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Abstract Background Tumor-associated macrophages (TAM) are critical elements of intercellular communication in tumor microenvironment (TME), and exosomes are key mediators between tumor cells and the TME. According to previous reports, miRNAs exert a pivotal role in ovarian cancer (OC) development. The purpose of this work was to explore the function of TAM-derived exosomal miR-589-3p in OC development and elucidate the underlying molecular mechanisms. Methods First, peripheral blood mononuclear cells (PBMC) were treated with IL-4 and IL-13 to polarize them into M2-type macrophages. Exosomes were separated from M2-type macrophages, and the physical properties of exosomes were evaluated using transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA). Next, quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) was applied to examine the expression of relevant genes. Subsequently, Targetscan and miRDB were utilized to predict miR-589-3p target genes, and then the interaction between miR-589-3p and BCL2L13 was verified by dual luciferase assay and RNA Binding Protein Immunoprecipitation (RIP) assay. Finally, Cell Counting Kit-8 (CCK-8) and flow cytometry experiments were employed to explore the changes in the proliferative and apoptotic abilities of OC cells. Results In this research, we demonstrated that TAM-derived exosomes facilitated OC cell proliferation and suppressed OC cell apoptosis. Then, qRT-PCR results indicated that miR-589-3p were markedly elevated after co-culture of TAM-derived exosomes with OC cells. In addition, we discovered that miR-589-3p was bound to BCL-2-like protein 13 (BCL2L13), which was confirmed through luciferase assay and RIP assay. Furthermore, functional analysis displayed that TAM-derived exosomes treated with miR-589-3p inhibitor attenuated the promotion of OC cell progression by exosomes. Conclusion TAM-derived exosomal miR-589-3p enhanced OC progression through BCL2L13, which offers a novel for OC therapy.

Abstract Background T1 mapping can quantify the longitudinal relaxation time of tissues. This study aimed to investigate the repeatability and reproducibility of T1 mapping radiomics features of lung cancer and the feasibility of T1 mapping-based radiomics model to predict its pathological types. Methods The chest T1 mapping images and clinical characteristics of 112 lung cancer patients (54 with adenocarcinoma and 58 with other types of lung cancer) were collected retrospectively. 54 patients underwent twice short-term T1 mapping scans. Regions of interest were manually delineated on T1 mapping pseudo-color images to measure the mean native T1 values of lung cancer, and radiomics features were extracted using the semi-automatic segmentation method by two independent observers. The patients were randomly divided into training group (77 cases) and validation group (35 cases) with the ratio of 7:3. Interclass correlation coefficients (ICCs), Student’s t-test or Mann-Whitney U tests and least absolute shrinkage and selection operator (LASSO) were used for feature selection. The optimum features were selected to establish a logistic regression (LR) radiomics model. Independent sample t-test, Mann Whitney U-test or chi square test were used to compare the differences of clinical characteristics and T1 values. Performance was compared by the area under the receiver operating characteristic (ROC) curve (AUC). Results In the training group, smoking history, lesion type and native T1 values were different between adenocarcinoma and non-adenocarcinoma patients (P = 0.004–0.038). There were 1035 (54.30%) radiomics features meet the intra-and inter-observer, and test-retest reproducibility with ICC > 0.80. After feature dimensionality reduction and model construction, the AUC of T1 mapping-based radiomics model for predicting the pathological types of lung cancer was 0.833 and 0.843, respectively, in the training and validation cohorts. The AUCs of T1 value and clinical model (including smoking history and lesion type) were 0.657 and 0.692 in the training group, and 0.722 and 0.686 in the validation group. Combined with T1 mapping radiomics, clinical model and T1 value to establish a combined model, the prediction efficiency was further improved to 0.895 and 0.915 in the training and validation groups. Conclusions About 50% of the T1 mapping-based radiomics features displayed relatively poor repeatability and reproducibility. While T1 mapping-based radiomics model is valuable in identification of histological types of lung cancer despite the measurement variability. Combination of T1 mapping radiomics model, clinical characteristics and native T1 value can improve the predictive value of pathological types of lung cancer.

Abstract Positive human epidermal growth factor receptor 2 (HER2) expression is associated with an increased risk of metastases especially those to the brain in patients with advanced breast cancer (BC). Neratinib as a tyrosine kinase inhibitor can prevent the transduction of HER1, HER2 and HER4 signaling pathways thus playing an anticancer effect. Moreover, neratinib has a certain efficacy to reverse drug resistance in patients with BC with previous HER2 monoclonal antibody or targeted drug resistance. Neratinib, as monotherapy and in combination with other therapies, has been tested in the neoadjuvant, adjuvant, and metastatic settings. Neratinib with high anticancer activity is indicated for the prolonged adjuvant treatment of HER2-positive early BC, or in combination with other drugs including trastuzumab, capecitabine, and paclitaxel for the treatment of advanced HER2-positive BC especially cancers with central nervous system (CNS) metastasis to reduce the risk of BC recurrence. This article reviewed the pharmacological profiles, efficacy, safety, tolerability, and current clinical trials pertaining to neratinib, with a particular focus on the use of neratinib in patients with metastatic breast cancer (MBC) involving the CNS. We further discussed the use of neratinib for HER2-negative and HER2-mutant breast cancers, and mechanisms of resistance to neratinib. The current evidence suggests that neratinib has promising efficacy in patients with BC which is at least non-inferior compared to previous therapeutic regimens. The most common AE was diarrhea, and the incidence, severity and duration of neratinib-related grade 3 diarrhea can be reduced with loperamide. Of note, neratinib has the potential to effectively control and prevent brain metastasis in patients with advanced BC, providing a therapeutic strategy for HER2-positive BC.

