Image_1_Construction of disulfidptosis-based immune response prediction model with artificial intelligence and validation of the pivotal grouping oncogene c-MET in regulating T cell exhaustion.png

BackgroundGiven the lack of research on disulfidptosis, our study aimed to dissect its role in pan-cancer and explore the crosstalk between disulfidptosis and cancer immunity.MethodsBased on TCGA, ICGC, CGGA, GSE30219, GSE31210, GSE37745, GSE50081, GSE22138, GSE41613, univariate Cox regression, LASSO regression, and multivariate Cox regression were used to construct the rough gene signature based on disulfidptosis for each type of cancer. SsGSEA and Cibersort, followed by correlation analysis, were harnessed to explore the linkage between disulfidptosis and cancer immunity. Weighted correlation network analysis (WGCNA) and Machine learning were utilized to make a refined prognosis model for pan-cancer. In particular, a customized, enhanced prognosis model was made for glioma. The siRNA transfection, FACS, ELISA, etc., were employed to validate the function of c-MET.ResultsThe expression comparison of the disulfidptosis-related genes (DRGs) between tumor and nontumor tissues implied a significant difference in most cancers. The correlation between disulfidptosis and immune cell infiltration, including T cell exhaustion (Tex), was evident, especially in glioma. The 7-gene signature was constructed as the rough model for the glioma prognosis. A pan-cancer suitable DSP clustering was made and validated to predict the prognosis. Furthermore, two DSP groups were defined by machine learning to predict the survival and immune therapy response in glioma, which was validated in CGGA. PD-L1 and other immune pathways were highly enriched in the core blue gene module from WGCNA. Among them, c-MET was validated as a tumor driver gene and JAK3-STAT3-PD-L1/PD1 regulator in glioma and T cells. Specifically, the down-regulation of c-MET decreased the proportion of PD1+ CD8+ T cells.ConclusionTo summarize, we dissected the roles of DRGs in the prognosis and their relationship with immunity in pan-cancer. A general prognosis model based on machine learning was constructed for pan-cancer and validated by external datasets with a consistent result. In particular, a survival-predicting model was made specifically for patients with glioma to predict its survival and immune response to ICIs. C-MET was screened and validated for its tumor driver gene and immune regulation function (inducing t-cell exhaustion) in glioma.</p

Induction of K15 transcription in keratinocytes cultured at increasing cell densities.

<p>N-Terts growing in SFM at low (0.09 mM) (a) and high (1.8 mM) (b) calcium concentrations were allowed to reach the desired confluence before being used for expression of K1, K10, K14, K15, cornifin and FOXM1B. In (c) N-Terts at low calcium (0.09 mM) were plated at the required density, allowed to attach for 24 h, after which they were used to measure mRNA levels by qPCR. Each bar represents the mean±SEM where n = 3.</p

Induction of K15 in terminally differentiated N-Tert keratinocytes.

<p>N-Terts growing in SFM were suspended in DMEM +20% FCS containing 1.3% (w/v) methylcellulose. At 24 h the cells were harvested and washed with PBS before being suspended in 20–30 µl FCS. A 3–4 µl aliquot was streaked on glass slides. At the same time freshly trypsinised N-Terts were also streaked and used as 0 h control. The cells were dried in air, fixed in formaldehyde and immunostained with different monoclonal antibodies as described in the ‘Materials and Methods’ section. K15 (a, b), K14 (c, d), Involucrin (e, f), Cornifin (g, h). All slides were photographed at the same magnification. The cells in b, d, f and h were difficult to focus because they underwent aggregation in methylcellulose (magnification bar  = 20 µm).</p

Induction of K15 at high cell density.

<p>N-Terts were grown on coverslips at low (30%) or high (95%) cell densities in RM+. The cells were fixed in formaldehyde and immunostained with antibodies against K15 (a, b), K14 (c, d), involucrin (e, f) and cornifin (g, h). All slides were photographed at the same magnification. The insets in a and b were magnified in i and j, respectively, to show the presence of K15 aggregates, shown by arrows, in keratinocytes grown at low cell density (magnification bar = 20 µm).</p

Influence of PKC activator and inhibitor on the expression of K15 in keratinocytes.

<p>(a) N-Terts in RM⁺ were exposed to different concentrations of PMA (0–500 nM) or DMSO for 24 h and mRNA expression was determined by qPCR. (b) The keratinocytes were exposed overnight to either 0 or 10 nM PMA, and protein levels were determined by western blotting. (c) N-Terts grown in SFM were suspended in 1.3% (w/v) methylcellulose with no additive, 0.02% DMSO, or 5 µM PKC inhibitor GF109203X for 24 h and the cells were used to determine mRNA expression. Freshly trypsinised single cell suspension of N-Terts was used as 0 h control cells. (d) N-Tert keratinocytes were suspended as in (c) with GF109203X and protein expression at 0 h or 24 h was determined by western blotting. Each bar represents the mean±SEM where n = 3. (P<0.01, very significant, **; P<0.001, extremely significant, ***). For immunostaining N-Terts growing on glass coverslips in RM+ were treated with 10 nM PMA (f, h, j, l) or DMSO control (e, g, i, k) for 24 h. The cells were fixed in 3.8% formaldehyde and immunostained with antibodies against K15 (e, f), K14 (g, h), involucrin (i, j) and cornifin (k, l) (magnification bar = 20 µm).</p

