Identification of Key Genes and Pathways in Myeloma side population cells by Bioinformatics Analysis

Targeting cancer stem cells in multiple myeloma

Multiple myeloma (MM) is a hematological malignancy of bone marrow (BM) plasma cells with excessive clonal expansion and is associated with the overproduction of light-chain or monoclonal immunoglobulins (Igs). MM remains incurable, with high rates of relapses and refractory disease after first-line treatment. Cancer stem cells (CSCs) have been implicated in drug resistance in MM; however, the evidence for CSCs in MM is not adequate, partly due to a lack of uniformity in the definitions of multiple myeloma stem cells (MMSCs). We review advances in understanding MMSCs and their role in drug resistance to MM therapies. We also discuss novel therapeutic strategies to overcome MMSC-mediated relapses and drug resistance.

TAZ downregulated ANXA1 expression to modulate myeloma cell interactions with bone marrow mesenchymal stromal cells

We and others have previously shown that TAZ plays a tumor suppressive role in multiple myeloma. However, recent reports suggest that molecular crosstalk between the myeloma cells and bone marrow stromal components contributes to the myeloma cell survival and drug resistance. These reports further point to reciprocal interaction via adhesion molecules as the most prominent mechanism of intercellular crosstalk between myeloma cells and bone marrow mesenchymal stromal cells (BM-MSCs). YAP/TAZ silencing/expression has been shown to correlate across all cancers with a set of adhesion/extracellular matrix proteins. Therefore, we hypothesized that TAZ may regulate myeloma cell interaction with BM stromal cells by influencing the expression of distinct cell adhesion signatures. We used previously established TAZ myeloma cell line models, including DELTA47-pLENTI or TAZ knockout DELTA47 cells cocultured with or without BM-MSCs, as our study models. Using RNA sequencing analysis, we performed the first comprehensive screen for cell adhesion-related transcriptional targets of TAZ in multiple myeloma (MM). In doing so, we uncovered an enrichment of cell adhesion-related genes in TAZ knockout DELTA47 cells relatively to pLENTI-DELTA47 cells, including 11 genes with log2 fold change > 2 (p < 0.05), namely, ANXA1, ADGRL2, NCAM1, NCAM2, ADGRL3, CXADR, ALCAM, JAM2, KIRREL1, KIRREL2, and ADGRG7, suggesting possible relationship with TAZ. We validated ANXA1 as a bona fide target of TAZ in MM. We show that TAZ represses myeloma cell migration and interaction with BM-MSCs by transcriptionally downregulating ANXA1 expression via TEAD-dependent mechanism. Our data provide new insights into the understanding of the role of TAZ in the intercellular communication signals between myeloma cells and BM-MSCs. Our findings also suggest that ANXA1 represents a putative cell adhesion target to attenuate BM-MSC driven, tumor-promoting interaction with myeloma cells.

Strategies for the Isolation and Identification of Gastric Cancer Stem Cells

Gastric cancer stem cells (GCSCs) originate from both gastric adult stem cells and bone marrow cells and are conspicuously present within the histological milieu of gastric cancer tissue. GCSCs play pivotal and multifaceted roles in the initiation, progression, and recurrence of gastric cancer. Hence, the characterization of GCSCs not only facilitates precise target identification for prospective therapeutic interventions in gastric cancer but also has significant implications for targeted therapy and the prognosis of gastric cancer. The prevailing techniques for GCSC purification involve their isolation using surface-specific cell markers, such as those identified by flow cytometry and immunomagnetic bead sorting techniques. In addition, in vitro culture and side-population cell sorting are integral methods in this context. This review discusses the surface biomarkers, isolation techniques, and identification methods of GCSCs, as well as their role in the treatment of gastric cancer.

The Clinical Significance and Involvement in Molecular Cancer Processes of Chemokine CXCL1 in Selected Tumors

Chemokines play a key role in cancer processes, with CXCL1 being a well-studied example. Due to the lack of a complete summary of CXCL1's role in cancer in the literature, in this study, we examine the significance of CXCL1 in various cancers such as bladder, glioblastoma, hemangioendothelioma, leukemias, Kaposi's sarcoma, lung, osteosarcoma, renal, and skin cancers (malignant melanoma, basal cell carcinoma, and squamous cell carcinoma), along with thyroid cancer. We focus on understanding how CXCL1 is involved in the cancer processes of these specific types of tumors. We look at how CXCL1 affects cancer cells, including their proliferation, migration, EMT, and metastasis. We also explore how CXCL1 influences other cells connected to tumors, like promoting angiogenesis, recruiting neutrophils, and affecting immune cell functions. Additionally, we discuss the clinical aspects by exploring how CXCL1 levels relate to cancer staging, lymph node metastasis, patient outcomes, chemoresistance, and radioresistance.

