Integrated insights into gene expression dynamics and transcription factor roles in diabetic and diabetic-infectious wound healing using rat model

BACKGROUND

Diabetic or diabetic infectious wounds pose a global challenge, marked by delayed healing and high amputation/mortality rates. This study of participating transcriptomes and their regulators unveils critical alterations.

METHODS

Transcriptome data from GEO analyzed DEGs in diabetic foot ulcers vs. controls using RNA-Seq, limma, STRINGdb, Cytoscape, and clusterProfiler for PPI networks and functional enrichment. TRRUST database was used to predict transcriptional factors (TFs). Adverse molecular pathology in different models of wounds (non-diabetic, acute diabetic, diabetic infectious wounds) was validated by RT-PCR, Western blotting, oxidative stress markers, cytokines, and histological analysis.

RESULTS

RNA-Seq dataset 'GSE199939' was analyzed after normalization to identify DEGs (total 47 DEG, 31 upregulated, 16 downregulated) in diabetic wound healing using limma. PPI networks revealed seven hub genes which were further processed for functional enrichment and highlighted oxidative stress, ECM remodeling, AGE-RAGE, and IL-17 signaling in diabetic wound pathology. Additionally, 17 key TFs were identified as hub gene regulators. The healing rate was significantly impaired in diabetic wounds, with delayed contraction, elevated pro-inflammatory cytokines, oxidative stress, reduced anti-inflammatory cytokines, antioxidants, angiogenesis, collagen deposition, and re-epithelialization. Further, RT-PCR and Western blot analysis validated the expression of target genes including the overexpression of HSPA1B, FOS, and down-expression of SOD2, COL1A1, and CCL2, whereas TFs including upregulation of RELA, NFKB1, STAT3, and downregulation of SP1 and JUN in diabetic and diabetic infectious wounds.

CONCLUSION

Molecular analyses reveal disrupted oxidative stress, ECM remodeling, and inflammatory signaling in diabetic and diabetic infectious, emphasizing impaired healing dynamics and identifying therapeutic targets.

Shared Genomic Features Between Lung Adenocarcinoma and Type 2 Diabetes: A Bioinformatics Study

BACKGROUND

Lung adenocarcinoma (LUAD) is a common histopathological variant of non-small cell lung cancer. Individuals with type 2 diabetes (T2DM) face an elevated risk of developing LUAD. We examined the common genomic characteristics between LUAD and T2DM through bioinformatics analysis.

METHODS

We acquired the GSE40791, GSE25724, GSE10072, and GSE71416 datasets. Differentially expressed genes (DEGs) were identified through R software, particularly its version 4.1.3 and analyzed via gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Subsequently, we analyzed the relationship between immune cell infiltration and DEGs. we constructed a protein-protein interaction network using STRING and visualized it with Cytoscape. Moreover, gene modules were identified utilizing the MCODE plugin, and hub genes were selected through the CytoHubba plugin. Additionally, we evaluated the predictive significance of hub genes using receiver operating characteristic curves and identified the final central hub genes. Finally, we forecasted the regulatory networks of miRNA and transcription factors for the central hub genes.

RESULTS

A total of 748 DEGs were identified. Analysis of immune infiltration showed a notable accumulation of effector-memory CD8 T cells, T follicular helper cells, type 1 T helper cells, activated B cells, natural killer cells, macrophages, and neutrophils in both LUAD and T2DM. Moreover, these DEGs were predominantly enriched in immune-related pathways, including the positive regulation of I-κB kinase/NF-κB signaling, positive regulation of immunoglobulin production, cellular response to interleukin-7, and cellular response to interleukin-4. The TGF-β signaling pathway was significantly important among them. Additionally, seven hub genes were identified, including ATR, RFC4, MCM2, NUP155, NUP107, NUP85, and NUP37. Among them, ATR, RFC4, and MCM2 were identified as pivotal hub genes. Additionally, hsa-mir147a, hsa-mir16-5p, and hsa-mir-1-3p were associated with LUAD and T2DM. SP1 (specific protein 1) and KDM5A (lysine-specific demethylase 5A) regulated MCM2, ATR, and RFC4.

CONCLUSIONS

Our study elucidates the common mechanisms of immune response, TGF-β signaling pathway, and natural killer cells in LUAD and T2DM, and identifies ATR, RFC4, and MCM2 as key potential biomarkers and therapeutic targets for the comorbidity of these two conditions.

