Investigation of Tumor Microenvironment After CRPC Along With Before and After Neoadjuvant Therapy for Prostate Cancer

Prostate cancer is a high incidence of cancer in Europe and the United States. In recent years, due to factors such as increasing awareness of testing and an aging population, the incidence of prostate cancer in China has been increasing year by year, and it has become the sixth most common cancer in men. Most of the patients with middle-advanced prostate cancer respond to ADT treatment, but the vast majority of patients eventually develop castration-resistant prostate cancer (CRPC) after the disease recurs or continues to progress after castration treatment. The related drug resistance mechanism is mainly caused by abnormal AR signaling pathway, including AR gene amplification, AR splicing variant and AR coregulator activation and other factors. In recent years, studies have shown that inhibitory immune cell infiltration and immune microenvironment also promote the emergence of CRPC. The cytokine IL-23 secreted by infiltrating myeloid-derived suppressor cells (MDSCs) can activate the STAT3-RORγ pathway, which in turn activates the AR pathway, resulting in resistance to ADT and other AR-targeted therapies. In addition, advanced prostate cancer tissue has always been considered to be a relatively "cold" immune microenvironment with relatively little immune cell infiltration. Metastatic castration-resistant prostate cancer (mCRPC) lacks efficacy against immune checkpoint inhibitors such as PD-1, and only those with mismatch repair gene deficiency (dMMR) or microsatellite instability-high (MSI-H) have must benefit. Most studies have only focused on patients with advanced CRPC without systematically comparing the immune microenvironment of patients with early and advanced prostate cancer. Advances in next-generation sequencing (NGS) technologies have led to a greater understanding of genomic alterations in prostate cancer. The most common genomic abnormalities in this malignancy are the TMPRSS2-ETS transcription factor fusion, and mutations in TP53, AR, RB1, and PTEN/PIK3CA. Some of these abnormalities are already targeted with clinically available drugs. At present, there have been large-scale foreign research on prostate cancer, such as "The Cancer Genome Atlas" (TCGA), "International Cancer Genome Consortium" (ICGC), etc., and a western cancer omics research system has been established. In the Chinese Prostate Cancer Genome and Epigenome Atlas (CPGEA) study, the incidence of the hallmark ETS fusion (53% TCGA) was much lower in the Chinese prostate cancer population (9% CPGEA) in contrast to Western prostate cancer . Among Chinese prostate cancers, the highest gene fusion rates were SCHLAP1-UBE2E3 (29%) and PAOX-MTG1 (10%), and the researchers found that FOXA1 was the gene with the highest mutation rate (41%) in our Chinese prostate cancer patients. In terms of methylation, the Chinese cohort study is similar to the Western cohort, the prostate cancer genome is hypomethylated relative to normal prostate tissue, and the 5' untranslated region (UTR) and CpG island (CGI) are relatively hypermethylated, while the penetrance Introns, introns and repeat elements are hypomethylated. Megabase-scale partially methylated domains (PMDs) are widespread and affect up to half of the cancer genome, suggesting that tumor progression correlates with the extent of genome-wide hypomethylation. Given the many differences in the genomes of Chinese and western prostate cancer patients, the response of Chinese prostate cancer patients to various treatments and the changes in gene, transcription, and translation levels after treatment may also be different from foreign prostate cancer patients. However, NGS data for Chinese prostate cancer patients before and after chemotherapy, endocrine therapy, radiotherapy, or immunotherapy are still missing. The NGS data of these patients before and after treatment will provide new drug design targets and new drug development ideas for prostate cancer treatment in China, and will also provide a solid theoretical basis for the optimization of existing treatment methods.