PLEK2 mediates metastasis and invasion via α5-nAChR activation in nicotine-induced lung adenocarcinoma

Evidence has shown a strong relationship between smoking and epithelial mesenchymal transition (EMT). α5-nicotinic acetylcholine receptor (α5-nAChR) contributes to nicotine-induced lung cancer cell EMT. The cytoskeleton-associated protein PLEK2 is mainly involved in cytoskeletal protein recombination and cell stretch migration regulation, which is closely related to EMT. However, little is known about the link between nicotine/α5-nAChR and PLEK2 in lung adenocarcinoma (LUAD). Here, we identified a link between α5-nAChR and PLEK2 in LUAD. α5-nAChR expression was correlated with PLEK2 expression, smoking status and lower survival in vivo. α5-nAChR mediated nicotine-induced PLEK2 expression via STAT3. α5-nAChR/PLEK2 signaling is involved in LUAD cell migration, invasion and stemness. Moreover, PLEK2 was found to interact with CFL1 in nicotine-induced EMT in LUAD cells. Furthermore, the functional link among α5-nAChR, PLEK2 and CFL1 was confirmed in mouse xenograft tissues and human LUAD tissues. These findings reveal a novel α5-nAChR/PLEK2/CFL1 pathway involved in nicotine-induced LUAD progression.

The screening and validation process of miR-223-3p for saliva identification

More accurate identification of the types of body fluids left at a crime scene is indispensable for improving the judicial chain of evidence. MicroRNAs (miRNAs) have become recognized as ideal molecular markers for the identification of body fluids in forensic science due to their short length, stability and high tissue specificity. In this study, small RNA sequencing was performed on 20 samples of five types of body fluids (peripheral blood, menstrual blood, saliva, semen, and vaginal secretions) with the BGISEQ-500 sequencing platform, and the specific miRNA markers of saliva and vaginal secretions were screened by bioinformatics methods, including differential expression analysis and significant enrichment analysis. Through RT-qPCR validation of 169 samples, we confirmed that miR-223-3p can be used as a saliva-specific marker. In addition, we considered miR-223-3p in combination with four other miRNA molecules (miR-451a, miR-891a-5p, miR-144-5p, miR-203a-3p) that had been previously screened and verified in our laboratory, and seven body fluid prediction models based on machine learning algorithms were constructed and verified. The results showed that a kernel density estimation (KDE) model based on the five miRNA markers for body fluid identification could achieve 100% accuracy in the samples tested in the present study.

Meta-analysis of integrated ChIP-seq and transcriptome data revealed genomic regions affected by estrogen receptor alpha in breast cancer

BACKGROUND

The largest group of patients with breast cancer are estrogen receptor-positive (ER+) type. The estrogen receptor acts as a transcription factor and triggers cell proliferation and differentiation. Hence, investigating ER-DNA interaction genomic regions can help identify genes directly regulated by ER and understand the mechanism of ER action in cancer progression.

METHODS

In the present study, we employed a workflow to do a meta-analysis of ChIP-seq data of ER+ cell lines stimulated with 10 nM and 100 nM of E2. All publicly available data sets were re-analyzed with the same platform. Then, the known and unknown batch effects were removed. Finally, the meta-analysis was performed to obtain meta-differentially bound sites in estrogen-treated MCF7 cell lines compared to vehicles (as control). Also, the meta-analysis results were compared with the results of T47D cell lines for more precision. Enrichment analyses were also employed to find the functional importance of common meta-differentially bound sites and associated genes among both cell lines.