Negative regulation of cannabinoid receptor 2‑induced tumorigenic effect by sphingosine‑1‑phosphate receptor 5 activation

G protein‑coupled receptors (GPCR), also known as seven‑transmembrane proteins, serve a role in transmitting extracellular information into the cellular environment. Type 2 cannabinoid receptors (CB2) and type 5 sphingosine‑1‑phosphate receptor (S1P5) are GPCRs that are activated by biolipids and involved in tumor progression in various cancer types. At present, effects of crosstalk between CB2 and S1P5 receptors on tumor cell proliferation and migration in gliomas are not fully understood. The present study screened S1Ps for potential interactions with CB2 using bioluminescence resonance energy transfer analysis. S1P5 interacted strongly and specifically with CB2. 293T cells were transfected with CB2 tagged with Venus and S1P5 tagged with mCherry to investigate the cellular localization of both receptors. After 24 h, Confocal microscopy analysis revealed that, in the absence of agonists, both receptors were predominantly localized at the plasma membrane. Notably, both receptors were co‑internalized from the membrane to the cytoplasm upon individual and combined activation. The effects of co‑activation of both receptors on tumor progression were investigated using U‑87 MG, the human glioblastoma cell line. Activation of CB2 induced an increase in cell migration and proliferation, which were downregulated following the co‑activation of S1P5. Furthermore, activation of S1P5 significantly attenuated the upregulation of tumor progression‑related genes, including zinc finger protein 91, activating transcription factor 3, Ki67, basic transcription factor 3, and p21, induced by CB2 activation. This suggests that S1P5 exerts a negative regulatory effect on CB2‑mediated tumor progression. The present findings provide evidence of the crosstalk between CB2 and S1P5.

Epigenetic characterization of adult rhesus monkey spermatogonial stem cells identifies key regulators of stem cell homeostasis

Spermatogonial stem cells (SSCs) play crucial roles in the preservation of male fertility. However, successful ex vivo expansion of authentic human SSCs remains elusive due to the inadequate understanding of SSC homeostasis regulation. Using rhesus monkeys (Macaca mulatta) as a representative model, we characterized SSCs and progenitor subsets through single-cell RNA sequencing using a cell-specific network approach. We also profiled chromatin status and major histone modifications (H3K4me1, H3K4me3, H3K27ac, H3K27me3 and H3K9me3), and subsequently mapped promoters and active enhancers in TSPAN33+ putative SSCs. Comparing the epigenetic changes between fresh TSPAN33+ cells and cultured TSPAN33+ cells (resembling progenitors), we identified the regulatory elements with higher activity in SSCs, and the potential transcription factors and signaling pathways implicated in SSC regulation. Specifically, TGF-β signaling is activated in monkey putative SSCs. We provided evidence supporting its role in promoting self-renewal of monkey SSCs in culture. Overall, this study outlines the epigenetic landscapes of monkey SSCs and provides clues for optimization of the culture condition for primate SSCs expansion.

Prognostic value of anoikis-related genes revealed using multi-omics analysis and machine learning based on lower-grade glioma features and tumor immune microenvironment

Background

The investigation explores the involvement of anoikis-related genes (ARGs) in lower-grade glioma (LGG), seeking to provide fresh insights into the disease's underlying mechanisms and to identify potential targets for therapy.

Methods

We applied unsupervised clustering techniques to categorize LGG patients into distinct molecular subtypes based on ARGs with prognostic significance. Additionally, various machine learning algorithms were employed to pinpoint genes most strongly correlated with patient outcomes, which were then used to develop and assess risk profiles.

Results

Our analysis identified two distinct molecular subtypes of LGG, each with significantly different prognoses. Patients in Cluster 2 had a median survival of 2.036 years, markedly shorter than the 7.994 years observed in Cluster 1 (P < 0.001). We also constructed a six-gene ARG signature that efficiently classified patients into two risk categories, showing median survival durations of 4.084 years for the high-risk group and 10.304 years for the low-risk group (P < 0.001). Significantly, the immune profiles, tumor mutation characteristics, and drug sensitivity varied greatly among these risk groups. The high-risk group was characterized by a "cold" tumor microenvironment (TME), a lower IDH1 mutation rate (61.7 % vs. 91.4 %), a higher TP53 mutation rate (53.7 % vs. 38.9 %), and greater sensitivity to targeted therapies such as QS11 and PF-562271. Furthermore, our nomogram, integrating risk scores with clinicopathological features, demonstrated strong predictive accuracy for clinical outcomes in LGG patients, with an AUC of 0.903 for the first year. The robustness of this prognostic model was further validated through internal cross-validation and across three external cohorts.

