Identification of gene modules associated with survival of diffuse large B-cell lymphoma treated with CHOP-based chemotherapy

Identification of key potassium channel genes of temporal lobe epilepsy by bioinformatics analyses and experimental verification

One of the most prevalent types of epilepsy is temporal lobe epilepsy (TLE), which has unknown etiological factors and drug resistance. The detailed mechanisms underlying potassium channels in human TLE have not yet been elucidated. Hence, this study aimed to mine potassium channel genes linked to TLE using a bioinformatic approach. The results found that Four key TLE-related potassium channel genes (TERKPCGs) were identified: potassium voltage-gated channel subfamily E member (KCNA) 1, KCNA2, potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11), and KCNS1. A protein-protein interaction (PPI) network was constructed to analyze the relationship between TERKPCGs and other key module genes. The results of gene set enrichment analysis (GSEA) for a single gene indicated that the four TERKPCGs were highly linked to the cation channel, potassium channel, respiratory chain, and oxidative phosphorylation. The mRNA-TF network was established using four mRNAs and 113 predicted transcription factors. A ceRNA network containing seven miRNAs, two mRNAs, and 244 lncRNAs was constructed based on the TERKPCGs. Three common small-molecule drugs (enflurane, promethazine, and miconazole) target KCNA1, KCNA2, and KCNS1. Ten small-molecule drugs (glimepiride, diazoxide, levosimendan, and thiamylal et al.) were retrieved for KCNJ11. Compared to normal mice, the expression of KCNA1, KCNA2, KCNJ11, and KCNS1 was downregulated in the brain tissue of the epilepsy mouse model at both the transcriptional and translational levels, which was consistent with the trend of human data from the public database. The results indicated that key potassium channel genes linked to TLE were identified based on bioinformatics analysis to investigate the potential significance of potassium channel genes in the development and treatment of TLE.

Identification of novel biomarkers involved in doxorubicin-induced acute and chronic cardiotoxicity, respectively, by integrated bioinformatics

Background

The mechanisms of doxorubicin (DOX) cardiotoxicity were complex and controversial, with various contradictions between experimental and clinical data. Understanding the differences in the molecular mechanism between DOX-induced acute and chronic cardiotoxicity may be an ideal entry point to solve this dilemma.

Methods

Mice were injected intraperitoneally with DOX [(20 mg/kg, once) or (5 mg/kg/week, three times)] to construct acute and chronic cardiotoxicity models, respectively. Survival record and ultrasound monitored the cardiac function. The corresponding left ventricular (LV) myocardium tissues were analyzed by RNA-seq to identify differentially expressed genes (DEGs). Gene Ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG), and Gene Set Enrichment Analysis (GSEA) found the key biological processes and signaling pathways. DOX cardiotoxicity datasets from the Gene expression omnibus (GEO) database were combined with RNA-seq to identify the common genes. Cytoscape analyzed the hub genes, which were validated by quantitative real-time PCR. ImmuCo and ImmGen databases analyzed the correlations between hub genes and immunity-relative markers in immune cells. Cibersort analyzed the immune infiltration and correlations between the hub genes and the immune cells. Logistic regression, receiver operator characteristic curve, and artificial neural network analysis evaluated the diagnosis ability of hub genes for clinical data in the GEO dataset.

Results

The survival curves and ultrasound monitoring demonstrated that cardiotoxicity models were constructed successfully. In the acute model, 788 DEGs were enriched in the activated metabolism and the suppressed immunity-associated signaling pathways. Three hub genes (Alas1, Atp5g1, and Ptgds) were upregulated and were negatively correlated with a colony of immune-activating cells. However, in the chronic model, 281 DEGs showed that G protein-coupled receptor (GPCR)-related signaling pathways were the critical events. Three hub genes (Hsph1, Abcb1a, and Vegfa) were increased in the chronic model. Furthermore, Hsph1 combined with Vegfa was positively correlated with dilated cardiomyopathy (DCM)-induced heart failure (HF) and had high accuracy in the diagnosis of DCM-induced HF (AUC = 0.898, P = 0.000).

Conclusion

Alas1, Atp5g1, and Ptgds were ideal biomarkers in DOX acute cardiotoxicity. However, Hsph1 and Vegfa were potential biomarkers in the myocardium in the chronic model. Our research, first, provided bioinformatics and clinical evidence for the discovery of the differences in mechanism and potential biomarkers of DOX-induced acute and chronic cardiotoxicity to find a therapeutic strategy precisely.

