ABSTRACT
Background: The precise etiology of approximately 50% of patients with recurrent spontaneous abortion (RSA) is unclear, known as unexplained recurrent spontaneous abortion (URSA). This study identified the genetic polymorphisms in patients with URSA. Methods: Genomic DNA was extracted from 30 couples with URSA and 9 couples with normal reproductive history for whole exome sequencing. Variations in annotation, filtering, and prediction of harmfulness and pathogenicity were examined. Furthermore, predictions of the effects of changes in protein structure, Sanger validation, and functional enrichment analyses were performed. The missense mutated genes with significant changes in protein function, and genes with mutations of premature stop, splice site, frameshift, and in-frame indel were selected as candidate mutated genes related to URSA. Results: In 30 unrelated couples with URSA, 50%, 20%, and 30% had 2, 3, and more than 4 miscarriages, respectively. Totally, 971 maternal and 954 paternal mutations were found to be pathogenic or possibly pathogenic after preliminary filtering. Total variations were not associated with age nor the number of miscarriages. In 28 patients (involving 23 couples), 22 pathogenic or possibly pathogenic variants of 19 genes were found to be strongly associated with URSA, with an abnormality rate of 76.67%. Among these, 12 missense variants showed obvious changes in protein functions, including ANXA5 (c.949G>C; p.G317R), APP (c.1530G>C; p.K510N), DNMT1 (c.2626G>A; p.G876R), FN1 (c.5621T>C; p.M1874T), MSH2 (c.1168G>A; p.L390F), THBS1 (c.2099A>G; p.N700S), KDR (c.2440G>A; p.D814N), POLR2B (c.406G>T; p.G136C), ITGB1 (c.655T>C; p.Y219H), PLK1 (c.1210G>T; p.A404S), COL4A2 (c.4808 A>C; p.H1603P), and LAMA4 (c.3158A>G; p.D1053G). Six other genes with mutations of premature stop, splice site, frameshift, and in-frame indel were also identified, including BUB1B (c.1648C>T; p.R550*) and MMP2 (c.1462_1464delTTC; p.F488del) from the father, and mutations from mother and/or father including BPTF (c.396_398delGGA; p.E138 del and c.429_431GGA; p.E148del), MECP2 (c.21_23delCGC; p.A7del), LAMA2 (HGVS: NA; Exon: NA; SPLICE_SITE, DONOR), and SOX21 (c.640 _641insT; p. A214fs, c.644dupC; p. A215fs and c.644_645ins ACGCGTCTTCTTCCCGCAGTC; p. A215dup). Conclusions: These pathogenic or potentially pathogenic mutated genes may be potential biomarkers for URSA and may play an auxiliary role in the treatment of URSA.
ABSTRACT
PURPOSE: Cervical cancer (CC) is one of the most general gynecological malignancies and is associated with high morbidity and mortality. We aimed to select candidate genes related to the diagnosis and prognosis of CC. METHODS: The mRNA expression profile datasets were downloaded. We also downloaded RNA-sequencing gene expression data and related clinical materials from TCGA, which included 307 CC samples and 3 normal samples. Differentially expressed genes (DEGs) were obtained by R software. GO function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed in the DAVID dataset. Using machine learning, the optimal diagnostic mRNA biomarkers for CC were identified. We used qRT-PCR and Human Protein Atlas (HPA) database to exhibit the differences in gene and protein levels of candidate genes. RESULTS: A total of 313 DEGs were screened from the microarray expression profile datasets. DNA methyltransferase 1 (DNMT1), Chromatin Assembly Factor 1, subunit B (CHAF1B), Chromatin Assembly Factor 1, subunit A (CHAF1A), MCM2, CDKN2A were identified as optimal diagnostic mRNA biomarkers for CC. Additionally, the GEPIA database showed that the DNMT1, CHAF1B, CHAF1A, MCM2 and CDKN2A were associated with the poor survival of CC patients. HPA database and qRT-PCR confirmed that these genes were highly expressed in CC tissues. CONCLUSION: The present study identified five DEmRNAs, including DNMT1, CHAF1B, CHAF1A, MCM2 and Kinetochore-related protein 1 (KNTC1), as potential diagnostic and prognostic biomarkers of CC.