Up-regulated SPP1 increases the risk from IPF to lung cancer via activating the pro-tumor macrophages.

The incidence of lung cancer (LC) in Idiopathic Pulmonary Fibrosis (IPF) patients is more than twice that in non-IPF. This study aims to investigate IPF-to-LC pathogenesis and to develop a predictor for detecting IPF predisposing patients to LC. We conducted unsupervised clustering to detect high-risk subtypes from IPF to LC. Subsequently, we performed single-cell RNA-seq analysis to characterize high-risk IPF by examining the immune microenvironment. We identified 42 common immune function-related pathogenic genes between IPF and LC. We developed an LC risk classifier for IPF patients, comprising five genes: SPP1, MMP9, MMP12, FABP4, and IL1B. The five-gene classifier can successfully distinguish the high-risk population from IPF patients. High-risk IPF patients exhibited an immunosuppressive microenvironment with higher oncogene expression than low-risk patients. Single-cell analysis revealed that SPP1+ macrophages at the terminal of macrophages' developmental trajectory may promote the progression from IPF to LC. The strong crosstalk between SPP1+ macrophages and inflammation-related cancer-associated fibroblasts promoted the tumorigenic process in IPF. In vitro, assays showed that co-culturing macrophages overexpressing SPP1 with MRC-5 cells induced the transition of fibroblasts into cancer-associated fibroblasts. SPP1 produced by macrophages promoted epithelial-mesenchymal transition in alveolar epithelial cells via stimulating the upregulation of N-cadherin and Vimentin in MLE-12 cells. This study provided a novel method to identify the LC risk population from IPF, revealing the cellular interactions involved in the transition from IPF to LC. Our findings highlighted SPP1 as a critical driver in IPF progression, offering a potential target for therapy in fibrosis.

FDRdb: a manually curated database of fibrotic disease-associated RNAome and high-throughput datasets.

Fibrosis is a common and serious disease that exists as a complicated impairment in many organs and triggers a complex cascade of responses. The deregulation of Ribonucleic Acids (RNAs) plays important roles in a variety of organ fibrosis cases. However, for fibrotic diseases, there is still a lack of an integrated platform with up-to-date information on RNA deregulation and high-throughput data. The Fibrotic Disease-associated RNAome database (FDRdb) (http://www.medsysbio.org/FDRdb) is a manually curated database of fibrotic disease-associated RNAome information and high-throughput datasets. This initial release (i) contains 1947 associations between 912 RNAs and 92 fibrotic diseases in eight species; (ii) collects information on 764 datasets of fibrotic diseases; (iii) provides a user-friendly web interface that allows users to browse, search and download the RNAome information on fibrotic diseases and high-throughput datasets and (iv) provides tools to analyze the expression profiles of fibrotic diseases, including differential expression analysis and pathway enrichment. The FDRdb is a valuable resource for researchers to explore the mechanisms of RNA dysregulation in organ fibrosis. Database URL: http://www.medsysbio.org/FDRdb.

Systematic analyses identify the anti-fibrotic role of lncRNA TP53TG1 in IPF.

Long non-coding RNA (lncRNA) was reported to be a critical regulator of cellular homeostasis, but poorly understood in idiopathic pulmonary fibrosis (IPF). Here, we systematically identified a crucial lncRNA, p53-induced long non-coding RNA TP53 target 1 (TP53TG1), which was the dysregulated hub gene in IPF regulatory network and one of the top degree genes and down-regulated in IPF-drived fibroblasts. Functional experiments revealed that overexpression of TP53TG1 attenuated the increased expression of fibronectin 1 (Fn1), Collagen 1α1, Collagen 3α1, ACTA2 mRNA, Fn1, and Collagen I protein level, excessive fibroblasts proliferation, migration and differentiation induced by TGF-ß1 in MRC-5 as well as PMLFs. In vivo assays identified that forced expression of TP53TG1 by adeno-associated virus 5 (AAV5) not only prevented BLM-induced experimental fibrosis but also reversed established lung fibrosis in the murine model. Mechanistically, TP53TG1 was found to bind to amount of tight junction proteins. Importantly, we found that TP53TG1 binds to the Myosin Heavy Chain 9 (MYH9) to inhibit its protein expression and thus the MYH9-mediated activation of fibroblasts. Collectively, we identified the TP53TG1 as a master suppressor of fibroblast activation and IPF, which could be a potential hub for targeting treatment of the disease.