RESULTS

Remarkably, POU5F1B, ZNF662, ZNF442, KIN, ZNF410, and SGSM2 transcription factors were recognized in the meta-analysis but not in individual studies. Enrichment of the meta-differentially bound sites resulted in the candidacy of pathways not previously reported in breast cancer. PCGF2, HNF1B, and ZBED6 transcription factors were also predicted through the enrichment analysis of associated genes. In addition, comparing the meta-analysis results of both ChIP-seq and RNA-seq data showed that many transcription factors affected by ER were up-regulated.

CONCLUSION

The meta-analysis of ChIP-seq data of estrogen-treated MCF7 cell line leads to the identification of new binding sites of ER that have not been previously reported. Also, enrichment of the meta-differentially bound sites and their associated genes revealed new terms and pathways involved in the development of breast cancer which should be examined in future in vitro and in vivo studies.

Network pharmacology based research into the effect and potential mechanism of Portulaca oleracea L. polysaccharide against ulcerative colitis

BACKGROUND

Ulcerative colitis (UC) as a chronic inflammatory bowel disease (IBD) has received extensive concerns worldwide. As a traditional herbal medicine, Portulaca oleracea L. (POL) has a wide application in gastrointestinal diseases such as diarrhea and dysentery. This study aims to investigate the target and potential mechanisms of Portulaca oleracea L. polysaccharide (POL-P) in the treatment of UC.

METHOD

The active ingredients and relevant targets of POL-P were searched through the TCMSP and Swiss Target Prediction databases. UC related targets were collected through the GeneCards and DisGeNET databases. The intersection of POL-P targets with UC targets was done using Venny. Then, protein-protein interaction (PPI) network of the intersection targets was constructed through the STRING database and analyzed using Cytohubba to identify the key targets of POL-P in the treatment of UC. In addition, GO and KEGG enrichment analyses were performed on the key targets and the binding mode of POL-P to the key targets was further analyzed by molecular docking technology. Finally, the efficacy and target of POL-P were verified using animal experiments and immunohistochemical staining.

RESULTS

A total of 316 targets were obtained based on POL-P monosaccharide structures, among which 28 were related to UC. Cytohubba analysis showed that VEGFA, EGFR, TLR4, IL-1β, STAT3, IL-2, PTGS2, FGF2, HGF, and MMP9 were the key targets for UC treatment and were mainly involved in multiple signaling pathways such as proliferation, inflammation, and immune response. Molecular docking results revealed that POL-P had a good binding potential to TLR4. In vivo validation results showed that POL-P significantly reduced the overexpression of TLR4 and its downstream key proteins (MyD88 and NF-κB) in intestinal mucosa of UC mice, which indicated that POL-P improved UC by mediating TLR4 related proteins.

CONCLUSION

POL-P may be a potential therapeutic agent for UC and its mechanism is closely related to the regulation of TLR4 protein. This study will provide novel insights for the treatment of UC with POL-P.

Gene network interaction analysis to elucidate the antimicrobial resistance mechanisms in the Clostridiumdifficile

Antimicrobial resistance has caused chaos worldwide due to the depiction of multidrug-resistant (MDR) infective microorganisms. A thorough examination of antimicrobial resistance (AMR) genes and associated resistant mechanisms is vital to solving this problem. Clostridium difficile (C. difficile) is an opportunistic nosocomial bacterial strain that has acquired exogenous AMR genes that confer resistance to antimicrobials such as erythromycin, azithromycin, clarithromycin, rifampicin, moxifloxacin, fluoroquinolones, vancomycin, and others. A network of interactions, including 20 AMR genes, was created and analyzed. In functional enrichment analysis, Cellular components (CC), Molecular Functions (MF), and Biological Processes (BP) were discovered to have substantial involvement. Mutations in the rpl genes, which encode ribosomal proteins, confer resistance in Gram-positive bacteria. Full erythromycin and azithromycin cross-resistance can be conferred if more than one of the abovementioned genes is present. In the enriched BP, rps genes related to transcriptional regulation and biosynthesis were found. The genes belong to the rpoB gene family, which has previously been related to rifampicin resistance. The genes rpoB, gyrA, gyrB, rpoS, rpl genes, rps genes, and Van genes are thought to be the hub genes implicated in resistance in C. difficile. As a result, new medications could be developed using these genes. Overall, our observations provide a thorough understanding of C. difficile AMR mechanisms.

