Overexpression of LncRNA PSMG3-AS1 Distinguishes Glioblastomas from Sarcoidosis.

In clinical practices, glioblastomas (GBM) in some cases can be misdiagnosed as sarcoidosis. This study aimed to develop a biomarker to distinguish GBM from sarcoidosis. In this study, we found that PSMG3-AS1 was upregulated in plasma of GBM patients in comparison with that in sarcoidosis patients and healthy controls.

RCOR1 directly binds to MED28 and weakens its inducing effect on cancer stem cell-like activity of oral cavity squamous cell carcinoma cells.

Background: Mediator is a multiprotein complex that acts as an essential transcriptional coactivator in eukaryotic cells for successful transcription. In this study, we aimed to explore the expression profile of 33 mediator subunit genes in oral cavity squamous cell carcinoma (OCSCC) and the functional role of MED28 in cellular behaviors of OCSCC cells.

Methods: Single-cell (sc)RNA-seq data from OCSCC cells (Puram 2017's dataset) and bulk-seq data of the OCSCC subgroup of TCGA-head and neck squamous cell carcinoma (HNSC) were used for bioinformatic analysis.

PIM1 overexpression in T-cell lymphomas protects tumor cells from apoptosis and confers doxorubicin resistance by upregulating c-myc expression.

T-cell lymphomas (TCLs) are a malignancy characterized by tumor aggression and resistance to traditional chemotherapy. Disruption of the extrinsic cell death pathway is essential for resistance to chemotherapy. PIM1 serves as a crucial modulator in cancers.

Knowledge database assisted gene marker selection for chronic lymphocytic leukemia.

Objective To investigate whether previously curated chronic lymphocytic leukemia (CLL) risk genes could be leveraged in gene marker selection for the diagnosis and prediction of CLL. Methods A CLL genetic database (CLL_042017) was developed through a comprehensive CLL-gene relation data analysis, in which 753 CLL target genes were curated. Expression values for these genes were used for case-control classification of four CLL datasets, with a sparse representation-based variable selection (SRVS) approach employed for feature (gene) selection.