Conclusions

The evidence from our research suggests that ARGs could potentially serve as reliable indicators for evaluating immunotherapy effectiveness and forecasting clinical results in patients with LGG.

Unraveling the complexity of the senescence-associated secretory phenotype in adamantinomatous craniopharyngioma using multimodal machine learning analysis

BACKGROUND

Cellular senescence can have positive and negative effects on the body, including aiding in damage repair and facilitating tumor growth. Adamantinomatous craniopharyngioma (ACP), the most common pediatric sellar/suprasellar brain tumor, poses significant treatment challenges. Recent studies suggest that senescent cells in ACP tumors may contribute to tumor growth and invasion by releasing a senesecence-associated secretory phenotype. However, a detailed analysis of these characteristics has yet to be completed.

METHODS

We analyzed primary tissue samples from ACP patients using single-cell, single-nuclei, and spatial RNA sequencing. We performed various analyses, including gene expression clustering, inferred senescence cells from gene expression, and conducted cytokine signaling inference. We utilized LASSO to select essential gene expression pathways associated with senescence. Finally, we validated our findings through immunostaining.

RESULTS

We observed significant diversity in gene expression and tissue structure. Key factors such as NFKB, RELA, and SP1 are essential in regulating gene expression, while senescence markers are present throughout the tissue. SPP1 is the most significant cytokine signaling network among ACP cells, while the Wnt signaling pathway predominantly occurs between epithelial and glial cells. Our research has identified links between senescence-associated features and pathways, such as PI3K/Akt/mTOR, MYC, FZD, and Hedgehog, with increased P53 expression associated with senescence in these cells.

CONCLUSIONS

A complex interplay between cellular senescence, cytokine signaling, and gene expression pathways underlies ACP development. Further research is crucial to understand how these elements interact to create novel therapeutic approaches for patients with ACP.

Modulation of Krüppel-like factors (KLFs) interaction with their binding partners in cancers through acetylation and phosphorylation

Post-translational modifications (PTMs) of transcription factors regulate transcriptional activity and play a key role in essentially all biological processes and generate indispensable insight towards biological function including activity state, subcellular localization, protein solubility, protein folding, substrate trafficking, and protein-protein interactions. Amino acids modified chemically via PTMs, function as molecular switches and affect the protein function and characterization and increase the proteome complexity. Krüppel-like transcription factors (KLFs) control essential cellular processes including proliferation, differentiation, migration, programmed cell death and various cancer-relevant processes. We investigated the interactions of KLF group-2 members with their binding partners to assess the role of acetylation and phosphorylation in KLFs on their binding affinity. It was observed that acetylation and phosphorylation at different positions in KLFs have a variable effect on binding with specific partners. KLF2-EP300, KLF4-SP1, KLF6-ATF3, KLF6-JUN, and KLF7-JUN show stabilization upon acetylation or phosphorylation at variable positions. On the other hand, KLF4-CBP, KLF4-EP300, KLF5-CBP, KLF5-WWP1, KLF6-SP1, and KLF7-ATF3 show stabilization or destabilization due to acetylation or phosphorylation at variable positions in KLFs. This provides a molecular explanation of the experimentally observed dual role of KLF group-2 members as a suppressor or activator of cancers in a PTM-dependent manner.

Significance of Oxidative Stress in the Diagnosis and Subtype Classification of Intervertebral Disc Degeneration