The Transcription Factor Twist1 Has a Significant Role in Mycosis Fungoides (MF) Cell Biology: An RNA Sequencing Study of 40 MF Cases

The purpose of this RNA sequencing study was to investigate the biological mechanism underlying how the transcription factors (TFs) Twist1 and Zeb1 influence the prognosis of mycosis fungoides (MF). We used laser-captured microdissection to dissect malignant T-cells obtained from 40 skin biopsies from 40 MF patients with stage I-IV disease. Immunohistochemistry (IHC) was used to determinate the protein expression levels of Twist1 and Zeb1. Based on RNA sequencing, principal component analysis (PCA), differential expression (DE) analysis, ingenuity pathway analysis (IPA), and hub gene analysis were performed between the high and low Twist1 IHC expression cases. The DNA from 28 samples was used to analyze the TWIST1 promoter methylation level. In the PCA, Twist1 IHC expression seemed to classify cases into different groups. The DE analysis yielded 321 significant genes. In the IPA, 228 significant upstream regulators and 177 significant master regulators/causal networks were identified. In the hub gene analysis, 28 hub genes were found. The methylation level of TWIST1 promoter regions did not correlate with Twist1 protein expression. Zeb1 protein expression did not show any major correlation with global RNA expression in the PCA. Many of the observed genes and pathways associated with high Twist1 expression are known to be involved in immunoregulation, lymphocyte differentiation, and aggressive tumor biology. In conclusion, Twist1 might be an important regulator in the disease progression of MF.

Comprehensive analysis of thirteen-gene panel with prognosis value in Multiple Myeloma

BACKGROUND

Although there are many treatments for Multiple myeloma (MM), patients with MM still unable to escape the recurrence and aggravation of the disease.

OBJECTIVE

We constructed a risk model based on genes closely associated with MM prognosis to predict its prognostic value.

METHODS

Gene function enrichment and signal pathway enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, univariate and multivariate Cox regression analysis, Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) analysis were used to identify the prognostic gene signature for MM. Finally, the prognostic gene signature was validated using the Gene Expression Omnibus (GEO) database.

RESULTS

Thirteen prognostic genes were screened by univariate Cox analysis and LASSO regression analysis. Multivariate Cox analysis revealed risk score to be an independent prognostic factor for patients with MM [Hazard Ratio (HR) = 2.564, 95% Confidence Interval (CI) = 2.223-2.958, P< 0.001]. The risk score had a high level of predictive value according to ROC analysis, with an area under the curve (AUC) of 0.744.

CONCLUSIONS

The potential prognostic signature of thirteen genes were assessed and a risk model was constructed that significantly correlated with prognosis in MM patients.

Mechanism Research of Platelet Core Marker Prediction and Molecular Recognition in Cardiovascular Events

BACKGROUND

Thrombosis triggered by platelet activation plays a vital role in the pathogenesis of cardiovascular and cerebrovascular diseases.

OBJECTIVE

This study aims to find platelet combined biomarkers for cardiovascular diseases and investigate the possibility of Concanavalin A (ConA) acting on platelets as a new pharmacological target.

METHODS

High-throughput Technology and bioinformatics analysis were combined and groups of microarray chip gene expression profiles for acute myocardial infarction (AMI) and sickle cell disease (SCD) were obtained using GEO database screening. R language limma package was used to obtain differentially expressed genes (DEGs). GO, KEGG, and other databases were utilized to perform the enrichment analysis of DEGs' functions, pathways, etc. PPI network was constructed using STRING database and Cytoscape software, and MCC algorithm was used to obtain the 200 core genes of the two groups of DEGs. Core targets were confirmed by constructing an intersection area screening. A type of molecular probe, ConA, was molecularly docked with the above core targets on the Zdock, HEX, and 3D-DOCK servers.

RESULTS

We found six core markers, CD34, SOCS2, ABL1, MTOR, VEGFA, and SMURF1, which were simultaneously related to both diseases, and the docking effect showed that VEGFA is the best-performing.

CONCLUSION

VEGFA is most likely to reduce its expression by binding to ConA, which could affect the downstream regulation of the PI3K/Akt signaling pathway during platelet activation. Some other core targets also have the opportunity to interact with ConA to affect platelet-activated thrombosis and trigger changes in cardiovascular events.

