvironment, particularly Cancer Associated Fibroblasts (CAFs) and macrophages, contributes to immune evasion by promoting a fibrotic and desmoplastic barrier that limits TIL infiltration. The prognostic significance of TILs is increasingly recognized, with higher densities correlating with improved survival, whereas regulatory T-cell infiltration and immunosuppressive stromal interactions are associated with poor outcomes. Emerging therapeutic strategies targeting the TIME (e.g., CAFs), immune checkpoint inhibitors, and TIL-based therapies offer the potential to overcome resistance. Future research must focus on optimizing immunotherapy strategies and unravelling the complex stromal-immune interactions to improve clinical translation.

The intratumoral microbiota is closely associated with tumor initiation and progression in multiple solid tumors, including gastric cancer (GC). Single-cell analysis of host-microbiome interactions (SAHMI) is a pipeline used to systematically recover and denoise microbial signals in human clinical tissues and examine tumor-microbiome interactions at the single-cell transcriptome level. In a large GC cohort, we used SAHMI to detect 12 bacteria, among which Helicobacter pylori (H. pylori) was widely present in multiple tumor and normal samples. Meanwhile, we verified the presence of H. pylori in GC tissues via fluorescence in situ hybridization and immunohistochemistry. We performed single-cell RNA sequencing to analyze 11 cell populations, including B cells, T cells, and epithelial cells, and these cell types contained large numbers of H. pylori. We detected obvious enrichment of H. pylori in cancer cells and identified 13 upregulated differentially expressed genes exhibiting significantly negative correlations with patient survival in the H. pylori-positive tumor group compared with the findings in the other groups, indicating that these genes could represent prognostic biomarkers or therapeutic targets for H. pylori-infected patients with GC. Moreover, H. pylori-enriched immune cells, including T cells, B cells, and macrophages, were associated with cell-type-specific gene expression and pathway activities, including cell fate and immune signaling. In summary, tumor-microbiome interactions might reflect or influence tumorigenesis in GC, which has implications for clinical practice.

Gut microbiome has a considerable impact on the central nervous system via the "gut-brain axis." Neuroepigenome emerges as the interface between environment and genes, potentially help conveying the signals derived from the microbiome to the brain tissue. While only a limited number of studies have implicated epigenetic roles in the gut-brain axis, this review explores how gut microbiome might impact various brain-based epigenetic mechanisms, including DNA methylation, histone modification, ncRNA and RNA methylation, notably in the context of the specific neural complications. Among the epigenetic mechanisms, histone acetylation was most well-studied with respect to its relationships with gut microbiome, exerting a dynamic influence on gene expression in the brain. Furthermore, the pathways connecting gut bacteria to neuroepigenome were summarized, highlighting the roles of metabolites such as butyrate, propionate, acetate, lactate, and folate. Of particular interest, the roles of butyrate are emphasized due to their outstanding inhibitory activity towards histone deacetylases (HDACs), among other mechanisms. It is worth noting that some indirect gut-brain pathways may also be associated with the interplay between microbiome and neuroepigenome, while IL-6 has been found to effectively transmit microbe-derived signals to histone methylation in brains. Finally, we recapitulate the future perspectives critical to understanding this gut-brain crosstalk, such as clarifying the cause-and-effect relationship, bacterial cross-feeding within the gut, and the mechanisms underlying the site-specific histone modification in the brain. Together, this review attempts to consolidate our current knowledge about the "microbiome-neuroepigenome interplay" and propose a conceptual pathway to decipher the gut-brain axis in various neurological conditions.

The intricate interplay between host genes and intrahepatic microbes is vital in shaping the hepatic microenvironment. This study aims to elucidate how host-microbiota interactions contribute to the progression of nonalcoholic fatty liver disease (NAFLD). Hepatic gene and microbial profiles were analyzed from 570 samples across five cohorts, including 72 control, 124 nonalcoholic fatty liver (NAFL), 143 Borderline, and 231 nonalcoholic steatohepatitis (NASH) samples. Least absolute shrinkage and selection operator penalized regression and sparse canonical correlation analysis were utilized to identify host-microbiota interactions and their function. Validation was performed using a bulk transcriptomic data set comprising 1,332 samples and a single-cell transcriptomic data set of seven samples. We observed stage-specific gene expression changes of disrupting energy metabolism and immune responses, alongside microbial shifts shaping the NAFLD microenvironment. Additionally, we identified 5,537, 1,937, 1,485, and 2,933 host-microbiota interactions in control, NAFL, Borderline, and NASH samples, respectively. Escherichia coli and Actinomyces naeslundii dominated the interaction network in control but were replaced by Sphingomonadales and Sphingomonadaceae in disease stages from NAFL, preceding the transcriptomic tipping point observed in Borderline. In NASH, interactions significantly weakened, accompanied by the loss of mutualistic interactions between bacteria such as Bacillales, Ralstonia insidiosa, Sphingomonadaceae, and host mitophagy genes including SQSTM1, OPTN, and BNIP3L. Single-cell data sets confirmed these interactions were co-localized in macrophages and monocytes in control, which shifted to hepatocytes and endothelial cells in NAFLD. Shifts in host-microbial interaction signal early microenvironment changes. Disturbed host-microbiota interactions impacting mitophagy can trigger a pro-inflammatory hepatic microenvironment, potentially driving disease progression.IMPORTANCEThis study integrated multiple cohorts to uncover fundamental and generalizable signals in the progression of nonalcoholic fatty liver disease. Key changes in both liver gene expression and microbiota were identified across disease stages, with microbial composition and interactions with host offering earlier insights into microenvironmental changes. Notably, host-microbiota interactions related to mitophagy, crucial in early stages, were destroyed in nonalcoholic steatohepatitis. This disruption may contribute to the worsening inflammation and disease progression.

