Analysis of the expressions of Bmi-1 and EMT makers in five breast cancer cell lines.

<p>The protein expression levels of Bmi-1, vimentin, E-cadherin and β-action were determined using Western blot analysis.</p

The effect of PI3K and Akt inhibitors on IR-altered EMT process and migration of breast cancer cells and breast cancer cells with Bmi-1 knockdown.

<p>Established Hs578t (Panel A) and MDA-MB-231 (Panel B) cell lines infected with Bmi-1-targeting shRNA (shBmi-1) or non-targeting control shRNA (NC) and wild type (WT) cells were treated with IR (2 Gy) in the presence or absence of LY294002 or AKT I. Migrations of the cells were determined by the transwell assay at day 7 after the treatment. The data (A–B) represents the means ± SD from 3 independent experiments. *: p<0.05, IR+ LY294002 vs. IR alone; **: p<0.05 IR+AKT I vs. IR alone.</p

The time-dependent analysis of Bmi-1 expression and its correlation with migration of Hs578t and MDA-MB-231 cells after IR.

<p>Panel A: The cells were treated with IR (2 Gy) and lysed at indicated time-points. The protein expression levels in total lysates were determined using Western blot analysis. Panel B: Migrations of the cells were determined by the transwell assay at day 1 (24 h) and day 7 (168 h) post-IR (2 Gy). Panel C: Apoptosis of the cells was analyzed by flow cytometry at day 1 and day 7 post-IR (2 Gy). The data represents the means ± SD from 3 independent experiments. *: <i>p</i><0.05.</p

The effect of Bmi-1 knockdown on IR-altered EMT process and migration of Hs578t and MDA-MB-231 cells.

<p>Panel A: Established Hs578t and MDA-MB-231 cell lines infected with Bmi-1-targeting shRNA (shBmi-1) or non-targeting control shRNA (NC) and wild type (WT) cells were treated with IR (2 Gy) and lysed at day 1 (24 h) and day 7 (168 h) post-IR (2 Gy). The protein expression levels in total lysates were determined using western blotting analysis. Panel B: Migrations of the cells were determined by the transwell assay at day 1 and day 7 post-IR (2 Gy). The data represents the means ± SD from 3 independent experiments. *: <i>p</i><0.05.</p

Reduced Recombination by Fullerene Composited Metal Oxide as Electron Extraction Layers for Hybrid Optoelectronic Devices

The performance of solar cells and photodetectors based on metal oxide/conjugated polymer hybrids was significantly enhanced by embedding fullerene (C₆₀) in the metal oxide of TiO₂. With the TiO₂–C₆₀ bulk composites as electron extraction layers, photodetectors based on poly­(3-hexylthiophene) (P3HT)/TiO₂–C₆₀ hybrids exhibited the highest detectivity of 6.54 × 10¹² jones at 520 nm and a fast response with the shortest rise time of 32 us. The key role of the C₆₀ in the TiO₂ layer is causing a fast electron transfer from defect state excitons to C₆₀, resulting in the suppression of the recombination of the defect state excitons produced by a fluorescence (Föster) resonance energy transfer process from photoinduced P3HT excitons to the TiO₂ defect states

DataSheet_3_Expression, tumor immune infiltration, and prognostic impact of HMGs in gastric cancer.xlsx

BackgroundIn the past decade, considerable research efforts on gastric cancer (GC) have been expended, however, little advancement has been made owing to the lack of effective biomarkers and treatment options. Herein, we aimed to examine the levels of expression, mutations, and clinical relevance of HMGs in GC to provide sufficient scientific evidence for clinical decision-making and risk management.MethodsGC samples were obtained from The Cancer Genome Atlas (TCGA). University of California Santa Cruz (UCSC) XENA, Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier Plotter, cBioPortal, GeneMANIA, STRING, LinkedOmics, and DAVID databases were employed. The “ggplot2” package in the R software (×64 3.6.3) was used to thoroughly analyze the effects of HMGs. qRT-PCR was performed to assess HMG levels in GC cell lines.ResultsA total of 375 GC tissues and 32 paraneoplastic tissues were analyzed. The levels of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN1, HMGN2, and HMGN4 expression were increased in GC tissues relative to normal gastric tissues. HMGA1, HMGA2, HMGB1, HMGB2, and HMGB3 were highly expressed in GC cell lines. The OS was significantly different in the group showing low expressions of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN2, HMGN3, and HMGN5. There was a significant difference in RFS between the groups with low HMGA2, HMGB3, and high HMGN2 expression. The levels of HMGA2, HMGB3, and HMGN1 had a higher accuracy for prediction to distinguish GC from normal tissues (AUC value > 0.9). HMGs were tightly associated with immune infiltration and tumor immune escape and antitumor immunity most likely participates in HMG-mediated oncogenesis in GC. GO and KEGG enrichment analyses showed that HMGs played a vital role in the cell cycle pathway.ConclusionsOur results strongly suggest a vital role of HMGs in GC. HMGA2 and HMGB3 could be potential markers for prognostic prediction and treatment targets for GC by interrupting the cell cycle pathway. Our findings might provide renewed perspectives for the selection of prognostic biomarkers among HMGs in GC and may contribute to the determination of the optimal strategy for the treatment of these patients.</p

DataSheet_2_Expression, tumor immune infiltration, and prognostic impact of HMGs in gastric cancer.pdf

