High glucose concentrations induce TNF-α production through the down-regulation of CD33 in primary human monocytes

<p>Abstract</p> <p>Background</p> <p>CD33 is a membrane receptor containing a lectin domain and a cytoplasmic immunoreceptor tyrosine-based inhibitory motif (ITIM) that is able to inhibit cytokine production. CD33 is expressed by monocytes, and reduced expression of CD33 correlates with augmented production of inflammatory cytokines, such as IL-1β, TNF-α, and IL-8. However, the role of CD33 in the inflammation associated with hyperglycemia and diabetes is unknown. Therefore, we studied CD33 expression and inflammatory cytokine secretion in freshly isolated monocytes from patients with type 2 diabetes. To evaluate the effects of hyperglycemia, monocytes from healthy donors were cultured with different glucose concentrations (15-50 mmol/l D-glucose), and CD33 expression and inflammatory cytokine production were assessed. The expression of suppressor of cytokine signaling protein-3 (SOCS-3) and the generation of reactive oxygen species (ROS) were also evaluated to address the cellular mechanisms involved in the down-regulation of CD33.</p> <p>Results</p> <p>CD33 expression was significantly decreased in monocytes from patients with type 2 diabetes, and higher levels of TNF-α, IL-8 and IL-12p70 were detected in the plasma of patients compared to healthy donors. Under high glucose conditions, CD33 protein and mRNA expression was significantly decreased, whereas spontaneous TNF-α secretion and SOCS-3 mRNA expression were increased in monocytes from healthy donors. Furthermore, the down-regulation of CD33 and increase in TNF-α production were prevented when monocytes were treated with the antioxidant α-tocopherol and cultured under high glucose conditions.</p> <p>Conclusion</p> <p>Our results suggest that hyperglycemia down-regulates CD33 expression and triggers the spontaneous secretion of TNF-α by peripheral monocytes. This phenomenon involves the generation of ROS and the up-regulation of SOCS-3. These observations support the importance of blood glucose control for maintaining innate immune function and suggest the participation of CD33 in the inflammatory profile associated with type 2 diabetes.</p

<i>CDKN3</i> gene expression decreased in cervical cancer cell lines transfected with specific siRNAs against <i>CDKN3</i>.

<p>a. Level of mRNA normalized with an internal control (<i>GAPDH</i>).</p><p>b. Cells transfected with a mix of 3 scrambled siRNAs. The optimal concentration of siRNAs that greatest decreases the <i>CDKN3</i> messenger was 80 nM for SiHa and CaSki, and 100 nM for HeLa cell lines.</p><p>c. Cells transfected with a mix of 3 specific siRNAs against <i>CDKN3</i>. The optimal concentration of siRNAs that greatest decreases the CDKN3 messenger was 80 nM for SiHa and CaSki, and 100nM for HeLa cell lines.</p><p>d. % of Decrease = 100—(siRNA <i>CDKN3</i>/siRNA Control)*100</p><p>e. t test.</p><p><i>CDKN3</i> gene expression decreased in cervical cancer cell lines transfected with specific siRNAs against <i>CDKN3</i>.</p

Univariate and multivariate survival analysis of patients with CC including <i>CDKN3</i> expression, clinical stage and HPV type.

<p>a. Unadjusted Hazard Ratio. Univariate analysis was performed for each variable.</p><p>b. Cox proportional hazards model.</p><p>c. Adjusted Hazard Ratio. Multivariate analysis was performed considering CDKN3 expression (FC) and FIGO.</p><p>d. FC, fold change, expression of <i>CDKN3</i> in tumors in relation to the mean in the control group.</p><p>e. Positive tumors for HPVs 18, 31, 33, 35, 45, 51, 52, 53, 58, 59 and 68.</p><p>Univariate and multivariate survival analysis of patients with CC including <i>CDKN3</i> expression, clinical stage and HPV type.</p

Survival analysis of women with cervical cancer according to <i>CDKN3</i> expression.

<p>The Kaplan-Meier curves for cyclin-dependent kinase inhibitor 3 (CDKN3) expression are shown. Patients were followed up for at least 60 months. Overall survival analyzed with Kaplan-Meier curves is shown for CDKN3 expression status, (A) all CC sample set, (B) HPV16-positive CC cases, (C) CC positive for HPVs other than HPV16. In all panels, the p-value was calculated by comparing the curves with the log-rank test. The number of patients at risk in each time intervals are noted in the tables below the curves. Censored patients are labeled with vertical bars (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0137397#sec002" target="_blank">material and methods</a>).</p

Histological analysis of CDKN3 protein expression.

<p>CDKN3 protein expression was determined by immunohistochemistry using formalin-fixed paraffin-embedded tissue sections. Representative experiments in HPV16-positive squamous cell carcinomas (A–D) and adenocarcinomas (E and F), and squamous cell carcinomas positive for other HPVs (G–I) are shown. Specific signals are shown as brown staining (counterstained with hematoxylin, original magnification ×800; bars, 20 μm). High-grade squamous intraepithelial lesion (J), normal cervical epithelium (K and L), and experimental controls without primary antibody (M–O) are also shown.</p

<i>CDKN3</i> gene expression in normal cervical epithelium and cervical cancer samples.

