Ockham's razor for the MET-driven invasive growth linking idiopathic pulmonary fibrosis and cancer

Prognostic impact of interstitial lung abnormalities in lung cancer: a systematic review and meta-analysis

Background

Newly identified as a radiological concept, interstitial lung abnormalities (ILA) is emerging as a prognostic factor for lung cancer. Yet, debates persist regarding the prognostic significance of ILA in lung cancer. Our inaugural meta-analysis aimed to investigate the correlation between ILA and lung cancer outcomes, offering additional insights for clinicians in predicting patient prognosis.

Methods

Articles meeting the criteria were found through PubMed, the Cochrane Library, EMBASE, and Web of Science by February 29, 2024. The outcomes evaluated were the survival rates such as overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and cancer-specific survival (CSS).

Results

A total of 12 articles with 4416 patients were included in this meta-analysis. The pooled results showed that lung cancer patients with interstitial lung abnormalities had an inferior OS (n=11; HR=2.22; 95% CI=1.68-2.95; P<0.001; I2 = 72.0%; Ph<0.001), PFS (n=3; HR=1.59; 95% CI=1.08-2.32; P=0.017; I2 = 0%; Ph=0.772), and CSS (n=2; HR=4.00; 95% CI=1.94-8.25; P<0.001; I2 = 0%; Ph=0.594) than those without, however, the ILA was not significantly associated with the DFS (n=2; HR=2.07; 95% CI=0.94-7.02; P=0.066; I2 = 90.4%; Ph=0.001). Moreover, lung cancer patients with ILA were significantly correlated with male (OR=2.43; 95% CI=1.48-3.98; P<0.001), smoking history (OR=2.11; 95% CI=1.37-3.25; P<0.001), advanced age (OR=2.50; 95% CI=1.56-4.03; P<0.001), squamous carcinoma (OR=0.42; 95% CI=0.24-0.71; P=0.01), and EGFR mutation (OR=0.50; 95% CI=0.32-0.78; P=0.002). The correlation between ILA and race, stage, ALK, however, was not significant.

Conclusion

ILA was a availability factors of prognosis in patients with lung cancers. These findings highlight the importance of early pulmonary fibrosis, namely ILA for prognosis in patients with lung cancer, and provide a partial rationale for future clinical work.

Multi-omics integration reveals a nonlinear signature that precedes progression of lung fibrosis

Objectives

Idiopathic pulmonary fibrosis (IPF) is a devastating progressive interstitial lung disease with poor outcomes. While decades of research have shed light on pathophysiological mechanisms associated with the disease, our understanding of the early molecular events driving IPF and its progression is limited. With this study, we aimed to model the leading edge of fibrosis using a data-driven approach.

Methods

Multiple omics modalities (transcriptomics, metabolomics and lipidomics) of healthy and IPF lung explants representing different stages of fibrosis were combined using an unbiased approach. Multi-Omics Factor Analysis of datasets revealed latent factors specifically linked with established fibrotic disease (Factor1) and disease progression (Factor2).

Results

Features characterising Factor1 comprised well-established hallmarks of fibrotic disease such as defects in surfactant, epithelial-mesenchymal transition, extracellular matrix deposition, mitochondrial dysfunction and purine metabolism. Comparatively, Factor2 identified a signature revealing a nonlinear trajectory towards disease progression. Molecular features characterising Factor2 included genes related to transcriptional regulation of cell differentiation, ciliogenesis and a subset of lipids from the endocannabinoid class. Machine learning models, trained upon the top transcriptomics features of each factor, accurately predicted disease status and progression when tested on two independent datasets.

Conclusion

This multi-omics integrative approach has revealed a unique signature which may represent the inflection point in disease progression, representing a promising avenue for the identification of therapeutic targets aimed at addressing the progressive nature of the disease.

Up-regulation by overexpression of c-MET in fibroblastic foci of usual interstitial pneumonia

Background

Usual interstitial pneumonia (UIP) is the radiologic and histologic hallmark of idiopathic pulmonary fibrosis (IPF) and the commonest histologic pattern of other progressive fibrosing interstitial lung diseases (e.g., fibrotic hypersensitivity pneumonia). Analogous to lung cancer, activation of epithelial-to-mesenchymal transition (EMT) is one of the main molecular pathways recently identified by transcriptomic studies in IPF. Fibroblastic foci (FF) are considered the active/trigger component of UIP pattern. The proto-oncogene C-MET is a key gene among molecules promoting EMT against which several inhibitors are currently available or promising in ongoing studies on lung cancer.