Analysis of scRNA-seq and bulk RNA-seq demonstrates the effects of EVI2B or CD361 on CD8+ T cells in osteosarcoma

Osteosarcoma (OS) is a common primary malignant tumor of the bone in children and adolescents. The five-year survival rate is estimated to be ~70% based on the currently available treatment modalities. It is well known that tumor-infiltrating immune cells (TIICs) that are the most important components in the tumor microenvironment can exert a killing effect on tumor cells. Therefore, in the present study, 85 RNA-sequencing OS samples were categorized into high- and low-immune score groups with ESTIAMATE. Based on the immune score groups, 474 differentially expressed genes (DEGs) were acquired using the LIMMA package of R language. Subsequently, 86 DEGs were taken through univariate COX regression analysis, of which 14 were screened out by least absolute shrinkage and selection operator regression analysis. Furthermore, multivariate COX regression analysis was performed to obtain 4 DEGs. Finally, ecotropic virus integration site 2B (EVI2B) or CD361 gene was screened out via Kaplan-Meier analysis. In addition, CIBERSORT algorithm was used to evaluate the proportion of 22 kinds of TIICs in OS. Correlation analysis revealed that the high expression level of EVI2B can elevate the infiltrated proportion of CD8⁺ T cells. Moreover, analysis of single cell RNA-sequencing transcriptome datasets and immunohistochemical staining uncovered that EVI2B was mainly expressed on CD8⁺ T cells and that EVI2B could promote the expression of granzyme A and K of CD8⁺ T cells to exhibit a potent killing effect on tumor cells. Therefore, EVI2B was identified as a protective immune-related gene and contributed to good prognosis in OS patients.

Enhancement of effector functions of anti-CD20 monoclonal antibody by increased afucosylation in CHO cell line through cell culture medium optimization

Background

Recombinant therapeutic anti-CD20 monoclonal antibody (mAb) is used for the treatment of non-Hodgkin’s lymphoma, a common B cell lymphoma constituting 80% of all lymphomas. Anti-CD20 mAb contains an Fc-linked biantennary glycan. Although, anti-CD20 monoclonal antibodies are being increasingly used for immunotherapy, their efficacy is limited in a section of patients with drug resistance to immunotherapy. There is a need to improve the efficacy by increasing the effector functions, such as the antibody-dependent cellular cytotoxicity (ADCC) activity of anti-CD20 monoclonal antibodies.

Results

We developed a simple and cost-effective approach to enhance ADCC effector activity in an in-house developed clone of anti-CD20 monoclonal antibody by increasing afucosylation in a new clone of Chinese Hamster Ovary (CHO) cells using 8X uridine, manganese, and galactose (UMG) to modulate the osmolality of the medium. The purified anti-CD20 monoclonal antibody from 8X UMG-containing medium showed a 2-fold increase in afucose content and 203% ADCC activity in comparison to control antibody.

Conclusions

Our study reports enhanced ADCC activity by modulating afucosylation using osmolality by altering simple feed additives in the culture medium.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-022-00421-5.

High Expression of VAV Gene Family Predicts Poor Prognosis of Acute Myeloid Leukemia

Objectives: VAV family genes (VAV1, VAV2, and VAV3) are associated with prognosis in various cancers; however, they have not been evaluated in acute myeloid leukemia (AML). In this study, the prognostic value of VAV expression in AML was evaluated by a single-center study in combination with bioinformatics analyses. Methods: The expression and prognostic value of VAVs in patients with AML were investigated using various databases, including GEPIA, CCLE, EMBL-EBI, UALCAN, cBioPortal, STRING, and DAVID. Blood samples from 35 patients with AML (non-M3 subtype) and 13 benigh individuals were collected at our center. VAV expression levels were detected by real-time quantitative PCR (RT-qPCR) and western blotting. Clinical data were derived from medical records. Results: Based on data from multiple databases, the expression levels of VAV1, VAV2, and VAV3 were significantly higher in AML than in control tissues (P < 0.05). RT-qPCR and western blotting results showed that VAV expression in mRNA and protein levels were higher in patients with AML that in the control group (P < 0.05). Complete remission rates were lower and risks were higher in patients with AML with high VAV1 expression than with low VAV1 expression (P < 0.05). High levels of VAV2, VAV3, and VAV1 were related to a poor overall survival, and this relationship was significant for VAV1 (P < 0.05). High expression levels of genes correlated with VAV1, such as SIPA1, SH2D3C, and HMHA1 were also related to a poor prognosis in AML. Functional and pathways enrichment analyses indicated that the contribution of the VAV family to AML may be mediated by the NF-κB, cAMP, and other pathways. Conclusion: VAVs were highly expressed in AML. In particular, VAV1 has prognostic value and is a promising therapeutic target for AML.