Systems biology and in silico-based analysis of PCOS revealed the risk of metabolic disorders

Background

Polycystic ovarian syndrome (PCOS) is a common condition of hyperandrogenism, chronic ovulation, and polycystic ovaries in females during the reproduction and maturation of the ovum. Although PCOS has been associated with metabolic disorders, including type 2 diabetes (T2D), obesity (OBE), and cardiovascular disease (CVD), Causal connection and molecular features are still unknown.

Purpose

Therefore, we investigated the shared common differentially expressed genes (DEGs), pathways, and networks of associated proteins in PCOS and metabolic diseases with therapeutic intervention.

Methods

We have used a bioinformatics pipeline to analyze transcriptome data for the polycystic ovarian syndrome (PCOS), type 2 diabetes (T2D), obesity (OBE), and cardiovascular diseases (CVD) in female patients. Then we employed gene-disease association network, gene ontology (GO) and signaling pathway analysis, selection of hub genes from protein-protein interaction (PPI) network, molecular docking, and gold benchmarking approach to screen potential hub proteins.

Result

We discovered 2225 DEGs in PCOS patients relative to healthy controls and 34, 91, and 205 significant DEGs with T2D, Obesity, and CVD, respectively. Gene Ontology analysis revealed several significant shared and metabolic pathways from signaling pathway analysis. Furthermore, we identified ten potential hub proteins from PPI analysis that may serve as a therapeutic intervention in the future. Finally, we targeted one significant hub protein, IGF2R (PDB ID: 2V5O), out of ten hub proteins based on the Maximal clique centrality (MCC) algorithm and literature review for molecular docking study. Enzastaurin (-12.5), Kaempferol (-9.1), Quercetin (-9.0), and Coumestrol (-8.9) kcal/mol showed higher binding affinity in the molecular docking approach than 19 drug compounds. We have also found that the selected four compounds displayed favorable ADMET properties compared to the native ligand.

Conclusion

Our in-silico research findings identified a shared molecular etiology between PCOS and metabolic diseases that may suggest new therapeutic targets and warrants future experimental validation of the key targets.

An interactive analysis of the mouse oviductal miRNA profiles

MicroRNAs are small non-coding molecules that control several cellular functions and act as negative post-transcriptional regulators of the mRNA. While their implication in several biological functions is already known, an important role as regulators of different physiological and pathological processes in fertilization and embryo development is currently emerging. Indeed, miRNAs have been found in the oviductal fluid packaged within the extracellular vesicles, which might act as natural nanoshuttles by transporting lipids, proteins, RNA molecules and miRNAs from the oviduct to the gametes or embryos. Here, an exhaustive bibliography search was carried out, followed by the construction of a computational model based on the networks theory in an attempt to recreate and elucidate the pathways potentially activated by the oviductal miRNA. The omics data published to date were gathered to create the Oviductal MiRNome, in which the miRNA target genes and their interactions are represented by using stringApp and the Network analyzer from Cytoscape 3.7.2. Then, the hyperlinked nodes were identified to investigate the pathways in which they are involved using the gene ontology enrichment analysis. To study the phenotypical effects after the removal of key genes on the reproductive system and embryo, knockout mouse lines for every protein-coding gene were investigated by using the International Mouse Phenotyping Consortium database. The creation of the Oviductal MiRNome revealed the presence of important genes and their interactions within the network. The functional enrichment analysis revealed that the hyperlinked nodes are involved in fundamental cellular functions, both structural and regulatory/signaling, suggesting their implication in fertilization and early embryo development. This fact was as well evidenced by the effects of the gene deletion in KO mice on the reproductive system and embryo development. The present study highlights the importance of studying the miRNA profiles and their enormous potential as tools to improve the assisted reproductive techniques currently used in human and animal reproduction.

PLEK2 promotes cancer stemness and tumorigenesis of head and neck squamous cell carcinoma via the c-Myc-mediated positive feedback loop

Background

Head and neck squamous cell carcinoma (HNSCC) is one of the most frequent malignancies worldwide and is characterized by unfavorable prognosis, high lymph node metastasis and early recurrence. However, the molecular events regulating HNSCC tumorigenesis remain poorly understood. Therefore, uncovering the underlying mechanisms is urgently needed to identify novel and promising therapeutic targets for HNSCC. In this study, we aimed to explore the role of pleckstrin‐2 (PLEK2) in regulating HNSCC tumorigenesis.

