High Expression of COL17A1 Predicts Poor Prognosis and Promotes the Tumor Progression via NF-κB Pathway in Pancreatic Adenocarcinoma

Collagen XVII regulates tumor growth in pancreatic cancer through interaction with the tumor microenvironment

Expression of the gene for collagen XVII (COL17A1) in tumor tissue is positively or negatively associated with patient survival depending on cancer type. High COL17A1 expression is thus a favorable prognostic marker for breast cancer but unfavorable for pancreatic cancer. This study explored the effects of COL17A1 expression on pancreatic tumor growth and their underlying mechanisms. Analysis of published single-cell RNA-sequencing data for human pancreatic cancer tissue revealed that COL17A1 was expressed predominantly in cancer cells rather than surrounding stromal cells. Forced expression of COL17A1 did not substantially affect the proliferation rate of the mouse pancreatic cancer cell lines KPC and AK4.4 in vitro. However, in mouse homograft tumor models in which KPC or AK4.4 cells were injected into syngeneic C57BL/6 or FVB mice, respectively, COL17A1 expression promoted or suppressed tumor growth, respectively, suggesting that the effect of COL17A1 on tumor growth was influenced by the tumor microenvironment. RNA-sequencing analysis of tumor tissue revealed effects of COL17A1 on gene expression profiles (including the expression of genes related to cell proliferation, the immune response, Wnt signaling, and Hippo signaling) that differed between C57BL/6-KPC and FVB-AK4.4 tumors. Our data thus suggest that COL17A1 promotes or suppresses cancer progression in a manner dependent on the interaction of tumor cells with the tumor microenvironment.

Establishment of a N1-methyladenosine-related risk signature for breast carcinoma by bioinformatics analysis and experimental validation

OBJECTIVES

Breast carcinoma (BRCA) has resulted in a huge health burden globally. N1-methyladenosine (m¹A) RNA methylation has been proven to play key roles in tumorigenesis. Nevertheless, the function of m¹A RNA methylation-related genes in BRCA is indistinct.

METHODS

The RNA sequencing (RNA-seq), copy-number variation (CNV), single-nucleotide variant (SNV), and clinical data of BRCA were acquired via The Cancer Genome Atlas (TCGA) database. In addition, the GSE20685 dataset, the external validation set, was acquired from the Gene Expression Omnibus (GEO) database. 10 m¹A RNA methylation regulators were obtained from the previous literature, and further analyzed through differential expression analysis by rank-sum test, mutation by SNV data, and mutual correlation by Pearson Correlation Analysis. Furthermore, the differentially expressed m¹A-related genes were selected through overlapping m¹A-related module genes obtained by weighted gene co-expression network analysis (WGCNA), differentially expressed genes (DEGs) in BRCA and DEGs between high- and low- m¹A score subgroups. The m¹A-related model genes in the risk signature were derived by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. In addition, a nomogram was built through univariate and multivariate Cox analyses. After that, the immune infiltration between the high- and low-risk groups was investigated through ESTIMATE and CIBERSORT. Finally, the expression trends of model genes in clinical BRCA samples were further confirmed by quantitative real-time PCR (RT‒qPCR).

RESULTS

Eighty-five differentially expressed m¹A-related genes were obtained. Among them, six genes were selected as prognostic biomarkers to build the risk model. The validation results of the risk model showed that its prediction was reliable. In addition, Cox independent prognosis analysis revealed that age, risk score, and stage were independent prognostic factors for BRCA. Moreover, 13 types of immune cells were different between the high- and low-risk groups and the immune checkpoint molecules TIGIT, IDO1, LAG3, ICOS, PDCD1LG2, PDCD1, CD27, and CD274 were significantly different between the two risk groups. Ultimately, RT-qPCR results confirmed that the model genes MEOX1, COL17A1, FREM1, TNN, and SLIT3 were significantly up-regulated in BRCA tissues versus normal tissues.

CONCLUSIONS

An m¹A RNA methylation regulator-related prognostic model was constructed, and a nomogram based on the prognostic model was constructed to provide a theoretical reference for individual counseling and clinical preventive intervention in BRCA.

The Role of Gene Expression in Stress Urinary Incontinence: An Integrative Review of Evidence

Stress urinary incontinence (SUI) is defined as unintentional urine leakage occurring as a consequence of increased intraabdominal pressure due to absent or weak musculus detrusor contractility. It affects postmenopausal women more often than premenopausal and is associated with quality of life (QoL) deterioration. The complex SUI etiology is generally perceived as multifactorial; however, the overall impact of environmental and genetic influences is deficiently understood. In this research report, we have disclosed the upregulation of 15 genes and the downregulation of 2 genes in the genetic etiology of SUI according to the accessible scientific literature. The analytical methods used for the analysis of gene expression in the studies investigated were immunohistochemistry, immunofluorescence staining, PCR, and Western blot. In order to facilitate the interpretation of the results, we have used GeneMania, a potent software which describes genetic expression, co-expression, co-localization, and protein domain similarity. The importance of this review on the genetic pathophysiology of SUI lies in determining susceptibility for targeted genetic therapy, detecting clinical biomarkers, and other possible therapeutic advances. The prevention of SUI with the timely recognition of genetic factors may be important for avoiding invasive operative urogynecological methods.

