Biology Direct最新文献

Background: Ovarian cancer is a complicated and heterogeneous disease. In this study, we investigated the functional significance of the gene TIMM8B, which is differentially expressed in ovarian cancer to better understand the molecular processes involved in the development of this disease.

Methods: RNA sequencing was performed on ovarian cancer tissues and adjacent noncancerous tissues. The mRNA expression profiles obtained from the sequencing data (transcripts), TCGA-OV, and GSE14407 were subsequently used to identify common DEGs. GO, KEGG pathway, and PPI network analyses of these common DEGs were conducted. The expression of TIMM8B was examined in ovarian cancer tissues and cell lines. The effects of TIMM8B on cellular behaviors, such as proliferation, apoptosis, migration, invasion, and energy metabolism, were assessed by conducting cell-based assays. Additionally, the regulation of these processes by TIMM8B through the mtROS/ASK1/JNK signaling pathway was investigated.

Results: A total of 233 common DEGs were identified in ovarian cancer. The results of the GO analysis revealed enrichment in extracellular matrix organization, collagen-containing extracellular matrix, and transmembrane transporter activity, among others. The results of the KEGG pathway analysis revealed the involvement of DEGs in pathways such as oxidative phosphorylation and glycolysis/gluconeogenesis. TIMM8B was upregulated in ovarian cancer tissues and cell lines. TIMM8B enhanced oxidative phosphorylation, glycolysis, proliferation, migration, and invasion and inhibited apoptosis in ovarian cancer cells. TIMM8B was found to exert its effects through the suppression of mtROS/ASK1/JNK signaling.

Conclusion: TIMM8B may regulate the mtROS/ASK1/JNK pathways, leading to an increase in oxidative phosphorylation and glycolysis. Targeting TIMM8B and its associated signaling pathway may help in the development of new treatment approaches for ovarian cancer.

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by excessive macrophage infiltration and extracellular matrix deposition. The progress of IPF is promoted by M2 macrophages which produce pro-fibrotic factors and induce fibroblast differentiation. SESN3 was upregulated in lung tissues of IPF patients and mice with bleomycin-induced pulmonary fibrosis. However, the role of SESN3 in IPF and its related mechanisms remain largely unknown.

Methods: Here, we used IL-4/13 to induce macrophage M2 polarization in RAW264.7 cells and constructed a mouse model of pulmonary fibrosis by intratracheal injection of bleomycin. Adenoviruses targeting SESN3 were constructed to infect RAW264.7 cells and BLM-induced mice to assess the function of SESN3 in macrophage M2 polarization in the progress of IPF and mRNA-seq and Co-IP-MS analysis were performed to find the downstream factors.

Results: For in vitro experiments, SESN3 knockdown promoted the M2 polarization level, the release of pro-fibrosis factors and the activation of fibroblast, overexpression of SESN3 had an opposite trend. For in vivo experiments, the increased degree of pulmonary fibrosis in BLM mice was relieved after overexpression of SESN3. Meanwhile, overexpression of SESN3 repressed the increased macrophage M2 polarization level induced by BLM. Mechanically, FOSL2 was screened out through mRNA-seq and Co-IP-MS analysis due to its binding affinity with SESN3 and the observed downregulation of its downstream pro-fibrotic factor expression. The expression of FOSL2 in the nucleus was down-regulated after SESN3 overexpression. Under IL-4/13 treatment, the increased levels of macrophage M2 polarization and pro-fibrotic factors induced by SESN3 knockdown was recovered after knocking down FOSL2 in RAW264.7 cells.

Conclusion: In summary, our study suggested that SESN3 regulated the IPF process through inhibiting macrophage M2 polarization by targeting the activity of FOSL2.

Background: Pathological complete response (pCR) to neoadjuvant systemic therapy (NAST) is an established prognostic marker in breast cancer (BC). Multimodal deep learning (DL), integrating diverse data sources (radiology, pathology, omics, clinical), holds promise for improving pCR prediction accuracy. This systematic review synthesizes evidence on multimodal DL for pCR prediction and compares its performance against unimodal DL.

Methods: Following PRISMA, we searched PubMed, Embase, and Web of Science (January 2015-April 2025) for studies applying DL to predict pCR in BC patients receiving NAST, using data from radiology, digital pathology (DP), multi-omics, and/or clinical records, and reporting AUC. Data on study design, DL architectures, and performance (AUC) were extracted. A narrative synthesis was conducted due to heterogeneity.

