Prostate Cancer Adenocarcinoma
Conditions
Keywords
Prostate cancer, Intratumoral microbiota, Tumor immune microenvironment, Spatial omics, Low-biomass microbiome
Brief summary
Prostate cancer is a common malignancy in men, with rising incidence worldwide. Current clinical risk assessment tools-including PSA, Gleason score/ISUP grade, pathological stage, margin status, perineural invasion, and postoperative PSA kinetics-cannot fully explain the marked heterogeneity in disease progression, recurrence, and treatment response, highlighting the need for novel microenvironment-based biomarkers. Emerging evidence has identified intratumoral microbiota as a component of the tumor microenvironment in various solid tumors (e.g., breast, lung, ovarian, pancreatic, and melanoma), where microbial signals correlate with immune infiltration, inflammation, drug metabolism, and patient outcomes. However, the composition, spatial distribution, and immune-related roles of intratumoral microbiota in prostate cancer remain poorly characterized. Given that prostatic tissue resides at the urogenital junction and is continuously exposed to urine, prostatic fluid, and local inflammation, it is plausible that microbial components influence local immunity and tumor behavior. Importantly, intratumoral microbiota represent low-biomass samples, highly susceptible to contamination from reagents, environment, and laboratory procedures. Therefore, this study incorporates rigorous quality controls-including negative controls, process blanks, batch records, contaminant identification, spatial localization validation, and cross-platform verification-to ensure data reliability. Using residual tissue specimens, archived pathological slides, and comprehensive clinicopathological data from prostate cancer patients, we will employ 16S rRNA sequencing, metagenomic/metatranscriptomic sequencing, spatial transcriptomics, spatial proteomics, immunofluorescence, immunohistochemistry, and bioinformatic analyses to profile intratumoral microbiota. Our specific objectives are: (1) to compare microbial composition, abundance, and diversity among tumor, adjacent-normal, and benign tissues; (2) to validate spatial localization of candidate microbial signals via in situ hybridization, immunohistochemistry, and spatial omics; (3) to assess differences in immune cell infiltration, macrophage polarization, T-cell exhaustion markers, and inflammatory pathways between microbe-high and microbe-cold regions; (4) to explore associations between microbial features and Gleason score/ISUP grade, stage, perineural invasion, margin status, postoperative PSA changes, biochemical recurrence, and other clinical outcomes; and (5) to establish a standardized workflow for low-biomass intratumoral microbiome research in prostate cancer. This study aims to provide new insights into microenvironmental heterogeneity and to lay a foundation for identifying prognostic biomarkers and potential therapeutic targets.
Interventions
DIAGNOSTIC_TESTValidate spatial localization of candidate microbial signals via 16S rRNA ISH, FISH, immunofluorescence, IHC, and spatial omics.
Compare microbe-high and microbe-cold areas for differences in immune cell infiltration, macrophage phenotype, T-cell exhaustion/suppression markers, inflammatory factors, and tumor-associated pathways.
Sponsors
Anhui Medical University
Study design
Observational model
COHORT
Time perspective
OTHER
Eligibility
Sex/Gender
MALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
（1）Age ≥18 years, male.（2）Patients with a pathological diagnosis of prostate cancer, or patients with benign prostatic diseases who undergo diagnostic workup or treatment and are eligible to serve as control samples.（3）Patients who undergo prostate biopsy, transurethral prostate surgery, radical prostatectomy, or other relevant diagnostic or therapeutic procedures at the First Affiliated Hospital of Anhui Medical University.（4）Have available residual tissue samples, formalin-fixed paraffin-embedded (FFPE) tissues, frozen tissues, pathological slides, or existing assay data that can be used for research purposes.（5）Have basic clinicopathological data available; postoperative PSA and follow-up information may be obtained when necessary.（6）For subjects from whom additional residual samples are prospectively collected, or for those who need to be actively contacted for supplementary data, the subject or their legal representative must consent to participate in the study and sign the informed consent form. \-
Exclusion criteria
（1）Insufficient sample quantity or sample quality that fails to meet the requirements for the intended assays.（2）Severe deficiency in clinicopathological data, rendering the primary analyses unfeasible.（3）Definite risk of contamination during sample storage, transportation, sectioning, extraction, or library preparation, which cannot be reliably ruled out or eliminated through quality control procedures.（4）The patient explicitly refuses to allow their samples or clinical data to be used for research.（5）Other conditions deemed unsuitable for inclusion by the investigator or the ethics committee.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Biochemical Progression-Free Survival (bPFS) | From treatment initiation until biochemical progression or last follow-up, assessed every 3 months (+1 month) for up to 24 months. | Time from initiation of ADT plus ARPI therapy to biochemical progression or deathfrom any cause, whichever occurs first. Biochemical progression is defined as a PSA rise to 0.2ng/mL after having reached an undetectable level, confirmed by a second measurement at least 2weeks apart. Participants without an event will be censored at the date of last follow-up. |
Countries
China
Contacts
CONTACTSheng Tai, M.D.
CONTACTBowen Li, M.D.
Outcome results
None listed