Methods

Twenty surgical cases of diffuse fibrosing interstitial lung diseases (fILD) with UIP pattern and FF-rich (17 IPF and 3 patients with fibrotic hypersensitivity pneumonia, fHP) were retrospectively selected. FF were manually microdissected and analysed for c-MET gene alterations (FISH amplification and gene hot-spot mutations Sanger sequencing) and tested with a c-MET companion diagnostic antibody (clone SP44 metmab) by immunohistochemistry.

Results

FF are characterized by upregulation of c-MET as shown by overexpression of the protein in 80% of cases, while no gene amplification by FISH or mutations were detected. C-MET upregulation of FF was observed either in IPF and fHP, with a tropism for the epithelial cell component only.

Conclusion

Upregulation of c-MET in FF of ILD with UIP pattern further confirms the key role of the proto-oncogene c-MET in its pathogenesis, possibly representing an interesting and easily-detectable molecular target for selective therapy using specific inhibitors in future clinical trials, similar to lung cancer. It is reasonable to speculate that molecular alterations in FF can also be detected in FF by transbronchial cryobiopsy.

Idiopathic pulmonary fibrosis and lung cancer: future directions and challenges

Idiopathic pulmonary fibrosis (IPF) is a progressive disease of pulmonary scarring. New treatments slow disease progression and allow pulmonary fibrosis patients to live longer. Persistent pulmonary fibrosis increases a patient's risk of developing lung cancer. Lung cancer in patients with IPF differs from cancers that develop in the non-fibrotic lung. Peripherally located adenocarcinoma is the most frequent cell type in smokers who develop lung cancer, while squamous cell carcinoma is the most frequent in pulmonary fibrosis. Increased fibroblast foci in IPF are associated with more aggressive cancer behaviour and shorter doubling times. Treatment of lung cancer in fibrosis is challenging because of the risk of inducing an exacerbation of fibrosis. In order to improve patient outcomes, modifications of current lung cancer screening guidelines in patients with pulmonary fibrosis will be necessary to avoid delays in treatment. 2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET) computed tomography (CT) imaging can help identify cancer earlier and more reliably than CT alone. Increased use of wedge resections, proton therapy and immunotherapy may increase survival by decreasing the risk of exacerbation, but further research will be necessary.

Identification and validation of autophagy-related gene expression for predicting prognosis in patients with idiopathic pulmonary fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and fatal fibrotic pulmonary disease with unknow etiology. Owing to lack of reliable prognostic biomarkers and effective treatment measures, patients with IPF usually exhibit poor prognosis. The aim of this study is to establish a risk score prognostic model for predicting the prognosis of patients with IPF based on autophagy-related genes.

Methods

The GSE70866 dataset was obtained from the gene expression omnibus (GEO) database. The autophagy-related genes were collected from the Molecular Signatures Database (MSigDB). Gene enrichment analysis for differentially expressed genes (DEGs) was performed to explore the function of DEGs. Univariate, least absolute shrinkage and selection operator (LASSO), as well as multivariate Cox regression analyses were conducted to identify a multi-gene prognostic model. Receiver operating characteristic (ROC) curve was applied to assess the prediction accuracy of the model. The expression of genes screened from the prognostic model was validated in clinical samples and human lung fibroblasts by qPCR and western blot assays.

Results

Among the 514 autophagy-related genes, a total of 165 genes were identified as DEGs. These DEGs were enriched in autophagy-related processes and pathways. Based on the univariate, LASSO, and multivariate Cox regression analyses, two genes (MET and SH3BP4) were included for establishing the risk score prognostic model. According to the median value of the risk score, patients with IPF were stratified into high-risk and low-risk groups. Patients in high-risk group had shorter overall survival (OS) than low-risk group in both training and test cohorts. Multivariate regression analysis indicated that prognostic model can act as an independent prognostic indicator for IPF. ROC curve analysis confirmed the reliable predictive value of prognostic model. In the validation experiments, upregulated MET expression and downregulated SH3BP4 expression were observed in IPF lung tissues and TGF-β1-activated human lung fibroblasts, which is consistent with results from microarray data analysis.

