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Immunotherapy has significantly altered the treatment paradigm of non-small cell lung cancer (NSCLC), but not all patients experience durable benefits. Predictive biomarkers are needed to identify patients who may benefit from immunotherapy. We retrospectively collected tumor tissues from 65 patients with advanced NSCLC before treatment, and performed transcriptomic and genomic analysis. By performing single-sample gene set enrichment analysis, we constructed a predictor named IKCscore based on the tumor microenvironment characteristics. IKCscore is a robust biomarker predicting response to immunotherapy, and its predictive capacity was confirmed from public datasets across different cancer types ( = 892), including OAK, POPLAR, IMvigor210, GSE135222, GSE126044, and Kim cohorts. High IKCscore was characterized by inflammatory tumor microenvironment phenotype and higher T cell receptor diversity. The IKCscore exhibits promise as a bioindicator that can predict the efficacy of both immunotherapy and immunotherapy-based combination therapies, while providing guidance for personalized therapeutic strategies for advanced NSCLC patients.
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http://dx.doi.org/10.1016/j.isci.2024.111340 | DOI Listing |
Biomaterials
September 2025
Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China. Electronic address:
The stimulator of interferon genes (STING) pathway represents a promising target in cancer immunotherapy. However, the clinical translation of cyclic dinucleotide (CDN)-based STING agonists remains hindered by insufficient formation of functional CDN-STING complexes. This critical bottleneck arises from two interdependent barriers: inefficient cytosolic CDN delivery and tumor-specific STING silencing via DNA methyltransferase-mediated promoter hypermethylation.
View Article and Find Full Text PDFBlood Adv
September 2025
BC Cancer, Vancouver, British Columbia, Canada.
Classical Hodgkin Lymphoma (CHL) is characterized by a complex tumor microenvironment (TME) that supports disease progression. While immune cell recruitment by Hodgkin and Reed-Sternberg (HRS) cells is well-documented, the role of non-malignant B cells in relapse remains unclear. Using single-cell RNA sequencing (scRNA-seq) on paired diagnostic and relapsed CHL samples, we identified distinct shifts in B-cell populations, particularly an enrichment of naïve B cells and a reduction of memory B cells in early-relapse compared to late-relapse and newly diagnosed CHL.
View Article and Find Full Text PDFPLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
View Article and Find Full Text PDFJ Neurooncol
September 2025
Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Purpose: NOTCH3 is increasingly implicated for its oncogenic role in many malignancies, including meningiomas. While prior work has linked NOTCH3 expression to higher-grade meningiomas and treatment resistance, the metabolic phenotype of NOTCH3 activation remains unexplored in meningioma.
Methods: We performed single-cell RNA sequencing on NOTCH3 + human meningioma cell lines.
Discov Nano
September 2025
Department of Rehabilitation Medicine, Rehabilitation Medical Center, Key Laboratory of Rehabilitation Medicine in Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.
Immunoelectron Microscopy (IEM) is a technique that combines specific immunolabeling with high-resolution electron microscopic imaging to achieve precise spatial localization of biomolecules at the subcellular scale (< 10 nm) by using high-electron-density markers such as colloidal gold and quantum dots. As a core tool for analyzing the distribution of proteins, organelle interactions, and localization of disease pathology markers, it has irreplaceable value, especially in synapse research, pathogen-host interaction mechanism, and tumor microenvironment analysis. According to the differences in labeling sequence and sample processing, the IEM technology system can be divided into two categories: the first is pre-embedding labeling, which optimizes the labeling efficiency through the pre-exposure of antigenic epitopes and is especially suitable for the detection of low-abundance and sensitive antigens; the second is post-embedding labeling, which relies on the low-temperature resin embedding (e.
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