The role of HIF-1α-VEGF pathway in bronchiolitis obliterans after lung transplantation

Expression and clinical significance of hypoxia-induced long non-coding RNA TCONS_I2_00001955 in breast cancer

BACKGROUND

Long non-coding RNAs (lncRNAs) have been found to play important roles in occurrence, development, and metastasis of various tumors. We aimed to screen long non-coding RNAs (lncRNAs) that promote invasion and metastasis of breast cancer cells under hypoxia, and investigate the relationship between lncRNA expression and clinicopathological features and prognosis in invasive breast cancer.

METHODS

LncRNA microarray was used to screen the differentially expressed lncRNAs in MCF7, MDA-MB-231, and SKBR3 breast cancer cell lines cultured under normoxia and hypoxia, respectively. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to verify the microarray results. CCK8 and Transwell experiments were performed to identify the lncRNA that promote proliferation, migration, and invasion of breast cancer cells. Expression of the lncRNA and HIF-1α in invasive breast cancer was detected by RNAscope and immunohistochemistry, respectively. Correlation between the lncRNA expression and baseline characteristics was analyzed. Prognostic value of the lncRNA was evaluated using univariate and multivariate Cox regression.

RESULTS

Expression of lncRNA TCONS_I2_00001955 in all the three breast cancer cells was increased under hypoxia. Overexpression of TCONS_I2_00001955 significantly enhanced proliferation, migration, and invasion of SKBR3 cells. Positive expression of TCONS_I2_00001955 was associated with recurrence, metastasis, and high expression of HIF-1α (P < 0.05), and it was an independent risk factor for poor disease-free survival of breast cancer.

CONCLUSION

Hypoxia-induced lncRNA TCONS_I2_00001955 was associated with aggressive feature and poor prognosis of breast cancer.

Deep Learning Reveals Key Immunosuppression Genes and Distinct Immunotypes in Periodontitis

Background

Periodontitis is a chronic immuno-inflammatory disease characterized by inflammatory destruction of tooth-supporting tissues. Its pathogenesis involves a dysregulated local host immune response that is ineffective in combating microbial challenges. An integrated investigation of genes involved in mediating immune response suppression in periodontitis, based on multiple studies, can reveal genes pivotal to periodontitis pathogenesis. Here, we aimed to apply a deep learning (DL)-based autoencoder (AE) for predicting immunosuppression genes involved in periodontitis by integrating multiples omics datasets.

Methods

Two periodontitis-related GEO transcriptomic datasets (GSE16134 and GSE10334) and immunosuppression genes identified from DisGeNET and HisgAtlas were included. Immunosuppression genes related to periodontitis in GSE16134 were used as input to build an AE, to identify the top disease-representative immunosuppression gene features. Using K-means clustering and ANOVA, immune subtype labels were assigned to disease samples and a support vector machine (SVM) classifier was constructed. This classifier was applied to a validation set (Immunosuppression genes related to periodontitis in GSE10334) for predicting sample labels, evaluating the accuracy of the AE. In addition, differentially expressed genes (DEGs), signaling pathways, and transcription factors (TFs) involved in immunosuppression and periodontitis were determined with an array of bioinformatics analysis. Shared DEGs common to DEGs differentiating periodontitis from controls and those differentiating the immune subtypes were considered as the key immunosuppression genes in periodontitis.

Results

We produced representative molecular features and identified two immune subtypes in periodontitis using an AE. Two subtypes were also predicted in the validation set with the SVM classifier. Three “master” immunosuppression genes, PECAM1, FCGR3A, and FOS were identified as candidates pivotal to immunosuppressive mechanisms in periodontitis. Six transcription factors, NFKB1, FOS, JUN, HIF1A, STAT5B, and STAT4, were identified as central to the TFs-DEGs interaction network. The two immune subtypes were distinct in terms of their regulating pathways.

Conclusion

This study applied a DL-based AE for the first time to identify immune subtypes of periodontitis and pivotal immunosuppression genes that discriminated periodontitis from the healthy. Key signaling pathways and TF-target DEGs that putatively mediate immune suppression in periodontitis were identified. PECAM1, FCGR3A, and FOS emerged as high-value biomarkers and candidate therapeutic targets for periodontitis.