Emerging evidence reveals that microbiota plays a crucial role in multiple cancers. Nasopharyngeal carcinoma (NPC) tissues harbour microbiota, highlighting the need to investigate the clinical implications of tissue-resident microbiota in the development of NPC. Here, we aim to clarify the specific profile of tissue-resident microbiota and its influence on NPC outcomes.

This retrospective study included 491 NPC patients from Sun Yat-sen University Cancer Center (Guangzhou, China) and the Affiliated Hospital of Guilin Medical College (Guilin, China). We profiled the microbial composition of 343 NPC and 36 normal nasopharyngeal tissues through sequencing of the genes encoding the 16S rRNA subunit of bacterial ribosomes. There were significant differences in microbial composition, alpha diversity (Shannon index, P = 0.007; Simpson index, P = 0.036), and beta diversity (Bray-Curtis distance: R2 = 0.016, F = 5.187, P = 0.001; unweighted UniFrac distance: R2 = 0.017, F = 5.373, P = 0.001) between NPC and normal nasopharyngeal tissues. A bacterial signature comprising four risk bacterial genera, including Bacteroides, Alloprevotella, Parvimonas, and Dialister, was constructed in the training cohort (n = 171). Patients in the high-risk group had shorter disease-free (HR 2.80, 95% CI 1.51-5.18, P < 0.001), distant metastasis-free (HR 4.00, 95% CI 1.77-9.01, P < 0.001), and overall survival (HR 3.45, 95% CI 1.77-6.72, P < 0.001) than those of patients in the low-risk group. Similar results were yielded in the internal validation (n = 172) and external validation (n = 148) cohorts. Integrated multi-omics analysis revealed that NPC tissues harbouring abundant risk bacteria were characterised by deficient immune infiltration, which was verified by multiplex immunohistochemistry.

This study developed and validated the applicability of a four-bacteria signature as a prognostic tool for NPC prognostication. Integrated multi-omics analysis further uncovered that the tumour immune microenvironment was perturbed by tissue-resident microbiota, which might pave the way towards the era of microbiota-targeted precision medicine for NPC. Video Abstract.

This review provides an overview of research evidence focused on the microbial components essential to clinical cancer care, called the oncobiota (the interaction of human microbiota and cancer cells). It specifically examines the oncobiota in central nervous system cancer,breast cancer, pancreatic cancer, liver cancer, lung cancer, and cervical cancer. The literature review reveals insufficient knowledge about the oncobiota of organs once considered sterile. Many studies on oncobiota focus on small, geographically specific patient groups, and the absence of a reference (control) group complicates the development of microbial profiles for selected cancers. Consequently, this review aims to analyze the literature data and reports on the role of oncobiota in selected "sterile" organs and the resulting therapeutic or preventive implications. All relevant publications on oncobiota in patients with the selected cancers were considered to provide the most thorough analysis possible. Understanding the significance and role of oncobiota in the pathomechanisms of carcinogenesis may pave the way for targeted cancer prevention methods. Furthermore, therapeutic strategies based on oncobiota could represent a novel area of ​​personalized cancer treatment. Additionally, oncobiota may serve as an additional diagnostic tool in oncology.

Cancer remains a significant global health challenge, with its progression shaped by complex and multifactorial mechanisms. Recent research suggests that the vagus nerve could play a critical role in mediating communication between the tumor microenvironment and the central nervous system (CNS). This review highlights the diversity of vagal afferent receptors, which could position the vagus nerve as a unique pathway for transmitting immune, metabolic, mechanical, and chemical signals from tumors to the CNS. Such signaling could influence systemic disease progression and tumor-related responses. Additionally, the vagus nerve's interactions with the microbiome and the renin-angiotensin system (RAS)-both implicated in cancer biology-further underscore its potential central role in modulating tumor-related processes. Contradictions in the literature, particularly concerning vagal fibers, illustrate the complexity of its involvement in tumor progression, with both tumor-promoting and tumor-suppressive effects reported depending on cancer type and context. These contradictions often overlook certain experimental biases, such as the failure to distinguish between vagal afferent and efferent fibers during vagotomies or the localized parasympathetic effects that cannot always be extrapolated to the systemic level. By focusing on the homeostatic role of the vagus nerve, understanding these mechanisms could open the door to new perspectives in cancer research related to the vagus nerve and lead to potential therapeutic innovations.