Upregulation of CXCL1 and LY9 contributes to BRCAness in ovarian cancer and mediates response to PARPi and immune checkpoint blockade.

BACKGROUND: Mutations in BRCA1 or BRCA2 (BRCA1/2) cause homologous recombination deficiency (HRD). Ovarian cancer (OvCa) patients harbouring HRD beyond BRCA1/2 mutation result in a state referred to as "BRCAness". OvCa with BRCAness could benefit from PARP inhibitors. This study aims to identify a signature to detect the BRCAness population at the transcriptome level. METHODS: We used a rank-based algorithm to develop a qualitative BRCAness signature for OvCa. Upregulation of CXCL1 with downregulation of SV2A and upregulation of LY9 with downregulation of CHRNB3 were constructed as the BRCAness signature (2 gene pairs, 2-GPS) for OvCa. RESULTS: OvCa samples that were classified as BRCAness by 2-GPS showed improved overall survival, progression-free survival and exhibited increased multi-omics alterations in homologous recombination genes and enhanced sensitivity to immune checkpoint blockade. BRCAness cells were sensitive to PARP inhibitors. By biological experiments, we validated SKOV3 cells and patients with HRD exhibited higher expression of CXCL1 than SV2A and higher expression of LY9 than CHRNB3 at mRNA level. Both SKOV3 and A2780 with HRD were sensitive to mitomycin C, cisplatin and olaparib. CONCLUSIONS: In conclusion, 2-GPS could robustly predict BRCAness OvCa at the individual level and extend the population who may benefit from PARP inhibitors.

A transcriptional signature detects homologous recombination deficiency in pancreatic cancer at the individual level.

Pancreatic cancer (PC) with homologous recombination deficiency (HRD) has been reported to benefit from poly ADP-ribose polymerase (PARP) inhibitors. However, accurate identification of HRD status for PC patients from the transcriptional level is still a great challenge. Here, based on a relative expression ordering (REO)-based algorithm, we developed an HRD signature including 24 gene pairs (24-GPS) using PC transcriptional profiles from The Cancer Genome Atlas (TCGA). HRD samples classified by 24-GPS showed worse overall survival (p = 4.4E-3 for TCGA; p = 1.2E-3 for International Cancer Genome Consortium-Australia cohort; p = 6.4E-2 for GSE17891; p = 7.5E-2 for GSE57495) and higher HRD scores than non-HRD samples (p = 1.4E-4). HRD samples showed highly unstable genomic characteristics and also displayed HRD-related alterations at the epigenomic and proteomic levels. Moreover, HRD cell lines identified by 24-GPS tended to be sensitive to PARP inhibitors (p = 6.6E-2 for olaparib; p = 2.6E-3 for niraparib). Compared with the non-HRD group, the HRD group presented lower immune scores and CD4/CD8 T cell infiltration proportion. Interestingly, PC tumor cells with co-inhibition of PARP-related genes and ATR showed reduced survival ability. In conclusion, 24-GPS can robustly identify PC patients with HRD status at the individualized level.

Discovering a qualitative transcriptional signature of homologous recombination defectiveness for prostate cancer.

The discovery of homologous recombination deficiency (HRD) biomarkers in prostate cancer is important for patients who will benefit from poly ADP-ribose polymerase inhibitor (PARPi). Here, we developed a transcriptional homologous recombination defectiveness (HRDness) signature, comprising 16 gene pairs (16-GPS), for prostate cancer by a relative expression ordering (REO)-based discovery procedure. Subsequently, two newly subtypes classified by 16-GPS showed a higher significance level in various clinicopathological and HRD features than subtypes obtained by other methods, such as HRDetect. HRDness subtype also displayed more aggressive features and higher genomics scores than non-HRDness in three independent datasets. HRDness prostate cancer cells were more sensitive to PARPi than non-HRDness. Moreover, the HRDness samples showed distinct multi-omics characteristics related to homologous recombination repair function loss. Overall, the newly proposed qualitative signature can robustly determine the HRD status for prostate cancer at the personalized level, and especially be an auxiliary tool for PARPi treatment strategy.

