Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.

BACKGROUND: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A predictive model for RCC micrometastasis based on pathomics could be beneficial for clinicians to make treatment decisions. METHODS: A total of 895 formalin-fixed and paraffin-embedded whole slide images (WSIs) derived from three cohorts, including Shanghai General Hospital (SGH), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Cancer Genome Atlas (TCGA) cohorts, and another 588 frozen section WSIs from TCGA dataset were involved in the study. The deep learning-based strategy for predicting lymphatic metastasis was developed based on WSIs through clustering-constrained-attention multiple-instance learning method and verified among the three cohorts. The performance of the model was further verified in frozen-pathological sections. In addition, the model was also tested the prognosis prediction of patients with RCC in multi-source patient cohorts. RESULTS: The AUC of the lymphatic metastasis prediction performance was 0.836, 0.865 and 0.812 in TCGA, SGH and CPTAC cohorts, respectively. The performance on frozen section WSIs was with the AUC of 0.801. Patients with high deep learning-based prediction of lymph node metastasis values showed worse prognosis. CONCLUSIONS: In this study, we developed and verified a deep learning-based strategy for predicting lymphatic metastasis from primary RCC WSIs, which could be applied in frozen-pathological sections and act as a prognostic factor for RCC to distinguished patients with worse survival outcomes.

The feasibility of proteomics sequencing based immune-related prognostic signature for predicting clinical outcomes of bladder cancer patients.

BACKGROUND: Bladder cancer (BCa) shows its potential immunogenity in current immune-checkpoint inhibitor related immunotherapies. However, its therapeutic effects are improvable and could be affected by tumor immune microenvironment. Hence it is interesting to find some more prognostic indicators for BCa patients concerning immunotherapies. METHODS: In the present study, we retrospect 129 muscle-invasive BCa (MIBC) patients with radical cystectomy in Shanghai General Hospital during 2007 to 2018. Based on the results of proteomics sequencing from 9 pairs of MIBC tissue from Shanghai General Hospital, we focused on 13 immune-related differential expression proteins and their related genes. An immune-related prognostic signature (IRPS) was constructed according to Cancer Genome Atlas (TCGA) dataset. The IRPS was verified in ArrayExpress (E-MTAB-4321) cohort and Shanghai General Hospital (General) cohort, separately. A total of 1010 BCa patients were involved in the study, including 405 BCa patients in TCGA cohort, 476 BCa patients in E-MTAB-4321 cohort and 129 MIBC patients in General cohort. RESULT: It can be indicated that high IRPS score was related to poor 5-year overall survival and disease-free survival. The IRPS score was also evaluated its immune infiltration. We found that the IRPS score was adversely associated with GZMB, IFN-γ, PD-1, PD-L1. Additionally, higher IRPS score was significantly associated with more M2 macrophage and resting mast cell infiltration. CONCLUSION: The study revealed a novel BCa prognostic signature based on IRPS score, which may be useful for BCa immunotherapies.

PD-1-Positive Tumor-Associated Macrophages Define Poor Clinical Outcomes in Patients With Muscle Invasive Bladder Cancer Through Potential CD68/PD-1 Complex Interactions.

Tumor-associated macrophages (TAMs) regulate tumor immunity. Previous studies have shown that the programmed cell death protein 1 (PD-1)-positive TAMs have an M2 macrophage phenotype. CD68 is a biomarker of TAMs and is considered to be a poor prognostic marker of several malignancies. Our results show that PD-1-positive TAMs can be a negative survival indicator in patients with muscle-invasive bladder cancer (MIBC), and that the mechanistic effects could result due to a combination of PD-1 and CD68 activity. We analyzed 22 immune cell types using data from 402 patients with MIBC from the TCGA database, and found that a high immune score and M2 TAMs were strongly associated with poor clinical outcomes in patients with MIBC. Further, we analyzed resected samples from 120 patients with MIBC and found that individuals with PD-1-positive TAMs showed a reduction in 5-year overall survival and disease-free survival. Additionally, PD-1-positive TAMs showed a significant association with higher programmed death-ligand 1 (PD-L1) expression, the Ki67 index, the pT stage and fewer CD8-positive T cells. Through the co-immunoprecipitation (co-IP) assay of THP-1 derived macrophages, we found that CD68 can bind to PD-1. The binding of CD68 and PD-1 can induce M2 polarization of THP-1 derived macrophages and promote cancer growth. The anti-CD68 treatment combined with peripheral blood mononuclear cells (PBMC) showed obvious synergy effects on inhibiting the proliferation of T24 cells. Together, these results indicate for the first time that CD68/PD-1 may be a novel target for the prognosis of patients with MIBC.