CHN1 is a Novel Prognostic Marker for Diffuse Large B-Cell Lymphoma

Purpose

Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy. Thirty to forty percent of DLBCL patients still experience relapse or develop refractory disease even with standard immunochemotherapy, leading to a poor prognosis. Currently, although several gene-based classification methods can be used to predict the prognosis of DLBCL, some patients are still unable to be classified. This study was performed to identify a novel prognostic biomarker for DLBCL.

Patients and Methods

A total of 1850 B-cell non-Hodgkin lymphoma (B-NHL) patients in 8 independent datasets with microarray gene expression profiles were retrieved from the Gene Expression Omnibus (GEO) database and Lymphoma/Leukemia Molecular Profiling Project (LLMPP). The candidate genes were selected through three filters in a strict pipeline. Survival analysis was performed in two independent datasets of patients with both gene expression data and clinical information. Gene set enrichment analysis (GSEA) and the CIBERSORT algorithm were used to explore the biological functions of the genes.

Results

We identified 6 candidate genes associated with the clinical outcome of DLBCL patients: CHN1, CD3D, CLU, ICOS, KLRB1 and LAT. Unlike the other five genes, CHN1 has not been previously reported to be implicated in lymphoma. We also observed that CHN1 had prognostic significance in important clinical subgroups; in particular, high CHN1 expression was significantly related to good outcomes in DLBCL patients with the germinal center B-cell-like (GCB) subtype, stage III–IV, or an International Prognostic Index (IPI) score > 2. Multivariate Cox regression analysis of the two datasets showed that CHN1 was an independent prognostic factor for DLBCL. Additionally, GSEA and CIBERSORT indicated that CHN1 was correlated with cell adhesion and T cell immune infiltration.

Conclusion

Our data indicate for the first time that high CHN1 expression is associated with favorable outcomes in DLBCL patients, suggesting its potential utility as a prognostic marker in DLBCL.

Conditional expression of HGAL leads to the development of diffuse large B-cell lymphoma in mice

Diffuse large B-cell lymphomas (DLBCLs) are clinically and genetically heterogeneous tumors. Deregulation of diverse biological processes specific to B cells, such as B-cell receptor (BCR) signaling and motility regulation, contribute to lymphomagenesis. Human germinal center associated lymphoma (HGAL) is a B-cell-specific adaptor protein controlling BCR signaling and B lymphocyte motility. In normal B cells, it is expressed in germinal center (GC) B lymphocytes and promptly downregulated upon further differentiation. The majority of DLBCL tumors, primarily GC B-cell types, but also activated types, express HGAL. To investigate the consequences of constitutive expression of HGAL in vivo, we generated mice that conditionally express human HGAL at different stages of hematopoietic development using 3 restricted Cre-mediated approaches to initiate expression of HGAL in hematopoietic stem cells, pro-B cells, or GC B cells. Following immune stimulation, we observed larger GCs in mice in which HGAL expression was initiated in GC B cells. All 3 mouse strains developed DLBCL at a frequency of 12% to 30% starting at age 13 months, leading to shorter survival. Immunohistochemical studies showed that all analyzed tumors were of the GC B-cell type. Exon sequencing revealed mutations reported in human DLBCL. Our data demonstrate that constitutive enforced expression of HGAL leads to DLBCL development.

Computational prediction of CRISPR-impaired non-coding regulatory regions

Genome-wide CRISPR screens are becoming more widespread and allow the simultaneous interrogation of thousands of genomic regions. Although recent progress has been made in the analysis of CRISPR screens, it is still an open problem how to interpret CRISPR mutations in non-coding regions of the genome. Most of the tools concentrate on the interpretation of mutations introduced in gene coding regions. We introduce a computational pipeline that uses epigenomic information about regulatory elements for the interpretation of CRISPR mutations in non-coding regions. We illustrate our analysis protocol on the analysis of a genome-wide CRISPR screen in hTERT-RPE1 cells and reveal novel regulatory elements that mediate chemoresistance against doxorubicin in these cells. We infer links to established and to novel chemoresistance genes. Our analysis protocol is general and can be applied on any cell type and with different CRISPR enzymes.