Revealing biomarkers associated with PARP inhibitors based on genetic interactions in cancer genome.

Poly (ADPribose) polymerase inhibitors (PARPis) are clinically approved drugs designed according to the concept of synthetic lethality (SL) interaction. It is crucial to expand the scale of patients who can benefit from PARPis, and overcome drug resistance associated with it. Genetic interactions (GIs) include SL and synthetic viability (SV) that participate in drug response in cancer cells. Based on the hypothesis that mutated genes with SL or SV interactions with PARP1/2/3 are potential sensitive or resistant PARPis biomarkers, respectively, we developed a novel computational method to identify them. We analyzed fitness variation of cell lines to identify PARP1/2/3-related GIs according to CRISPR/Cas9 and RNA interference functional screens. Potential resistant/sensitive mutated genes were identified using pharmacogenomic datasets. We identified 41 candidate resistant and 130 candidate sensitive PARPi-response related genes, and observed that EGFR with gain-of-function mutation induced PARPi resistance, and predicted a combination therapy with PARP inhibitor (veliparib) and EGFR inhibitor (erlotinib) for lung cancer. We also revealed that a resistant gene set (TNN, PLEC, and TRIP12) in lower grade glioma and a sensitive gene set (BRCA2, TOP3A, and ASCC3) in ovarian cancer, which were associated with prognosis. Thus, cancer genome-derived GIs provide new insights for identifying PARPi biomarkers and a new avenue for precision therapeutics.

LncRNA CTD-2528L19.6 prevents the progression of IPF by alleviating fibroblast activation.

Long non-coding RNAs (lncRNAs) have emerged as critical factors for regulating multiple biological processes during organ fibrosis. However, the mechanism of lncRNAs in idiopathic pulmonary fibrosis (IPF) remains incompletely understood. In the present study, two sets of lncRNAs were defined: IPF pathogenic lncRNAs and IPF progression lncRNAs. IPF pathogenic and progression lncRNAs-mRNAs co-expression networks were constructed to identify essential lncRNAs. Network analysis revealed a key lncRNA CTD-2528L19.6, which was up-regulated in early-stage IPF compared to normal lung tissue, and subsequently down-regulated during advanced-stage IPF. CTD-2528L19.6 was indicated to regulate fibroblast activation in IPF progression by mediating the expression of fibrosis related genes LRRC8C, DDIT4, THBS1, S100A8 and TLR7 et al. Further studies showed that silencing of CTD-2528L19.6 increases the expression of Fn1 and Collagen I both at mRNA and protein levels, promoted the transition of fibroblasts into myofibroblasts and accelerated the migration and proliferation of MRC-5 cells. In contrast, CTD-2528L19.6 overexpression alleviated fibroblast activation in MRC-5 cells induced by TGF-ß1. LncRNA CTD-2528L19.6 inhibited fibroblast activation through regulating the expression of LRRC8C in vitro assays. Our results suggest that CTD-2528L19.6 may prevent the progression of IPF from early-stage and alleviate fibroblast activation during the advanced-stage of IPF. Thus, exploring the regulatory effect of lncRNA CTD-2528L19.6 may provide new sights for the prevention and treatment of IPF.

Individualized lncRNA differential expression profile reveals heterogeneity of breast cancer.

