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2022 ◽  
Author(s):  
Yongsheng Zhang ◽  
Yunlong Wang ◽  
Jichuang Wang ◽  
Kaixiang Zhang

Abstract Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI picture of BLCA remains unclear. Common gene expression data was obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package "limma" was applied to find differentially expressed genes (DEGs). Principal-component analysis (PCA) was used to calculate the ICI score. A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with Macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibits better outcome than the low one (p < 0.001). Finally, the group with a high tumor mutation burden (TMB) as well as a high ICI score had the best outcome. (p <0.001). Combining TMB and ICI score resulted in a more accurate survival prediction, suggesting that ICI score could be used as a prognostic marker for BLCA patients.


2021 ◽  
Vol 12 ◽  
Author(s):  
Fan Gao ◽  
Lei Tian ◽  
Hui Shi ◽  
Peihao Zheng ◽  
Jing Wang ◽  
...  

In our research, we screened 1,495 documents, compiled the whole-exome sequencing data of several studies, formed a data set including 92 observations of RRDLBCL (Relapsed and refractory diffuse large B-cell lymphoma), and performed association analysis on the high-frequency mutations among them. The most common mutations in the data set include TTN, KMT2D, TP53, IGLL5, CREBBP, BCL2, MYD88, and SOCS1 etc. Among these, CREBBP, KMT2D, and BCL2 have a strong association with each other, and SOCS1 has a strong association with genes such as STAT6, ACTB, CIITA, ITPKB, and GNA13. TP53 lacks significant associations with most genes. Through SOM clustering, expression-level analysis and protein interaction analysis of common gene mutations, we believe that RRDLBCL can be divided into five main types. We tested the function of the model and described the clinical characteristics of each subtype through a targeted sequencing RRDLBCL cohort of 96 patients. The classification is stated as follows: 1) JAK-STAT-related type: including STAT6, SOCS1, CIITA, etc. The genetic lineage is similar to PMBL and cHL. Retrospective analysis suggests that this subtype responds poorly to induction therapy (R-CHOP, p &lt; 0.05). 2) BCL-CREBBP type: Epigenetic mutations such as KMT2D and CREBBP are more common in this type, and are often accompanied by BCL2 and EZH2 mutations. 3) MCD type: including MYD88 and CD79B, PIM1 is more common in this subtype. 4) TP53 mutation: TP53 mutant patients, which suggests the worst prognosis (p &lt; 0.05) and worst response to CART treatment. 5) Undefined type (Sparse item type): Major Genetic Change Lacking Type, which has a better prognosis and better response to CART treatment. We also reviewed the literature from recent years concerning the previously mentioned common gene mutations.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4317-4317
Author(s):  
Alessandra Trojani ◽  
Barbara Di Camillo ◽  
Luca Emanuele Bossi ◽  
Antonino Greco ◽  
Livia Leuzzi ◽  
...  

