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Abstract Background Immune checkpoint inhibitors (ICIs) have emerged as a novel and effective treatment strategy, yet their effectiveness is limited to a subset of patients. The gut microbiota, recognized as a promising anticancer adjuvant, is being increasingly suggested to augment the efficacy of ICIs. Despite this, the causal link between the gut microbiota and the success of immunotherapy is not well understood. This gap in knowledge has driven us to identify beneficial microbiota and explore the underlying molecular mechanisms. Methods Through 16S rDNA sequencing, we identified distinct gut microbiota in patients undergoing treatment with ICIs. Following this, we assessed the impact of probiotics on anti-PD-1 therapy in bladder cancer using mouse models, employing a multi-omics strategy. Subsequently, we uncovered the mechanisms through which Blautia-produced metabolites enhance antitumor immunity, utilizing untargeted metabolomics and a range of molecular biology techniques. Results In our research, the LEfSe analysis revealed a significant enrichment of the Blautia genus in the gut microbiota of patients who responded to immunotherapy. We discovered that the external addition of Blautia coccoides hampers tumor growth in a bladder cancer mouse model by enhancing the infiltration of CD8+ T cells within the tumor microenvironment (TME). Further investigations through untargeted metabolomics and molecular biology experiments showed that oral administration of Blautia coccoides elevated trigonelline levels. This, in turn, suppresses the β-catenin expression both in vitro and in vivo, thereby augmenting the cancer-killing activity of CD8+ T cells. Conclusions This research provided valuable insights into enhancing the efficacy of PD-1 inhibitors in clinical settings. It was suggested that applying Blautia coccoides and its metabolic product, trigonelline, could serve as a synergistic treatment method with PD-1 inhibitors in clinical applications. Graphical Abstract

Abstract Objective Bladder cancer(BCa) was a disease that seriously affects patients’ quality of life and prognosis. To address this issue, many researches suggested that the gut microbiota modulated tumor response to treatment; however, this had not been well-characterized in bladder cancer. In this study, our objective was to determine whether the diversity and composition of the gut microbiota or the density of specific bacterial genera influence the prognosis of patients with bladder cancer. Methods We collected fecal samples from a total of 50 bladder cancer patients and 22 matched non-cancer individuals for 16S rDNA sequencing to investigate the distribution of Parabacteroides in these two groups. Further we conducted follow-up with cancer patients to access the impact of different genera of microorganisms on patients survival. We conducted a Fecal Microbiota Transplantation (FMT) and mono-colonization experiment with Parabacteroides distasonis to explore its potential enhancement of the efficacy of anti-PD-1 immunotherapy in MB49 tumor-bearing mice. Immunohistochemistry, transcriptomics and molecular experiment analyses were employed to uncover the underlying mechanisms. Results The 16S rDNA showed that abundance of the genus Parabacteroides was elevated in the non-cancer control group compared to bladder cancer group. The results of tumor growth curves showed that a combination therapy of P. distasonis and ICIs treatment significantly delayed tumor growth and increased the intratumoral densities of both CD4+T and CD8+T cells. The results of transcriptome analysis demonstrated that the pathways associated with antitumoral immune response were remarkably upregulated in the P. distasonis gavage group. Conclusion P. distasonis delivery combined with α-PD-1 mAb could be a new strategy to enhance the effect of anti-PD-1 immunotherapy. This effect might be achieved by activating immune and antitumor related pathways.

Summary: Background: The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value. Methods: In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed. Findings: In total, 8225 slides from 1297 patients with PCa were collected and digitised. Overall, 8158 slides (18,761 lymph nodes) from 1297 patients with PCa (median age 68 years [interquartile range 64–73]; 331 [26%] with LNM) were used to train and validate ProCaLNMD. The AUROC of ProCaLNMD ranged from 0.975 (95% confidence interval 0.953–0.998) to 0.992 (0.982–1.000) in the training and validation datasets, with sensitivities > 0.955 and specificities > 0.921. ProCaLNMD also demonstrated an AUROC of 0.979 in the cross-cancer dataset. ProCaLNMD use triggered true reclassification in 43 (4.3%) slides in which micrometastatic tumour regions were initially missed by pathologists, thereby correcting 28 (8.5%) missed-diagnosed cases of previous routine pathological reports. In the human-AI comparison and collaboration study, the sensitivity of ProCaLNMD (0.983 [0.908–1.000]) surpassed that of two junior pathologists (0.862 [0.746–0.939], P = 0.023; 0.879 [0.767–0.950], P = 0.041) by 10–12% and showed no difference to that of two senior pathologists (both 0.983 [0.908–1.000], both P > 0.99). Furthermore, ProCaLNMD significantly boosted the diagnostic sensitivity of two junior pathologists (both P = 0.041) to the level of senior pathologists (both P > 0.99), and substantially reduced the four pathologists’ slide reviewing time (−31%, P

Prostate cancer (PCa) is initially sensitive to androgen deprivation therapy (ADT) but ultimately develops resistance and progresses to castration-resistant prostate cancer (CRPC) with a poor prognosis. This study indicated that some PCa patients and mice were more sensitive to ADT and entered CRPC later, which was related to the gut microbiota, especially the enrichment of Akkermansia muciniphila (AKK). Untargeted metabolomics analysis found that serum inosine level was upregulated in the treatment-sensitive group and significantly correlated with AKK. Furthermore, we revealed that intestinal permeability and serum lipopolysaccharide (LPS) levels increased in treatment-resistant mice. LPS stimulated the upregulation of p-NF-κB p65 and AR in tumors. Supplementing AKK metabolite inosine could alleviate intestinal barrier damage and reduce serum LPS level, ultimately inhibiting castration resistance via the LPS/NF-κB/AR axis. Finally, we constructed a predictive model for CRPC combining gut microbiota and clinical information (AUC = 0.729). This study revealed the potential mechanism of gut microbiota on CRPC and provided potential therapeutic targets and prognostic indicators.