A kognitív készségek rendszere és fejlődése

Additional file 7: Figure S1. The KEGG pathways separately enriched with hypermethylated (a) and hypomethylated (b) genes in at least 10% of the 539 TCGA lung adenocarcinoma samples

Functional Comparison between Genes Dysregulated in Ulcerative Colitis and Colorectal Carcinoma

<div><p>Background</p><p>Patients with ulcerative colitis (UC) are predisposed to colitis-associated colorectal cancer (CAC). However, the transcriptional mechanism of the transformation from UC to CAC is not fully understood.</p><p>Methodology</p><p>Firstly, we showed that CAC and non-UC-associated CRC were very similar in gene expression. Secondly, based on multiple datasets for UC and CRC, we extracted differentially expressed (DE) genes in UC and CRC versus normal controls, respectively. Thirdly, we compared the dysregulation directions (upregulation or downregulation) between DE genes of UC and CRC in CRC-related functions overrepresented with the DE genes of CRC, and proposed a regulatory model to explain the CRC-like dysregulation of genes in UC. A case study for “positive regulation of immune system process” was done to reveal the functional implication of DE genes with reversal dysregulations in these two diseases.</p><p>Principal Findings</p><p>In all the 44 detected CRC-related functions except for “viral transcription”, the dysregulation directions of DE genes in UC were significantly similar with their counterparts in CRC, and such CRC-like dysregulation in UC could be regulated by transcription factors affected by pro-inflammatory stimuli for colitis. A small portion of genes in each CRC-related function were dysregulated in opposite directions in the two diseases. The case study showed that genes related to humoral immunity specifically expressed in B cells tended to be upregulated in UC but downregulated in CRC.</p><p>Conclusions</p><p>The CRC-like dysregulation of genes in CRC-related functions in UC patients provides hints for understanding the transcriptional basis for UC to CRC transition. A small portion of genes with distinct dysregulation directions in each of the CRC-related functions in the two diseases implicate that their reversal dysregulations might be critical for UC to CRC transition. The cases study indicates that the humoral immune response might be inhibited during the transformation from UC to CRC.</p></div

Additional file 1 of Individualized detection of TMPRSS2-ERG fusion status in prostate cancer: a rank-based qualitative transcriptome signature

Additional file 1: Table S1. List of maker genes in cell annotation. Table S2. Annotation results of cells from scRNA-seq samples in single-cell analysis. Fig. S1. Five stability indexes (F-stastic, outlier, entropy, CV and MAD) distribution of normal, stable and unstable genes in training dataset. Fig. S2. Performance of ERG in the training and validation datasets Fig. S3. Venn map of diagnosis results between 5-cs-ERG-mRPs and fusion prediction tools for 495 TCGA samples. Fig. S4. UMAP of tumor-infiltrating (A-B) T or (C-D) B lymphocytes annotated from samples GSM4089155 or GSM4089156

The microarray datasets analyzed in this study.

<p><b>Notes:</b> Patients with CRC from GSE9348 were at an early stage (Stage I/II), patients with CRC from GSE18105 were at stage II and stage III, and patients with CRC from GSE23878 and GSE20916 were metastasis-negative. In the datasets GSE18105, we just used the 17 paired CRC and adjacent normal samples to assure the clinical characteristics matching.</p

The CRC-related functions in the directed acyclic graph of Biological Process.

<p><b>A.</b> All the CRC-related functions. <b>B.</b> A case for both the ancestor and offspring terms retained simultaneously. <b>C.</b> A case for just one term retained in a biological process branch.</p

The consistency of every two datasets for UC.

<p>The consistency of every two datasets for UC.</p

The significant regulatory links between UC-stimulus-functions and CRC-related functions in UC.

<p><b>A.</b> The significant regulatory relationships between functions. The gray nodes represent the stimulus-related functions in UC, whereas the other nodes in each color represent functions that are located in the same branch of the Gene Ontology Biological Process (GO BP) tree. Edges represent the significant links between transcription factors (TFs) dysregulated in stimulus-related functions and their differentially expressed (DE) target genes in CRC-related functions in UC (see details in Materials and Methods), and its thickness is proportional to the significance level (-log₁₀[P value]). <b>B.</b> A case for the significant regulatory links from “response to oxidative stress” to “cell proliferation”. <b>C.</b> Another case for the significant regulatory links from “inflammatory response” to “apoptosis”. These pink and green diamond nodes, in “response to oxidative stress” and “inflammatory response”, represent upregulated and downregulated DE genes in UC, respectively. In “cell proliferation” and “apoptosis”, the pink and green diamond nodes, respectively, represent genes consistently upregulated or downregulated in UC and CRC. An arrow represents the regulation relationship between a TF and one of its targets.</p

The consistency of every two datasets for CRC.

<p><b>Notes:</b> *(number1/number2) followed the percentage of the DE genes with consistent dysregulation direction in all commonly detected DE genes between two datasets represent the number of the DE genes with consistent dysregulation direction and the number of all commonly detected DE genes, respectively.</p

El Diario de Pontevedra : periódico liberal: Ano XXIII Número 6794 - 1906 decembro 11

Detail information of differentially expressed lncRNAs identified based on RNA-Seq data. (XLSX 230 kb

Deconvolution of the Gene Expression Profiles of Valuable Banked Blood Specimens for Studying the Prognostic Values of Altered Peripheral Immune Cell Proportions in Cancer Patients

<div><p>Background</p><p>The altered composition of immune cells in peripheral blood has been reported to be associated with cancer patient survival. However, analysis of the composition of peripheral immune cells are often limited in retrospective survival studies employing banked blood specimens with long-term follow-up because the application of flow cytometry to such specimens is problematic. The aim of this study was to demonstrate the feasibility of deconvolving blood-based gene expression profiles (GEPs) to estimate the proportions of immune cells and determine their prognostic values for cancer patients.</p><p>Methods and Results</p><p>Here, using GEPs from peripheral blood mononuclear cells (PBMC) of 108 non-small cell lung cancer (NSCLC) patients, we deconvolved the immune cell proportions and analyzed their association with patient survival. Univariate Kaplan-Meier analysis showed that a low proportion of T cells was significantly associated with poor patient survival, as was the proportion of T helper cells; however, only the proportion of T cells was independently prognostic for patients by a multivariate Cox regression analysis (hazard ratio = 2.23; 95% CI, 1.01–4.92; <i>p</i> = .048). Considering that altered peripheral blood compositions can reflect altered immune responses within the tumor microenvironment, based on a tissue-based GEPs of NSCLC patients, we demonstrated a significant association between poor patient survival and the low level of antigen presentation, which play a critical role in T cell proliferation.</p><p>Conclusions</p><p>These results demonstrate that it is feasible to deconvolve GEPs from banked blood specimens for retrospective survival analysis of alterations of immune cell composition, and suggest the proportion of T cells in PBMC which might reflect the antigen presentation level within the tumor microenvironment can be a prognostic marker for NSCLC patients.</p></div