Intratumoral and fecal microbiota reveals microbial markers associated with gastric carcinogenesis.

Background: The relationship between dysbiosis of the gastrointestinal microbiota and gastric cancer (GC) has been extensively studied. However, microbiota alterations in GC patients vary widely across studies, and reproducible diagnostic biomarkers for early GC are still lacking in multiple populations. Thus, this study aimed to characterize the gastrointestinal microbial communities involved in gastric carcinogenesis through a meta-analysis of multiple published and open datasets. Methods: We analyzed 16S rRNA sequencing data from 1,642 gastric biopsy samples and 394 stool samples across 11 independent studies. VSEARCH, QIIME and R packages such as vegan, phyloseq, cooccur, and random forest were used for data processing and analysis. PICRUSt software was employed to predict functions. Results: The α-diversity results indicated significant differences in the intratumoral microbiota of cancer patients compared to non-cancer patients, while no significant differences were observed in the fecal microbiota. Network analysis showed that the positive correlation with GC-enriched bacteria increased, and the positive correlation with GC-depleted bacteria decreased compared to healthy individuals. Functional analyses indicated that pathways related to carbohydrate metabolism were significantly enriched in GC, while biosynthesis of unsaturated fatty acids was diminished. Additionally, we investigated non-Helicobacter pylori (HP) commensals, which are crucial in both HP-negative and HP-positive GC. Random forest models, constructed using specific taxa associated with GC identified from the LEfSe analysis, revealed that the combination of Lactobacillus and Streptococcus included alone could effectively discriminate between GC patients and healthy individuals in fecal samples (area under the curve (AUC) = 0.7949). This finding was also validated in an independent cohort (AUC = 0.7712). Conclusions: This study examined the intratumoral and fecal microbiota of GC patients from a dual microecological perspective and identified Lactobacillus, Streptococcus, Roseburia, Faecalibacterium and Phascolarctobacterium as intratumoral and intestinal-specific co-differential bacteria. Furthermore, it confirmed the validity of the combination of Lactobacillus and Streptococcus as GC-specific microbial markers across multiple populations, which may aid in the early non-invasive diagnosis of GC.

Leucine restriction ameliorates Fusobacteriumnucleatum-driven malignant progression and radioresistance in nasopharyngeal carcinoma.

Radiotherapy resistance is the main cause of treatment failure among patients with nasopharyngeal carcinoma (NPC). Recently, increasing evidence has linked the presence of intratumoral Fusobacterium nucleatum (Fn) with the malignant progression and therapeutic resistance of multiple tumor types, but its influence on NPC has remained largely unknown. We found that Fn is prevalent in the tumor tissue of patients with NPC and is associated with radioresistance. Fn invaded and proliferated inside NPC cells and aggravated tumor progression. Mechanistically, Fn slowed mitochondrial dysfunction by promoting mitochondrial fusion and decreasing ROS generation, preventing radiation-induced oxidative damage. Fn inhibited PANoptosis by the SLC7A5/leucine-mTORC1 axis during irradiation stress, thus promoting radioresistance. Treatment with the mitochondria-targeted antibiotics or dietary restriction of leucine reduced intratumoral Fn load, resensitizing tumors to radiotherapy in vivo. These findings demonstrate that Fn has the potential to be a predictive marker for radioresistance and to help guide individualized treatment for patients with NPC.

CT-based conventional radiomics and quantification of intratumoral heterogeneity for predicting benign and malignant renal lesions.

BACKGROUND: With the increasing incidence of renal lesions, pretreatment differentiation between benign and malignant lesions is crucial for optimized management. This study aimed to develop a machine learning model utilizing radiomic features extracted from various regions of interest (ROIs), intratumoral ecological diversity features, and clinical factors to classify renal lesions. METHODS: CT images (arterial phase) of 1,795 renal lesions with confirmed pathology from three hospital sites were split into development (1184, 66%) and test (611, 34%) cohorts by surgery date. Conventional radiomic features were extracted from eight ROIs of arterial phase images. Intratumoral ecological diversity features were derived from intratumoral subregions. The combined model incorporating these features with clinical factors was developed, and its performance was compared with radiologists' interpretation. RESULTS: Combining intratumoral and peritumoral radiomic features, along with ecological diversity features yielded the highest AUC of 0.929 among all combinations of features extracted from CT scans. After incorporating clinical factors into the features extracted from CT images, our combined model outperformed the interpretation of radiologists in the whole (AUC = 0.946 vs 0.823, P < 0.001) and small renal lesion (AUC = 0.935 vs 0.745, P < 0.001) test cohorts. Furthermore, the combined model exhibited favorable concordance and provided the highest net benefit across threshold probabilities exceeding 60%. In the whole and small renal lesion test cohorts, the AUCs for subgroups with predicted risk below or above 95% sensitivity and specificity cutoffs were 0.974 and 0.978, respectively. CONCLUSIONS: The combined model, incorporating intratumoral and peritumoral radiomic features, ecological diversity features, and clinical factors showed good performance for distinguishing benign from malignant renal lesions, surpassing radiologists' diagnoses in both whole and small renal lesions. It has the potential to save patients from unnecessary invasive biopsies/surgeries and to enhance clinical decision-making.

