Identification of Immune-Related Breast Cancer Chemotherapy Resistance Genes via Bioinformatics Approaches.

Chemotherapy resistance in breast cancer is an important factor affecting the prognosis of breast cancer patients. We computationally analyzed the differences in gene expression before and after chemotherapy in breast cancer patients, drug-sensitive groups, and drug-resistant groups. Through functional enrichment analysis, immune microenvironment analysis, and other computational analysis methods, we identified PRC1, GGTLC1, and IRS1 as genes that may mediate breast cancer chemoresistance through the immune pathway. After validation of certain other clinical datasets and in vitro cellular assays, we found that the above three genes influenced drug resistance in breast cancer patients and were closely related to the tumor immune microenvironment. Our finding that chemoresistance in breast cancer could be influenced by the mediation of tumor immunity expanded our knowledge of how to address this problem and could guide future research involving chemoresistance.

Identification of Novel Diagnostic Biomarkers in Prostate Adenocarcinoma Based on the Stromal-Immune Score and Analysis of the WGCNA and ceRNA Network.

Prostate cancer is still a significant global health burden in the coming decade. Novel biomarkers for detection and prognosis are needed to improve the survival of distant and advanced stage prostate cancer patients. The tumor microenvironment is an important driving factor for tumor biological functions. To investigate RNA prognostic biomarkers for prostate cancer in the tumor microenvironment, we obtained relevant data from The Cancer Genome Atlas (TCGA) database. We used the bioinformatics tools Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm and weighted coexpression network analysis (WGCNA) to construct tumor microenvironment stromal-immune score-based competitive endogenous RNA (ceRNA) networks. Then, the Cox regression model was performed to screen RNAs associated with prostate cancer survival. The differentially expressed gene profile in tumor stroma was significantly enriched in microenvironment functions, like immune response, cancer-related pathways, and cell adhesion-related pathways. Based on these differentially expressed genes, we constructed three ceRNA networks with 152 RNAs associated with the prostate cancer tumor microenvironment. Cox regression analysis screened 31 RNAs as the potential prognostic biomarkers for prostate cancer. The most interesting 8 prognostic biomarkers for prostate cancer included lncRNA LINC01082, miRNA hsa-miR-133a-3p, and genes TTLL12, PTGDS, GAS6, CYP27A1, PKP3, and ZG16B. In this systematic study for ceRNA networks in the tumor environment, we screened out potential biomarkers to predict prognosis for prostate cancer. Our findings might apply a valuable tool to improve prostate cancer clinical management and the new target for mechanism study and therapy.

Folate receptor-positive circulating tumor cell count, lymphocyte count and derived neutrophil-to- lymphocyte ratio for diagnosing lung cancer relapse.

The folate receptor-positive circulating tumor cell (FR+-CTC) count can be used to improve the diagnosis rate of lung cancer. The lymphocyte count (LC) and derived neutrophil-to-lymphocyte ratio (dNLR) are involved in inflammatory processes. Whether the FR+-CTC count combined with the dNLR or LC is helpful for diagnosing lung cancer recurrence is not clear. Sixty-eight patients who were initially diagnosed with lung cancer and received first-line treatment were included. The clinicopathological characteristics, routine blood examination results and CTC examination results of the patients were collected. The role of the complete blood count and FR+-CTC count in lung cancer treatment response and prognosis was analyzed. The FR+-CTC count after treatment was significantly correlated with the T stage (p=0.005). Multivariate analysis showed that the pathological type and FR+-CTC count were independent predictors of disease-or progression-free survival (DFS/PFS) in patients with lung cancer (p=0.010 and p=0.030, respectively). The FR+-CTC count, LC and dNLR predicted the recurrence of lung cancer (sensitivity and specificity of the FR+-CTC count, 69.2% and 71.4%; the LC, 50.0% and 88.5%; and the dNLR, 50.0% and 88.1%, respectively). The FR+-CTC count combined with the LC or dNLR improved the diagnostic rate of lung cancer recurrence (sensitivity and specificity of the FR+-CTC count plus the LC, 53.8% and 90.5%, and the FR+-CTC count plus the dNLR, 73.1% and 73.8%, respectively). When these three indicators were combined to predict lung cancer recurrence, the AUC value was 0.817. The FR+-CTC count combined with the dNLR and/or LC after treatment can improve the diagnostic rate of lung cancer recurrence. A higher FR+-CTC count predicts worse DFS/PFS in patients with lung cancer.

Latex agglutination: diagnose the early cryptococcus neoformans test of capsular polysaccharide antigen.

This paper aims to discuss the early diagnosis value of latex agglutination test in Cryptococcal meningitis. The cerebrospinal fluid (CSF) of 112 patients with definite Cryptococcal meningitis and 26 patients with tubercular meningitis and virus meningitis were collected, latex agglutination test is adopted to detect Cryptococcal capsular polysaccharide antigen. Then it was compared with fungal culture and direct microscopy method for evaluating the sensitivity and specificity of the diagnosis. The sensitivity of three methods including latex agglutination test, fungal culture and direct microscopy was 91.1%,69.6% and 73.2% respectively. The specificity of latex agglutination test was 96.0%, 100% and 100% respectively. That latex agglutination test to detect Cryptococcal capsular polysaccharide antigen could be taken as the early diagnostic method of Cryptococcus neoformans meningitis.