Recent Advances in Detection for Breast-Cancer-Derived Exosomes.

Breast cancer is the most common malignant tumor in women, its incidence is secret, and more than half of the patients are diagnosed in the middle and advanced stages, so it is necessary to develop simple and efficient detection methods for breast cancer diagnosis to improve the survival rate and quality of life of breast cancer patients. Exosomes are extracellular vesicles secreted by all kinds of living cells, and play an important role in the occurrence and development of breast cancer and the formation of the tumor microenvironment. Exosomes, as biomarkers, are an important part of breast cancer fluid biopsy and have become ideal targets for the early diagnosis, curative effect evaluation, and clinical treatment of breast cancer. In this paper, several traditional exosome detection methods, including differential centrifugation and immunoaffinity capture, were summarized, focusing on the latest research progress in breast cancer exosome detection. It was summarized from the aspects of optics, electrochemistry, electrochemiluminescence and other aspects. This review is expected to provide valuable guidance for exosome detection of clinical breast cancer and the establishment of more reliable, efficient, simple and innovative methods for exosome detection of breast cancer in the future.

Prediction of bladder cancer outcome by identifying and validating a mutation-derived genomic instability-associated long noncoding RNA (lncRNA) signature.

Bladder cancer is one of the most common malignant tumors worldwide. Accordingly, its incidence and mortality are high. One of the characteristics of cancer is genomic instability. New studies suggest that long non-coding RNAs (lncRNAs) play an important role in maintaining genomic instability. This study aimed to identify a genomic instability-associated lncRNA signature to predict the outcome of patients with bladder cancer. We downloaded data for bladder cancer patients from The Cancer Genome Atlas database to obtain lncRNA expression profiles as well as somatic mutation profiles. Using the lncRNA computational framework, a genomic instability-related lncRNA signature (GIlncSig) was established and the prognostic value of this signature was assessed and validated. A five-lncRNA signature based on genomic instability (CFAP58-DT, MIR100HG, LINC02446, AC078880.3, and LINC01833) was obtained from 58 differentially expressed lncRNAs. Patients were divided into high-risk and low-risk groups, with the high-risk group having a substantially worse prognosis than the low-risk group. Univariate and multivariate Cox analyses indicated that GIlncSig may be an independent prognostic factor; this finding was subsequently validated. In addition, enrichment analysis indicated that GIlncSig is associated with genomic instability in bladder cancer. GIlncSig has a predictive value for the prognosis of bladder cancer patients and provides guidance for the clinical treatment of these patients.

Toll-like receptor 2 (TLR2) is a candidate prognostic factor in testicular germ cell tumors as well as an indicator of immune function in the tumor microenvironment.

Testicular cancer is the most common malignant tumor in young men, and its incidence has increased in recent years. The tumor microenvironment (TME) plays a crucial role in the development and progression of tumors; however, the TME of testicular germ cell tumor (TGCT) is poorly understood. In this study, we downloaded information for 156 TGCT cases from The Cancer Genome Atlas (TCGA) database, used the ESTIMATE method to determine immune and stromal scores, and used CIBERSORT to calculate the proportion of tumor-infiltrating immune cells (TICs). The differentially expressed genes were subjected to a COX regression analysis and used for the construction of a protein-protein interaction (PPI) network. Toll-like receptor 2 (TLR2) was identified as a predictive marker by combining the results of the Cox regression analysis and PPI network. A survival analysis showed that TLR2 was positively correlated with TGCT survival. A gene set enrichment analysis indicated that genes in the high TLR2 expression group were enriched for cell adhesion molecules (CAMs) and the chemokine signaling pathway, and genes in the low TLR2 expression group were mainly enriched in the spliceosome. Regarding proportions of TICs, naive B cells and follicular helper T cells were negatively correlated with the expression of TLR2. This suggests that as TLR2 expression increases, the immunocompetence of the TME decreases. The expression of TLR2 may affect the prognosis of TGCT, suggesting that this locus can be used as a prognostic factor for TGCT.