Cancer therapy remains a critical medical challenge. Immunotherapy is an emerging approach to regulating the immune system to fight cancer and has shown therapeutic potential. Due to their immunogenicity, bacteria have been developed as drug-delivery vehicles in cancer immunotherapy. However, ensuring the safety and efficacy of this approach poses a considerable challenge. This paper comprehensively explains the fundamental processes and synthesis principles involved in immunotherapy utilizing engineered bacteria. Initially, we list common engineered strains and discuss that growth control through genetic mutation promises therapeutic safety. By considering the characteristics of the tumor microenvironment and the interaction of specific molecules, the precision targeting of tumors can be improved. Furthermore, we present a foundational paradigm for genetic circuit construction to achieve controlled gene activation and logical expression, directly determining drug synthesis and release. Finally, we review the immunogenicity, the expression of immunomodulatory factors, the delivery of immune checkpoint inhibitors, and the utilization of bacteria as tumor vaccines to stimulate the immune system and facilitate the efficacy of cancer immunotherapy.

Neoadjuvant immunotherapy combined with chemotherapy (Chemo-IM) is associated with significantly improved pathological complete response (pCR) rates and long-term survival outcomes in patient with early-stage triple-negative breast cancer (TNBC). However, only a small proportion of patients benefit from the addition of immunotherapy. Here, we explored and confirmed the role of intratumoral microbiota in screening patients with TNBC who are likely to benefit from neoadjuvant Chemo-IM.

Patients with previously untreated, non-metastatic TNBC receiving neoadjuvant Chemo-IM were enrolled. Differences in the intratumoral microbiota between the pCR and non-pCR groups were explored via 16S rDNA sequencing (16S-seq). Single-cell transcriptome sequencing (scRNA-seq) was employed to profile the tumor microenvironment (TME). Moreover, correlations between the intratumor microbiota and the TME were explored. Finally, machine-learning models based on the intratumoral microbiota were constructed to predict pCR.

A total of 89 female patients with early-stage TNBC treated by neoadjuvant Chemo-IM were enrolled. We found that the pCR group had greater diversity and a higher load of intratumoral microbiota than the non-pCR group. Intriguingly, scRNA-seq revealed significantly increased T cell infiltration and decreased tumor-associated macrophage infiltration into tumors in the pCR group. Moreover, intratumoral microbiota load was positively associated with CD4+CXCL13+ T cell infiltration and negatively associated with CD68+SPP1+ macrophage infiltration. Combined analysis of 16S-seq and scRNA-seq data revealed that intratumoral microbiota were present in both cancer and immune cells. Finally, we developed a model incorporating intratumoral microbiota and clinicopathological characteristics, and it showed strong power for predicting pCR to neoadjuvant Chemo-IM.

Intratumoral microbiota may serve as a strong and specific predictor of the response of patients with early-stage TNBC to neoadjuvant Chemo-IM. Our findings could contribute to the development of individualized Chemo-IM strategies for treating TNBC.

The human microbiome plays a crucial role in modulating health and disease susceptibility through a complex network of interactions with the host. When the delicate balance of this microbial ecosystem is disrupted, it often correlates with the onset of systemic diseases. An over-abundance of pathogenic microorganisms within the microbiome has been implicated as a driving factor in the development of disease conditions such as diabetes, obesity, and chronic infections. It has been observed that microbiome dysbiosis perturbs metabolic, inflammatory, and immunological pathways, potentially facilitating carcinogenesis. Furthermore, the metabolites associated with microbial dysbiosis exert multifaceted effects, including metabolic interference, host DNA damage, and tumor promotion, further underscoring the microbiome's significance in several of the cancers. This new exploration of microbiome involvement in carcinogenesis needs additional patient sample analysis, which could provide new insights into cancer diagnosis and treatment. However, treating these diseases using drugs, traditional methods, etc. has resulted in multi-drug resistance, and this has eventually made the situation worrisome. This review highlights the importance of nanotechnology, which may tackle these pathogenic conditions simultaneously by targeting common receptors present in bacteria and cancer. Herein, we have explained how nanotechnology may come to the forefront for these treatments. It explores the potential of non-antibiotic disinfectants, i.e., nanoparticles (NPs) with dual targeting capabilities against microbes and cancer cells, using mechanisms such as ROS generation and DNA damage while minimizing the chances of drug resistance.

The garlic bulb comprises several cloves, the swelling growth of which is significantly hindered by the accumulation of viruses. Herein, we describe a single-cell transcriptomic atlas of swelling cloves with virus accumulation, which comprised 19 681 high-quality cells representing 11 distinct cell clusters. Cells of two clusters, clusters 7 (C7) and 11 (C11), were inferred to be from the meristem. Cell trajectory analysis suggested the differentiation of clove cells to start from the meristem cells, along two pseudo-time paths. Investigation into the cell-specific activity of invasive viruses demonstrated that garlic virus genes showed relatively low-expression activity in cells of the clove meristem. There were 2060 garlic genes co-expressed with virus genes, many of which showed an association with the defense response. Five glutathione synthase/reductase genes co-expressed with virus genes displayed up-regulated expression, and the glutathione and related metabolites level showed an alteration in virus-invasive garlic clove, implying the role of glutathione in viral immunity of garlic. Our study offers valuable insights into the clove organogenesis and interaction between garlic and virus at single-cell resolution.