A case of adrenal cavernous hemangioma resected due to tumor growth accompanied by intratumoral hemorrhage.

Introduction: We describe a case of an adrenal cavernous hemangioma that was surgically resected because of tumor growth and intratumoral hemorrhage. Case presentation: A 73-year-old woman presented with an enlarged adrenal tumor and intratumoral hemorrhage during the follow-up of an incidental adrenal tumor. A computed tomography showed that the left adrenal tumor had grown from 23 to 44 mm over 1 year. Blood tests revealed a normal metabolic profile. Paragangliomas and metastatic tumors were suspected on imaging. Laparoscopic adrenalectomy was performed to prevent tumor rupture due to further bleeding. No adhesions or bleeding were observed around the tumor during surgery. Pathological diagnosis was adrenal cavernous hemangioma. Conclusion: Adrenal cavernous hemangioma is difficult to distinguish preoperatively from other adrenal tumors, including malignant tumors. The intraoperative findings of this case suggest that laparoscopic adrenalectomy is a safe treatment option for relatively small adrenal cavernous hemangioma.

Neo-adjuvant radiation and intratumoral immunotherapy followed by surgery-NARIS trial for extremity soft tissue sarcoma.

Extremity soft tissue sarcoma (ESTS) is a rare malignant nonepithelial disease, calling for combined modality treatments with surgery to further improve local control rates and long-term survival, especially in patients with multiple local recurrences with or without risk of amputation. In this double-arm, open-label, Phase II clinical trial, we will enroll 30 patients with pathologically confirmed ESTS without nodal involvement or distant metastases. Patients are randomly assigned to the combination treatment group or the radiation monotherapy group. Additionally, tumor and biological samples will be obtained directly before and after neoadjuvant therapy, allowing for studies of immune response and primary drug resistance mechanisms.Clinical Trial Registration: ChiCTR2200060659 (http://www.chictr.org.cn) (ClinicalTrials.gov).

[Box: see text].

Intratumoral injection and retention hold promise to improve cytokine therapies for cancer.

As powerful activators of the immune system, cytokines have been extensively explored for treating various cancers. But despite encouraging advances and some drug approvals, the broad adoption of cytokine therapies in the clinic has been limited by low response rates and sometimes severe toxicities. This in part reflects an inefficient biodistribution to tumors or a pleiotropic action on bystander cells and tissues. Here, we first review these issues and then argue for the intratumoral delivery of engineered cytokine fusion proteins that have been optimized for tumor retention as a potential solution to overcome these limitations and realize the potential of cytokines as highly effective therapeutics for cancer.

The microenvironmental factors induced invasive tumor cells in glioblastoma.

Glioblastoma (GBM) cells have the potential to switch from being "proliferative cells" to peritumoral "invasive cells". Peritumoral GBM cells have highly invasive properties that allow them to survive surgery, leading to recurrence. The mechanisms underlying the manner in which the tumor microenvironment (TME) regulates the invasiveness of GBM remain unclear. Single-cell RNA sequencing analysis revealed heterogeneity in GBM cells, microglia and macrophages. In this study, the Oncostatin M receptor (OSMR) and leukemia inhibitory factor receptor (LIFR) expression indicated higher invasiveness in core GBM cells. Under environmental stress, the expression of OSMR and LIFR were up-regulated with the effect of hypoxic, acidic, and low-glucose conditions in vitro. Functional experiments revealed that TME stress significantly influences the proliferation, migration and invasion of GBM cells. The differences in core/peripheral TMEs in GBM affected the invasive properties, indicating the significant role of OSMR expression within the TME in tumor progression and postoperative therapy.

