Npac Is A Co-factor of Histone H3K36me3 and Regulates Transcriptional Elongation in Mouse Embryonic Stem Cells.

Chromatin modification contributes to pluripotency maintenance in embryonic stem cells (ESCs). However, the related mechanisms remain obscure. Here, we show that Npac, a "reader" of histone H3 lysine 36 trimethylation (H3K36me3), is required to maintain mouse ESC (mESC) pluripotency since knockdown of Npac causes mESC differentiation. Depletion of Npac in mouse embryonic fibroblasts (MEFs) inhibits reprogramming efficiency. Furthermore, our chromatin immunoprecipitation followed by sequencing (ChIP-seq) results of Npac reveal that Npac co-localizes with histone H3K36me3 in gene bodies of actively transcribed genes in mESCs. Interestingly, we find that Npac interacts with positive transcription elongation factor b (p-TEFb), Ser2-phosphorylated RNA Pol II (RNA Pol II Ser2P), and Ser5-phosphorylated RNA Pol II (RNA Pol II Ser5P). Furthermore, depletion of Npac disrupts transcriptional elongation of the pluripotency genes Nanog and Rif1. Taken together, we propose that Npac is essential for the transcriptional elongation of pluripotency genes by recruiting p-TEFb and interacting with RNA Pol II Ser2P and Ser5P.

PATZ1 (MAZR) Co-occupies Genomic Sites With p53 and Inhibits Liver Cancer Cell Proliferation via Regulating p27.

Liver cancer is the third most common cause of cancer death in the world. POZ/BTB and AT-hook-containing zinc finger protein 1 (PATZ1/MAZR) is a transcription factor associated with various cancers. However, the role of PATZ1 in cancer progression remains controversial largely due to lack of genome-wide studies. Here we report that PATZ1 regulates cell proliferation by directly regulating CDKN1B (p27) in hepatocellular carcinoma cells. Our PATZ1 ChIP-seq and gene expression microarray analyses revealed that PATZ1 is strongly related to cancer signatures and cellular proliferation. We further discovered that PATZ1 depletion led to an increased rate of colony formation, elevated Ki-67 expression and greater S phase entry. Importantly, the increased cancer cell proliferation was accompanied with suppressed expression of the cyclin-dependent kinase inhibitor CDKN1B. Consistently, we found that PATZ1 binds to the genomic loci flanking the transcriptional start site of CDKN1B and positively regulates its transcription. Notably, we demonstrated that PATZ1 is a p53 partner and p53 is essential for CDKN1B regulation. In conclusion, our study provides novel mechanistic insights into the inhibitory role of PATZ1 in liver cancer progression, thereby yielding a promising therapeutic intervention to alleviate tumor burden.

Preterm birth prediction in asymptomatic women at mid-gestation using a panel of novel protein biomarkers: the Prediction of PreTerm Labor (PPeTaL) study.

BACKGROUND: Accurate prediction of spontaneous preterm labor/preterm birth in asymptomatic women remains an elusive clinical challenge because of the multi-etiological nature of preterm birth. OBJECTIVE: The aim of this study was to develop and validate an immunoassay-based, multi-biomarker test to predict spontaneous preterm birth. MATERIALS AND METHODS: This was an observational cohort study of women delivering from December 2017 to February 2019 at 2 maternity hospitals in Melbourne, Australia. Cervicovaginal fluid samples were collected from asymptomatic women at gestational week 16+0-24+0, and biomarker concentrations were quantified by enzyme-linked immunosorbent assay. Women were assigned to a training cohort (n = 136) and a validation cohort (n = 150) based on chronological delivery dates. RESULTS: Seven candidate biomarkers representing key pathways in utero-cervical remodeling were discovered by high-throughput bioinformatic search, and their significance in both in vivo and in vitro studies was assessed. Using a combination of the biomarkers for the first 136 women allocated to the training cohort, we developed an algorithm to stratify term birth (n = 124) and spontaneous preterm birth (n = 12) samples with a sensitivity of 100% (95% confidence interval, 76-100%) and a specificity of 74% (95% confidence interval, 66-81%). The algorithm was further validated in a subsequent cohort of 150 women (n = 139 term birth and n = 11 preterm birth), achieving a sensitivity of 91% (95% confidence interval, 62-100%) and a specificity of 78% (95% confidence interval, 70-84%). CONCLUSION: We have identified a panel of biomarkers that yield clinically useful diagnostic values when combined in a multiplex algorithm. The early identification of asymptomatic women at risk for preterm birth would allow women to be triaged to specialist clinics for further assessment and appropriate preventive treatment.