CDKN2A promoter methylation enhances self-renewal of glioblastoma stem cells and confers resistance to carmustine.

BACKGROUND: Glioblastoma, a highly aggressive form of brain cancer, poses significant challenges due to its resistance to therapy and high recurrence rates. This study aimed to investigate the expression and functional implications of CDKN2A, a key tumor suppressor gene, in glioblastoma cells, building upon the existing background of knowledge in this field. METHOD: Quantitative reverse transcription PCR (qRT-PCR) analysis was performed to evaluate CDKN2A expression in U87 glioblastoma cells compared to normal human astrocytes (NHA). CDKN2A expression levels were manipulated using small interfering RNA (siRNA) and CDKN2A overexpression vector. Cell viability assays and carmustine sensitivity tests were conducted to assess the impact of CDKN2A modulation on glioblastoma cell viability and drug response. Sphere formation assays and western blot analysis were performed to investigate the role of CDKN2A in glioblastoma stem cell (GSC) self-renewal and pluripotency marker expression. Additionally, methylation-specific PCR (MSP) assays and demethylation treatment were employed to elucidate the mechanism of CDKN2A downregulation in U87 cells. RESULT: CDKN2A expression was significantly reduced in glioblastoma cells compared to NHA. CDKN2A overexpression resulted in decreased cell viability and enhanced sensitivity to carmustine treatment. CDKN2A inhibition promoted self-renewal capacity and increased pluripotency marker expression in U87 cells. CDKN2A upregulation led to elevated protein levels of p16INK4a, p14ARF, P53, and P21, which are involved in cell cycle regulation. CDKN2A downregulation in U87 cells was associated with high promoter methylation, which was reversed by treatment with a demethylating agent. CONCLUSION: Our findings demonstrate that CDKN2A downregulation in glioblastoma cells is associated with decreased cell viability, enhanced drug resistance, increased self-renewal capacity, and altered expression of pluripotency markers. The observed CDKN2A expression changes are mediated by promoter methylation. These results highlight the potential role of CDKN2A as a therapeutic target and prognostic marker in glioblastoma.

[Effect of High-Volume Leukapheresis on Hematological Indexes of Patients with Hyperleukocytic Leukemia].

OBJECTIVE: To improve the collection efficiency of leukapheresis, explore relatively scientific and objective evaluation indicators for collection effect, and observe the effect of high-volume leukapheresis on blood cells and coagulation function. METHODS: A total of 158 times of high-volume leukapheresis were performed on 93 patients with hyperleukocytic leukemia by using continuous flow centrifugal blood component separator. 1/5-1/4 of total blood volume of the patients was taken as the target value of leukocyte suspension for single treatment. In addition, the total number of white blood cells (WBCs) subtracted, value of WBCs reduction, rate of WBCs reduction, decrease value of WBCs count, decrease rate of WBCs count, amount of hemoglobin (Hb) lost, value of Hb lost, decreased value of Hb, total number of platelet (PLT) lost, the value of PLT loss, and decrease value of PLT count were used to comprehensively evaluate the collection effect of leukapheresis and influence on Hb level and PLT count of the patients. The prothrombin time (PT), activated partial thromboplastin time (aPTT), thrombin time (TT), and fibrinogen (Fib) concentration were detected before and after treatment, and the effect of leukapheresis on coagulation function of the patients was observed. RESULTS: The volume of leukocyte suspension collected in a single treatment was 793.01±214.23 ml, the total number of WBCs subtracted was 353.25 (241.99-547.28)×109, the value of WBCs reduction was 86.98 (63.05-143.43)×109/L, the rate of WBCs reduction was 44.24 (28.37-70.48)%, decrease value of WBCs count was 65.73 (37.17-103.97)×109/L, decrease rate of WBCs count was (35.67±23.08)%, the amount of Hb lost was 17.36 (12.12-24.94) g, the value of Hb lost was 4.31 (3.01-6.12) g/L, decreased value of Hb was 4.80 (-1.25-9.33) g/L, total number of PLT lost was 222.79 (67.03-578.31)×109, the value of PLT loss was 54.45 (17.29-139.08)×109/L, and decrease value of PLT count was 26.00 (8.38-62.50)×109/L. Before and after a single treatment, the PT was 14.80 (13.20-16.98) s and 15.20 (13.08-16.90) s (z=-1.520, P>0.05), the aPTT was 35.20 (28.68-39.75) s and 35.40 (28.00-39.75) s (z=-2.058, P<0.05), the TT was 17.50 (16.30-18.80) s and 17.70 (16.70-19.10) s (z=-3.928, P<0.001), and the Fib concentration was 2.87±1.13 g/L and 2.64±1.03 g/L (t=7.151, P<0.001), respectively. CONCLUSION: High-volume leukapheresis can improve the efficiency of leukapheresis while maintaining the relative stability of the patients' circulating blood volume. The degree of influence on the patients' Hb level, PLT count, Fib concentration, and comprehensive coagulation indicators reflecting the patients' intrinsic and cxtrinsic coagulation activity is within the body's compensation range.