Intratumoral heterogeneity of oncogenic drivers in mixed histology lung adenocarcinomas: How tissue selection impacts molecular testing?

Majority of the lung adenocarcinomas show a mixture of different histological patterns. The possibility of histologically heterogeneous areas of the adenocarcinoma showing genetic heterogeneity and harboring different driver mutations, with potentially significant clinical impact, has not been adequately addressed. Currently, there are no guidelines to suggest how to submit tumor tissue in adenocarcinomas with mixed histological features for molecular testing. The objective of this study is to assess intra-tumoral heterogeneity in prominent driver mutations among different morphological patterns of lung adenocarcinoma, its implications on the future of molecular testing as well as its potential impact on patient management. Twenty-three cases of mixed histology lung adenocarcinoma resected between 2018 and 2023 were retrieved from the archives. H&E slides were reviewed to identify the predominant and second most predominant histological patterns. The morphologically different tumor areas were manually macro-dissected for DNA extraction. Next-Generation Sequencing with Ion AmpliSeq™ Cancer Hotspot Panel v2 (Thermo Fisher Scientific, USA). Thirteen cases showed the same pathological variant in both histological components tested. Three cases (13 %) exhibited disparities in the variants detected across the different histological patterns tested (p=0.025). The discrepant findings had a direct therapeutic impact in 4.3 % cases. Seven cases showed no pathogenic variants detected on either of the histological components tested. This study elucidates the presence of infrequent yet significant intra-tumoral heterogeneity in the molecular profiles of mixed histology adenocarcinomas, highlighting the need for guidelines directing tissue selection for molecular testing to avoid missed therapeutic opportunities and mitigate disease relapse.

A CD25×TIGIT bispecific antibody induces anti-tumor activity through selective intratumoral Treg cell depletion.

Intratumoral regulatory T cells (Tregs) express high levels of CD25 and TIGIT, which are also recognized as markers of effector T cell (Teff) activation. Targeting these molecules each alone with monoclonal antibodies (mAbs) poses a risk of concurrently depleting both Teffs and peripheral Tregs, thereby compromising the effectiveness and selectivity of intratumoral Treg depletion. Here, leveraging the increased abundance of CD25+ TIGIT+ double-positive Tregs in the solid tumor microenvironment (but not in peripheral tissues), we explore the feasibility of using a CD25×TIGIT bispecific antibody (bsAb) to selectively deplete intratumoral Tregs. We initially constructed a bsAb co-targeting mouse CD25 and TIGIT, NSWm7210, and found that NSWm7210 conferred enhanced intratumoral Treg depletion, Teff activation, and tumor suppression as compared to the parental monotherapies in mouse models. We subsequently constructed a bsAb co-targeting human CD25 and TIGIT (NSWh7216), which preferentially eliminated CD25+ TIGIT+ double-positive cells over single-positive cells in vitro. NSWh7216 exhibited enhanced anti-tumor activity without toxicity of peripheral Tregs in CD25 humanized mice compared to the parental monotherapies. Our study illustrates the use of CD25×TIGIT bsAbs as effective agents against solid tumors based on selective depletion of intratumoral Tregs.

Role of B cells in intratumoral MBTA immunotherapy of murine pheochromocytoma model.

Immunotherapy represents a revolutionary advancement in cancer treatment, which has traditionally focused on T cells; however, the role of B cells in cancer immunotherapy has gained interest because of their role in antigen presentation, antibody production, and cytokine release. In this study, we examined the role of B cells in previously developed intratumoral MBTA therapy (mannan-BAM, TLR ligands, and anti-CD40 antibody) in murine models of MTT pheochromocytoma. The results indicated that B cells significantly enhance the success of MBTA therapy, with wild-type mice exhibiting a lower tumor incidence and smaller tumors compared with B cell-deficient mice. Increased IL-6 and TNF-alpha levels indicated severe inflammation and a potential cytokine storm in B cell-deficient mice. Neutralization of TNF-alpha ameliorated these complications but resulted in increased tumor recurrence. The results highlight the important role of B cells in enhancing the immune response and maintaining immune homeostasis during MBTA therapy. Our findings offer new insights into improving therapeutic outcomes.

Intratumoral calcification on CT assists in distinguishing benign and malignant upper abdomen neoplasm.