The European Union-sponsored ONCOBIOME network has spurred an international effort to identify and validate relevant gut microbiota-related biomarkers in oncology, generating a unique and publicly available microbiome resource. ONCOBIOME explores the effects of the microbiota on gut permeability and metabolism as well as on antimicrobial and antitumor immune responses. Methods for the diagnosis of gut dysbiosis have been developed based on oncomicrobiome signatures associated with the diagnosis, prognosis and treatment responses in patients with cancer. The mechanisms explaining how dysbiosis compromises natural or therapy-induced immunosurveillance have been explored. Through its integrative approach of leveraging multiple cohorts across populations, cancer types and stages, ONCOBIOME has laid the theoretical and practical foundations for the recognition of microbiota alterations as a hallmark of cancer. ONCOBIOME has launched microbiota-centered interventions and lobbies in favor of official guidelines for avoiding diet-induced or iatrogenic (for example, antibiotic- or proton pump inhibitor-induced) dysbiosis. Here, we review the key advances of the ONCOBIOME network and discuss the progress toward translating these into oncology clinical practice.

Growing evidence suggests that cancer should not be viewed solely as a genetic disease but also as the result of functional defects in the metaorganism, including disturbances in the gut microbiota (i.e., gut dysbiosis). The human microbiota plays a critical role in regulating epithelial barrier function in the gut, airways, and skin, along with host metabolism and systemic immune responses against microbes and cancer. Collaborative international networks, such as ONCOBIOME, are essential in advancing research equity and building microbiome resources to identify and validate microbiota-related biomarkers and therapies. In this review, we explore the intricate relationship between the microbiome, metabolism, and cancer immunity, and we propose microbiota-based strategies to improve outcomes for individuals at risk of developing cancer or living with the disease.

The pancreas tumor microbiota may influence tumor microenvironment and influence survival in early-stage pancreatic ductal adenocarcinoma (PDAC); however, current studies are limited and small. We investigated the relationship of tumor microbiota to survival in 201 surgically resected patients with localized PDAC (Stages I-II), from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts. We characterized the tumor microbiome using RNA-sequencing data. We examined the association of the tumor microbiome with overall survival (OS), via meta-analysis with the Cox PH model. A microbial risk score (MRS) was calculated from the OS-associated microbiota. We further explored whether the OS-associated microbiota is related to host tumor immune infiltration. PDAC tumor microbiome α- and β-diversities were not associated with OS; however, 11 bacterial species, including species of Gammaproteobacteria, confirmed by extensive resampling, were significantly associated with OS (all Q < 0.05). The MRS summarizing these bacteria was related to a threefold change in OS (hazard ratio = 2.96 per standard deviation change in the MRS, 95% confidence interval = 2.26-3.86). This result was consistent across the two cohorts and in stratified analyses by adjuvant therapy (chemotherapy/radiation). Identified microbiota and the MRS also exhibited association with memory B cells and naïve CD4+ T cells, which may be related to the immune landscape through BCR and TCR signaling pathways. Our study shows that a unique tumor microbiome structure, potentially affecting the tumor immune microenvironment, is associated with poorer survival in resected early-stage PDAC. These findings suggest that microbial mechanisms may be involved in PDAC survival, potentially informing PDAC prognosis and guiding personalized treatment strategies.IMPORTANCEMuch of the available data on the PDAC tumor microbiome and survival are derived from relatively small and heterogeneous studies, including those involving patients with advanced stages of pancreatic cancer. There is a critical knowledge gap in terms of the tumor microbiome and survival in early-stage patients treated by surgical resection; we expect that advancements in survival may initially be best achieved in these patients who are treated with curative intent.

Growing evidence reveals that the tumor microbiome-comprising distinct microbial communities within neoplastic tissues-exerts a profound influence on cancer initiation, progression, and therapeutic response. These microbes actively reshape the tumor microenvironment (TME) through metabolite secretion, the modulation of immune pathways, and direct interactions with host cells, thereby affecting tumor biology and therapeutic outcomes. Despite substantial heterogeneity among cancer types, recent insights underscore the tumor microbiome's potential as both a diagnostic/prognostic biomarker and a targetable component for innovative treatments. In this review, we synthesize emerging knowledge on the mechanistic roles of tumor-associated microbiota in shaping the TME, with a focus on how these discoveries can guide novel therapeutic strategies. We further explore interdisciplinary advances, including the convergence of microbiomics and nanotechnology, to enhance drug delivery, circumvent resistance, and foster TME remodeling. By highlighting these cutting-edge developments, our review underscores the transformative potential of integrating tumor microbiome research into precision oncology and advancing more personalized cancer therapies.

Recent advancements have revealed the presence of a microbiome within tumor tissues, underscoring the crucial role of the tumor microbiome in the tumor ecosystem. This review delves into the characteristics of the intratumoral microbiome, underscoring its dual role in modulating immune responses and its potential to both suppress and promote tumor growth. We examine state-of-the-art techniques for detecting and analyzing intratumoral bacteria, with a particular focus on their interactions with the immune system and the resulting implications for cancer prognosis and treatment. By elucidating the intricate crosstalk between the intratumoral microbiome and the host immune system, we aim to uncover novel therapeutic strategies that enhance the efficacy of cancer treatments. Additionally, this review addresses the existing challenges and future prospects within this burgeoning field, advocating for the integration of microbiome research into comprehensive cancer therapy frameworks.