Association of a BMP9 Haplotype with Ossification of the Posterior Longitudinal Ligament (OPLL) in a Chinese Population

<div><p>Direct or <em>ex vivo</em> BMP9 adenoviral gene therapy can induce massive bone formation at the injection sites and clearly promote spinal fusion. A comprehensive analysis of the osteogenic activity indicated that BMP9 was one of the most potent inducers of osteogenic differentiation both in vitro and in vivo among 14 types of human BMPs. However, genetic variations and whether they correlated with OPLL were not considered. We have sequenced the complete BMP9 gene in 450 patients with OPLL and in 550 matched controls. Analyses were performed on single markers and haplotypes. Single marker tests identified 6 SNPs, among which the minor alleles of rs7923671 (T>C; <em>P = 0.0026</em>; OR: 1.33, CI: 1.10–1.60), rs75024165 (C>T, Thr304Met; <em>P<0.001</em>; OR: 1.76, CI: 1.47–2.12) and rs34379100 (A>C; <em>P<0.001</em>; OR: 1.52, CI: 1.27–1.82) were associated with OPLL. Logistic regression analysis showed that the additive model of rs75024165 (TT vs. CT vs. CC; <em>P<0.001</em>; OR: 1.74) and rs34379100 (CC vs. AC vs. AA; <em>P = 0.003</em>; OR: 1.95) retained statistical significance when adjusted for clinical and demographic characteristics. Linkage disequilibrium (LD) analysis identified one 3 kb block of intense LD in BMP9 and one specific haplotype, CTCA (<em>P<0.001</em>; OR: 2.37), that contained the OPLL-associated risk alleles and was a risk factor for OPLL. This haplotype is associated with increased severity of OPLL, as shown by the distribution of ossified vertebrae in patients with OPLL (<em>P = 0.001</em>). In summary, in the Chinese population studied, SNPs in the BMP9 gene appear to contribute to the risk of OPLL in association with certain clinical and demographic characteristics. The severity of OPLL seems to be mediated predominantly by genetic variations in a 3kb BMP9 locus with the specific haplotype CTCA.</p> </div

FOXM1B binding site on the K15 promoter.

<p>(a) K15 promoter divided into seven fragments (F1–F7) with the unique FOXM1B binding motif (K15) and its comparison with the consensus sequence (con) is shown and the nucleotides in red highlight the differences. (b) X-chromatin immunoprecipitation (X-ChIP): Primary human keratinocytes transduced with FOXM1B-GFP chimera were subjected to X-ChIP using FOXM1B and GAPDH (as control) antibodies. The immunoprecipitated DNA was quantified by qPCR using primers specific for different regions (F1–F7) (see panel a). All primers produced a single product (Melting peak) and the trace before (Total input) and after addition of FOXM1B (FOX) and GAPDH (GAP) antibodies (IP Fraction) is shown. Data for only 3 primer sets are shown for clarity. (c) The DNA fragments immunoprecipitated with FOXM1B antibody were quantified by qPCR. Each bar represents the mean±SEM where n = 3.</p

Knocking down PKCδ suppresses suspension-induced expression of K15.

<p>N-Terts were transfected separately with mock (no oligo), control siRNA or siRNA for PKCδ or PKCη. After 48 h of transfection, the cells were suspended in methylcellulose for 24 h, and used to determine the mRNA expression of K15, PKCδ and PKCη by qPCR. Each bar represents the mean±SEM where n = 3. (P<0.05, significant, *; P<0.01, very significant, **).</p

Haplotypes of the <i>BMP9</i> SNPs in cases and controls.

<p>Note: Haplotype 1 includes the risk alleles of rs75024165 *T and rs34379100 *C (<i>P<0.01</i>).</p>*<p>p-value of haplotype by χ² and Monte Carlo (Number of permutation = 100).</p

Analysis of the genotype distribution in BMP9 between the OPLL and control groups.

<p><b>Note:</b> P (χ²) calculated by χ² test of the additive model. P (Logistic) indicates correction for clinical and demographic characteristics and the additive model of each SNP using the binary logistic method (backward). <b>Gender (male)  =  (WALD: 4.10; </b><b><i>P</i></b><b> = </b><b><i>0.043</i></b><b>; OR: 1.32, CI: 1.01–1.73), FBG =  (SCORE: 65.86; </b><b><i>P<0.001</i></b><b>; OR: 5.42, CI: 3.60–8.15), rs7923671, rs75024165 and rs34379100 show statistical significance </b><b><i>(P<0.05).</i></b></p>*<p> = <i>P</i><b><i><</i></b><i>0.05</i>,</p>**<p> = <i>P</i><b><i><</i></b><i>0.01</i>,</p>***<p> = <i>P</i><b><i><</i></b><i>0.001.</i></p