Image_1_The Effect of Centrifugal Force in Quantification of Colorectal Cancer-Related mRNA in Plasma Using Targeted Sequencing.PDF

<p>In our previous study, we detected the effects of centrifugal forces on plasma RNA quantification by quantitative reverse transcription PCR. The aims of this study were to perform targeted mRNA sequencing and data analysis in healthy donors' plasma prepared by two centrifugation protocols and to investigate the effects of centrifugal forces on plasma mRNA quality and quantity. Targeted mRNA sequencing was performed using a custom panel with 108 colorectal cancer-related genes in 18 healthy donors' plasma that prepared by (1) 3,500 g for 10 min at 4°C and (2) 1,600 g for 10 min at 4°C followed by 16,000 g for 10 min at 4°C. Results showed that plasma ribosomal RNA was detected in 16/18 (88.9%) 3,500 g and 6/18 (33.3%) 1,600 g followed by 16,000 g centrifuged plasma. For targeted sequencing, 75/108 (69.4%) and 86/108 (79.6%) genes were detected in 3,500 and 1,600 g followed by 16,000 g, respectively, while 16/108 (14.8%) genes were not detected in both centrifugations. Detailed analysis showed that 2 of 108 (1.85%) genes showed lower expressions in 3,500 g than in 1,600 g followed by 16,000 g. The median expressions of genes in 3,500 g were positively correlated with the expressions in 1,600 g followed by 16,000 g (R² = 0.9471, P < 0.0001, Spearman rank correlation). Meanwhile, plasma samples were not distinctively clustered based on centrifugal forces according to hierarchical clustering. Targeted mRNA sequencing and subsequent data analysis were performed in this study to investigate the effects of two different centrifugal forces that are commonly used in plasma collection. Our targeted sequencing results help to understand the centrifugal force effects on plasma mRNA, and these findings show that the centrifugation protocol for plasma mRNA research using targeted sequencing can be standardized which facilitates multicenter studies for comparison and quality assurance in the future.</p

Table_1_The Effect of Centrifugal Force in Quantification of Colorectal Cancer-Related mRNA in Plasma Using Targeted Sequencing.PDF

<p>In our previous study, we detected the effects of centrifugal forces on plasma RNA quantification by quantitative reverse transcription PCR. The aims of this study were to perform targeted mRNA sequencing and data analysis in healthy donors' plasma prepared by two centrifugation protocols and to investigate the effects of centrifugal forces on plasma mRNA quality and quantity. Targeted mRNA sequencing was performed using a custom panel with 108 colorectal cancer-related genes in 18 healthy donors' plasma that prepared by (1) 3,500 g for 10 min at 4°C and (2) 1,600 g for 10 min at 4°C followed by 16,000 g for 10 min at 4°C. Results showed that plasma ribosomal RNA was detected in 16/18 (88.9%) 3,500 g and 6/18 (33.3%) 1,600 g followed by 16,000 g centrifuged plasma. For targeted sequencing, 75/108 (69.4%) and 86/108 (79.6%) genes were detected in 3,500 and 1,600 g followed by 16,000 g, respectively, while 16/108 (14.8%) genes were not detected in both centrifugations. Detailed analysis showed that 2 of 108 (1.85%) genes showed lower expressions in 3,500 g than in 1,600 g followed by 16,000 g. The median expressions of genes in 3,500 g were positively correlated with the expressions in 1,600 g followed by 16,000 g (R² = 0.9471, P < 0.0001, Spearman rank correlation). Meanwhile, plasma samples were not distinctively clustered based on centrifugal forces according to hierarchical clustering. Targeted mRNA sequencing and subsequent data analysis were performed in this study to investigate the effects of two different centrifugal forces that are commonly used in plasma collection. Our targeted sequencing results help to understand the centrifugal force effects on plasma mRNA, and these findings show that the centrifugation protocol for plasma mRNA research using targeted sequencing can be standardized which facilitates multicenter studies for comparison and quality assurance in the future.</p

FZD3 expression in various non-CRC metastatic carcinomas.

<p>(A) Percentage of various non-CRC metastatic carcinomas with FZD3 ICC staining and (B) ICC scores of FZD3 in various non-CRC metastatic carcinomas. (HCC = hepatocellular carcinoma, RCCC = renal clear cell carcinoma, SCC1 = squamous cell carcinoma, LAC = lung adenocarcinoma, LNSCC = lung non-small cell carcinoma, PTC = papillary thyroid carcinoma, BC = breast carcinoma, OCCC = ovary clear cell carcinoma, CNSCC = cervical non-small cell carcinoma, FTSAC = fallopian tube serous adenocarcinoma, TCC = transitional cell carcinoma, SCC2 = small cell carcinoma and CND = carcinoma with neuroendocrine differentiation).</p

ICC scores of FZD3 in various Dukes stage of patients with CRC.

<p>ICC scores of FZD3 in various Dukes stage of patients with CRC.</p

ICC staining of FZD3 in (A) a lymph node with CRC metastasis from a Dukes 3 patient and (B) an ovary with CRC metastasis from a Dukes 4 patient (T = tumor, Lym = lymphoid cells, original magnification, X400, scale bar = 100 µm).