Results: Fifty-one studies, mostly retrospective (90.2%, median cohort 281), were included. Magnetic resonance imaging and DP were common primary modalities. Multimodal approaches were used in 52.9% of studies, often combining imaging with clinical data. Convolutional neural networks were the dominant architecture (88.2%). Longitudinal imaging improved prediction over baseline-only (median AUC 0.91 vs. 0.82). Overall, the median AUC across studies was 0.88, with 35.3% achieving AUC ≥ 0.90. Multimodal models showed a modest but consistent improvement over unimodal approaches (median AUC 0.88 vs. 0.83). Omics and clinical text were rarely primary DL inputs.

Conclusion: DL models demonstrate promising accuracy for pCR prediction, especially when integrating multiple modalities and longitudinal imaging. However, significant methodological heterogeneity, reliance on retrospective data, and limited external validation hinder clinical translation. Future research should prioritize prospective validation, integration underutilized data (multi-omics, clinical), and explainable AI to advance DL predictors to the clinical setting.

In sepsis, immunosuppression is commonly observed as lipopolysaccharide (LPS) tolerance in macrophages. Leukocyte immunoglobulin-like receptor B2 (LILRB2) is an inhibitory receptor on immune cells that may play a crucial role in the immunosuppressive phenotype of LPS-tolerant macrophages, although its exact function in sepsis remains unclear. In this study, macrophages were exposed to single or sequential LPS doses to induce LPS stimulation or tolerance. Cell viability was assessed using CCK-8 assay, apoptosis, and macrophage polarization were detected by flow cytometry, and pro-inflammatory cytokine levels were measured by RT-qPCR and ELISA. Molecular interactions were explored using Co-IP, ChIP, and dual-luciferase assays, while mRNA and protein expression were assessed by RT-qPCR and Western blotting. The results showed that LILRB2 was upregulated in macrophages following LPS stimulation, with a more significant increase in the LPS-tolerant group. Knocking down LILRB2 reversed the immunosuppressive phenotype of LPS-tolerant macrophages and restored the inhibition of MyD88/NF-κB signaling and p65 nuclear translocation caused by LPS tolerance. Mechanistically, LILRB2 interacted with Toll-like receptor 8 (TLR8) to inhibit the MyD88/NF-κB signaling pathway in LPS-tolerant macrophages. Furthermore, the upregulation of the Spi-1 proto-oncogene (SPI1) enhanced the immunosuppressive phenotype by transcriptionally activating LILRB2. In conclusion, SPI1 upregulation promoted the immunosuppressive phenotype of LPS-tolerant macrophages by activating LILRB2 transcription, which inhibited TLR8-mediated MyD88/NF-κB signaling. This study clarifies the role of LILRB2 and its underlying mechanisms in LPS-tolerant macrophages.

Background: Anti-Müllerian hormone (AMH) levels are frequently elevated in women with polycystic ovary syndrome (PCOS) and serve as a valuable diagnostic biomarker. However, the molecular mechanisms driving AMH overexpression in PCOS remain poorly understood.

Methods: A PCOS mouse model was generated by subcutaneously administering dehydroepiandrosterone (DHEA). Gene and protein expression levels were measured using RT-qPCR and Western blot analysis, respectively. Isobaric tags for relative and absolute quantitation (iTRAQ) proteomic analysis was performed to identify differentially expressed proteins. Protein interactions were assessed via immunoprecipitation and co-immunoprecipitation experiments. Additionally, both in vitro and in vivo experiments were conducted to evaluate phosphorylation and ubiquitination processes.

Results: Conducting proteomic profiling of polycystic ovaries, we identified 417 differentially expressed proteins, including upregulated CRTC1 (CREB-regulated transcription coactivator 1), AR (androgen receptor), HIPK2 protein kinase, and AMH. We demonstrated that CRTC1 interacted with the histone acetyltransferase CBP (CREB binding protein) and AR to form a transcriptional complex that activates AMH expression. Importantly, the stability of CRTC1 was regulated by HIPK2-mediated phosphorylation. Specifically, HIPK2 phosphorylated CRTC1 at Ser36, which prevented its ubiquitination and subsequent proteasomal degradation. Inhibition or knockdown of HIPK2 disrupted this protective mechanism, leading to RNF121 (Ring finger protein 121) E3 ubiquitin ligase-mediated degradation of CRTC1. This resulted in the dissociation of the CRTC1-CBP-AR complex and a significant reduction in AMH expression. Furthermore, in DHEA-induced PCOS mice, administration of HIPK2 inhibitors effectively suppressed AMH expression and attenuated PCOS progression.

Conclusion: These findings provide novel insights into the molecular mechanisms underlying AMH upregulation in PCOS. They highlight the CRTC1-CBP-AR transcriptional complex and HIPK2-mediated phosphorylation as critical regulatory nodes in PCOS pathogenesis.