BackgroundIn the past decade, considerable research efforts on gastric cancer (GC) have been expended, however, little advancement has been made owing to the lack of effective biomarkers and treatment options. Herein, we aimed to examine the levels of expression, mutations, and clinical relevance of HMGs in GC to provide sufficient scientific evidence for clinical decision-making and risk management.MethodsGC samples were obtained from The Cancer Genome Atlas (TCGA). University of California Santa Cruz (UCSC) XENA, Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier Plotter, cBioPortal, GeneMANIA, STRING, LinkedOmics, and DAVID databases were employed. The “ggplot2” package in the R software (×64 3.6.3) was used to thoroughly analyze the effects of HMGs. qRT-PCR was performed to assess HMG levels in GC cell lines.ResultsA total of 375 GC tissues and 32 paraneoplastic tissues were analyzed. The levels of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN1, HMGN2, and HMGN4 expression were increased in GC tissues relative to normal gastric tissues. HMGA1, HMGA2, HMGB1, HMGB2, and HMGB3 were highly expressed in GC cell lines. The OS was significantly different in the group showing low expressions of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN2, HMGN3, and HMGN5. There was a significant difference in RFS between the groups with low HMGA2, HMGB3, and high HMGN2 expression. The levels of HMGA2, HMGB3, and HMGN1 had a higher accuracy for prediction to distinguish GC from normal tissues (AUC value > 0.9). HMGs were tightly associated with immune infiltration and tumor immune escape and antitumor immunity most likely participates in HMG-mediated oncogenesis in GC. GO and KEGG enrichment analyses showed that HMGs played a vital role in the cell cycle pathway.ConclusionsOur results strongly suggest a vital role of HMGs in GC. HMGA2 and HMGB3 could be potential markers for prognostic prediction and treatment targets for GC by interrupting the cell cycle pathway. Our findings might provide renewed perspectives for the selection of prognostic biomarkers among HMGs in GC and may contribute to the determination of the optimal strategy for the treatment of these patients.</p

DataSheet_1_Expression, tumor immune infiltration, and prognostic impact of HMGs in gastric cancer.pdf

BackgroundIn the past decade, considerable research efforts on gastric cancer (GC) have been expended, however, little advancement has been made owing to the lack of effective biomarkers and treatment options. Herein, we aimed to examine the levels of expression, mutations, and clinical relevance of HMGs in GC to provide sufficient scientific evidence for clinical decision-making and risk management.MethodsGC samples were obtained from The Cancer Genome Atlas (TCGA). University of California Santa Cruz (UCSC) XENA, Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier Plotter, cBioPortal, GeneMANIA, STRING, LinkedOmics, and DAVID databases were employed. The “ggplot2” package in the R software (×64 3.6.3) was used to thoroughly analyze the effects of HMGs. qRT-PCR was performed to assess HMG levels in GC cell lines.ResultsA total of 375 GC tissues and 32 paraneoplastic tissues were analyzed. The levels of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN1, HMGN2, and HMGN4 expression were increased in GC tissues relative to normal gastric tissues. HMGA1, HMGA2, HMGB1, HMGB2, and HMGB3 were highly expressed in GC cell lines. The OS was significantly different in the group showing low expressions of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN2, HMGN3, and HMGN5. There was a significant difference in RFS between the groups with low HMGA2, HMGB3, and high HMGN2 expression. The levels of HMGA2, HMGB3, and HMGN1 had a higher accuracy for prediction to distinguish GC from normal tissues (AUC value > 0.9). HMGs were tightly associated with immune infiltration and tumor immune escape and antitumor immunity most likely participates in HMG-mediated oncogenesis in GC. GO and KEGG enrichment analyses showed that HMGs played a vital role in the cell cycle pathway.ConclusionsOur results strongly suggest a vital role of HMGs in GC. HMGA2 and HMGB3 could be potential markers for prognostic prediction and treatment targets for GC by interrupting the cell cycle pathway. Our findings might provide renewed perspectives for the selection of prognostic biomarkers among HMGs in GC and may contribute to the determination of the optimal strategy for the treatment of these patients.</p

PRR11 Is a Prognostic Marker and Potential Oncogene in Patients with Gastric Cancer

<div><p>PRR11 is a potential candidate oncogene that has been implicated in the pathogenesis of lung cancer, however the role of PRR11 in gastric cancer is currently unclear. In the present study, we investigated the role of PRR11 in gastric cancer by evaluating its expression status in samples from a cohort of 216 patients with gastric cancer. PRR11 was found to be overexpressed in 107 (49.5%) patients by immunohistochemistry of tissue microarrays generated using the patient samples. Furthermore, PRR11 overexpression was found to correlate significantly with clinicopathologic features such as tumor invasion, tumor differentiation, and disease stage. Survival analysis of the cohort revealed that PRR11 is an independent prognostic factor for gastric cancer patients. PRR11 was stably silenced in a gastric carcinoma cell line using an shRNA-based approach, and treated cells showed decreased cellular proliferation and colony formation in vitro and cell growth in vivo, companied by decreased expression of CTHRC1 and increased expression of LXN, proteins involved in tumor progression. Evaluation of human gastric cancer samples demonstrated that PRR11 expression was also associated with increased CTHRC1 and decreased LXN expression. These data indicate that PRR11 may be widely activated in human gastric cancer and are consistent with the hypothesis that PRR11 functions as an oncogene in the development and progression of gastric cancer.</p></div

Kaplan-Meier survival curves of gastric carcinoma patients with and without tumor expression of PRR11.

<p>(A) Survival was significantly longer in patients with tumor lacking expression of PRR11 (OS, 76.6 month) versus those with positive PRR11 expression status (OS, 46.6 month; P < 0.001). (B) A subgroup analysis of stage I & II patients revealed that patients with a positive PRR11 expression status was associated with a shorter survival duration than patients without PRR11 expression (58.5mon vs. 97.9mon; <i>P</i><0.001). (C) A subgroup analysis of stage III & IV patients demonstrated that positive PRR11 overexpression was associated with a shorter overall survival than patients without PRR11 expression (34.3mon vs. 51.3mon; <i>P</i> = 0.036).</p