Despite significant progress in cancer treatment, traditional therapies still face considerable challenges, including poor targeting, severe toxic side effects, and the development of resistance. Recent advances in biotechnology have revealed the potential of bacteria and their derivatives as drug delivery systems for tumor therapy by leveraging their biological properties. Engineered bacteria, including Escherichia coli, Salmonella, and Listeria monocytogenes, along with their derivatives─outer membrane vesicles (OMVs), bacterial ghosts (BGs), and bacterial spores (BSPs)─can be loaded with a variety of antitumor agents, enabling precise targeting and sustained drug release within the tumor microenvironment (TME). These bacteria and their derivatives possess intrinsic properties that stimulate the immune system, enhancing both innate and adaptive immune responses to further amplify therapeutic effects. The ability of bacteria to naturally accumulate in hypoxic tumor regions and their versatility in genetic modifications allow for tailored drug delivery strategies that synergistically enhance the effectiveness of chemotherapy, immunotherapy, and targeted therapies. This review comprehensively examines the fundamental principles of bacterial therapy, focusing on the strategies employed for bacterial engineering, drug loading, and the use of bacteria and their derivatives in targeted tumor therapy. It also discusses the challenges faced in optimizing bacterial delivery systems, such as safety concerns, unintended immune responses, and scalability for clinical applications. By exploring these aspects, this review provides a theoretical framework for improving bacterial-based drug delivery systems, contributing to the development of more effective and personalized cancer treatments.

The presence of microbes within healthy human internal organs still remains under question. Our study endeavors to discern microbial signatures within normal human internal tissues using data from the Genotype-Tissue Expression (GTEx) consortium. Machine learning (ML) models were developed to classify each tissue type based solely on microbial profiles, with the identification of tissue-specific microbial signatures suggesting the presence of distinct microbial communities inside tissues.

We analyzed 13,871 normal RNA-seq samples from 28 tissues obtained from the GTEx consortium. Unaligned sequencing reads with the human genome were processed using AGAMEMNON, an algorithm for metagenomic microbial quantification, with a reference database comprising bacterial, archaeal, and viral genomes, alongside fungal transcriptomes. Gradient-boosting ML models were trained to classify each tissue against all others based on its microbial profile. To validate the findings, we analyzed 38 healthy living tissue samples (samples from healthy tissues obtained from living individuals, not deceased) from an independent study, as the GTEx samples were derived from post-mortem biopsies.

Tissue-specific microbial signatures were identified in 11 out of the 28 tissues while the signatures for 8 tissues (Muscle, Heart, Stomach, Colon tissue, Testis, Blood, Liver, and Bladder tissue) demonstrated resilience to in silico contamination. The models for Heart, Colon tissue, and Liver displayed high discriminatory performance also in the living dataset, suggesting the presence of a tissue-specific microbiome for these tissues even in a living state. Notably, the most crucial features were the fungus Sporisorium graminicola for the heart, the gram-positive bacterium Flavonifractor plautii for the colon tissue, and the gram-negative bacterium Bartonella machadoae for the liver.

The presence of tissue-specific microbial signatures in certain tissues suggests that these organs are not devoid of microorganisms even in healthy conditions and probably they harbor low-biomass microbial communities unique to each tissue. The discoveries presented here confront the enduring dogma positing the sterility of internal tissues, yet further validation through controlled laboratory experiments is imperative to substantiate this hypothesis. Exploring the microbiome of internal tissues holds promise for elucidating the pathophysiology underlying both health and a spectrum of diseases, including sepsis, inflammation, and cancer.

Recent controversy around the cancer microbiome highlights the need for improved microbial analysis methods for human genomics data. We developed PRISM, a computational approach for precise microorganism identification and decontamination from low-biomass sequencing data. PRISM removes spurious signals and achieves excellent performance when benchmarked on a curated dataset of 62,006 known true- and false-positive taxa. We then use PRISM to detect microbes in 8 cancer types from the CPTAC and TCGA datasets. We identify rich microbiomes in gastrointestinal tract tumors in CPTAC and identify bacteria in a subset of pancreatic tumors that are associated with altered glycoproteomes, more extensive smoking histories, and higher tumor recurrence risk. We find relatively sparse microbes in other cancer types and in TCGA, which we demonstrate may reflect differing sequencing parameters. Overall, PRISM does not replace gold-standard controls, but it enables higher-confidence analyses and reveals tumor-associated microorganisms with potential molecular and clinical significance.

The polymorphic microbiome is considered a new hallmark of cancer. Advances in High-Throughput Sequencing have fostered rapid developments in microbiome research. The interaction between cancer cells, immune cells, and microbiota is defined as the immuno-oncology microbiome (IOM) axis. Fungal microbes (the mycobiome), although representing only ∼ 0.1-1% of the microbiome, are a critical immunologically active component of the tumor microbiome. Accumulating evidence suggests a possible involvement of commensal and pathogenic fungi in cancer initiation, progression, and treatment responsiveness. The tumor-associated mycobiome mainly consists of the gut mycobiome, the oral mycobiome, and the intratumoral mycobiome. However, the role of fungi in cancer remains poorly understood, and the diversity and complexity of analytical methods make it challenging to access this field. This review aims to elucidate the causal and complicit roles of mycobiome in cancer development and progression while highlighting the issues that need to be addressed in executing such research. We systematically summarize the advantages and limitations of current fungal detection and analysis methods. We enumerate and integrate these recent findings into our current understanding of the tumor mycobiome, accompanied by the prospect of novel and exhilarating clinical implications.