Abstract We performed a comparative gene expression profiling (GEP) study on B-cells and plasma cells of Waldenström Macroglobulinemia (WM), IgM monoclonal gammopathies of undetermined significance (IgMMGUS), and normal individuals (CTRLs) to identify GEP changes as reliable predictors of progression of IgMMGUS to WM. We analyzed bone marrow B-cells and plasma cells from 36 WM patients, 13 IgMMGUS subjects, and 7 CTRLs by Affymetrix microarray, respectively (Table 1). GEP experiments were performed on the CD19+ and CD138+ cells using GeneChip-HGU133 Plus 2.0. Data were preprocessed and normalized by Robust Multi-Array Average and ComBat. Selection of the different expressed genes was performed separately for CD19+ and CD138+ cells, using Significance Analysis of Microarrays (SAM) on the 3 groups and a false discovery rate threshold of 5%, followed, for significance comparisons, by a pair-wise SAM test corrected for multiple testing. We focused on the comparison of the CD19+ cells of WM vs. IgMMGUS vs. CTRLs which highlighted 2038 unique genes whereas the same comparison of the CD138+ cells determined 29 unique genes (Trojani et.al. Cancers 2021). Among the 2038 DEGs, 115 genes were grouped in KEGG pathways involved in Wnt-signaling, BCR-signaling, calcium signaling, hematopoietic cell antigens, cell adhesion, adherens junctions, coagulation cascade, platelet activation, cytokine receptor, and signaling pathways responsible for cell cycle, apoptosis, and survival. Interestingly, most of the 115 DEGs in B-cells were different expressed in WM vs. IgMMGUS and CTRLs. Only 9/115 DEGs were significantly different expressed in WM vs. CTRLs and in IgMMGUS vs. CTRLs, but no significant expression changes were noted between WM and IgMMGUS (Table 2). To further inspect the similarities and the differences among WM and IgMMGUS, we computed the Euclidean pair-wise distance between subjects and, using this distance as weight, constructed a minimum spanning tree (MST) (Figure 1). Considerably, four probesets identified ADRB2 (transmembrane Beta adrenergic receptor) which was up regulated in WM and IgMMGUS compared to CTRLs. The over expression of ADRB2 was also demonstrated in Mantle Cell Lymphoma cell lines and in Diffuse large B-cell lymphoma (DLBCL) lymphocytes compared to normal B-cells (doi10.1016/j.cellsig.2017.08.002), and in most malignancies (doi10.1007/s11033-021-06250-y) . As far as we know, ADAM23 (ADAM Metallopeptidase Domain23) has not been found in WM, whereas we suggest its possible role in WM patients with Sjogren's syndrome (SS). ADAM23 plays a role in the peripheral neuropathy by controlling the activity of potassium channels in SS (doi10.1007/s10067-016-3499-z). Some authors found that sensory/motor neuropathies were associated with MGUS patients (doi10.1017/s0317167100011483). We strongly believe that the down regulation of ADAM23 in WM and IgMMGUS has a good chance to be associated with clinical neuropathy in WM and IgMMGUS. RASGRP3 (RAS Guanyl Releasing Protein3) and PIK3AP1 (Phosphoinositide 3 Kinase Adaptor Protein1) play crucial roles in BCR signaling pathway: PIK3AP1 activates the PI3K-Akt signaling while RASGRP3 stimulates MAPK signaling pathway. The deregulation of LEF1 (Lymphoid Enhancer Binding Factor1) and genes of Wnt-pathway were previously demonstrated in B-cell disorders and multiple myeloma (doi10.1007/s00277-017-3207-3, doi10.1016/j.pathol.2019.09.009). According to these studies, we showed the under expression of LEF1 in WM and IgMMGUS compared to CTRLs. We identified the down regulation of EZH2 (Enhancer Of Zeste2 Polycomb Repressive Complex2Subunit) in WM and IgMMGUS compared to CTRLs. EZH2 is involved in Follicular lymphoma and DLBCL (doi10.1080/2162402X.2017.1321184). CDHR3 (Cadherin Related Family Member3), CHEK1 (Checkpoint Kinase1), and HIST1H1B (Histone-H1.5) were over expressed in CTRLs compared to IgMMGUS and WM. In conclusion, the common gene-set in WM and IgMMGUS could suggest two-hit hypothesis. First, the gene-set could play a role in the risk of progression of IgMMGUS to WM. Until now, all the IgMMGUS subjects have not been transformed in WM or other NHL, but they have been monitored every 6 months, and their possible transformation to lymphoma could highlight new insights. The second hypothesis suggests their involvement in the biological processes of leukemogenesis in WM and IgMMGUS which will be further investigated. Figure 1 Figure 1. Disclosures Tedeschi: AbbVie: Honoraria, Speakers Bureau; AstraZeneca: Honoraria, Speakers Bureau; Beigene: Honoraria, Speakers Bureau; Janssen: Honoraria, Speakers Bureau.