<p>ICC staining of FZD3 in (A) a lymph node with CRC metastasis from a Dukes 3 patient and (B) an ovary with CRC metastasis from a Dukes 4 patient (T = tumor, Lym = lymphoid cells, original magnification, X400, scale bar = 100 µm).</p

ICC scores of FZD3 in (A) adenomas with synchronous carcinomas (AWSC) and (B) pure adenomas.

<p>ICC scores of FZD3 in (A) adenomas with synchronous carcinomas (AWSC) and (B) pure adenomas.</p

ICC staining of FZD3 in (A) CRC, (B), CAD, (C) colorectal polyp, (D) normal colorectal tissues, (E) positive control and (F) negative control (Original magnification, X400, scale bar = 100 µm).

<p>ICC staining of FZD3 in (A) CRC, (B), CAD, (C) colorectal polyp, (D) normal colorectal tissues, (E) positive control and (F) negative control (Original magnification, X400, scale bar = 100 µm).</p

Overall survival analyses for the 1^st cohort of 186 Dukes A to D CRC patients (A) stratified by a median FZD3 ICC score of 327, (B) with high and low FZD3 expression and (C) with moderately high and moderately low FZD3 expression.

<p>Overall survival analyses for the 1^st cohort of 186 Dukes A to D CRC patients (A) stratified by a median FZD3 ICC score of 327, (B) with high and low FZD3 expression and (C) with moderately high and moderately low FZD3 expression.</p

Intricate relationship between IL-6, STAT3 activation and LMP1 in EBV-infected NPE cells.

<p>(A) A schematic diagram showing the positive feedback loop of IL-6 activation of STAT3 and LMP1 expression in EBV-infected cell. (B) NP460hTert-EBV, C666-1 and HONE-EBV cells were treated with IL-6 for 4 hours. Total RNA were extracted from treated and untreated cells and examined for mRNA expression levels of LMP1 by quantitative real-time (RT-PCR). Results were normalized to GAPDH. These results were computed from triplicates of individual experiments. * <i>p</i><0.05. (C) EBV-infected NP460hTert cells were stably transduced with STAT3-C or control vector. The mRNA expression levels of LMP1 were analyzed by quantitative RT-PCR. Results were normalized to GAPDH. * <i>p</i><<i>0.05</i>. (D) LMP1 expression was upregulated in NP460hTert-EBV cells after treating with IL-6 for 48 hours. (E) PLNSX-LMP1 vector and PLNSX control vector were introduced into CNE2 cells by retroviral infection. Both LMP1 expression and STAT3 phosphorylation in CNE2 cells were confirmed by Western blotting. (F) HONE1 and EBV-infected HONE1 cells were transiently co-transfected with m67 firefly luciferase reporter construct (luc-m67) in conjunction with a Renilla luciferase vector and STAT3-C plasmid or control plasmid. Cell lysates were assessed for luciferase activity 36 hours after transfection. Relative luciferase activity was calculated by normalizing the firefly luciferase activity to Renilla luciferase activity. These results were computed from triplicate separate experiments. * <i>p</i><0.05 ^#<i>p</i><0.05. (G) HONE1 cells were transiently co-transfected with IL-6 firefly luciferase reporter construct (pGL3-IL-6-Luc) in conjunction with a Renilla luciferase vector and pcDNA3/2117-LMP1 or control vector. These results were computed from triplicate separate experiments. * <i>p</i><0.05.</p

Upregulation of IL-6R in EBV-infected NPE cells is responsible for the enhanced responsiveness to IL-6-induced STAT3 activation.

<p>(A) The expression of IL-6R in EBV-infected and uninfected NP460hTert cells was analyzed by Western blot. Immunoblotting for β-actin was provided as protein loading control. (B) Total RNA was extracted and the expression levels of IL-6R mRNA in NP460hTert and NP460hTert-EBV cells were analyzed by quantitative real time RT-PCR. The mRNA levels of IL-6Rα were normalized to cellular GAPDH mRNA. Data were collected from triplicate separate experiments. * <i>p</i><<i>0.05</i>. (C) NP460hTert cells were infected with retroviral expression vectors, pBabe-IL-6Rα or pBabe empty vectors. Stably transduced cells were treated with IL-6 at 50 ng/ml for 30 minutes. Cell lysates were prepared and examined for expression of IL-6Rα and p-STAT3 (Tyr 705) by Western blot. Immunoblottings for STAT3 and β-actin are shown as controls for protein loading. (D) NP460hTert and NP460hTert-EBV cells were pre-treated with anti-IL-6R antibody at 5 µg/ml for 30 minutes before IL-6 treatment. The expression of p-STAT3 was analyzed by Western blot. Immunoblotting for total levels of STAT3 protein is shown as controls for protein loading. (E) After EBV infection, the EBV-infected NP460hTert cells and its uninfected parental cells were continuously subcultured. Cells lysates were prepared from the cells that had been passaged for 56, 99 and 133 times (designated as early, middle and late passage). The expression of IL-6R was analyzed by Western blotting. Immunoblotting for β-actin was included as control for protein loading. (F) The levels of IL-6R expression in cells were detected by Western blot in several paired uninfected and EBV-infected cell lines, including EBV-infected and non-infected pairs of NP460hTert, NP550-CDK4-hTert, NP361-cyclinD1-hTert, NP550-cyclinD1-hTert. β-actin expressions were shown as protein loading control.</p