BACKGROUND: The significance of calcification and microcalcification in diagnosing malignant tumors is well established, but their role in the upper abdomen is less explored in routine radiology. OBJECTIVES: To assess the effectiveness of computed tomography (CT) imaging in detecting intratumoral calcification within upper abdominal tumors. METHODS: This study retrospectively enrolled patients with upper abdominal tumors featuring intratumoral calcifications who underwent plain and contrast-enhanced CT scans between January 2016 and December 2019. We examined the imaging characteristics of calcifications, including location, edges, shape, CT values, and association with necrosis. The diagnostic utility of calcification for distinguishing benign and malignant tumors was assessed using receiver operating characteristic curves. Univariate and multivariate logistic regression analyses were conducted to identify independent predictive factors for the diagnosis of malignancy characterized by intratumoral calcification. RESULTS: This study included 153 patients (median age 49 ± 21 years; 83 men) with pathologically confirmed tumors of the upper abdomen (including liver, pancreas, and gastrointestinal tract) with intratumoral calcifications. Significant differences in CT values between benign and malignant tumors were observed (P < .001), with high diagnostic accuracy of calcification in CT imaging (receiver operating characteristic area = 0.884, sensitivity = 0.815, specificity = 0.976). The characteristics of calcification, including its edge and shape, were significantly correlated with tumor differentiation (P < .01). Multivariate logistic regression analysis revealed that the presence of adjacent necrosis around intracalcification is an independent predictor of malignancy (odds ratio = 5.48; 95% confidence interval: 1.55, 19.41; P = .008). CONCLUSION: Intratumoral calcification in CT imaging is a key marker for distinguishing between benign and malignant epigastric tumors, offering high specificity. Key message • What is already known on this topic - Intratumoral calcification, as a highly sensitive radiological marker, has shown potential in differentiating between benign and malignant tumors in thyroid and breast cancers. However, its discriminatory role in upper abdominal tumors is often overlooked. Therefore, assessing the diagnostic accuracy of intratumoral calcification on CT scans is crucial for improving diagnostic efficiency and avoiding unnecessary examinations. • What this study adds - Intratumoral calcification on CT exhibits high specificity in differentiating between benign and malignant upper abdominal tumors, providing a simple and reliable criterion for improving diagnostic accuracy. • How this study might affect research, practice or policy - This study highlights the significance of intratumoral calcification characteristics observed on CT in determining whether upper abdominal tumors are benign or malignant. The findings could pave the way for the development of a CT-based calcification scoring system, which would facilitate rapid and accurate diagnostics in clinical practice, thereby optimizing treatment strategies and enhancing patient prognosis.

Intratumoral microbiota in colorectal cancer: focus on specific distribution and potential mechanisms.

Colorectal cancer (CRC) is one of the most prevalent and lethal malignant tumors globally, posing significant health risks and societal burdens. Recently, advancements in next-generation sequencing technology have identified CRC intratumoral microbiota, thereby opening up novel avenues for further research. This review synthesizes the current advancements in CRC intratumoral microbiota and their impact on CRC progression and discusses the disparities in the relative abundance and community composition of CRC intratumoral microbiota across various colorectal tumors based on their anatomical location and molecular subtypes, as well as the tumor stages, and spatial tumor distribution. Intratumoral microbiota predominantly influence CRC development by modulating colonic epithelial cells, tumor cells, and the tumor microenvironment. Mechanistically, they can cause DNA damage, apoptosis and epithelial-mesenchymal transition. The effects of different intratumoral microbiota on CRC have been shown to be two-fold. In the future, to address the limitations of existing studies, it is important to develop comprehensive experimental protocols and suitable in vitro models for elucidating more mechanisms of intratumoral microbiota on CRC, which will facilitate the clinical application of microbe-related therapeutic strategies in CRC and potentially other tumors.

Intratumoral microbiota as a novel prognostic indicator in bladder cancer.

