第915回千葉医学会例会・第12回千葉精神科集談会

SNP-array data of Patient 1. (XLSX 13 kb

CNVs in the dizygotic twin sisters of Family 1.

<p>(A) Pedigree of family1 with dizygotic twins with PA. (B) Comparison of CNVs at 3p26.3-p26.1 and 10p15.3-p15.1 locus in twinA, twinB and the healthy mother. A minimal 620-kb duplication at 10p15.3 (chr10:103934-724229) was found in the twin sisters but not presented in the healthy mother. Annotated genes within this region are listed in the lower panel.</p

Three Chinese pair twins with pulmonary atresia and/or tetralogy of Fallot.

<p>PA, pulmonary atresia; TOF, tetralogy of Fallot; y, years; m, month; F, female</p

Rare CNVs identified in 82 patients with pulmonary atresia.

<p>P, pathogenic; UK, unknown; PP, potentially pathogenic.</p

Rare CNVs related to folate and Vitamin B₁₂ metabolism.

<p>(A) SNP-array shows a 4.8 Mb duplication at 5q14.1 (chr5:75132315-79958945); (B) A 175-kb duplication at 10p13 (chr10:16883466-17058324) (UCSC Genome Browser on Human GRCh37/hg19 Assembly). Log R ratio and B alle frequency are showed in the upper panel and annotated genes are listed in the lower panel. (C) Summary of Folate metabolic pathway (Methionine-Homocysteine-Folate-B12 Cycle). DHF, dihydrofolate; THF, tetrahydrofolate; DHFR, dihydrofolate reductase; MTHFR, methylenetetrahydrofolate reductase; SHMT, serine hydroxyl-methyltransferase; MAT, methionine adenosyltransferase; SAH, S-adenosylhomocysteine; SAM, S-adenosylmethionine; MTR, methionine synthase; PRMT, protein arginine methyltransferase; CUBN, Cubilin. Adapted from Lee <i>et al </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096471#pone.0096471-GueantRodriguez1" target="_blank">[41]</a>.</p

Illumina SNP-array result of the 17p13.2 region in patient 827979.

<p>(A) SNP based array shows a 1.05 Mb deletion at 17p13.2 (chr17:4041358-5091377) (Human GRCh37/hg19 Assembly). B allele frequency and Log R ratio are showed in the upper panel; (B) The lower panel shows genes mapped to the deleted region. OMIM genes are highlighted in green, DGV structure variants and Segmental Duplications are also enclosed in the lower panel.</p

DataSheet1_A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma.PDF

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort.Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package “Seurat” was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the “ssGSEA” algorithm. In order to develop possible medications for patients with high-risk ccRCC, the “pRRophetic” package is employed.Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature’s biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications.Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient’s prognosis for ccRCC and reflect the disease’s complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.</p