Conclusion

These findings indicated that the risk score prognostic model based on two autophagy-related genes can effectively predict the prognosis of patients with IPF.

A novel gene signature based on the hub genes of COVID-19 predicts the prognosis of idiopathic pulmonary fibrosis

Background: Increasing evidence has demonstrated that there was a strong correlation between COVID-19 and idiopathic pulmonary fibrosis (IPF). However, the studies are limited, and the real biological mechanisms behind the IPF progression were still uncleared.

Methods: GSE70866 and GSE 157103 datasets were downloaded. The weight gene co-expression network analysis (WGCNA) algorithms were conducted to identify the most correlated gene module with COVID-19. Then the genes were extracted to construct a risk signature in IPF patients by performing Univariate and Lasso Cox Regression analysis. Univariate and Multivariate Cox Regression analyses were used to identify the independent value for predicting the prognosis of IPF patients. What’s more, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set enrichment analysis (GSEA) were conducted to unveil the potential biological pathways. CIBERSORT algorithms were performed to calculate the correlation between the risk score and immune cells infiltrating levels.

Results: Two hundred thirty three differentially expressed genes were calculated as the hub genes in COVID-19. Fourteen of these genes were identified as the prognostic differentially expressed genes in IPF. Three (MET, UCHL1, and IGF1) of the fourteen genes were chosen to construct the risk signature. The risk signature can greatly predict the prognosis of high-risk and low-risk groups based on the calculated risk score. The functional pathway enrichment analysis and immune infiltrating analysis showed that the risk signature may regulate the immune-related pathways and immune cells.

Conclusion: We identified prognostic differentially expressed hub genes related to COVID-19 in IPF. A risk signature was constructed based on those genes and showed great value for predicting the prognosis in IPF patients. What’s more, three genes in the risk signature may be clinically valuable as potential targets for treating IPF patients and IPF patients with COVID-19.

Comparative Analysis of Gene Expression in Fibroblastic Foci in Patients with Idiopathic Pulmonary Fibrosis and Pulmonary Sarcoidosis

Background: Fibroblastic foci (FF) are characteristic features of usual interstitial pneumonia (UIP)/idiopathic pulmonary fibrosis (IPF) and one cardinal feature thought to represent a key mechanism of pathogenesis. Hence, FF have a high impact on UIP/IPF diagnosis in current guidelines. However, although less frequent, these histomorphological hallmarks also occur in other fibrotic pulmonary diseases. Currently, there is therefore a gap in knowledge regarding the underlying molecular similarities and differences of FF in different disease entities. Methods: In this work, we analyzed the compartment-specific gene expression profiles of FF in IPF and sarcoidosis in order to elucidate similarities and differences as well as shared pathomechanisms. For this purpose, we used laser capture microdissection, mRNA and protein expression analysis. Biological pathway analysis was performed using two different gene expression databases. As control samples, we used healthy lung tissue that was donated but not used for lung transplantation. Results: Based on Holm Bonferroni corrected expression data, mRNA expression analysis revealed a significantly altered expression signature for 136 out of 760 genes compared to healthy controls while half of these showed a similar regulation in both groups. Immunostaining of selected markers from each group corroborated these results. However, when comparing all differentially expressed genes with the fdr-based expression data, only 2 of these genes were differentially expressed between sarcoidosis and IPF compared to controls, i.e., calcium transport protein 1 (CAT1) and SMAD specific E3 ubiquitin protein ligase 1 (SMURF1), both in the sarcoidosis group. Direct comparison of sarcoidosis and IPF did not show any differentially regulated genes independent from the statistical methodology. Biological pathway analysis revealed a number of fibrosis-related pathways pronounced in IPF without differences in the regulatory direction. Conclusions: These results demonstrate that FF of end-stage IPF and sarcoidosis lungs, although different in initiation, are similar in gene and protein expression, encouraging further studies on the use of antifibrotic agents in sarcoidosis.