Microbes are important components of the tumor microenvironment and have a close relationship with tumors. However, there is still a lack of research on the intratumoral microbiota in bladder cancer and its impact on the tumor immune microenvironment. In this study, we used fluorescence in situ hybridization (FISH) and observed a substantial presence of microbiota in bladder cancer tissues, with greater abundance compared to that in normal bladder tissues. Based on the BIC database, we found that the microbiome of bladder cancer is highly diverse and its structure is significantly different from that of other tumors. To investigate the relationships among the intratumoral microbiota, tumor immunity, and prognosis in bladder cancer patients, we analyzed bladder cancer-specific differentially expressed immune- and antimicrobial-related genes from the ImmPort, TISIDB, and TCGA databases. We identified 11 hub genes and constructed a prognostic risk model. Further analysis revealed differences at the family and genus levels between distinct groups. Using LEfSe analysis, we identified six hub biomarkers and developed a novel microbial-based scoring system. The scoring system allows subgrouping of bladder cancer patients, with significant differences in prognosis, immune cell infiltration, tumor mutation burden, and immune checkpoints among different groups. Further FISH and immunofluorescence co-staining experiments initially verified that the specific distribution of microorganisms and M2 macrophages in bladder cancer may be closely related to the poor prognosis of patients. In conclusion, this study revealed the characteristics of the intratumoral microbiota in bladder cancer and identified potential prognostic targets for clinical application.

The emerging role of AI in enhancing intratumoral immunotherapy care.

The emergence of immunotherapy (IO), and more recently intratumoral IO presents a novel approach to cancer treatment which can enhance immune responses while allowing combination therapy and reducing systemic adverse events. These techniques are intended to change the therapeutic paradigm of oncology care, and means that traditional assessment methods are inadequate, underlining the importance of adopting innovative approaches. Artificial intelligence (AI) with machine learning algorithms and radiomics are promising approaches, offering new insights into patient care by analyzing complex imaging data to identify biomarkers to refine diagnosis, guide interventions, predict treatment responses, and adapt therapeutic strategies. In this editorial, we explore how integrating these technologies could revolutionize personalized oncology. We discuss their potential to enhance the survival and quality of life of patients treated with intratumoral IO by improving treatment effectiveness and minimizing side effects, potentially reshaping practice guidelines. We also identify areas for future research and review clinical trials to confirm the efficacy of these promising approaches.

Local administration of mRNA encoding cytokine cocktail confers potent anti-tumor immunity.

Immunotherapy using inflammatory cytokines, such as interleukin (IL)-2 and interferon (IFN)-α, has been clinically validated in treating various cancers. However, systemic immunocytokine-based therapies are limited by the short half-life of recombinant proteins and severe dose-limiting toxicities. In this study, we exploited local immunotherapy by intratumoral administration of lipid nanoparticle (LNP)-encapsulated mRNA cocktail encoding cytokines IL-12, IL-7, and IFN-α. The cytokine mRNA cocktail induced tumor regression in multiple syngeneic mouse models and anti-tumor immune memory in one syngeneic mouse model. Additionally, immune checkpoint blockade further enhanced the anti-tumor efficacy of the cytokine mRNAs. Furthermore, human cytokine mRNAs exhibited robust anti-tumor efficacy in humanized mouse tumor models. Mechanistically, cytokine mRNAs induced tumor microenvironment inflammation, characterized by robust T cell infiltration and significant inflammatory cytokine and chemokine production.

Decoding the secret of extracellular vesicles in the immune tumor microenvironment of the glioblastoma: on the border of kingdoms.

Over the last decades, extracellular vesicles (EVs) have become increasingly popular for their roles in various pathologies, including cancer and neurological and immunological disorders. EVs have been considered for a long time as a means for normal cells to get rid of molecules it no longer needs. It is now well established that EVs play their biological roles also following uptake or by the interaction of EV surface proteins with cellular receptors and membranes. In this review, we summarize the current status of EV production and secretion in glioblastoma, the most aggressive type of glioma associated with high mortality. The main purpose is to shed light on the EVs as a universal mediator of interkingdom and intrakingdom communication in the context of tumor microenvironment heterogeneity. We focus on the immunomodulatory EV functions in glioblastoma-immune cross-talk to enhance immune escape and reprogram tumor-infiltrating immune cells. We critically examine the evidence that GBM-, immune cell-, and microbiome-derived EVs impact local tumor microenvironment and host immune responses, and can enter the circulatory system to disseminate and drive premetastatic niche formation in distant organs. Taking into account the current state of the art in intratumoral microbiome studies, we discuss the emerging role of bacterial EV in glioblastoma and its response to current and future therapies including immunotherapies.

Single-cell transcriptomics reveals tumor microenvironment remodeling in hepatocellular carcinoma with varying tumor subclonal complexity.