Expansion of mouse castration-resistant intermediate prostate stem cells in vitro

Background

Most castration-resistant prostate cancers (CRPCs) have a luminal phenotype with high androgen receptor (AR) and prostate-specific antigen (PSA) expression. Currently, it is difficult to culture castration-resistant luminal cells with AR and PSA expression.

Methods

We formulated a custom-made medium and isolated primary cells from the prostate of adult wild-type (WT) and TRAMP mice. The cells were characterized by immunofluorescence staining, transcriptomic analysis, and qRT-PCR verification. Their self-renewal and differentiation potential in vitro and in vivo were examined. We treated the cells with androgen deprivation and enzalutamide and performed immunofluorescence staining and western blotting to analyze their expression of AR and PSA.

Results

We isolated a novel type of castration-resistant intermediate prostate stem cells (CRIPSCs) from adult WT and TRAMP mice. The mouse CRIPSCs proliferated rapidly in two-dimensional (2D) culture dishes and can be cultured for more than six months. The mouse CRIPSCs expressed luminal markers (AR, PSA, and Dsg4), basal markers (CK5 and p63), Psca, and the intermediate cell marker (Ivl). Transcriptomic analysis showed that the mouse CRIPSCs had upregulated signaling pathways related to cancer development and drug resistance. In the long-term culture, TRAMP CRIPSCs had higher expression of the genes related to stem cells and cancers than WT mice. Both WT and TRAMP CRIPSCs formed organoids in Matrigel. WT CRIPSCs did not form prostate tissues when transplanted in vivo without urogenital sinus mesenchyme (UGM) cells. In contrast, TRAMP CRIPSCs formed prostate ducts in NOG mice without UGM  cells and differentiated into luminal, basal, and neuroendocrine cells. Androgens regulated AR translocation between the nucleus and cytoplasm in the mouse CRIPSCs. Treatment of androgen deprivation  (ADT) and enzalutamide reduced AR expression in WT and TRAMP CRIPSCs; however, this treatment promoted PSA expression in TRAMP, while not WT CRIPSCs, similar to the clinical observations of CRPC.

Conclusions

Our study established a method for isolating and expanding mouse CRIPSCs in 2D culture dishes. Mouse CRIPSCs had markers of basal and luminal cells, including AR and PSA, and can differentiate into prostate organoids and tissues. TRAMP CRIPSCs had elevated PSA expression upon ADT and enzalutamide treatment. Our method can be translated into clinical settings for CRPC precision medicine.

Integrated Analysis of ECT2 and COL17A1 as Potential Biomarkers for Pancreatic Cancer

Background

Pancreatic cancer (PC) is a malignant tumor of the digestive tract. It presents with atypical clinical symptoms and lacks specific diagnostic indicators. This study is aimed at exploring the potential biomarkers of PC.

Methods

TCGA database pancreatic cancer dataset was normalized and used to identify differentially expressed genes (DEGs). Survival, independent prognostic, and clinical correlation analyses were performed on DEGs to screen for key genes. DNA methylation, mutation, and copy number variation (CNV) analyses were used to analyze genetic variants in key genes. GSEA was performed to explore the functional enrichment of the key genes. Based on the expression of key genes, construction of a competing endogenous RNA (ceRNA) network, analysis of the tumor microenvironment (TME), and prediction of chemotherapeutic drug sensitivity were performed. Furthermore, the GEO database was used to validate the reliability of key genes.

Results

Two key genes (ECT2 and COL17A1) were identified, which were highly expressed in PC. The mRNA expression of ECT2 and COL17A1 was associated with DNA methylation and CNV. The cell cycle, proteasome, and pathways in cancer were enriched in the high-COL17A1 and ECT2 groups. The TME results showed that immune scores were decreased in the high-ECT2 group. CeRNA network results showed that there were eleven miRNAs were involved in the regulation of ECT2 and COL17A1. Moreover, pRRophetic analysis showed that 20 chemotherapeutic drugs were associated with ECT2 and COL17A1 expression.

Conclusions

Collectively, ECT2 and COL17A1 may be potential biomarkers for PC, providing a new direction for clinical diagnosis and treatment.