Three-gene prognostic biomarkers for seminoma identified by weighted gene co-expression network analysis

Abstract

Testicular germ cell tumors (TGCTs) are common in young males, and seminoma accounts for a large proportion of TGCTs. However, there are limited records on the exploration of novel biomarkers for seminoma. Hence, we aimed to identify new biomarkers associated with overall survival in seminoma. mRNA-seq and clinical traits of TGCTs were downloaded from UCSC XENA and analyzed by weighted gene co-expression network analysis. After intersection with differentially expressed genes in GSE8607, common genes were subjected to protein-protein interaction (PPI) network construction and enrichment analyses. Then, the top 10 common genes were investigated by Kaplan–Meier (KM) survival analyses and univariate Cox regression analyses. Ultimately, TYROBP , CD68 , and ITGAM were considered three prognostic biomarkers in seminoma. Based on correlation analysis between these genes and immune infiltrates, we suggest that the three biomarkers influence the survival of seminoma patients, possibly through regulating the infiltration of immune cells. In conclusion, our study demonstrated that TYROBP , CD68 , and ITGAM could be regarded as prognostic biomarkers and therapeutic targets for seminoma patients.

Machine learning-based identification of tumor-infiltrating immune cell-associated model with appealing implications in improving prognosis and immunotherapy response in bladder cancer patients

“…Thus, screening novel biomarkers is urgently needed to address this concern. With the development of high-throughput sequencing and increased demand for precision therapy, a wealth of predictive and prognostic biomarkers have been identified, and mounting multigene signatures have been established in previous studies (26,27). Although these published signatures demonstrated satisfactory performance in their training and external testing datasets, their performance decreased dramatically in other datasets (15).…”

The role of SPI1-TYROBP-FCER1G network in oncogenesis and prognosis of osteosarcoma, and its association with immune infiltration

“…Although the network was upregulated in certain cancer types (e.g., clear cell renal cell carcinoma, breast cancer, gastric cancer, and low-grade glioma) and positively associated with the poorer prognosis and higher immune infiltrations, the network was downregulated in OS, positively associated with higher immune infiltrations in OS, and negatively associated with the poorer prognosis of OS. Therefore, despite the same positive-correlation between TYROBP network and higher immune infiltrations across multiple cancer types [ 38 – 45 ], the associations between TYROBP network and overall survival in different cancer types were different, suggesting the altered role of immune infiltration or altered major infiltrating cell types among different cancer types. In a word, SPI1-TYROBP-FCER1G network is a conserved immune-related network underlying both the oncogenesis and the prognosis of OS and other cancer types.…”

“…Across multiple cancer studies, the TYROBP network was always positively-associated with immune infiltration, such as the increased infiltration of CD8 + T cells, DCs, and macrophages [ 38 – 45 ]. According to our study on its potential mechanism, the overexpression of TYROBP network may activate the immune infiltration by the co-expressed immune stimulators, MHC molecules, and chemokines.…”

POLR3G promotes EMT via PI3K/AKT signaling pathway in bladder cancer

“…As a result, physicians are now able to select high‐risk patients and potential responders with greater accuracy. This allows for the preferential use of chemotherapy or immune checkpoint blockade‐based immunotherapy, providing more personalized treatment approaches and improving patient outcomes 8–11 . Despite the availability of molecular biomarkers, their usefulness in clinical settings is often limited due to underutilized data information, lack of clinical validation, and insufficient independent verification.…”

“…This allows for the preferential use of chemotherapy or immune checkpoint blockade-based immunotherapy, providing more personalized treatment approaches and improving patient outcomes. [8][9][10][11] Despite the availability of molecular biomarkers, their usefulness in clinical settings is often limited due to underutilized data information, lack of clinical validation, and insufficient independent verification. To improve the prognosis of BLCA patients, it is critical to identify effective strategies that can overcome these limitations.…”