Metabolic reprogramming is an important feature in tumor progression. Long noncoding RNA’s (lncRNA) small nucleolar RNA host gene 6 (SNHG6) acts as a proto-oncogene in hepatocellular carcinoma (HCC) but its role in glycolysis is mostly unknown. The role of SNHG6 and Block of proliferation 1 (BOP1) on glycolysis is assessed by glucose uptake, lactate production, oxygen consumptive rate (OCR) and extracellular acidification rate (ECAR) and glycolytic enzyme levels. The regulatory effect of SNHG6 on BOP1 protein was confirmed by Western blotting, MS2 pull-down, RNA pull-down, and RIP assay. SNHG6 and BOP1 levels were increased in HCC tissues and cells. SNHG6 and BOP1 were prognostic factors in HCC patients and significantly correlated to TP53 mutant and tumor grade. SNHG6 promoted proliferation, inhibited apoptosis, enhanced glucose uptake and lactate production, decreased OCR, and increased ECAR in HCC cell lines. SNHG6 could bind the BOP1 protein and enhance its stability. BOP1 overexpression rescued the change of proliferation, apoptosis, and glycolysis in HCCLM3 and SMMC-7721 cells. Our data indicate that SNHG6 accelerates proliferation and glycolysis and inhibits the apoptosis of HCC cell lines by binding the BOP1 protein and enhancing its stability. Both SNHG6 and BOP1 are promising prognostic and therapeutic markers in HCC.
Graft-derived cell-free DNA (GcfDNA) is a promising non-invasive biomarker for detecting allograft injury. In this study, we aimed to evaluate the efficacy of programmed monitoring of GcfDNA for identifying BK polyomavirus-associated nephropathy (BKPyVAN) in kidney transplant recipients. We recruited 158 kidney transplant recipients between November 2020 and December 2021. Plasma GcfDNA was collected on the tenth day, first month, third month, and sixth month for programmed monitoring and one day before biopsy. ΔGcfDNA (cp/mL) was obtained by subtracting the baseline GcfDNA (cp/mL) from GcfDNA (cp/mL) of the latest programmed monitoring before biopsy. The receiver operating characteristic curve showed the diagnostic performance of GcfDNA (cp/mL) at biopsy time and an optimal area under the curve (AUC) of 0.68 in distinguishing pathologically proven BKPyVAN from pathologically unconfirmed BKPyVAN. In contrast, ΔGcfDNA (cp/mL) had a sensitivity and specificity of 80% and 84.6%, respectively, and an AUC of 0.83. When distinguishing clinically diagnosed BKPyVAN from clinical excluded BKPyVAN, the AUC of GcfDNA (cp/mL) was 0.59 at biopsy time, and ΔGcfDNA (cp/mL) had a sensitivity and specificity of 81.0% and 76.5%, respectively, and an AUC of 0.81. Plasma ΔGcfDNA (cp/mL) was not significantly different between TCMR [0.15 (0.08, 0.24) cp/mL] and pathologically proven BKPyVAN[0.34 (0.20, 0.49) cp/mL]. In conclusion, we recommend programmed monitoring of plasma GcfDNA levels after a kidney transplant. Based on our findings from the programmed monitoring, we have developed a novel algorithm that shows promising results in identifying and predicting BKPyVAN.
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