Limited research into the tumor immune microenvironment (TIME) for bladder urothelial carcinoma (BUC), particularly the neglect of the intratumoral microbiota, has hindered the development of immunotherapies targeting BUC. Here, we collect 401 patients with BUC with host transcriptome samples and matched tumor microbiome samples from The Cancer Genome Atlas database. Besides, two independent BUC cohorts receiving immunotherapy were obtained. First, we find that the TIME profile is closely related to the prognosis of patients with BUC. Additionally, the genus Lachnoclostridium in tumors could regulate the accumulation of chemokines to recruit immune cell populations into bladder tumors. Among them, chemokines include CCL3, CCL4, CXCL9, CXCL10, and CXCL11, and immune cells mainly involve macrophages and CD8+ T cells. Analyses based on two independent immunotherapy cohorts suggest that these immune-related chemokines strongly influence the immunotherapeutic efficacy of BUC. Furthermore, drug predictive analyses show that immune-related chemokines impact patients' sensitivity to diverse drugs. These results suggest a dual role of immune-related chemokines in combination therapy against BUC. Collectively, our study provides new insights into the regulation of TIME by intratumoral microbiota and provides guidance for improving immunotherapy against BUC.

Immune checkpoint blockade (ICB) has emerged as a promising therapy for both resectable urothelial carcinoma (UC) patients preparing for radical surgery and unresectable UC patients, whereas the objective response rate of ICB remains unsatisfactory due to various factors. Antibiotic (ATB) use can influence intratumoral bacteria, which may further reduce ICB efficacy. The study aims to evaluate the effects of ATB use on prognosis and response in UC patients undergoing ICB, and explore potential molecular mechanisms of ATBs and intratumoral bacteria impacting UC immune microenvironment.

Pooled analyses, synthesizing evidence from 3496 UC patients with ICB treatment, were conducted. In addition, single-cell RNA and single-cell microbiome data were analyzed based on eight UC samples and 63 185 single cells. Bulk RNA sequencing and clinical data from a single-arm, multicenter, atezolizumab-treated, phase 2 trial, IMvigor210, were used for validation.

ATB use exhibited worse overall survival (HR=1.46, 95% CI=[1.20-1.77], P <0.001 and lower objective response (OR=0.43, 95% CI=[0.27-0.68], P <0.001 in UC patients receiving ICB. Single-cell transcriptome and single-cell microbiome analyses identified the presence of intratumoral bacteria was obviously related to elevated antibacterial immune functions; and antibacterial immunity was positively correlated to antitumor immunity in UC immune microenvironment. Intratumoral bacteria could up-regulate CD74-MIF/COPA signaling of immune cells and activation of CD74-MIF/COPA mediated the promotion of T cell antitumor function induced by antibacterial immune cells. UC patients with higher CD74-MIF/COPA signaling carried better overall survival (HR=1.60, 95% CI=[1.19-2.15], P =0.002) in immunotherapy cohort.

ATB use reduces overall survival and objective response to ICB in UC patients. Antibacterial immune cell functions induced by intracellular bacteria in the UC microenvironment might up-regulate the function of antitumor T immune cells via activating CD74-MIF/COPA , whereas ATB could inhibit the above process through killing intracellular bacteria and result in poorer clinical benefit of ICB. The use of ATB should be considered carefully during the neoadjuvant immunotherapy period for resectable UC patients preparing for radical surgery and during the immunotherapy period for unresectable UC patients.

Recent studies have revealed that intratumoral microbiota is implicated in pancreatic cancer (PC), yet the spectra of intratumoral microbiota and their relationship with PC in Chinese patients remained to be clarified. In this study, tumor and paired paracancerous tissue from 53 patients were profiled by bacterial 16S rRNA gene sequencing. Both α- and β-diversity displayed significant differences between tumors and adjacent tissues, with higher diversity in tumors. Three bacteria phyla (Proteobacteria, Firmicutes, and Actinobacteria) were prevalent in both cancers and adjacent normal tissues. A high prevalence of Pseudomonas has been identified in the PC tumor microenvironment and was associated with prolonged overall survival. Furthermore, the results of in vitro experiments suggested that Pseudomonas fluorescens (P. fluorescens) could inhibit the proliferation and induce apoptosis of pancreatic cancer cells. These findings revealed distinctive microbial features of the PC tumors and normal tissues in Chinese populations and exhibited the antitumor potential of P. fluorescens in PC.