Clinical trial number: Not applicable.

Background: Autophagy is the primary catabolic process responsible for degrading intracellular components and potentially harmful cytosolic entities by delivering them to lysosomes. Notably, this mechanism is crucial for controlling intracellular pathogens, with significant implications for both innate and adaptive immunity. In the context of HIV-1 infection, emerging evidence suggests that autophagy contributes to immune responses against the virus. Various compounds can modulate autophagy, among which vitamin D₃ is particularly effective due to its ability to prevent inflammation and slow HIV-1 disease progression. Indeed, vitamin D₃ contributes to regulating both innate and adaptive immunity, thereby modulating antiviral and antibacterial inflammatory responses. Importantly, vitamin D₃ deficiency is highly prevalent among people with HIV (PWH) and has been associated with an increased risk of severe disease progression.

Results: In this study, we investigated the relationship between serum vitamin D₃ levels and the expression of autophagy markers in peripheral blood mononuclear cells from different categories of PWH: PWH under antiretroviral therapy (ART) with either normal vitamin D₃ levels or hypovitaminosis, and treatment-naïve PWH with either normal vitamin D₃ levels or hypovitaminosis. Our results show that low vitamin D₃ blood levels is associated with lower expression of the main factors involved in the autophagy mechanism, particularly in treatment-naïve PWH.

Conclusions: Our findings suggest that normal blood level of vitamin D₃ may play a crucial role in promoting autophagy in PWH. The observed differences in autophagy-related protein expression between ART-treated and untreated individuals underscore the intricate relationship between vitamin D₃ levels, ART exposure, and autophagic regulation. This is a preliminary exploration of the effects of vitamin D₃ on autophagy in PWH. Further studies are needed to deepen and explore the interplay between vitamin D₃ and autophagy in greater depth. A better understanding of these mechanisms could help to develop novel therapeutic strategies aimed at mitigating immune depletion and chronic inflammation, ultimately improving clinical outcomes for individuals living with HIV.

Background: Breast cancer is subdivided into four distinct subtypes based on the status of hormone receptors (HR) and human epidermal growth factor receptor 2 (HER2) as HER2^-/HR⁺, HER2⁺/HR⁺, HER2⁺/HR^- and HER2^-/HR^-. Among this, ERα positive breast cancer, even though they respond to endocrine treatment, half of the patients acquire resistance and progress with metastasis despite ERα status. Spatio-temporal changes in ERα and their loss under treatment pressure have been reported in a subset of patients, which is a serious problem.

Results: We have demonstrated that in vitro-generated resistance is correlated with the down regulation of ERα. To study the ERα status transition in live cells, triple-negative breast cancer cells were engineered to express EGFP-ERα, which further supported the existence of complex intracellular signaling that regulates ERα plasticity even in unperturbed conditions. Single-cell clones generate heterogeneity and loss of expression depending on proliferative cues. However, the initial response of cells to 4 μM of 4-hydroxytamoxifen and 1 μM of endoxifen involves up-regulation of ERα, likely due to its early effect on the proteasome or autophagy pathway. Supporting this, inhibition of autophagy and the proteasome further enhanced the expression of ERα. Systematic analysis of RNA sequencing of ERα stable cells further confirmed that ERα regulates diverse intracellular signaling networks such as ubiquitin, proteasome pathways, cell proliferation and Unfolded Protein Responses (UPR), implicating its direct role in post-translational protein modifications. Cell cycle indicator probe expressing receptor-positive breast cancer cells confirmed the ERα expression heterogeneity both in 2D and 3D culture in a cell cycle phase-independent manner.

Conclusions: Overall, the study confirms the cell's intrinsic post-transcriptional mechanisms of ERα plasticity that could play a role in receptor heterogeneity and tumor progression under endocrine treatment, which warrants further investigation.

Background: As members of the nuclear receptor (NR) family of transcription factors, peroxisome proliferator-activated receptors (PPARs) regulate essential cellular processes, including lipid metabolism, glucose uptake, cell proliferation, and programmed cell death through ligand-mediated activation. Within the PPAR subfamilies, PPAR-γ (PPARG) is crucial to the development of fat cells, sensitivity to insulin, apoptosis, and metastasis. Furthermore, it demonstrates properties that counteract fibrosis and inflammation, thus establishing itself as a notable target for therapeutic interventions against conditions such as type 2 diabetes and cancer. PPARG is reported to be a promising target for patients diagnosed with colorectal cancer (CRC). Globally, colorectal cancer ranks as the third most prevalent malignancy and is responsible for approximately 10% of all cancer mortalities, and PPARG is significantly expressed in 70% of the sporadic CRC. In individuals with CRC, the precise function of PPARG remains not entirely comprehended and elucidation of the PPARG transcriptional regulation in CRC seems promising.