Methods

The expression pattern of PLEK2 and its clinical significance in HNSCC were determined by analyzing publicly assessable datasets and our own independent HNSCC cohort. In vitro and in vivo experiments, including cell proliferation, colony formation, Matrigel invasion, tumor sphere formation, ALDEFLUOR, Western blotting assays and xenograft mouse models, were used to investigate the role of PLEK2 in regulating the malignant behaviors of HNSCC cells. The underlying molecular mechanisms for the tumor‐promoting role of PLEK2 were elucidated using co‐immunoprecipitation, cycloheximide chase analysis, ubiquitination assays, chromatin immunoprecipitation‐quantitative polymerase chain reaction, luciferase reporter assays and rescue experiments.

Results

The expression levels of PLEK2 mRNA and protein were significantly increased in HNSCC tissues, and PLEK2 overexpression was strongly associated with poor overall survival and therapeutic resistance. Additionally, PLEK2 was important for maintaining the proliferation, invasion, epithelial‐mesenchymal transition, cancer stemness and tumorigenesis of HNSCC cells and could alter the cellular metabolism of the cancer cells. Mechanistically, PLEK2 interacted with c‐Myc and reduced the association of F‐box and WD repeat domain containing 7 (FBXW7) with c‐Myc, thereby avoiding ubiquitination and subsequent proteasome‐mediated degradation of c‐Myc. Moreover, the c‐Myc signaling activated by PLEK2 was important for sustaining the aggressive malignant phenotypes and tumorigenesis of HNSCC cells. c‐Myc also directly bounded to the PLEK2 promoter and activated its transcription, forming a positive feedback loop.

Conclusions

Collectively, these findings uncover a previously unknown molecular basis of PLEK2‐enhanced c‐Myc signaling in HNSCC, suggesting that PLEK2 may represent a promising therapeutic target for treating HNSCC.

Systematic analysis of prognostic significance, functional enrichment and immune implication of STK10 in acute myeloid leukemia

Background

Despite deeper understanding of the genetic landscape of acute myeloid leukemia (AML), the improvement of survival is still a great challenge. STK10 is overexpressed in several cancers with functions varying according to cancer types. But the functions of STK10 in AML has never been reported.

Methods

We analyzed the expression, prognosis and potential functions of STK10 utilizing public web servers. Metascape and the String database were used for functional and protein–protein interaction analyses.

Results

We found STK10 was enriched in blood & immune cells and overexpressed in AML. High STK10 expression was associated with poor overall survival, which was also identified in the subgroups of patients ≤ 60 years old and patients with non-high-risk cytogenetics. We demonstrated genes associated with STK10 were enriched in blood, spleen and bone marrow, influencing the immune function and biological process of AML. ITGB2 and ITGAM might directly interact with STK10 and were associated with poor prognosis. Besides, STK10 was associated with the infiltration of immune cells and immune checkpoints, like HLA-E, CD274 and GAL-9.

Conclusions

The present study was the original description of STK10 in AML and set the stage for developing STK10 as a new prognostic marker or therapeutic target for AML.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01251-7.

Emerging Roles of Pleckstrin-2 Beyond Cell Spreading

Pleckstrin-2 is a member of pleckstrin family with well-defined structural features that was first identified in 1999. Over the past 20 years, our understanding of PLEK2 biology has been limited to cell spreading. Recently, increasing evidences support that PLEK2 plays important roles in other cellular events beyond cell spreading, such as erythropoiesis, tumorigenesis and metastasis. It serves as a potential diagnostic and prognostic biomarker as well as an attractive target for the treatment of cancers. Herein, we summary the protein structure and molecular interactions of pleckstrin-2, with an emphasis on its regulatory roles in tumorigenesis.

Key immune-related gene ITGB2 as a prognostic signature for acute myeloid leukemia

Background

The tumor microenvironment (TME) has an essential role in tumorigenesis, progression, and therapeutic response in many cancers. Currently, the role of TME in acute myeloid leukemia (AML) is unclear. This study investigated the correlation between immune-related genes and prognosis in AML patients.

