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

Identification of a proteomic signature for predicting immunotherapy response in patients with metastatic non-small cell lung cancer

BACKGROUND

Immunotherapy has improved survival rates in cancer patients, but identifying those who will respond to treatment remains a challenge. Recent advances in proteomic technologies have enabled the identification and quantification of nearly all expressed proteins in a single experiment. Integration of mass spectrometry with other high-throughput technologies has paved the way for comprehensive and systematic analysis of the plasma proteome in cancer, facilitating early diagnosis and personalized treatment. In this context, the objective of our study was 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 NSCLC patients who received pembrolizumab therapy.

METHODS

For this purpose, 64 newly diagnosed advanced NSCLC patients treated with pembrolizumab therapy were enrolled and blood samples were collected from all patients before and during therapy. In total 171 blood samples were collected, and plasma samples were analysed employing SWATH-MS strategy. Next, we compared the plasma protein expression of metastatic NSCLC patients prior to receiving pembrolizumab treatment and divided the cohort into two groups in order to identify a proteomic signature that allow us to predict immunotherapy response.

RESULTS

Proteomic analyses by SWATH-MS strategy allow us to identified 324 differentially expressed proteins between responder and non-responder patients. 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 that low levels of ATG9A, DCDC2, and HPS5 were associated with longer progression-free survival (PFS) and overall survival (OS), while low levels of SPTN2 were associated with worse OS.

CONCLUSIONS

Our work highlights the potential value of proteomic technologies to detect predictive biomarkers in blood samples of NSCLC patients. These analyses shed light on the correlation between the response to immunotherapy in patients with NSCLC and the set of 7 proteins.

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.