Smoking-associated Downregulation of FILIP1L Enhances Lung Adenocarcinoma Progression Through Mucin Production, Inflammation, and Fibrosis

A Comprehensive Analysis of the ceRNA Network and Hub Genes in Avian Leukosis Virus Subgroup J and Infectious Bursal Disease Virus Superinfection

In the realm of poultry production, viral superinfections pose significant challenges, causing substantial economic losses worldwide. Among these, avian leukosis virus subgroup J (ALV-J) and infectious bursal disease virus (IBDV) are particularly concerning as they frequently lead to superinfections in chicken, further exacerbating production losses and health complications. Our previous research delved into the pathogenicity and immunosuppressive effects of these superinfections through in vitro and in vivo analyses. Yet, the underlying key genes and pathways governing this phenomenon remained elusive. In this study, we randomly selected three chickens at 21 days post infection from each treatment group (ALV-J, IBDV, ALV-J+IBDV, and control group) to collect the bursa of Fabricius samples for full transcriptome analysis. Utilizing these data, we constructed a comprehensive circRNA/lncRNA-miRNA-mRNA network which elucidated both synergistic and specific activations during the superinfection. Notably, three pivotal genes (FILIP1L, DCX, and MYPN) were pinpointed in datasets reflecting synergistic activations. Conversely, four other genes (STAP, HKR6, XKR4, and TLR5) emerged in datasets associated with specific activations. Further exploration revealed diverse significant GO terms and pathways associated with both synergistic and distinct activation processes. These ceRNA network and core genes potentially wield substantial influence over the synergistic or specific activation of tumorigenesis and pathogenesis induced by ALV-J and IBDV. These findings could help develop targeted therapies and improve disease control in poultry, reducing economic losses.

Decoding tumor-fibrosis interplay: mechanisms, impact on progression, and innovative therapeutic strategies

Malignant tumors are a category of diseases that possess invasive and metastatic capabilities, with global incidence and mortality rates remaining high. In recent years, the pivotal role of fibrosis in tumor progression, drug resistance, and immune evasion has increasingly been acknowledged. Fibrosis enhances the proliferation, migration, and invasion of tumor cells by modifying the composition and structure of the extracellular matrix, thereby offering protection for immune evasion by tumor cells. The activation of cancer-associated fibroblasts (CAFs) plays a significant role in this process, as they further exacerbate the malignant traits of tumors by secreting a variety of cytokines and growth factors. Anti-fibrotic tumor treatment strategies, including the use of anti-fibrotic drugs and inhibition of fibrosis-related signaling pathways such as Transforming Growth Factor-β (TGF-β), have demonstrated potential in delaying tumor progression and improving the effectiveness of chemotherapy, targeted therapy, and immunotherapy. In the future, by developing novel drugs that target the fibrotic microenvironment, new therapeutic options may be available for patients with various refractory tumors.

Identification of a Proteomic Signature for Predicting Immunotherapy Response in Patients With Metastatic Non-Small Cell Lung Cancer

Immunotherapy has improved survival rates in patients with cancer, but identifying those who will respond to treatment remains a challenge. Advances in proteomic technologies have enabled the identification and quantification of nearly all expressed proteins in a single experiment. Integrating mass spectrometry with high-throughput technologies has facilitated comprehensive analysis of the plasma proteome in cancer, facilitating early diagnosis and personalized treatment. In this context, our study aimed to investigate the predictive and prognostic value of plasma proteome analysis using the SWATH-MS (Sequential Window Acquisition of All Theoretical Mass Spectra) strategy in newly diagnosed patients with non-small cell lung cancer (NSCLC) receiving pembrolizumab therapy. We enrolled 64 newly diagnosed patients with advanced NSCLC treated with pembrolizumab. Blood samples were collected from all patients before and during therapy. A total of 171 blood samples were analyzed using the SWATH-MS strategy. Plasma protein expression in metastatic NSCLC patients prior to receiving pembrolizumab was analyzed. A first cohort (discovery cohort) was employed to identify a proteomic signature predicting immunotherapy response. Thus, 324 differentially expressed proteins between responder and non-responder patients were identified. In addition, we developed a predictive model and found a combination of seven proteins, including ATG9A, DCDC2, HPS5, FIL1L, LZTL1, PGTA, and SPTN2, with stronger predictive value than PD-L1 expression alone. Additionally, survival analyses showed an association between the levels of ATG9A, DCDC2, SPTN2 and HPS5 with progression-free survival (PFS) and/or overall survival (OS). Our findings highlight the potential of proteomic technologies to detect predictive biomarkers in blood samples from NSCLC patients, emphasizing the correlation between immunotherapy response and the idenfied protein set.

Comprehensive evaluation of smoking exposures and their interactions on DNA methylation

BACKGROUND

Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS).

METHODS

We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C).

FINDINGS

Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs.

INTERPRETATION

Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases.

FUNDING

Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.

Decoding the Gene Regulatory Network of Muscle Stem Cells in Mouse Duchenne Muscular Dystrophy: Revelations from Single-Nuclei RNA Sequencing Analysis

The gene dystrophin is responsible for Duchenne muscular dystrophy (DMD), a grave X-linked recessive ailment that results in respiratory and cardiac failure. As the expression of dystrophin in muscle stem cells (MuSCs) is a topic of debate, there exists a limited understanding of its influence on the gene network of MuSCs. This study was conducted with the objective of investigating the effects of dystrophin on the regulatory network of genes in MuSCs. To comprehend the function of dystrophin in MuSCs from DMD, this investigation employed single-nuclei RNA sequencing (snRNA-seq) to appraise the transcriptomic profile of MuSCs obtained from the skeletal muscles of dystrophin mutant mice (DMDmut) and wild-type control mice. The study revealed that the dystrophin mutation caused the disruption of several long non-coding RNAs (lncRNAs), leading to the inhibition of MEG3 and NEAT1 and the upregulation of GM48099, GM19951, and GM15564. The Gene Ontology (GO) enrichment analysis of biological processes (BP) indicated that the dystrophin mutation activated the cell adhesion pathway in MuSCs, inhibited the circulatory system process, and affected the regulation of binding. The study also revealed that the metabolic pathway activity of MuSCs was altered. The metabolic activities of oxidative phosphorylation (OXPHOS) and glycolysis were elevated in MuSCs from DMDmut. In summary, this research offers novel insights into the disrupted gene regulatory program in MuSCs due to dystrophin mutation at the single-cell level.