Human ACAP2 is a homolog of C. elegans CNT-1 that promotes apoptosis in cancer cells

Forensic age estimation from human blood using age-related microRNAs and circular RNAs markers

Aging is a complicated process characterized by progressive and extensive changes in physiological homeostasis at the organismal, tissue, and cellular levels. In modern society, age estimation is essential in a large variety of legal rights and duties. Accumulating evidence suggests roles for microRNAs (miRNAs) and circular RNAs (circRNAs) in regulating numerous processes during aging. Here, we performed circRNA sequencing in two age groups and analyzed microarray data of 171 healthy subjects (17-104 years old) downloaded from Gene Expression Omnibus (GEO) and ArrayExpress databases with integrated bioinformatics methods. A total of 1,403 circular RNAs were differentially expressed between young and old groups, and 141 circular RNAs were expressed exclusively in elderly samples while 10 circular RNAs were expressed only in young subjects. Based on their expression pattern in these two groups, the circular RNAs were categorized into three classes: age-related expression between young and old, age-limited expression-young only, and age-limited expression-old only. Top five expressed circular RNAs among three classes and a total of 18 differentially expressed microRNAs screened from online databases were selected to validate using RT-qPCR tests. An independent set of 200 blood samples (20-80 years old) was used to develop age prediction models based on 15 age-related noncoding RNAs (11 microRNAs and 4 circular RNAs). Different machine learning algorithms for age prediction were applied, including regression tree, bagging, support vector regression (SVR), random forest regression (RFR), and XGBoost. Among them, random forest regression model performed best in both training set (mean absolute error = 3.68 years, r = 0.96) and testing set (MAE = 6.840 years, r = 0.77). Models using one single type of predictors, circular RNAs-only or microRNAs-only, result in bigger errors. Smaller prediction errors were shown in males than females when constructing models according to different-sex separately. Putative microRNA targets (430 genes) were enriched in the cellular senescence pathway and cell homeostasis and cell differentiation regulation, indirectly indicating that the microRNAs screened in our study were correlated with development and aging. This study demonstrates that the noncoding RNA aging clock has potential in predicting chronological age and will be an available biological marker in routine forensic investigation to predict the age of biological samples.

Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils the Characteristics of the Immune Microenvironment and Prognosis Signature in Prostate Cancer

The immune microenvironment is a culmination of the collaborative effort of immune cells and is important in cancer development. The underlying mechanisms of the tumor immune microenvironment in regulating prostate cancer (PRAD) are unclear. In the current study, 144 natural killer cell-related genes were identified using differential expression, single-sample gene set enrichment analysis, and weighted gene coexpression network analysis. Furthermore, VCL, ACTA2, MYL9, MYLK, MYH11, TPM1, ACTG2, TAGLN, and FLNC were selected as hub genes via the protein-protein interaction network. Based on the expression patterns of the hub genes, endothelial, epithelial, and tissue stem cells were identified as key cell subpopulations, which could regulate PRAD via immune response, extracellular signaling, and protein formation. Moreover, 27 genes were identified as prognostic signatures and used to construct the risk score model. Receiver operating characteristic curves revealed the good performance of the risk score model in both the training and testing datasets. Different chemotherapeutic responses were observed between the low- and high-risk groups. Additionally, a nomogram based on the risk score and other clinical features was established to predict the 1-, 3-, and 5-year progression-free interval of patients with PRAD. This study provides novel insights into the molecular mechanisms of the immune microenvironment and its role in the pathogenesis of PARD. The identification of key cell subpopulations has a potential therapeutic and prognostic use in PRAD.

