Targeting TJP1 attenuates cell-cell aggregation and modulates chemosensitivity against doxorubicin in leiomyosarcoma

Comparative Assessment of miR-185-5p and miR-191-5p Expression: From Normal Endometrium to High-Grade Endometrial Cancer

Endometrial cancer (EC) is a significant cause of cancer-related deaths in women. MicroRNAs (miRs) play a role in cancer development, acting as oncogenes or tumor suppressors. This study evaluated the diagnostic potential of hsa-miR-185-5p and hsa-miR-191-5p in EC and their correlation with clinical and histopathological features. A cross-sectional study analyzed formalin-fixed, paraffin-embedded tissue samples from 59 patients: 18 with EC, 21 with endometrial hyperplasia (EH), 17 with normal endometrium (NE), and 3 with endometrial polyps (EPs). Quantitative reverse transcription-polymerase chain reaction and TaqMan probes were used for miR expression analysis. The Shapiro-Wilk test was used to analyze the normal distribution of the data. Subsequently, parametric or non-parametric tests were used to evaluate the associations between the expression levels of each miR and clinical parameters. Both miRs were underexpressed in some precursor and malignant lesions compared to certain NE subtypes and benign lesions. Specifically, hsa-miR-185-5p showed underexpression in grade 3 EC compared to some NE and EH subtypes (FC: -57.9 to -8.5, p < 0.05), and hsa-miR-191-5p was underexpressed in EH and EC compared to secretory endometrium and EPs (FC: -4.2 to -32.8, p < 0.05). SETD1B, TJP1, and MSI1 were common predicted target genes. In conclusion, hsa-miR-185-5p and hsa-miR-191-5p are underexpressed in EC tissues, correlating with histopathological grades, highlighting their potential as diagnostic biomarkers and their role as tumor suppressors in EC.

THP-1 Monocytic Cells Are Polarized to More Antitumorigenic Macrophages by Serial Treatment with Phorbol-12-Myristate-13-Acetate and PD98059

Background and Objectives: As modulators of the tumor microenvironment, macrophages have been extensively studied for their potential in developing anticancer strategies, particularly in regulating macrophage polarization towards an antitumorigenic (M1) phenotype rather than a protumorigenic (M2) one in various experimental models. Here, we evaluated the effect of PD98059, a mitogen-activated protein kinase kinase MAPKK MEK1-linked pathway inhibitor, on the differentiation and polarization of THP-1 monocytes in response to phorbol-12-myristate-13-acetate (PMA) under various culture conditions for tumor microenvironmental application. Materials and Methods: Differentiation and polarization of THP-1 were analyzed by flow cytometry and RT-PCR. Polarized THP-1 subsets with different treatment were compared by motility, phagocytosis, and so on. Results: Clearly, PMA induced THP-1 differentiation occurs in adherent culture conditions more than nonadherent culture conditions by increasing CD11b expression up to 90%, which was not affected by PD98059 when cells were exposed to PMA first (post-PD) but inhibited when PD98059 was treated prior to PMA treatment (pre-PD). CD11bhigh THP-1 cells treated with PMA and PMA-post-PD were categorized into M0 (HLA-DRlow and CD206low), M1 (HLA-DRhigh and CD206low), and M2 (HLA-DRlow and CD206high), resulting in an increased population of M1 macrophages. The transcription levels of markers of macrophage differentiation and polarization confirmed the increased M1 polarization of THP-1 cells with post-PD treatment rather than with PMA-only treatment. The motility and cytotoxicity of THP-1 cells with post-PD treatment were higher than THP-1 cells with PMA, suggesting that post-PD treatment enhanced the anti-tumorigenicity of THP-1 cells. Confocal microscopy and flow cytometry showed the effect of post-PD treatment on phagocytosis by THP-1 cells. Conclusions: We have developed an experimental model of macrophage polarization with THP-1 cells which will be useful for further studies related to the tumor microenvironment.

Transcriptome Profiling Based at Different Time Points after Hatching Deepened Our Understanding on Larval Growth and Development of Amphioctopus fangsiao