Methods

Transcriptome RNA-Seq data for 151 AML samples were downloaded from TCGA database (https://portal.gdc.cancer.gov/), and the immune related genes (irgs) were selected from Immport database. Bioinformatics screening was used to identify irgs for AML, and genes with a critical role in the prognosis of AML were selected for further analysis. To confirm the prognostic role of irgs in AML, we undertook protein-protein interaction (PPI) network analysis of the top 30 interacting genes. We then investigated associations between immune cell infiltration and prognosis in AML patients. Immunohistochemistry was used to validate protein expression levels between AML and normal bone marrow samples. Analysis of the drug sensitivity of the selected gene was then performed.

Results

The integrin lymphocyte function-associated antigen 1 (CD11A/CD18; ITGAL/ITGB2) was identified as the key immune-related gene that significantly influenced prognosis in AML patients. Overexpression of ITGB2 indicated poor prognosis in AML patients (P=0.007). Risk modeling indicated that a high-risk score led to poor outcomes (P=3.076e−08) in AML patients. The risk model showed accuracy for predicting prognosis in AML patients, with area under curve (AUC) at 1 year, 0.816; AUC at 3 years, 0.82; and AUC at 5 years, 0.875. In addition, we found that ITGB2 had a powerful influence on immune cell infiltration into AML TME. The results of immunohistochemistry showed that AML patients had significantly higher ITGB2 protein expression than normal samples. The AML patients were divided into 2 groups based on ITGB2 risk scores. Drug sensitivity test results indicated that the high-risk group was sensitive to cytarabine, axitinib, bosutinib, and docetaxel, but resistant to cisplatin and bortezomib.

Conclusions

In the present study, we found that ITGB2 may be able to serve as a biomarker for assessing prognosis and drug sensitivity in AML patients.

Identification of Vital Hub Genes and Potential Molecular Pathways of Dermatomyositis by Bioinformatics Analysis

Dermatomyositis is an autoimmune disease characterized by severe symmetrical muscle dysfunction and pain. This study was aimed at discovering vital hub genes and potential molecular pathways of DM through bioinformatics analysis, which contributes to identifying potential diagnostic or therapeutic biomarkers and targets. In this study, a total of 915 DEGs in DM samples including 167 upregulated genes and 748 downregulated genes were screened out by the limma package based on the GSE142807 dataset from the Gene Expression Omnibus (GEO) database. Furthermore, the results of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that these downregulated genes were highly associated with the immune-related biological processes and pathways. Therefore, 41 genes closely related to DM were extracted for further study based on the subcluster analysis through the Molecular Complex Detection (MCODE) software plugin in Cytoscape. Ultimately, 10 hub genes (including ISG15, DDX58, IFIT3, CXCL10, and STAT1) were identified as the potential candidate biomarkers and targets. Besides, we found that the identified hub genes directly or indirectly communicated with each other via molecular signaling pathways on the protein and transcription level. In general, under the guidance of bioinformatics analysis, 10 vital hub genes and molecular mechanisms in DM were identified and the expression of proinflammatory factors and interferon family proteins and genes showed high association with DM, which might help provide a theoretical foundation for the development of point-to-point targeted therapy in the future treatment of DM.

Pleckstrin-2 as a Prognostic Factor and Mediator of Gastric Cancer Progression

Pleckstrin-2 (PLEK2) is a crucial mediator of cytoskeletal reorganization. However, the potential roles of PLEK2 in gastric cancer are still unknown. PLEK2 expression in gastric cancer was examined by western blotting and real-time PCR. Survival analysis was utilized to test the clinical impacts of the levels of PLEK2 in gastric cancer patients. In vitro and in vivo studies were used to estimate the potential roles played by PLEK2 in modulating gastric cancer proliferation, self-renewal, and tumourigenicity. Bioinformatics approaches were used to monitor the effect of PLEK2 on epithelial-mesenchymal transition (EMT) signalling pathways. PLEK2 expression was significantly upregulated in gastric cancer as compared with nontumour samples. Kaplan-Meier plotter analysis revealed that gastric cancer patients with higher PLEK2 levels had substantially poorer overall survival compared with gastric cancer patients with lower PLEK2 levels. The upregulation or downregulation of PLEK2 in gastric cancer cell lines effectively enhanced or inhibited cell proliferation and proinvasive behaviour, respectively. Additionally, we also found that PLEK2 enhanced EMT through downregulating E-cadherin expression and upregulating Vimentin expression. Our findings demonstrated that PLEK2 plays a potential role in gastric cancer and may be a novel therapeutic target for gastric cancer.