A novel lncRNA-mRNA-miRNA signature predicts recurrence and disease-free survival in cervical cancer

Cervical cancer (CC) patients have a poor prognosis due to the high recurrence rate. However, there are still no effective molecular signatures to predict the recurrence and survival rates for CC patients. Here, we aimed to identify a novel signature based on three types of RNAs [messenger RNA (mRNAs), microRNA (miRNAs), and long non-coding RNAs (lncRNAs)]. A total of 763 differentially expressed mRNAs (DEMs), 46 lncRNAs (DELs), and 22 miRNAs (DEMis) were identified between recurrent and non-recurrent CC patients using the datasets collected from the Gene Expression Omnibus (GSE44001; training) and The Cancer Genome Atlas (RNA- and miRNA-sequencing; testing) databases. A competing endogenous RNA network was constructed based on 23 DELs, 15 DEMis, and 426 DEMs, in which 15 DELs, 13 DEMis, and 390 DEMs were significantly associated with disease-free survival (DFS). A prognostic signature, containing two DELs (CD27-AS1, LINC00683), three DEMis (hsa-miR-146b, hsa-miR-1238, hsa-miR-4648), and seven DEMs (ARMC7, ATRX, FBLN5, GHR, MYLIP, OXCT1, RAB39A), was developed after LASSO analysis. The built risk score could effectively separate the recurrence rate and DFS of patients in the high- and low-risk groups. The accuracy of this risk score model for DFS prediction was better than that of the FIGO (International Federation of Gynecology and Obstetrics) staging (the area under receiver operating characteristic curve: training, 0.954 vs 0.501; testing, 0.882 vs 0.656; and C-index: training, 0.855 vs 0.539; testing, 0.711 vs 0.508). In conclusion, the high predictive accuracy of our signature for DFS indicated its potential clinical application value for CC patients.

Bioinformatics Analysis: The Regulatory Network of hsa_circ_0007843 and hsa_circ_0007331 in Colon Cancer

Objective

To analyze the molecular regulation network of circular RNA (circRNA) in colon cancer (CC) by bioinformatics method.

Methods

hsa_circ_0007843 and hsa_circ_0007331 proved to be associated with CC in previous studies were chosen as the research object. ConSite database was used to predict the transcription factors associated with circRNA, and the CC-associated transcription factors were screened out after intersection. The CircInteractome database was used to predict the RNA-binding proteins (RBPs) interacting with circRNAs and screen out the CC-associated RBPs after an intersection. Furthermore, the CircInteractome database was used to predict the miRNAs interrelated with circRNAs, and the HMDD v3.2 database was used to search for miRNAs associated with CC. The target mRNAs of miRNA were predicted by the miRWalk v3.0 database. CC-associated target genes were screened out from the GeneCards database, and the upregulated genes were enriched and analyzed by the FunRich 3.1.3 software. Finally, the molecular regulatory network diagram of circRNA in CC was plotted.

Results

The ConSite database predicted a total of 14 common transcription factors of hsa_circ_0007843 and hsa_circ_0007331, among which Snail, SOX17, HNF3, C-FOS, and RORα-1 were related to CC. The CircInteractome database predicted that the RBPs interacting with these two circRNAs were AGO2 and EIF4A3, and both of them were related to CC. A total of 17 miRNAs interacting with hsa_circ_0007843 and hsa_circ_0007331 were predicted by CircInteractome database. miR-145-5p, miR-21, miR-330-5p, miR-326, and miR-766 were associated with CC according to the HMDDv3.2 database. miR-145-5p and miR-330-5p, lowly expressed in CC, were analyzed in the follow-up study. A total of 676 common target genes of these two miRNAs were predicted by the miRWalk3.0 database. And 57 target genes were involved in the occurrence and development of CC from the GeneCards database, with 23 genes downregulated and 34 genes upregulated. Additionally, GO analysis showed that the 34 upregulated genes were mainly enriched in biological processes such as signal transduction and cell communication. KEGG pathway analysis showed that the upregulated genes were closely related to integrin, ErbB receptor, and ALK1 signal pathways. Finally, a complete regulatory network of hsa_circ_0007843 and hsa_circ_0007331 in CC was proposed, whereby each one of the participants was either directly or indirectly associated and whose deregulation may result in CC progression.

Conclusion

Predicting the molecular regulatory network of circRNAs by bioinformatics provides a new theoretical basis for further occurrence and development pathogenesis of CC and good guidance for future experimental research.

Prenatal detection of a 3q29 microdeletion in a fetus with ventricular septum defect: A case report and literature review

RATIONALE

Chromosomal 3q deletion is a recurrent genomic alternation, which is rarely reported in clinic.