PABPC1L depletion inhibits proliferation and migration via blockage of AKT pathway in human colorectal cancer cells.

Numerous studies have demonstrated that PABPC1 participates in the process of carcinogenesis and its function is inconsistent in different types of cancers. PABPC1-like (PABPC1L) is an important paralog of PABPC1 and few studies are available on the roles of PABPC1L in colorectal cancer (CRC) development. Hence, we explored the biological function and prognostic impact of PABPC1L in CRC. The mRNA expression of PABPC1L in CRC was determined based on the data obtained from The Cancer Genome Atlas (TCGA) database. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was utilized to determine the PABPC1L mRNA expression level in CRC HT-29 and LS-174T cell lines. Kaplan-Meier method and Cox proportional-hazards model were utilized to conduct the survival and prognosis analyses. HT-29 cells with silenced PABPC1L were constructed to explore the effect of PABPC1L on cell proliferation, invasion and migration capacities using cell counting kit-8 (CCK-8), clone formation, wound-healing and Transwell assays, respectively. To uncover the potential mechanisms of how PABPC1L influences CRC proliferation and migration, we analyzed the expression of AKT, p-AKT, PI3K, and p-PI3K in HT-29 cells using western blotting. Our results revealed that PABPC1L was overexpressed in CRC tissues compared with normal tissues based on the data obtained from TCGA database. Similarly, the mRNA expression of PABPC1L was higher in HT-29 and LS-174T cells than that in CCD-18Co cells. The expression of PABPC1L in CRC was found to be significantly related to age, pathologic stage, pathologic-node, pathologic-metastasis, and death. In univariate and multivariate analyses, pathologic-tumor and pathologic-metastasis were identified as independent prognostic factors for CRC. After PABPC1L depletion, cell proliferation rate, colony numbers, and the invasive and migratory capacity of HT-29 cells were all reduced. Western blot analysis showed that reduction of PABPC1L significantly inhibited p-AKT, and p-PI3K expression level in HT-29 cells. Collectively, our results suggested that PABPC1L is a potential novel candidate oncogene in CRC, and targeting PABPC1L may provide clinical utility in CRC.

[Effect of Highvolume Platelet Reduction Therapy on White Blood Cell Count and Hemoglobin Level in Patients with Thrombocytosis].

OBJECTIVE: To explore the effect of high volume platelet reduction therapy on the white blood cell (WBC) count and hemoglobin (Hb) level in patients with thrombocytosis. METHODS: Thirty-two plateletphoreses were performed for patients with thromocytosis by using ELP or MNC program of blood component isolator of COBE spectra continuous flow concentrifugation and the ACD-A preservation solution for blood as blood anticoagulant. In each treatment of patients, 2.5-3.0 tines total blood volume (TBV) were circulated, then the platelet suspension of 1/5-1/4 time TBV was prepared and collected. RESULTS: A single plateletpheresis took (212.53±41.54) minutes in which (8 812.63±2087.15) ml blood were treated, and (798.84±190.77) ml platelet suspension was collected. In the suspension, the platelet count was 4 486.50 (3 058.50-5 279.50)×109/L, containing 3 455.50 (2 288.68-4 226.71)×109. WBC count was 13.79 (10.21-20.72)×109/L, containing 11.90(7.81-14.40)×109. Hemoglobin concentration was (3.28±1.25) g/L，containing (2.62 ± 1.17) g. Before and after plateletpheresis, the patients' platelet count was 1 263.00 (1 052.50-1 807.50)×109/L and (778.83±247.25)×109/L（Z=4.94, P＜0.01), WBC count was 9.96(6.44-14.01)×109/L and 8.59(5.37, 13.12)×109/L (Z=13.31, P＜0.05), Hemoglobin concentration was (112.63 ± 24.56)g/L and (109.55 ± 24.46)g/L (t=1.68，P＞0.05). CONCLUSION: Using continuous flow centrifugation and blood component separating in plateletpheresis for the patients with thrombocytosis can obviously decrease the high ratio of platelets, and improve the effect of plateletpheresis. The high volume platelet reduction therapy can lead to decrease of WBC count to some alent, degree but WBC count still in the normal range, moreover not affect the hemoglobin level significantly.

Formation of Nanopits in Si Capping Layers on SiGe Quantum Dots.

In-situ annealing at a high temperature of 640°C was performed for a low temperature grown Si capping layer, which was grown at 300°C on SiGe self-assembled quantum dots with a thickness of 50 nm. Square nanopits, with a depth of about 8 nm and boundaries along 〈110〉, are formed in the Si capping layer after annealing. Cross-sectional transmission electron microscopy observation shows that each nanopit is located right over one dot with one to one correspondence. The detailed migration of Si atoms for the nanopit formation is revealed by in-situ annealing at a low temperature of 540°C. The final well-defined profiles of the nanopits indicate that both strain energy and surface energy play roles during the nanopit formation, and the nanopits are stable at 640°C. A subsequent growth of Ge on the nanopit-patterned surface results in the formation of SiGe quantum dot molecules around the nanopits.