2021 ◽  
Author(s):  
Neetu Tyagi ◽  
Dinesh Gupta

Abstract Background Autoimmune diseases develop when a person’s immune system starts developing immune response against its own healthy cells, tissues, or any other cell constituents. Rheumatoid Arthritis (RA) and Systemic Lupus Erythromatosus (SLE) are the two most common systemic inflammatory autoimmune diseases, sharing various clinical as well as pathological signatures. Although multiple studies have been conducted to date, very little is known about molecular pathogenesis and overlapping molecular signatures of the two diseases. Motivated to explore the common molecular disease features, we conducted a meta-analysis of the publicly available microarray gene expression datasets of RA and SLE. Methods Common and unique gene signatures of RA and SLE were identified based on analysis of microarray gene-expression datasets. Hub genes were identified by performing network analysis of protein-protein interaction (PPI) networks of the identified genes. Gene ontology functional enrichment and integrative pathway analysis was also performed to understand the underlying molecular mechanisms in the diseases. Results Intriguingly, out of the identified signature genes, 9 are upregulated and 24 are downregulated. Many of the common gene signatures identified in this study provide clues to the shared pathological mechanisms of RA and SLE. Amongst the identified signatures, MMP8, NFIL3, B4GALT5, HIST1H1C, NMT2, PTGDS and DUSP14, are the robust gene signatures shared by all the RA and SLE datasets. Functional analysis revealed that the common signatures are involved in the pathways such as mTOR signaling pathways, virus infection-related pathways, bone remodeling, activation of matrix metalloproteinase pathway, immune and inflammatory response-related pathways. Conclusions The common gene signatures and related pathways identified in this study substantiate the shared pathological mechanism involved in both diseases. Furthermore, our analysis of multi-cohort and multiple microarray datasets allow discovery of novel leads for clinical diagnosis and potential novel drug targets.


2021 ◽  
Author(s):  
Dan Lark ◽  
Thomas J LaRocca

Extracellular vesicles (EVs) like exosomes are secreted by numerous cell types in a variety of tissues. EVs have been implicated in both aging and age-related disorders like Alzheimer's disease (AD). However, how aging and AD affect EV biogenesis within and across cell types is poorly understood. Moreover, cells acquire characteristics based on tissue niche, but the impact of tissue residence on cell type EV biogenesis is unknown. We explored the Tabula Muris Senis, Mayo RNA-seq and ROSMAP data sets to characterize the cell and tissue-specific effects of aging and AD on genes involved in EV biogenesis. Specifically, we examined the age-dependent expression (age coefficient) of genes involved in EV biogenesis (22 genes), EV cargo (3 genes) and senescence (5 genes). Of the 131 cell populations (cell type x tissue) studied, 95 have at least one EV biogenesis gene impacted by age. The most common gene increased by age was charged multivesicular body protein 2A (CHMP2A) (54 cell populations). The most common gene decreased by age was syndecan binding protein (SDCBP) (58 cell populations). The senescence-associated genes cyclin-dependent kinase 1A (CDKN1A) and CDKN2A were not related to changes in CHMP2A and SDCBP and were altered by age in fewer cell populations. Finally, individuals with AD had decreased CHMP2A and increased SDCBP expression, opposite of what is observed with aging in the absence of diagnosed neurological disease. These findings indicate that age modifies exosome biogenesis gene expression in many cell populations mostly independent of senescence, and may be further altered in AD.


Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 542
Author(s):  
Hyun-Hwan Jeong ◽  
Arvind Chandrakantan ◽  
Adam C. Adler

Background: Obstructive Sleep Apnea (OSA) occurs in 7% of the adult population. The relationship between neurodegenerative diseases such as dementia and sleep disorders have long attracted clinical attention; however, no comprehensive data exists elucidating common gene expression between the two diseases. The objective of this study was to (1) demonstrate the practicability and feasibility of utilizing a systems biology approach called network-based identification of common driver genes (NICD) to identify common genomic features between two associated diseases and (2) utilize this approach to identify genes associated with both OSA and dementia. Methods: This study utilized 2 public databases (PCNet, DisGeNET) and a permutation assay in order to identify common genes between two co-morbid but mutually exclusive diseases. These genes were then linked to their mechanistic pathways through Enrichr, producing a list of genes that were common between the two different diseases. Results: 42 common genes were identified between OSA and dementia which were primarily linked to the G-coupled protein receptor (GPCR) and olfactory pathways. No single nucleotide polymorphisms (SNPs) were identified. Conclusions: This study demonstrates the viability of using publicly available databases and permutation assays along with canonical pathway linkage to identify common gene drivers as potential mechanistic targets for comorbid diseases.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexandre Leduc ◽  
Samia Chaouni ◽  
Frédéric Pouzoulet ◽  
Ludovic De Marzi ◽  
Frédérique Megnin-Chanet ◽  
...  