Long non-coding RNAs (lncRNAs) play key regulatory roles in breast cancer. However, population-level differential expression analysis methods disregard the heterogeneous expression of lncRNAs in individual patients. Therefore, we individualized lncRNA expression profiles for breast invasive carcinoma (BRCA) using the method of LncRNA Individualization (LncRIndiv). After evaluating the robustness of LncRIndiv, we constructed an individualized differentially expressed lncRNA (IDElncRNA) profile for BRCA and investigated the subtype-specific IDElncRNAs. The breast cancer subtype-specific IDElncRNA showed frequent co-occurrence with alterations of protein-coding genes, including mutations, copy number variation and differential methylation. We performed hierarchical clustering to subdivide TNBC and revealed mesenchymal subtype and immune subtype for TNBC. The TNBC immune subtype showed a better prognosis than the TNBC mesenchymal subtype. LncRNA PTOV1-AS1 was the top differentially expressed lncRNA in the mesenchymal subtype. And biological experiments validated that the upregulation of PTOV1-AS1 could downregulate TJP1 (ZO-1) and E-Cadherin, and upregulate Vimentin, which suggests PTOV1-AS1 may promote epithelial-mesenchymal transition and lead to migration and invasion of TNBC cells. The mesenchymal subtype showed a higher fraction of M2 macrophages, whereas the immune subtype was more associated with CD4 + T cells. The immune subtype is characterized by genomic instability and upregulation of immune checkpoint genes, thereby suggesting a potential response to immunosuppressive drugs. Last, drug response analysis revealed lncRNA ENSG00000230082 (PRRT3-AS1) is a potential resistance biomarker for paclitaxel in BRCA treatment. Our analysis highlights that IDElncRNAs can characterize inter-tumor heterogeneity in BRCA and the new TNBC subtypes indicate novel insights into TNBC immunotherapy.

The mechanism of hydrogen-accelerated melting of polycrystalline copper.

We investigate the melting process of polycrystalline copper doped with hydrogen atoms by using the newly developed Cu/H ReaxFF force field. Hydrogen atoms are found to effectively promote the melting of copper, and even make it happen at temperatures below the equilibrium melting temperature of copper during rapid heating. The enhanced melting is closely relevant to the interaction of hydrogen atoms with the grain boundary. We find that host Cu atoms perform cooperative vibration around the grain boundaries as the precursor of premelting. The doping of hydrogen atoms is shown to drive the vibration more violent so that the grain boundary becomes broader and the premelting is prematurely triggered. Meanwhile, hydrogen atoms segregated in grain boundaries massively diffuse into the bulk region with increasing temperature, resulting in intensification of lattice distortion of the bulk phase. This facilitates the rapid advancement of the liquid-solid interface during melting in contrast to the slow and discontinuous interface advancement in hydrogen-free polycrystalline copper. Our results suggest that even a small amount of hydrogen atoms is expected to significantly affect the thermodynamic properties of metals with the existence of structural defects.

Numerical Simulation of Supercooled Water Droplets Impacting Ice with Rapid Crystal Growth Taken into Consideration.

The impact of a supercooled water droplet is considerably affected by the rapid crystal growth when the duration of the recalescence stage is comparable to the typical time of impact. However, the recalescence stage is generally neglected in the existing numerical simulations using the enthalpy-porosity method. We propose a subregion function method to deal with the rapid crystal growth during the impact of supercooled water droplets. A restricted region named the dendrite cloud region is defined in the method, and the phase change is enabled only in this dendrite cloud region while the evolution of this region is determined by the initial nucleation sites and the dendritic growth velocity of the ice. The impacts of supercooled water droplets on a smooth ice surface are simulated using a three-phase volume-of-fluid method coupled with the subregion function method. The calculated residual ice layer thickness at the impact center is consistent with previous experimental results. This subregion function method can also be extended to the numerical simulations of other types of fluid flows involving rapid solidification.

Dendritic Growth Model Involving Interface Kinetics for Supercooled Water.

The dendritic growth of ice in supercooled water droplets is studied theoretically and experimentally. The measured dendritic growth velocity of ice shows a good agreement with the prediction of the Langer and Müller-Krumbhaar (LM-K) growth model at supercoolings less than 7 K, whereas an increasing overestimation in the latter is observed as the droplets are further supercooled. Therefore, the LM-K dendritic growth model is modified by considering the influence of interface kinetics. In the modified model, a dendrite grows in the limit of marginal stability coupled with diffusion at the liquid-solid interface, and the interface kinetics supercooling is introduced to predict the dendritic growth velocity. The interface kinetics factor is determined by fitting the experimental dendritic growth velocity within the framework of the modified model. This modification to the LM-K model well describes the dendritic growth of ice in water supercooled up to 25 K. It provides a solution to the dendritic growth of ice in the high-supercooling regime and can serve as a reliable input for studies on icing problems in engineering fields.