Results:  This study integrates RNA-seq and ChIP-seq reads to analyze the effects of Rosiglitazone on HT-29 colon cancer cells. Peak calling analysis from ChIP-seq data identified 14,000 to 34,000 binding sites for PPARG across different experimental conditions. RNA-seq analysis highlighted significant differential gene expression in Rosiglitazone-treated cells, with 4362 and 6780 genes significantly regulated at 24 and 48 h, respectively. The correlation of these datasets with PPRE-associated kinases resulted in the identification of 18 differentially expressed genes (DEGs), followed by subsequent analysis of gene ontology, pathway enrichment, and protein-protein interactions, culminating in the elucidation of seven hub genes (PTK2, HGS, CDK8, PRPF6, PRKDC, PRKCZ, MET). Further these hub genes correlated with CRC progression and patient survival. Validation using independent GEO datasets (GSE113513 and GSE210693) and gene effect scores derived from CRISPR knockout screens further supported the functional impact of these hub genes. Disease ontology and mutational analyses implicated the hub genes in various cancers, including CRC. Moreover, miRNA analysis identified 37 experimentally validated miRNAs potentially modulating hub gene expression.

Conclusions: These findings advance our understanding of PPARG's regulatory network and underscore its potential as a therapeutic target, establishing a robust framework for future research in PPARG-related pathways.

Beta-2 microglobulin (β₂m) is a small protein that forms the invariant subunit of the Major Histocompatibility Complex I. Monomeric β₂m is stable under physiological conditions, however high local concentrations can induce misfolding, leading to amyloid deposition. This accumulation has been recently observed in the lysosomes of tumour-associated macrophages from patients affected by multiple myeloma. Such aggregation has been linked to inflammation and tumour progression. Stabilizing the native state of β₂m could be the first step towards preventing this cancer-promoting process. To achieve this goal, the effect of affibody molecules, small and stress-resistant affinity proteins, was tested. Three affibodies molecules were selected against β₂m. Affibody-β₂m complex formation was initially assessed by size exclusion chromatography and subsequently confirmed by microscale thermophoresis and isothermal titration calorimetry. In parallel, in presence of one of the affibody (Z_{β2m_01}) a significant reduction in β₂m aggregation was observed. The inhibition of amyloid formation was also confirmed by transmission electron microscopy. Taken together, these results indicate that Z_{β2m_01} has the potential to act as β₂m aggregation inhibitor under lysosomal-like pH values.

Background: Single-cell RNA sequencing (scRNA-Seq) technology reveals biological processes and molecular-level genomic information among individual cells. Numerous computational methods, including methods based on graph neural networks (GNNs), have been developed to enhance scRNA-Seq data analysis. However, existing GNNs-based methods usually construct fixed graphs by applying the k-nearest neighbors algorithm, which may result in information loss.

Methods: To address this problem, we propose scE2EGAE, which learns cell graphs during the training processes. Firstly, the scRNA-Seq data is fed into a deep count autoencoder (DCA). Secondly, the hidden representations of DCA are extracted and then used to generate cell-to-cell graph edges through a straight-through estimator (STE) based on top-k sampling and Gumbel-Softmax. Finally, the generated cell-to-cell graph and scRNA-Seq data are fed into the GNNs-based downstream tasks. In this paper, we design a graph autoencoder which performs denoising on scRNA-Seq data as the downstream task.

Results: We evaluate scE2EGAE on eight public scRNA-Seq datasets and compare its performance with seven existing scRNA-Seq data denoising methods. In this paper, extensive experiments are conducted, encompassing: 1) the evaluation of denoising performance, with metrics including mean absolute error, Pearson correlation coefficient, and cosine similarity; 2) the assessment of clustering performance of the denoised results, utilizing adjusted rand index, normalized mutual information and silhouette score; and 3) the evaluation of the cell trajectory inference performance of the denoised results, measured by the pseudo-temporal ordering score. The results show that, on the scRNA-Seq data denoising task, scE2EGAE outperforms most of the methods, proving that it can learn cell-to-cell graphs containing real information of cell-to-cell relationships.

Conclusions: In this paper, we validate the proposed scE2EGAE method through its application to the denoising task of scRNA-Seq data. This method demonstrates its capability to learn inter-cellular relationships and construct cell-to-cell graphs, thereby enhancing the downstream analysis of scRNA-Seq data. Our approach can serve as an inspiration for future research on scRNA-Seq analysis methods based on GNNs, holding broad application prospects.