AbstractProton therapy allows to avoid excess radiation dose on normal tissues. However, there are some limitations. Indeed, passive delivery of proton beams results in an increase in the lateral dose upstream of the tumor and active scanning leads to strong differences in dose delivery. This study aims to assess possible differences in the transcriptomic response of skin in C57BL/6 mice after TBI irradiation by active or passive proton beams at the dose of 6 Gy compared to unirradiated mice. In that purpose, total RNA was extracted from skin samples 3 months after irradiation and RNA-Seq was performed. Results showed that active and passive delivery lead to completely different transcription profiles. Indeed, 140 and 167 genes were differentially expressed after active and passive scanning compared to unirradiated, respectively, with only one common gene corresponding to RIKEN cDNA 9930021J03. Moreover, protein–protein interactions performed by STRING analysis showed that 31 and 25 genes are functionally related after active and passive delivery, respectively, with no common gene between both types of proton delivery. Analysis showed that active scanning led to the regulation of genes involved in skin development which was not the case with passive delivery. Moreover, 14 ncRNA were differentially regulated after active scanning against none for passive delivery. Active scanning led to 49 potential mRNA-ncRNA pairs with one ncRNA mainly involved, Gm44383 which is a miRNA. The 43 genes potentially regulated by the miRNA Gm44393 confirmed an important role of active scanning on skin keratin pathway. Our results demonstrated that there are differences in skin gene expression still 3 months after proton irradiation versus unirradiated mouse skin. And strong differences do exist in late skin gene expression between scattered or scanned proton beams. Further investigations are strongly needed to understand this discrepancy and to improve treatments by proton therapy.


2020 ◽  
Vol 7 ◽  
Author(s):  
Melissa A. Nickles ◽  
Kai Huang ◽  
Yi-Shin Chang ◽  
Maria M. Tsoukas ◽  
Nadera J. Sweiss ◽  
...  

In this study we analyzed gene co-expression networks of three immune-related skin diseases: cutaneous sarcoidosis (CS), discoid lupus erythematosus (DLE), and psoriasis. We propose that investigation of gene co-expression networks may provide insights into underlying disease mechanisms. Microarray expression data from two cohorts of patients with CS, DLE, or psoriasis skin lesions were analyzed. We applied weighted gene correlation network analysis (WGCNA) to construct gene-gene similarity networks and cluster genes into modules based on similar expression profiles. A module of interest that was preserved between datasets and corresponded with case/control status was identified. This module was related to immune activation, specifically leukocyte activation, and was significantly increased in both CS lesions and DLE lesions compared to their respective controls. Protein-protein interaction (PPI) networks constructed for this module revealed seven common hub genes between CS lesions and DLE lesions: TLR1, ITGAL, TNFRSF1B, CD86, SPI1, BTK, and IL10RA. Common hub genes were highly upregulated in CS lesions and DLE lesions compared to their respective controls in a differential expression analysis. Our results indicate common gene expression patterns in the immune processes of CS and DLE, which may have indications for future therapeutic targets and serve as Th1-mediated disease biomarkers. Additionally, we identified hub genes unique to CS and DLE, which can help differentiate these diseases from one another and may serve as unique therapeutic targets and biomarkers. Notably, we find common gene expression patterns in the immune processes of CS and DLE through utilization of WGCNA.


Author(s):  
Ombretta Melaiu ◽  
Angelica Macauda ◽  
Juan Sainz ◽  
Diego Calvetti ◽  
Maria Sole Facioni ◽  
...  

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