Introduction: The complexity of tumor cell subclonal structure has been extensively investigated in hepatocellular carcinoma. However, the role of subclonal complexity in reshaping the tumor microenvironment (TME) remains poorly understood. Methods: We integrated single-cell transcriptome sequencing data from four independent HCC cohorts, involving 30 samples, to decode the associations between tumor subclonal complexity and the TME. We proposed a robust metric to accurately quantify the degree of subclonal complexity for each sample based on discrete copy number variations (CNVs) profiles. Results: We found that tumor cells in the high-complexity group originated from the cell lineage with FGB overexpression and exhibited high levels of transcription factors associated with poor survival. In contrast, tumor cells in low-complexity patients showed activation of more hallmark signaling pathways, more active cell-cell communications within the TME and a higher immune activation status. Additionally, cytokines signaling activity analysis suggested a link between HMGB1 expressed by a specific endothelial subtype and T cell proliferation. Discussion: Our study sheds light on the intricate relationship between the complexity of subclonal structure and the TME, offering novel insights into potential therapeutic targets for HCC.

An Abscopal Effect on Lung Metastases in Canine Mammary Cancer Patients Induced by Neoadjuvant Intratumoral Immunotherapy with Cowpea Mosaic Virus Nanoparticles and Anti-Canine PD-1.

Neoadjuvant intratumoral (IT) therapy could amplify the weak responses to checkpoint blockade therapy observed in breast cancer (BC). In this study, we administered neoadjuvant IT anti-canine PD-1 therapy (IT acPD-1) alone or combined with IT cowpea mosaic virus therapy (IT CPMV/acPD-1) to companion dogs diagnosed with canine mammary cancer (CMC), a spontaneous tumor resembling human BC. CMC patients treated weekly with acPD-1 (n = 3) or CPMV/acPD-1 (n = 3) for four weeks or with CPMV/acPD-1 (n = 3 patients not candidates for surgery) for up to 11 weeks did not experience immune-related adverse events. We found that acPD-1 and CPMV/acPD-1 injections resulted in tumor control and a reduction in injected tumors in all patients and in noninjected tumors located in the ipsilateral and contralateral mammary chains of treated dogs. In two metastatic CMC patients, CPMV/acPD-1 treatments resulted in the control and reduction of established lung metastases. CPMV/acPD-1 treatments were associated with altered gene expression related to TLR1-4 signaling and complement pathways. These novel therapies could be effective for CMC patients. Owing to the extensive similarities between CMC and human BC, IT CPMV combined with approved anti-PD-1 therapies could be a novel and effective immunotherapy to treat local BC and suppress metastatic BC.

Diagnostic and prognostic potential of the intra-tumoral microbiota profile in HPV-independent endocervical adenocarcinoma.

Background: Microbial community dynamics have been involved in numerous diseases, including cancer. The diversity of intertumoral microbiota in human papillomavirus independent endocervical adenocarcinoma (HPVI ECA) is not well-characterized. Objective: Our objective is to delineate the intratumoral microbiota profile in HPVI ECA and investigate its potential influence on oncogenesis. Methods: We analyzed 45 HPVI ECA cases, comprising 36 gastric-type ECA (GEA) and 9 clear cell carcinomas (CCC). We compared the microbial composition within cancerous and adjacent noncancerous tissue samples using 5R-16S ribosomal DNA sequencing. Further, we investigated the correlation between specific microbes and clinical-pathological metrics as well as patient outcomes. Results: Our findings demonstrate notable differences in the microbial spectra between cancerous and adjacent noncancerous tissues. Amongst HPVI ECA subtypes, GEAs exhibit more microbial variations compared to CCCs. Using the Random Forest algorithm, we identified two distinct microbial signatures that could act as predictive biomarkers for HPVI ECA and differentiate between GEA and CCC. Varied microbial abundances was related to clinical characteristics of HPVI ECA patients. In addition, high levels of Micrococcus and low levels of unknown genus75 from the Comamonadaceae family were associated with poorer outcomes in HPVI ECA patients. Similarly, an abundance of Microbacterium correlated with reduced overall survival (OS), and a high presence of Streptococcaceae family microbes was linked to reduced recurrence-free survival (RFS) in GEA patients. Intriguingly, a high abundance of Micrococcus was also associated with a worse OS in GEA patients. Conclusion: The study reveals distinct microbial signatures in HPVI ECA, which have potential as biomarkers for disease prognosis. The correlation between these tumor-associated microbiota features and clinicopathological characteristics underscores the possibility of microbiome-based interventions. Our research provides a foundation for more in-depth studies into the cervical microbiome's role in HPVI ECA.

An Explainable Graph Neural Framework to Identify Cancer-Associated Intratumoral Microbial Communities.

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.