The tumor microbiome, a complex community of microbes found in tumors, has been found to be linked to cancer development, progression, and treatment outcome. However, it remains a bottleneck in distangling the relationship between the tumor microbiome and host gene expressions in tumor microenvironment, as well as their concert effects on patient survival. In this study, we aimed to decode this complex relationship by developing ASD-cancer (autoencoder-based subtypes detector for cancer), a semi-supervised deep learning framework that could extract survival-related features from tumor microbiome and transcriptome data, and identify patients' survival subtypes. By using tissue samples from The Cancer Genome Atlas database, we identified two statistically distinct survival subtypes across all 20 types of cancer Our framework provided improved risk stratification (e.g., for liver hepatocellular carcinoma, [LIHC], log-rank test, P = 8.12E-6) compared to PCA (e.g., for LIHC, log-rank test, P = 0.87), predicted survival subtypes accurately, and identified biomarkers for survival subtypes. Additionally, we identified potential interactions between microbes and host genes that may play roles in survival. For instance, in LIHC, Arcobacter, Methylocella, and Isoptericola may regulate host survival through interactions with host genes enriched in the HIF-1 signaling pathway, indicating these species as potential therapy targets. Further experiments on validation data sets have also supported these patterns. Collectively, ASD-cancer has enabled accurate survival subtyping and biomarker discovery, which could facilitate personalized treatment for broad-spectrum types of cancers.IMPORTANCEUnraveling the intricate relationship between the tumor microbiome, host gene expressions, and their collective impact on cancer outcomes is paramount for advancing personalized treatment strategies. Our study introduces ASD-cancer, a cutting-edge autoencoder-based subtype detector. ASD-cancer decodes the complexities within the tumor microenvironment, successfully identifying distinct survival subtypes across 20 cancer types. Its superior risk stratification, demonstrated by significant improvements over traditional methods like principal component analysis, holds promise for refining patient prognosis. Accurate survival subtype predictions, biomarker discovery, and insights into microbe-host gene interactions elevate ASD-cancer as a powerful tool for advancing precision medicine. These findings not only contribute to a deeper understanding of the tumor microenvironment but also open avenues for personalized interventions across diverse cancer types, underscoring the transformative potential of ASD-cancer in shaping the future of cancer care.

Increasing evidence suggests that the human microbiome plays an important role in cancer risk and treatment. Untargeted 'omics' techniques have accelerated research into microbiome-cancer interactions, supporting the discovery of novel associations and mechanisms. However, these techniques require careful selection and use to avoid biases and other pitfalls. In this essay, we discuss selected challenges involved in the analysis of microbiome data in the context of cancer, including the application of machine learning (ML). We focus on DNA sequencing-based (e.g., metagenomics) methods, but many of the pitfalls and opportunities generalize to other omics technologies as well. We advocate for extended training opportunities, community standards, and best practices for sharing data and code to advance transparency and reproducibility in cancer microbiome research.

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

Immune checkpoint blockade (ICB) is one of the leading immunotherapies, although a variable extent of resistance has been observed among patients and across cancer types. Among the efforts underway to overcome this challenge, the microbiome has emerged as a factor affecting the responsiveness and efficacy of ICB. Active research, facilitated by advances in sequencing techniques, is assessing the predominant influence of the intestinal microbiome, as well as the effects of the presence of an intratumoral microbiome. In this review, we describe recent findings from clinical trials, observational studies of human patients, and animal studies on the impact of the microbiome on the efficacy of ICB, highlighting the role of the intestinal and tumor microbiomes and the contribution of methodological advances in their study.

Pancreatic ductal adenocarcinoma (PDAC) is a digestive system malignancy characterized by challenging early detection, limited treatment alternatives, and generally poor prognosis. Although there have been significant advancements in immunotherapy for hematological malignancies and various solid tumors in recent decades, with impressive outcomes in recent preclinical and clinical trials, the effectiveness of these therapies in treating PDAC continues to be modest. The unique immunological microenvironment of PDAC, especially the abnormal distribution, complex composition, and variable activation states of tumor-infiltrating immune cells, greatly restricts the effectiveness of immunotherapy. Undoubtedly, integrating data from both preclinical models and human studies helps accelerate the identification of reliable molecules and pathways responsive to targeted biological therapies and immunotherapies, thereby continuously optimizing therapeutic combinations. In this review, we delve deeply into how PDAC cells regulate the immune microenvironment through complex signaling networks, affecting the quantity and functional status of immune cells to promote immune escape and tumor progression. Furthermore, we explore the multi-modal immunotherapeutic strategies currently under development, emphasizing the transformation of the immunosuppressive environment into an anti-tumor milieu by targeting specific molecular and cellular pathways, providing insights for the development of novel treatment strategies.

Microbes are extensively present among various cancer tissues and play critical roles in carcinogenesis and treatment responses. However, the underlying relationships between intratumoral microbes and tumors remain poorly understood. Here, a MIcrobial Cancer-association Analysis using a Heterogeneous graph transformer (MICAH) to identify intratumoral cancer-associated microbial communities is presented. MICAH integrates metabolic and phylogenetic relationships among microbes into a heterogeneous graph representation. It uses a graph transformer to holistically capture relationships between intratumoral microbes and cancer tissues, which improves the explainability of the associations between identified microbial communities and cancers. MICAH is applied to intratumoral bacterial data across 5 cancer types and 5 fungi datasets, and its generalizability and reproducibility are demonstrated. After experimentally testing a representative observation using a mouse model of tumor-microbe-immune interactions, a result consistent with MICAH's identified relationship is observed. Source tracking analysis reveals that the primary known contributor to a cancer-associated microbial community is the organs affected by the type of cancer. Overall, this graph neural network framework refines the number of microbes that can be used for follow-up experimental validation from thousands to tens, thereby helping to accelerate the understanding of the relationship between tumors and intratumoral microbiomes.