Untangling Local Pro-Inflammatory, Reparative, and Regulatory Damage-Associated Molecular-Patterns (DAMPs) Pathways to Improve Transplant Outcomes

Detrimental inflammatory responses after solid organ transplantation are initiated when immune cells sense pathogen-associated molecular patterns (PAMPs) and certain damage-associated molecular patterns (DAMPs) released or exposed during transplant-associated processes, such as ischemia/reperfusion injury (IRI), surgical trauma, and recipient conditioning. These inflammatory responses initiate and propagate anti-alloantigen (AlloAg) responses and targeting DAMPs and PAMPs, or the signaling cascades they activate, reduce alloimmunity, and contribute to improved outcomes after allogeneic solid organ transplantation in experimental studies. However, DAMPs have also been implicated in initiating essential anti-inflammatory and reparative functions of specific immune cells, particularly Treg and macrophages. Interestingly, DAMP signaling is also involved in local and systemic homeostasis. Herein, we describe the emerging literature defining how poor outcomes after transplantation may result, not from just an over-abundance of DAMP-driven inflammation, but instead an inadequate presence of a subset of DAMPs or related molecules needed to repair tissue successfully or re-establish tissue homeostasis. Adverse outcomes may also arise when these homeostatic or reparative signals become dysregulated or hijacked by alloreactive immune cells in transplant niches. A complete understanding of the critical pathways controlling tissue repair and homeostasis, and how alloimmune responses or transplant-related processes disrupt these will lead to new immunotherapeutics that can prevent or reverse the tissue pathology leading to lost grafts due to chronic rejection.

Angiogenesis Inhibitors as Anti-Cancer Therapy Following Renal Transplantation: A Case Report and Review of the Literature

Solid organ transplant recipients on long-term immunosuppressive medication are at increased risk of developing malignancy, and treatment of advanced cancers with angiogenesis inhibitors in this context has not been widely studied. We present a case of recurrent high-grade serous ovarian carcinoma treated with paclitaxel and bevacizumab in the context of prior renal transplantation where the patient responded well to treatment with controlled toxicities, discussing the potential for increased rates of adverse events and drug interactions in this select population.

Hyperbaric oxygen therapy to prevent central airway stenosis after lung transplantation

BACKGROUND

Central airway stenosis (CAS) is a severe airway complication after lung transplantation associated with bronchial ischemia and necrosis. We sought to determine whether hyperbaric oxygen therapy (HBOT), an established treatment for tissue ischemia, attenuates post-transplant bronchial injury.

METHODS

We performed a randomized, controlled trial comparing usual care with HBOT (2 atm absolute for 2 hours × 20 sessions) in subjects with extensive airway necrosis 4 weeks after transplantation. Endobronchial biopsies were collected at 4, 7, and 10 weeks after transplantation for a quantitative polymerase chain reaction. Coprimary outcomes were incidence of airway stenting and acute cellular rejection (ACR) at 1 year.

RESULTS

The trial was stopped after enrolling 20 subjects (n = 10 per group) after a pre-planned interim analysis showed no difference between usual care and HBOT groups in stenting (both 40%), ACR (70% and 40%, respectively), or CAS (40% and 60%, respectively). Time to first stent placement (median [interquartile range]) was significantly shorter in the HBOT group (150 [73-150] vs 186 [167-206] days, p < 0.05). HIF gene expression was significantly increased in donor tissues at 4, 7, and 10 weeks after transplantation but was not altered by HBOT. Subjects who developed CAS or required stenting had significantly higher HMOX1 and VEGFA expression at 4 weeks (both p < 0.05). Subjects who developed ACR had significant FLT1, TIE2, and KDR expression at 4 weeks (all p < 0.05).

CONCLUSIONS

Incidence of CAS is high after severe, established airway necrosis after transplantation. HBOT does not reduce CAS severity or stenting. Elevated HMOX1 and VEGFA expressions appear to associate with airway complications.

Identification of key genes and pathways in scleral extracellular matrix remodeling in glaucoma: Potential therapeutic agents discovered using bioinformatics analysis