As the quality of life improves, there is an increasing demand for nutrition-rich marine organisms like fish, shellfish, and cephalopods. To address this, artificial cultivation of these organisms is being explored along with ongoing research on their growth and development. A case in point is Amphioctopus fangsiao, a highly valued cephalopod known for its tasty meat, nutrient richness, and rapid growth rate. Despite its significance, there is a dearth of studies on the A. fangsiao growth mechanism, particularly of its larvae. In this study, we collected A. fangsiao larvae at 0, 4, 12, and 24 h post-hatching and conducted transcriptome profiling. Our analysis identified 4467, 5099, and 4181 differentially expressed genes (DEGs) at respective intervals, compared to the 0 h sample. We further analyzed the expression trends of these DEGs, noting a predominant trend of continuous upregulation. Functional exploration of this trend entailed GO and KEGG functional enrichment along with protein-protein interaction network analyses. We identified GLDC, DUSP14, DPF2, GNAI1, and ZNF271 as core genes, based on their high upregulation rate, implicated in larval growth and development. Similarly, CLTC, MEF2A, PPP1CB, PPP1R12A, and TJP1, marked by high protein interaction numbers, were identified as hub genes and the gene expression levels identified via RNA-seq analysis were validated through qRT-PCR. By analyzing the functions of key and core genes, we found that the ability of A. fangsiao larvae to metabolize carbohydrates, lipids, and other energy substances during early growth may significantly improve with the growth of the larvae. At the same time, muscle related cells in A. fangsiao larvae may develop rapidly, promoting the growth and development of larvae. Our findings provide preliminary insights into the growth and developmental mechanism of A. fangsiao, setting the stage for more comprehensive understanding and broader research into cephalopod growth and development mechanisms.

Alpha-Lipoic Acid Promotes Intestinal Epithelial Injury Repair by Regulating MAPK Signaling Pathways

Intestinal epithelial cells are an essential barrier in human gastrointestinal tract, and healing of epithelial wound is a key process in many intestinal diseases. α-Lipoic acid (ALA) was shown to have antioxidative and anti-inflammatory effects, which could be helpful in intestinal epithelial injury repair. The effects of ALA in human colonic epithelial cells NCM460 and human colorectal adenocarcinoma cells Caco-2 were studied. ALA significantly promoted NCM460 and Caco-2 migration, increased mucosal tight junction factors ZO-1 and OCLN expression, and ALA accelerated cell injury repair of both cells in wound healing assay. Western blot analysis indicated that ALA inhibited a variety of mitogen-activated protein kinase (MAPK) signaling pathways in the epithelial cells. In conclusion, ALA was beneficial to repair of intestinal epithelial injury by regulating MAPK signaling pathways.

TJP1 Contributes to Tumor Progression through Supporting Cell-Cell Aggregation and Communicating with Tumor Microenvironment in Leiomyosarcoma

Leiomyosarcoma (LMS) is a mesenchymal malignancy with a complex karyotype. Despite accumulated evidence, the factors contributing to the development of LMS are unclear. Here, we investigated the role of tight-junction protein 1 (TJP1), a membrane-associated intercellular barrier protein during the development of LMS and the tumor microenvironment. We orthotopically transplanted SK-LMS-1 cells and their derivatives in terms of TJP1 expression by intramuscular injection, such as SK-LMS-1 Sh-Control cells and SK-LMS-1 Sh-TJP1. We observed robust tumor growth in mice transplanted with LMS cell lines expressing TJP1 while no tumor mass was found in mice transplanted with SK-LMS-1 Sh-TJP1 cells with silenced TJP1 expression. Tissues from mice were stained and further analyzed to clarify the effects of TJP1 expression on tumor development and the tumor microenvironment. To identify the TJP1-dependent factors important in the development of LMS, genes with altered expression were selected in SK-LMS-1 cells such as cyclinD1, CSF1 and so on. The top 10% of highly expressed genes in LMS tissues were obtained from public databases. Further analysis revealed two clusters related to cell proliferation and the tumor microenvironment. Furthermore, integrated analyses of the gene expression networks revealed correlations among TJP1, CSF1 and CTLA4 at the mRNA level, suggesting a possible role for TJP1 in the immune environment. Taken together, these results imply that TJP1 contributes to the development of sarcoma by proliferation through modulating cell-cell aggregation and communication through cytokines in the tumor microenvironment and might be a beneficial therapeutic target.

Bioinformatics prediction and experimental verification identify MAD2L1 and CCNB2 as diagnostic biomarkers of rhabdomyosarcoma

Background

Rhabdomyosarcoma (RMS) is a malignant soft-tissue tumour. In recent years, the tumour microenvironment (TME) has been reported to be associated with the development of tumours. However, the relationship between the occurrence and development of RMS and TME is unclear. The purpose of this study is to identify potential tumor microenvironment-related biomarkers in rhabdomyosarcoma and analyze their molecular mechanisms, diagnostic and prognostic significance.

Methods

We first applied bioinformatics method to analyse the tumour samples of 125 patients with rhabdomyosarcoma (RMS) from the Gene Expression Omnibus database (GEO). Differential genes (DEGs) that significantly correlate with TME and the clinical staging of tumors were extracted. Immunohistochemistry (IHC) was applied to validate the expression of mitotic arrest deficient 2 like 1 (MAD2L1) and cyclin B2 (CCNB2) in RMS tissue. Then, we used cell function and molecular biology techniques to study the influence of MAD2L1 and CCNB2 expression levels on the progression of RMS.