The intratumoral microbiome (TM) refers to the microorganisms in the tumor tissues, including bacteria, fungi, viruses, and so on, and is distinct from the gut microbiome and circulating microbiota. TM is strongly associated with tumorigenesis, progression, metastasis, and response to therapy. This paper highlights the current status of TM. Tract sources, adjacent normal tissue, circulatory system, and concomitant tumor co-metastasis are the main origin of TM. The advanced techniques in TM analysis are comprehensively summarized. Besides, TM is involved in tumor progression through several mechanisms, including DNA damage, activation of oncogenic signaling pathways (phosphoinositide 3-kinase [PI3K], signal transducer and activator of transcription [STAT], WNT/β-catenin, and extracellular regulated protein kinases [ERK]), influence of cytokines and induce inflammatory responses, and interaction with the tumor microenvironment (anti-tumor immunity, pro-tumor immunity, and microbial-derived metabolites). Moreover, promising directions of TM in tumor therapy include immunotherapy, chemotherapy, radiotherapy, the application of probiotics/prebiotics/synbiotics, fecal microbiome transplantation, engineered microbiota, phage therapy, and oncolytic virus therapy. The inherent challenges of clinical application are also summarized. This review provides a comprehensive landscape for analyzing TM, especially the TM-related mechanisms and TM-based treatment in cancer.

The multifaceted interactions among the immune system, cancer cells and microbial components have established a novel concept of the immuno-oncology-microbiome (IOM) axis. Microbiome sequencing technologies have played a pivotal role in not only analyzing how gut microbiota affect local and distant tumors, but also providing unprecedented insights into the intratumor host-microbe interactions. Herein, we discuss the emerging trends of transiting from bulk-level to single cell- and spatial-level analyses. Moving forward with advances in biotechnology, microbial therapies, including microbiota-based therapies and bioengineering-inspired microbes, will add diversity to the current oncotherapy paradigm.

Pancreatic ductal adenocarcinoma (PDAC) is the third-leading cause of tumor-related deaths. The gut microbiota has gained attention in cancer treatment, due to its influence on the immune system and drug activity.

Tintelnot and collaborators highlight distinct gut microbiota composition in metastatic PDAC (mPDAC) patients responding versus non-responding to chemotherapy. In the context of chemotherapy treatment, the gut microbiota of responders can metabolize tryptophan from food into indole-3-acetic acid (3-IAA). The presence of neutrophil-derived myeloperoxidase facilitates the role of 3-IAA in promoting the accumulation of reactive oxygen species in tumor cells. This accumulation, in turn, inducing tumor cell cytotoxicity. Additionally, 3-IAA can inhibit tumor cell autophagy activity, diminishing tumor cells' ability to adapt to cell stress. This manuscript provides a comprehensive analysis of the latest research on microbiota, metabolites, and PDAC, sourced from PubMed, ScienceDirect, and Google Scholar.

The evaluated study noted an elevation of the bacterial metabolite 3-IAA in responsive PDAC patients' serum, suggesting its potential to enhance chemotherapy sensitivity. Gaining a thorough comprehension of the impact of gut microbiota metabolites on drug activity is beneficial for broadening our strategies to mitigate chemotherapy resistance in tumors and identifying markers that predict chemotherapy outcomes.

The past several years have provided a more profound understanding of the role of microbial species in the lung. The respiratory tract is a delicate ecosystem of bacteria, fungi, parasites, and viruses. Detecting microbial DNA, pathogen-associated molecular patterns (PAMPs), and metabolites in sputum is poised to revolutionize the early diagnosis of lung cancer. The longitudinal monitoring of the lung microbiome holds the potential to predict treatment response and side effects, enabling more personalized and effective treatment options. However, most studies into the lung microbiota have been observational and have not adequately considered the impact of dietary intake and air pollutants. This gap makes it challenging to establish a direct causal relationship between environmental exposure, changes in the composition of the microbiota, lung carcinogenesis, and tumor progression. A holistic understanding of the lung microbiota that considers both diet and air pollutants may pave the way to improved prevention and management strategies for lung cancer.

Cells, as the fundamental units of life, contain multidimensional spatiotemporal information. Single-cell RNA sequencing (scRNA-seq) is revolutionizing biomedical science by analyzing cellular state and intercellular heterogeneity. Undoubtedly, single-cell transcriptomics has emerged as one of the most vibrant research fields today. With the optimization and innovation of single-cell sequencing technologies, the intricate multidimensional details concealed within cells are gradually unveiled. The combination of scRNA-seq and other multi-omics is at the forefront of the single-cell field. This involves simultaneously measuring various omics data within individual cells, expanding our understanding across a broader spectrum of dimensions. Single-cell multi-omics precisely captures the multidimensional aspects of single-cell transcriptomes, immune repertoire, spatial information, temporal information, epitopes, and other omics in diverse spatiotemporal contexts. In addition to depicting the cell atlas of normal or diseased tissues, it also provides a cornerstone for studying cell differentiation and development patterns, disease heterogeneity, drug resistance mechanisms, and treatment strategies. Herein, we review traditional single-cell sequencing technologies and outline the latest advancements in single-cell multi-omics. We summarize the current status and challenges of applying single-cell multi-omics technologies to biological research and clinical applications. Finally, we discuss the limitations and challenges of single-cell multi-omics and potential strategies to address them.