Abstract Background Microsatellites are a ubiquitous occurrence in prokaryotic and eukaryotic genomes. Microsatellites have become one of the most popular classes of genetic markers due to their high reproducibility, multi-allelic nature, co-dominant mode of inheritance, abundance and wide genome coverage. We characterised microsatellites in the genomes and genes of two bat species, Pteropus vampyrus and Miniopterus natalensis. This characterisation was used for gene ontology analysis and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment of coding sequences (CDS). Results Compared to M. natalensis, the genome size of P. vampyrus is larger and contains more microsatellites, but the total diversity of both species is similar. Mononucleotide and dinucleotide repeats were the most diverse in the genome of the two species. In each bat species, the microsatellite bias was obvious. The microsatellites with the largest number of repeat motifs in P. vampyrus from mononucleotide to hexanucleotide were (A)n, (AC)n, (CAA)n, (AAAC)n, (AACAA)n and (AAACAA)n, with frequencies of 97.94%, 58.75%, 30.53%, 22.82%, 54.68% and 22.87%, respectively, while in M. natalensis were (A)n, (AC)n, (TAT)n, (TTTA)n, (AACAA)n and (GAGAGG)n, with of 92.00%, 34.08%, 40.36%, 21.83%, 25.42% and 12.79%, respectively. In both species, the diversity of microsatellites was highest in intergenic regions, followed by intronic, untranslated and exonic regions and lowest in coding regions. Location analysis indicated that microsatellites were mainly concentrated at both ends of the genes. Microsatellites in the CDS are thus subject to higher selective pressure. In the GO analysis, two unique GO terms were found only in P. vampyrus and M. natalensis, respectively. In KEGG enriched pathway, the biosynthesis of other secondary metabolites and metabolism of other amino acids in metabolism pathways were present only in M. natalensis. The combined biological process, cellular components and molecular function ontology are reflected in the GO analysis and six functional enrichments in KEGG annotation, suggesting advantageous mutations during species evolution. Conclusions Our study gives a comparative characterization of the genomes of microsatellites composition in the two bat species. And also allow further study on the effect of microsatellites on gene function as well as provide an insight into the molecular basis for species adaptation to new and changing environments.

Abstract Background Radiofrequency ablation (RFA) is an effective treatment option for hepatocellular carcinoma (HCC). This study aimed to analyze the prognostic factors of HCC patients treated with RFA and to develop nomograms for outcome prediction. Methods A total of 3142 HCC patients treated with RFA were recruited, and their data were collected from the Surveillance, Epidemiology, and End Results database. Univariate and multifactor Cox analyses were performed to identify independent prognostic factors. These factors were integrated into a nomogram to predict 3- and 5-year cancer-specific survival (CSS) and overall survival (OS). Consistency indices and calibration plots were used to assess the accuracy of the nomograms in both the internal and external cohorts. Results The median follow-up periods for HCC patients treated with RFA were 27 and 29 months for OS and CSS, respectively. Marital status, age, race, histological grade of differentiation, tumor size, T stage, and serum alpha-fetoprotein levels at the time of diagnosis were identified as prognostic factors for OS and CSS. Additionally, M stage was identified as risk factors for OS. These risk factors are included in the nomogram. The calibration plots of the OS and CSS nomograms showed excellent consistency between actual survival and nomogram predictions. The bootstrap-corrected concordance indices of the OS and CSS nomograms were 0.637 (95% CI, 0.628–0.646) and 0.670 (95% 0.661–0.679), respectively. Importantly, our nomogram performed better discriminatory compared with 8th edition tumor-node-metastasis (TNM) stage system for predicting OS and CSS. Conclusions We identified prognostic factors for HCC patients treated with RFA and provided an accurate and personalized survival prediction scheme.

Abstract Background Cancer metastasis is the major reason for cancer related deaths, and the mechanism of cancer metastasis still unclear. RPLP1, a member of a group of proteins known as ribosomal proteins, is associated with tumorigenesis and primary cell immortalization and is involved in cellular transformation. However, the expression and potential function of RPLP1 in TNBC remain unclear. Methods The expression of RPLP1 in TNBC tissues and cell lines were detected with Real-Time PCR and western blotting. 81 cases of TNBC tissue samples and adjacent non-tumor tissue samples were tested by immunochemistry to determine the correlation between the RPLP1 expression and clinicopathological characteristics. In vitro, we determined the role and mechanistic pathways of RPLP1 in tumor metastasis in TNBC cell lines. Results In this study, we detected high levels of RPLP1 expression in TNBC samples and cell lines. RPLP1 is upregulated in triple-negative breast cancer (TNBC) tissues and cells, and high expression levels correlate with an increased risk of recurrence and metastasis. Furthermore, high RPLP1 expression was associated with a poor prognosis and was an independent prognostic marker for TNBC. In RPLP1-induced cancer metastasis, RPLP1 may increase cancer cell invasion, which is likely the result of its effect on the cancer cell epithelial-mesenchymal transition. Conclusions Altogether, our findings indicate RPLP1 is a poor prognostic potential biomarker and anti-metastasis candidate therapeutic target in triple-negative breast cancer.