Engineering, Characterization, and Biological Evaluation of an Antibody Targeting the HGF Receptor

The Hepatocyte growth factor (HGF) and its receptor (MET) promote several physiological activities such as tissue regeneration and protection from cell injury of epithelial, endothelial, neuronal and muscle cells. The therapeutic potential of MET activation has been scrutinized in the treatment of acute tissue injury, chronic inflammation, such as renal fibrosis and multiple sclerosis (MS), cardiovascular and neurodegenerative diseases. On the other hand, the HGF-MET signaling pathway may be caught by cancer cells and turned to work for invasion, metastasis, and drug resistance in the tumor microenvironment. Here, we engineered a recombinant antibody (RDO24) and two derived fragments, binding the extracellular domain (ECD) of the MET protein. The antibody binds with high affinity (8 nM) to MET ECD and does not cross-react with the closely related receptors RON nor with Semaphorin 4D. Deletion mapping studies and computational modeling show that RDO24 binds to the structure bent on the Plexin-Semaphorin-Integrin (PSI) domain, implicating the PSI domain in its binding to MET. The intact RDO24 antibody and the bivalent Fab2, but not the monovalent Fab induce MET auto-phosphorylation, mimicking the mechanism of action of HGF that activates the receptor by dimerization. Accordingly, the bivalent recombinant molecules induce HGF biological responses, such as cell migration and wound healing, behaving as MET agonists of therapeutic interest in regenerative medicine. In vivo administration of RDO24 in the murine model of MS, represented by experimental autoimmune encephalomyelitis (EAE), delays the EAE onset, mitigates the early clinical symptoms, and reduces inflammatory infiltrates. Altogether, these results suggest that engineered RDO24 antibody may be beneficial in multiple sclerosis and possibly other types of inflammatory disorders.

Cabozantinib ameliorates lipopolysaccharide-induced lung inflammation and bleomycin--induced early pulmonary fibrosis in mice

The lung, as the primary organ for gas exchange in mammals, is the main target organ for many pathogens and allergens, which may cause acute lung injury. A certain proportion of acute lung injury may progress into irreversible pulmonary fibrosis. Both acute lung injury and pulmonary fibrosis have high mortality rates and few effective treatments. Cabozantinib is a multi-target small molecule tyrosine kinase inhibitor and has been approved for the treatment of multiple malignant solid tumors. In this study, we explored the role of cabozantinib in acute lung injury and pulmonary fibrosis in vivo and in vitro. In the lipopolysaccharide and bleomycin induced mouse lung injury models, cabozantinib significantly improved the pathological state and reduced the infiltration of inflammatory cells in the lung tissues. In the bleomycin induced pulmonary fibrosis model, cabozantinib significantly reduced the area of pulmonary fibrosis and improved lung function in mice. The results of in vitro studies showed that cabozantinib could inhibit the inflammatory response and apoptosis of alveolar epithelial cells by inhibiting the activation of TLR4/NF-κB and NLRP3 inflammasome pathways. At the same time, cabozantinib could inhibit the activation of lung fibroblasts through suppressing the TGF-β1/Smad pathway, and promote the apoptosis of fibroblasts. In summary, cabozantinib could alleviate lung injury through regulating the TLR4 /NF-κB/NLRP3 inflammasome pathway, and alleviate pulmonary fibrosis by inhibiting the TGF-β1/Smad3 signaling pathway.

Therapeutic targeting of argininosuccinate synthase 1 (ASS1)-deficient pulmonary fibrosis

Argininosuccinate synthase 1 (ASS1) serves as a critical enzyme in arginine biosynthesis; however, its role in interstitial lung diseases, particularly idiopathic pulmonary fibrosis (IPF), remains largely unknown. This study aims at characterization and targeting of ASS1 deficiency in pulmonary fibrosis. We find that ASS1 was significantly decreased and inversely correlated with fibrotic status. Transcriptional downregulation of ASS1 was noted in fibroblastic foci of primary lung fibroblasts isolated from IPF patients. Genetic manipulations of ASS1 studies confirm that ASS1 expression inhibited fibroblast cell proliferation, migration, and invasion. We further show that the hepatocyte growth factor receptor (Met) receptor was activated and acted upstream of the Src-STAT3 axis signaling in ASS1-knockdown fibroblasts. Interestingly, both arginine-free conditions and arginine deiminase treatment were demonstrated to kill fibrotic fibroblasts, attenuated bleomycin-induced pulmonary fibrosis in mice, as well as synergistically increased nintedanib efficacy. Our data suggest ASS1 deficiency as a druggable target and also provide a unique therapeutic strategy against pulmonary fibrosis.