Background: Glaucoma is a leading cause of irreversible blindness. Remodeling of the scleral extracellular matrix (ECM) plays an important role in the development of glaucoma. The aim of this study was to identify the key genes and pathways for the ECM remodeling of sclera in glaucoma by bioinformatics analysis and to explore potential therapeutic agents for glaucoma management. Methods: Genes associated with glaucoma, sclera and ECM remodeling were detected using the text mining tool pubmed2ensembl, and assigned Gene Ontology (GO) biological process terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using the GeneCodis program. A protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape, module analysis was performed using the Molecular Complex Detection (MCODE) plugin, and GO and KEGG analyses of the gene modules were performed using the Database of Annotation, Visualization and Integrated Discovery (DAVID) platform. The genes that clustered in the significant module were selected as core genes, and functions and pathways of the core genes were visualized using ClueGO and CluePedia. Lastly, the drug-gene interaction database was used to explore drug-gene interactions of the core genes to find drug candidates for glaucoma. Results: We identified 125 genes common to "Glaucoma", "Sclera", and "ECM remodeling" by text mining. Gene functional enrichment analysis yielded 30 enriched GO terms and 20 associated KEGG pathways. A PPI network that included 60 nodes with 249 edges was constructed, and three gene modules were obtained using the MCODE. We selected 13 genes that clustered in module 1 as core candidate genes that were associated mainly with ECM degradation and cell proliferation and division. The HIF-1 signaling pathway, FOXO signaling pathway, PI3K-Akt signaling pathway and TGFB signaling pathway were found to be enriched. We found that 11 of the 13 selected genes could be targeted by 26 existing drugs. Conclusions: The results showed that VEGFA, TGFB1, TGFB2, TGFB3, IGF2, IGF1, EGF, FN1, KNG1, TIMP1, SERPINE1, THBS1, and VWF were potential key genes involved to scleral ECM remodeling. Furthermore, 26 drugs were identified as potential therapeutic agents for glaucoma treatment and management.

Hypoxia, HIF-1α, and COVID-19: from pathogenic factors to potential therapeutic targets

The pandemic of coronavirus disease 2019 (COVID-19) and its pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have become the greatest current threat to global public health. The highly infectious SARS-CoV-2 virus primarily attacks pulmonary tissues and impairs gas exchange leading to acute respiratory distress syndrome (ARDS) and systemic hypoxia. The current pharmacotherapies for COVID-19 largely rely on supportive and anti-thrombi treatment and the repurposing of antimalarial and antiviral drugs such as hydroxychloroquine and remdesivir. For a better mechanistic understanding of COVID-19, our present review focuses on its primary pathophysiologic features: hypoxia and cytokine storm, which are a prelude to multiple organ failure and lethality. We discussed a possible link between the activation of hypoxia inducible factor 1α (HIF-1α) and cell entry of SARS-CoV-2, since HIF-1α is shown to suppress the angiotensin-converting enzyme 2 (ACE2) receptor and transmembrane protease serine 2 (TMPRSS2) and upregulate disintegrin and metalloproteinase domain-containing protein 17 (ADAM17). In addition, the protein targets of HIF-1α are involved with the activation of pro-inflammatory cytokine expression and the subsequent inflammatory process. Furthermore, we hypothesized a potential utility of so-called "hypoxic conditioning" to activate HIF-1α-induced cytoprotective signaling for reduction of illness severity and improvement of vital organ function in patients with COVID-19. Taken together, we would propose further investigations into the hypoxia-related molecular mechanisms, from which novel targeted therapies can be developed for the improved management of COVID-19.

Differences in airway microbiome and metabolome of single lung transplant recipients

Background

Recent studies suggest that alterations in lung microbiome are associated with occurrence of chronic lung diseases and transplant rejection. To investigate the host-microbiome interactions, we characterized the airway microbiome and metabolome of the allograft (transplanted lung) and native lung of single lung transplant recipients.

Methods

BAL was collected from the allograft and native lungs of SLTs and healthy controls. 16S rRNA microbiome analysis was performed on BAL bacterial pellets and supernatant used for metabolome, cytokines and acetylated proline-glycine-proline (Ac-PGP) measurement by liquid chromatography-high-resolution mass spectrometry.

Results

In our cohort, the allograft airway microbiome was distinct with a significantly higher bacterial burden and relative abundance of genera Acinetobacter & Pseudomonas. Likewise, the expression of the pro-inflammatory cytokine VEGF and the neutrophil chemoattractant matrikine Ac-PGP in the allograft was significantly higher. Airway metabolome distinguished the native lung from the allografts and an increased concentration of sphingosine-like metabolites that negatively correlated with abundance of bacteria from phyla Proteobacteria.

Conclusions

Allograft lungs have a distinct microbiome signature, a higher bacterial biomass and an increased Ac-PGP compared to the native lungs in SLTs compared to the native lungs in SLTs. Airway metabolome distinguishes the allografts from native lungs and is associated with distinct microbial communities, suggesting a functional relationship between the local microbiome and metabolome.