Results

Bioinformatics results show that the RMS TME key genes were screened, and a TME-related tumour clinical staging model was constructed. The top 10 hub genes were screened through the establishment of a protein–protein interaction (PPI) network, and then Gene Expression Profiling Interactive Analysis (GEPIA) was conducted to measure the overall survival (OS) of the 10 hub genes in the sarcoma cases in The Cancer Genome Atlas (TCGA). Six DEGs of statistical significance were acquired. The relationship between these six differential genes and the clinical stage of RMS was analysed. Further analysis revealed that the OS of RMS patients with high expression of MAD2L1 and CCNB2 was worse and the expression of MAD2L1 and CCNB2 was related to the clinical stage of RMS patients. Gene set enrichment analysis (GSEA) revealed that the genes in MAD2L1 and CCNB2 groups with high expression were mainly related to the mechanism of tumour metastasis and recurrence. In the low-expression MAD2L1 and CCNB2 groups, the genes were enriched in the metabolic and immune pathways. Immunohistochemical results also confirmed that the expression levels of MAD2L1 (30/33, 87.5%) and CCNB2 (33/33, 100%) were remarkably higher in RMS group than in normal control group (0/11, 0%). Moreover, the expression of CCNB2 was related to tumour size. Downregulation of MAD2L1 and CCNB2 suppressed the growth, invasion, migration, and cell cycling of RMS cells and promoted their apoptosis. The CIBERSORT immune cell fraction analysis indicated that the expression levels of MAD2L1 and CCNB2 affected the immune status in the TME.

Conclusions

The expression levels of MAD2L1 and CCNB2 are potential indicators of TME status changes in RMS, which may help guide the prognosis of patients with RMS and the clinical staging of tumours.

CircCDYL Acts as a Tumor Suppressor in Wilms' Tumor by Targeting miR-145-5p

Circular RNAs (circRNA) have been reported to exert evident functions in many human carcinomas. However, the possible mechanisms concerning the circRNA in various tumors are still elusive. In this research, we analyzed the expression profile and biological functions of circular RNA CDYL (circCDYL, circBase ID: hsa_circ_0008285) in Wilms' tumor. Here, miRNA and gene expression were examined by real-time PCR in Wilms' tumor tissues and cell lines. The functions of circCDYL and its potential targets to influence cell proliferation, migration, and invasion in Wilms' tumor cells were determined by biological functional experiments in vitro and in vivo. We predicted and analyzed potential miRNA targets through online bioinformatic tools. To validate the interactions between circCDYL and its targets, we performed RNA fluorescence in situ hybridization, biotin-coupled miRNA capture assay, and biotin-coupled probe pull-down assay. Tight junction protein l (TJP1) was proved to be the target gene of the predicted miRNA by dual-luciferase reporter assay. The expression level of TJP1 in Wilms' tumor cells was identified via Western blot. We showed that circCDYL was downregulated in WT tissue compared with adjacent non-tumor tissue. Upregulation of circCDYL could reduce cell proliferation, migration, and invasion. Mechanically, circCDYL, functioning as a miRNA sponge, decreased the expression level of miR-145-5p and TJP1 3'UTR was validated as the target of miR-145-5p, facilitating the circCDYL/miR-145-5p/TJP1 axis. In conclusion, our study suggested circCDYL as a novel biomarker and therapeutic target for WT treatment.

Merida: a novel boolean logic based integer linear program for personalized cancer therapy

Motivation

A major goal of personalized medicine in oncology is the optimization of treatment strategies given measurements of the genetic and molecular profiles of cancer cells. To further our knowledge on drug sensitivity, machine learning techniques are commonly applied to cancer cell line panels.

Results

We present a novel integer linear programming formulation, called MEthod for Rule Identification with multi-omics DAta (MERIDA), for predicting the drug sensitivity of cancer cells. The method represents a modified version of the LOBICO method and yields easily interpretable models amenable to a Boolean logic-based interpretation. Since the proposed altered logical rules lead to an enormous acceleration of the running times of MERIDA compared to LOBICO, we cannot only consider larger input feature sets integrated from genetic and molecular omics data but also build more comprehensive models that mirror the complexity of cancer initiation and progression. Moreover, we enable the inclusion of a priori knowledge that can either stem from biomarker databases or can also be newly acquired knowledge gathered iteratively by previous runs of MERIDA. Our results show that this approach does not only lead to an improved predictive performance but also identifies a variety of putative sensitivity and resistance biomarkers. We also compare our approach to state-of-the-art machine learning methods and demonstrate the superior performance of our method. Hence, MERIDA has great potential to deepen our understanding of the molecular mechanisms causing drug sensitivity or resistance.

Availability and implementation

The corresponding code is available on github (https://github.com/unisb-bioinf/MERIDA.git).

Supplementary information

Supplementary data are available at Bioinformatics online.