ArticleInternational journal of molecular sciences2022
High IGKC-Expressing Intratumoral Plasma Cells Predict Response to Immune Checkpoint Blockade.
Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 29 citations in OpenAlex.
- Integrating tumor and immune cell transcriptomics to predict immune checkpoint inhibitor primary resistance in metastatic melanoma.Oncoimmunology · 2026Article
- B cells and humoral immunity in melanoma: regulatory and autoimmune-like features and implications for immunotherapy.Oncoimmunology · 2026Review
- The multifaceted roles of tumor-infiltrating plasma cells in cancer immunology.Fundamental research · 2026Review
- Phenotypic, functional, prognostic and predictive significance of B-cell and antibody responses in human melanoma: a scoping review.The British journal of dermatology · 2026Article
- Conventional type-1 DC density is associated with checkpoint inhibitor response across multiple types of cancer.The Journal of clinical investigation · 2026Article
- SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Integrative multiomic profiling of cfDNA methylation and EV-miRNAs identifies immunotherapy-outcome molecular subtypes in NSCLC.Journal for immunotherapy of cancer · 2026Article
- UAP1 as a prognostic biomarker regulating malignant biological functions in multiple myeloma cells.Frontiers in oncology · 2026Article
- Concerted changes in Epithelium and Stroma: a multi-scale, multi-omics analysis of progression from Barrett's Esophagus to adenocarcinoma.Developmental cell · 2025Article
- Differentially Expressed Genes Identify FIGO Stage II Cervical Cancer Patients with a Higher Risk of Relapse in a Small Cohort.Journal of personalized medicine · 2025Article
- Heterogeneity-optimized method for predicting immune checkpoint blockade response.Scientific reports · 2025Article
- Investigating the potential role of EIF2S2 in OSCC progression through comprehensive bioinformatics analysis and experimental validation.European journal of medical research · 2025Article
- A dynamic molecular landscape in colorectal cancer progression at single-cell resolution.Journal of translational medicine · 2025Article
- Article
- Single-Cell Sequencing Reveals PD-L1-Mediated Immune Escape Signaling in Lung Adenocarcinoma.Journal of Cancer · 2025Article
- Multi-dimensional characterization of apoptosis in the tumor microenvironment and therapeutic relevance in melanoma.Cellular oncology (Dordrecht, Netherlands) · 2024Article
- Integration of bioinformatics and machine learning approaches for the validation of pyrimidine metabolism-related genes and their implications in immunotherapy for osteoporosis.BMC musculoskeletal disorders · 2024Article
- Epigenetic targets to enhance antitumor immune response through the induction of tertiary lymphoid structures.Frontiers in immunology · 2024Review
- Bioinformatics and machine learning were used to validate glutamine metabolism-related genes and immunotherapy in osteoporosis patients.Journal of orthopaedic surgery and research · 2023Article
- Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy.Journal of clinical medicine · 2023Review
Corrections and comments
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Authors and funding
23 authors at 3 institutions in 2 countries.
Funding
Abstract
Resistance to Immune Checkpoint Blockade (ICB) constitutes the current limiting factor for the optimal implementation of this novel therapy, which otherwise demonstrates durable responses with acceptable toxicity scores. This limitation is exacerbated by a lack of robust biomarkers. In this study, we have dissected the basal TME composition at the gene expression and cellular levels that predict response to Nivolumab and prognosis. BCR, TCR and HLA profiling were employed for further characterization of the molecular variables associated with response. The findings were validated using a single-cell RNA-seq data of metastatic melanoma patients treated with ICB, and by multispectral immunofluorescence. Finally, machine learning was employed to construct a prediction algorithm that was validated across eight metastatic melanoma cohorts treated with ICB. Using this strategy, we have unmasked a major role played by basal intratumoral Plasma cells expressing high levels of IGKC in efficacy. IGKC, differentially expressed in good responders, was also identified within the Top response-related BCR clonotypes, together with IGK variants. These results were validated at gene, cellular and protein levels; CD138+ Plasma-like and Plasma cells were more abundant in good responders and correlated with the same RNA-seq-defined fraction. Finally, we generated a 15-gene prediction model that outperformed the current reference score in eight ICB-treated metastatic melanoma cohorts. The evidenced major contribution of basal intratumoral IGKC and Plasma cells in good response and outcome in ICB in metastatic melanoma is a groundbreaking finding in the field beyond the role of T lymphocytes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.