<p>The expression of cyclin-dependent kinase inhibitor 3 (<i>CDKN3</i>) was measured by RT-qPCR in 25 normal healthy cervix samples and 134 cervical cancer (CC) samples positive for human papillomavirus (HPV)16 (n = 90) or for other HPV types (n = 44), including 18, 31, 33, 35, 45, 51, 52, 53, 58, 59, and 68. (A) Intensity of gene expression, expressed in Log2 values, in box plots. The upper and lower boundaries of the boxes represent the 75th and 25th percentiles, respectively. The black and dotted lines within the boxes represent the median and mean values, respectively, and the whiskers represent the minimum and maximum values that lie within 1.5x the interquartile range from the end of the box. Values outside this range are represented by black circles. The fold change (FC) was calculated by dividing the median of each CC group by the median of the control group. Statistical differences between groups were calculated using the nonparametric Mann-Whitney U test. (B) Frequency (%) distribution of <i>CDKN3</i> FCs, which were calculated in each tumor considering the median of the control group.</p

Cell migration and invasion of cervical cancer (CC)-derived cell lines transfected with specific siRNAs against cyclin-dependent kinase inhibitor 3 <i>(CDKN3)</i> or scrambled siRNAs.

<p>Cell lines were transfected with specific <i>CDKN3</i> (black bars) or scrambled siRNAs (white bars). Cells were harvested 48 h after transfection. Cell migration (A) and invasion (B) was assayed in a 24-well transwell polycarbonate membrane inserts and in a 24-well transwell matrigel invasion chamber, respectively. After incubation time, cells that migrated through the filters or invaded through the matrigel membranes were collected and stained with MTT colorimetric assay. The experiments were repeated two times by triplicate, and the figure shows the mean ± S.D. of one experiment.</p

Analysis of <i>CDKN3</i> transcripts.

<p>Figure shows gel electrophoresis of mRNA variants of <i>CDKN3</i> gene identified in CC, controls, and cell lines using reverse transcription-polymerase chain reaction (RT-PCR). Panel A and B show wild-type (wt) <i>CDKN3</i> mRNA transcript. (A) RT-PCR was performed with external primers F1/R1 (756 bp, black arrow). (B) A 2-μL sample of 1:5 dilution of reactions of (A) were re-amplified using the nested primers F2/R5. In some samples, other weak transcripts were observed below wt<i>CDKN3</i> transcript (721 bp) including variants cx1, cx2, cx3, cx4, and cx5 (200, < 200, 400, 450, and 500 bp, respectively). (C) RT-PCR identified the “f” variant (453 bp) using primers F1/R9f. Most samples showed an additional lower band (cx6 variant, 370 bp). (D) RT-PCR identified “i” variant (633 bp) using primers F6i/R5. (E) RT-PCR identified “k” variant (392 bp) using primers F4/R5. Lower panel shows RT-PCR amplification of glyceraldehyde 3-phosphate dehydrogenase (<i>GAPDH</i>) gene as internal control. Cell lines were transfected with random siRNAs (-) or specific CDKN3 siRNAs (+), treated, and then incubated as described in Material and methods. RT-PCR was performed on RNAs extracted 48 h after transfections.</p

<i>CDKN3</i> mRNA as a Biomarker for Survival and Therapeutic Target in Cervical Cancer

<div><p>The cyclin-dependent kinase inhibitor 3 (<i>CDKN3</i>) gene, involved in mitosis, is upregulated in cervical cancer (CC). We investigated <i>CDKN3</i> mRNA as a survival biomarker and potential therapeutic target for CC. <i>CDKN3</i> mRNA was measured in 134 CC and 25 controls by quantitative PCR. A 5-year survival study was conducted in 121 of these CC patients. Furthermore, <i>CDKN3</i>-specific siRNAs were used to investigate whether <i>CDKN3</i> is involved in proliferation, migration, and invasion in CC-derived cell lines (SiHa, CaSki, HeLa). <i>CDKN3</i> mRNA was on average 6.4-fold higher in tumors than in controls (p = 8 x 10⁻⁶, Mann-Whitney). A total of 68.2% of CC patients over expressing <i>CDKN3</i> gene (fold change ≥ 17) died within two years of diagnosis, independent of the clinical stage and HPV type (Hazard Ratio = 5.0, 95% CI: 2.5–10, p = 3.3 x 10⁻⁶, Cox proportional-hazards regression). In contrast, only 19.2% of the patients with lower <i>CDKN3</i> expression died in the same period. In vitro inactivation of <i>CDKN3</i> decreased cell proliferation on average 67%, although it had no effect on cell migration and invasion. <i>CDKN3</i> mRNA may be a good survival biomarker and potential therapeutic target in CC.</p></div