PATIENT CONCERNS

A 27-year-old woman underwent amniocentesis for cytogenetic analysis and single nucleotide polymorphism (SNP) array analysis at 27 weeks of gestation, due to ventricular septum defect in prenatal ultrasound findings.

DIAGNOSES

G-banding analysis showed the karyotype of the fetus was normal and the couple also had normal karyotypes. However, SNP array detected a 1.71 Mb microdelection in 3q29, which was described as arr[hg19]3q29(194184392-195887205) × 1. There are 12 genes located in this locus.

INTERVENTIONS

The couple refused SNP array to testify the 3q29 microdeletion was inherited or de novo and they chose termination of pregnancy.

OUTCOMES

The deleted region in the fetus overlapped with part 3q29 microdeletion syndrome, which was characterized by learning disability, speech delay, mental deficiency, ocular abnormalities and craniofacial features. In addition, no similar/overlapping 3q29 microdeletion cases were reported according to the published literature and database.

LESSONS

For the chromosomal microscopic imbalances partially overlapping with the defined pathogenic syndrome, deleted/duplicated size, genetic materials and phenotypic diversity should be taken into consideration when genetic counseling is offered by the clinicians.

Cancer-associated fibroblasts-derived exosomal miR-3656 promotes the development and progression of esophageal squamous cell carcinoma via the ACAP2/PI3K-AKT signaling pathway

Esophageal squamous cell carcinoma (ESCC) is one of the most common gastrointestinal tumors, accounting for almost half a million deaths per year. Cancer-associated fibroblasts (CAFs) are the major constituent of the tumor microenvironment (TME) and dramatically impact ESCC progression. Recent evidence suggests that exosomes derived from CAFs are able to transmit regulating signals and promote ESCC development. In this study, we compared different the component ratios of miRNAs in exosomes secreted by CAFs in tumors and with those from normal fibroblasts (NFs) in precancerous tissues. The mRNA level of hsa-miR-3656 was significantly upregulated in the former exosomes. Subsequently, by comparing tumor cell development in vitro and in vivo, we found that the proliferation, migration and invasion capabilities of ESCC cells were significantly improved when miR-3656 was present. Further target gene analysis confirmed ACAP2 was a target gene regulated by miR-3656 and exhibited a negative regulatory effect on tumor proliferation. Additionally, the downregulation of ACAP2 triggered by exosomal-derived miR-3656 further promotes the activation of the PI3K/AKT and β-catenin signaling pathways and ultimately improves the growth of ESCC cells both in vitro and in xenograft models. These results may represent a potential therapeutic target for ESCC and provide a new basis for clinical treatment plans.

Genome-wide linkage analysis in Spanish melanoma-prone families identifies a new familial melanoma susceptibility locus at 11q

The main genetic factors for familial melanoma remain unknown in >75% of families. CDKN2A is mutated in around 20% of melanoma-prone families. Other high-risk melanoma susceptibility genes explain <3% of families studied to date. We performed the first genome-wide linkage analysis in CDKN2A-negative Spanish melanoma-prone families to identify novel melanoma susceptibility loci. We included 68 individuals from 2, 3, and 6 families with 2, 3, and at least 4 melanoma cases. We detected a locus with significant linkage evidence at 11q14.1-q14.3, with a maximum het-TLOD of 3.449 (rs12285365:A>G), using evidence from multiple pedigrees. The genes contained by the subregion with the strongest linkage evidence were: DLG2, PRSS23, FZD4, and TMEM135. We also detected several regions with suggestive linkage evidence (TLOD >1.9) (1q, 6p, 7p, 11q, 12p, 13q) including the region previously detected in melanoma-prone families from Sweden at 3q29. The family-specific analysis revealed three loci with suggestive linkage evidence for family #1: 1q31.1-q32.1 (max. TLOD 2.447), 6p24.3-p22.3 (max. TLOD 2.409), and 11q13.3-q21 (max. TLOD 2.654). Future next-generation sequencing studies of these regions may allow the identification of new melanoma susceptibility genetic factors.