Identification and Characterization of Multiple Myeloma Stem Cell-Like Cells

Multiple myeloma (MM) is a B-cell tumor of the blood system with high incidence and poor prognosis. With a further understanding of the pathogenesis of MM and the bone marrow microenvironment, a variety of adjuvant cell therapies and new drugs have been developed. However, the drug resistance and high relapse rate of MM have not been fundamentally resolved. Studies have shown that, in patients with MM, there is a type of poorly differentiated progenitor cell (MM stem cell-like cells, MMSCs). Although there is no recognized standard for identification and classification, it is confirmed that they are closely related to the drug resistance and relapse of MM. This article therefore systematically summarizes the latest developments in MMSCs with possible markers of MMSCs, introduces the mechanism of how MMSCs work in MM resistance and recurrence, and discusses the active pathways that related to stemness of MM.

Construction and Analysis of a Diagnostic Model Based on Differential Expression Genes in Patients With Major Depressive Disorder

Background: Major depressive disorder (MDD) is a common and severe psychiatric disorder with a heavy burden on the individual and society. However, the prevalence varies significantly owing to the lack of auxiliary diagnostic biomarkers. To identify the shared differential expression genes (DEGs) with potential diagnostic value in both the hippocampus and whole blood, a systematic and integrated bioinformatics analysis was carried out. Methods: Two datasets from the Gene Expression Omnibus database (GSE53987 and GSE98793) were downloaded and analyzed separately. A weighted gene co-expression network analysis was performed to construct the co-expression gene network of DEGs from GSE53987, and the most disease-related module was extracted. The shared DEGs from the module and GSE98793 were identified using a Venn diagram. Functional pathway prediction was used to identify the most disease-related DEGs. Finally, several DEGs were chosen, and their potential diagnostic value was determined by receiver operating characteristic curve analysis. Results: After weighted gene co-expression network analysis, the most MDD-related module (MEgrey) was identified, and 623 DEGs were extracted from this module. The intersection between MEgrey and GSE98793 was calculated, and 163 common DEGs were identified. The co-expression network of 163 DEGs from these was then reconstructed. All hub genes were identified based on the connective degree of the reconstructed co-expression network. Based on the results of functional pathway enrichment, 17 candidate hub genes were identified. Finally, logistic regression and receiver operating characteristic curves showed that three candidate hub genes (CEP350, SMAD5, and HSPG2) had relatively high auxiliary value in the diagnosis of MDD. Conclusion: Our results showed that the combination of CEP350, SMAD5, and HSPG2 has a relatively high diagnostic value for MDD. Pathway enrichment analysis also showed that these genes may play an important role in the pathogenesis of MDD. These results suggest a potentially important role for this gene combination in clinical practice.

Distinguishing Glioblastoma Subtypes by Methylation Signatures

Glioblastoma, also called glioblastoma multiform (GBM), is the most aggressive cancer that initiates within the brain. GBM is produced in the central nervous system. Cancer cells in GBM are similar to stem cells. Several different schemes for GBM stratification exist. These schemes are based on intertumoral molecular heterogeneity, preoperative images, and integrated tumor characteristics. Although the formation of glioblastoma is remarkably related to gene methylation, GBM has been poorly classified by epigenetics. To classify glioblastoma subtypes on the basis of different degrees of genes' methylation, we adopted several powerful machine learning algorithms to identify numerous methylation features (sites) associated with the classification of GBM. The features were first analyzed by an excellent feature selection method, Monte Carlo feature selection (MCFS), resulting in a feature list. Then, such list was fed into the incremental feature selection (IFS), incorporating one classification algorithm, to extract essential sites. These sites can be annotated onto coding genes, such as CXCR4, TBX18, SP5, and TMEM22, and enriched in relevant biological functions related to GBM classification (e.g., subtype-specific functions). Representative functions, such as nervous system development, intrinsic plasma membrane component, calcium ion binding, systemic lupus erythematosus, and alcoholism, are potential pathogenic functions that participate in the initiation and progression of glioblastoma and its subtypes. With these sites, an efficient model can be built to classify the subtypes of glioblastoma.