Intervertebral disc degeneration (IVDD) is a common illness of aging, and its pathophysiological process is mainly manifested by cell aging and apoptosis, an imbalance in the production and catabolism of extracellular matrix, and an inflammatory response. Oxidative stress (OS) is an imbalance that decreases the body's intrinsic antioxidant defense system and/or raises the formation of reactive oxygen species and performs multiple biological functions in the body. However, our current knowledge of the effect of OS on the progression and treatment of IVDD is still extremely limited. In this study, we obtained 35 DEGs by differential expression analysis of 437 OS-related genes (OSRGs) between IVDD patients and healthy individuals from GSE124272 and GSE150408. Then, we identified six hub OSRGs (ATP7A, MELK, NCF1, NOX1, RHOB, and SP1) from 35 DEGs, and the high accuracy of these hub genes was confirmed by constructing ROC curves. In addition, to forecast the risk of IVDD patients, we developed a nomogram. We obtained two OSRG clusters (clusters A and B) by consensus clustering based on the six hub genes. Then, 3147 DEGs were obtained by differential expression analysis in the two clusters, and all samples were further divided into two gene clusters (A and B). We investigated differences in immune cell infiltration levels between different clusters and found that most immune cells had higher infiltration levels in OSRG cluster B or gene cluster B. In conclusion, OS is important in the formation and progression of IVDD, and we believe that our work will help guide future research on OS in IVDD.

Coding RNA expression profile and transcription factor analysis of H.pylori-associated chronic atrophic gastritis

PURPOSE

Atrophic gastritis, one of the processes leading to gastric cancer (GC), is closely related to Helicobacter pylori (HP) infection. This study aimed to understand how HP causes chronic inflammation that leads to ulcers and stomach problems.

METHODS

Twenty-eight CAG patients were included in the study (9 HP-infected and 19 HP-uninfected). Endoscopy, histopathology, and high-throughput mRNA sequencing were performed. Differentially expressed genes (DEGs) were validated via qRT-PCR.

RESULTS

Principal component analysis (PCA) results showed that more than 88.9 ​% of the samples were classified into the HP (+) group. A total of 157 DEGs were identified, of which 38 were up-regulated and 119 were down-regulated. The DEGs were mainly enriched in the biological process (BP) terms associated with immune system process, adaptive immune response, G protein-coupled receptor signaling pathway, as well as point to numerous key pathways, including fat digestion and absorption, retinol metabolism, steroid hormone biosynthesis, ascorbate and aldarate metabolism, and chemical carcinogenesis. APOA1, APOA4, FOXP3, NR1H4, ABCG5, ACTA1, CCL19, CCR7, CYP3A4, and PDCD had the highest degrees in protein-protein interaction network as the hub genes; they were also included into the transcription factor (TF)-target network except for PDCD. APOA1 and CYP3A4 were extremely significantly up-regulated in HP (+) CAG patients compared with the HP (-) CAG patients, while FOXP3, CCR7 and CCL19 were significantly down-regulated.

CONCLUSION

The expression of APOA1, CYP3A4, FOXP3, CCR7, and CCL19 are the potential indicators for CAG to GC development, being the biomarkers to predict progression of CAG and poor prognosis of GC.

Sp1 Controls the Basal Level of Interleukin-34 Transcription

Interleukin-34 (IL-34) is a cytokine that plays important roles at steady state and in diseases. The induced or inhibited expression of IL-34 by stimuli has been deeply investigated. However, the regulation of IL-34 basal expression is largely unknown. The aim of this study is to investigate whether IL-34 expression is regulated by a general transcription factor Specificity Protein 1 (Sp1) at transcription level. By using bioinformatic software, four putative Sp1-binding sites overlapping GC boxes were found in the core promoter region of IL-34. Alignment of the core promoter sequences of mammalian IL-34 showed GC box-C (-62/-57) and D (-11/-6) were conserved in some mammals. Luciferase assay results showed that only deletion of GC box-C (-62/-57) significantly reduced luciferase activities of IL-34 core promoter in SH-SY5Y cells. By using electrophoretic mobility shift assay (EMSA), it was found that Sp1 specifically interacted with GC box-C sequence CCCGCC (-62/-57) in the core promoter of IL-34. By using chromatin immunoprecipitation (ChIP), it was discovered that Sp1 bound to the core promoter of IL-34 in living cells. In addition, silencing of Sp1 expression by its specific siRNA reduced IL-34 mRNA and protein levels significantly in SH-SY5Y cells. Likewise, IL-34 expression was inhibited in a dose-dependent manner by a Sp1 inhibitor Plicamycin. Furthermore, silencing of Sp1 also downregulated mRNA and protein expression of IL-34 in GES-1 and 293T cell lines, suggesting that IL-34 transcription regulated by Sp1 was not cell-type specific. Taken together, these results indicate that Sp1 controls the basal level of IL-34 transcription.