Periodic Reporting for period 1 - milieuPCa (Defining the immunosuppressive milieu of prostate cancer with single cell Omics technologies)
Periodo di rendicontazione: 2021-05-01 al 2023-04-30
In recent years, novel immunotherapies, such as antibodies targeting immune checkpoints or CAR T cells, have revolutionized the way cancers are treated. Nonetheless, the treatment of solid tumors has remained challenging, inter alia due to the small number of tumor-infiltrating T lymphocytes or their inactivity in the immunosuppressive tumor microenvironment (TME). Prostate cancer is among the most common tumors in men. While early stages can be successfully managed by surgery or radiation, no curative treatment exists for advanced stages.
Here, we aimed at understanding the immune milieu of prostate cancer by employing bulk and single cell high-throughput sequencing on prostatectomy samples in order to obtain a comprehensive view of the immunosuppressive mechanisms in prostate carcinoma.
RNAseq data was collected for both tumor and normal adjacent regions from about 30 prostate cancer samples. Single cell data was collected for a subset of patients to have a deeper view of where the signal comes from. Integration of data obtained from these analyses is enabling us to improve our understanding of the complex interplay between the immune system and tumor cells.
These data will moreover provide a potent source for translational studies to diagnose and treat prostate cancer.
The project has been early terminated because the research fellow accepted a industry job offer. There are no publications yet, because data was collected until the research fellow left; however, a manuscript is in preparation.
Here, we aimed at understanding the immune milieu of prostate cancer by employing bulk and single cell high-throughput sequencing on prostatectomy samples in order to obtain a comprehensive view of the immunosuppressive mechanisms in prostate carcinoma.
RNAseq data was collected for both tumor and normal adjacent regions from about 30 prostate cancer samples. Single cell data was collected for a subset of patients to have a deeper view of where the signal comes from. Integration of data obtained from these analyses is enabling us to improve our understanding of the complex interplay between the immune system and tumor cells.
These data will moreover provide a potent source for translational studies to diagnose and treat prostate cancer.
The project has been early terminated because the research fellow accepted a industry job offer. There are no publications yet, because data was collected until the research fellow left; however, a manuscript is in preparation.
Fresh-frozen tissues from 31 prostate resectomies were selected in order to have samples representing various tumor stages with or without biochemical recurrence. Ethical approval was obtained from the Ethic Commission of the Medical Center of Freiburg (Project 21-1614). For those samples, tissue sections were diagnosed as tumorigenic or adjacent normal. RNAseq was performed on all tumor and normal adjacent samples, while scRNAseq was performed on a subset of those sample (8 tumor and 6 normal). For scRNAseq, nuclei dissociation was performed according to manufacture instruction (10x genomics) and the Chromium controller was used for the library preparation.
Data analysis was mainly performed on the R environment using packages such as EdgeR and Seurat for bulk and single cell data analysis.
Data integration is performed between scRNAseq and RNAseq. Differential gene expression obtained from different cell types from the scRNAseq is validated in RNAseq data. This allows to clarify if the signal coming from only a few cells is strong enough to be detected at the bulk level.
Data analysis was mainly performed on the R environment using packages such as EdgeR and Seurat for bulk and single cell data analysis.
Data integration is performed between scRNAseq and RNAseq. Differential gene expression obtained from different cell types from the scRNAseq is validated in RNAseq data. This allows to clarify if the signal coming from only a few cells is strong enough to be detected at the bulk level.
Gene expression enrichment analysis shows that normal samples overexpress genes involved in extracellular structure maintenance, while cancer samples show metabolic activation and in particular RNA translation of viral components. Enrichment analysis of samples at stage 2c shows that there is an initial degradation of maintenance of the extracellular structure, while samples at stage 3b show activation of pathways that allow bypass of DNA reparation.
Using data integration between bulk and single cell RNA-seq, various genes were found to have specificity in tumor proliferative cells, such as: PTPRT, LUZP2 and SCHLAP1.
Results will still need to be published in a peer reviewed journal and the socio-economic impact can only be seen on a long-term basis. Years will be necessary to translate biomedical results to clinics. However, the understanding of prostate cancer microenvironment is at the foundation for the development of novel therapeutic approaches.
Using data integration between bulk and single cell RNA-seq, various genes were found to have specificity in tumor proliferative cells, such as: PTPRT, LUZP2 and SCHLAP1.
Results will still need to be published in a peer reviewed journal and the socio-economic impact can only be seen on a long-term basis. Years will be necessary to translate biomedical results to clinics. However, the understanding of prostate cancer microenvironment is at the foundation for the development of novel therapeutic approaches.