MET Activation and Physical Dynamics of the Metastatic Process: The Paradigm of Cancers of Unknown Primary Origin

The molecular and cellular mechanisms which drive metastatic spread are the topic of constant debate and scientific research due to the potential implications for cancer patients' prognosis. In addition to genetics and environmental factors, mechanics of single cells and physical interaction with the surrounding environment play relevant role in defining invasive phenotype. Reconstructing the physical properties of metastatic clones may help to clarify still open issues in disease progression as well as to lead to new diagnostic and therapeutic approaches. In this perspective cancer of unknown primary origin (CUP) identify the ideal model to study physical interactions and forces involved in the metastatic process. We have previously demonstrated that MET oncogene is mutated with unexpected high frequency in CUPs. We here analyze and discuss how the MET activation by somatic mutation may affect physical properties in giving rise to such a highly malignant syndrome, as that defined by CUP.

Stereotactic body radiotherapy for lung cancer patients with idiopathic interstitial pneumonias

PURPOSE

To compare toxicity and survival after stereotactic body radiotherapy (SBRT) between lung cancer patients with or without idiopathic interstitial pneumonias (IIPs), and to investigate the potential value of SBRT for the patients.

METHODS

Among lung cancer patients receiving SBRT between 2005 and 2016, we evaluated those treated with a total dose of 40-60Gy in five fractions with curative intent who either were staged as cT1-4N0M0 or experienced postoperative isolated local recurrence. We analyzed the incidence of radiation pneumonitis (RP) in all patients and local recurrence and overall survival (OS) in T1a-2a patients.

RESULTS

A total of 508 patients were eligible, including 42 with IIPs. The median follow-up was 32.3 (6.0-120.9) months. Significantly more patients with IIPs had grade ≥3RP than did those without IIPs (12% vs. 3%, p=0.009). The 2-year local recurrence rate was low in both groups (3.4% vs. 5.6%, p=0.38). The 2-year OS rate was significantly lower in the patients with IIPs (42.2% vs. 80.9%, p<0.001), although death from lung cancer was comparable (p=0.74).

CONCLUSION

SBRT achieved excellent local control with acceptable pulmonary toxicity in lung cancer patients with IIPs. SBRT can be a reasonable option for early lung cancer patients with IIPs.

Enabling Precision Cardiology Through Multiscale Biology and Systems Medicine

The traditional paradigm of cardiovascular disease research derives insight from large-scale, broadly inclusive clinical studies of well-characterized pathologies. These insights are then put into practice according to standardized clinical guidelines. However, stagnation in the development of new cardiovascular therapies and variability in therapeutic response implies that this paradigm is insufficient for reducing the cardiovascular disease burden. In this state-of-the-art review, we examine 3 interconnected ideas we put forth as key concepts for enabling a transition to precision cardiology: 1) precision characterization of cardiovascular disease with machine learning methods; 2) the application of network models of disease to embrace disease complexity; and 3) using insights from the previous 2 ideas to enable pharmacology and polypharmacology systems for more precise drug-to-patient matching and patient-disease stratification. We conclude by exploring the challenges of applying a precision approach to cardiology, which arise from a deficit of the required resources and infrastructure, and emerging evidence for the clinical effectiveness of this nascent approach.

Lung cancer in patients with idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic fibrotic lung disease of unknown etiology. With a gradually increasing worldwide prevalence and a mortality rate exceeding that of many cancers, IPF diagnosis and management are critically important and require a comprehensive multidisciplinary approach. This approach also involves assessment of comorbid conditions, such as lung cancer, that exerts a dramatic impact on disease survival. Emerging evidence suggests that progressive lung scarring in the context of IPF represents a risk factor for lung carcinogenesis. Both disease entities present with major similarities in terms of pathogenetic pathways, as well as potential causative factors, such as smoking and viral infections. Besides disease pathogenesis, anti-cancer agents, including nintedanib, have been successfully applied in the treatment of patients with IPF while an oncologic approach with a cocktail of several pleiotropic anti-fibrotic agents is currently in the therapeutic pipeline of IPF. Nevertheless, epidemiologic association between IPF and lung cancer does not prove causality. Currently there is significant lack of knowledge supporting a direct association between lung fibrosis and cancer reflecting to disappointing therapeutic algorithms. An optimal therapeutic strategy for patients with both IPF and lung cancer represents an amenable need. This review article synthesizes the current state of knowledge regarding pathogenetic commonalities between IPF and lung cancer and focuses on clinical and therapeutic data that involve both disease entities.