A5008272495- Immune cells in cancer
- Cancer Immunotherapy and Biomarkers
- Glioma Diagnosis and Treatment
- Ferroptosis and cancer prognosis
- Cancer Genomics and Diagnostics
- Single-cell and spatial transcriptomics
- MicroRNA in disease regulation
- Immunotherapy and Immune Responses
- Neuroinflammation and Neurodegeneration Mechanisms
- Molecular Biology Techniques and Applications
- RNA modifications and cancer
- Immune Cell Function and Interaction
- Cancer, Hypoxia, and Metabolism
- Barrier Structure and Function Studies
- Advanced Electron Microscopy Techniques and Applications
- CRISPR and Genetic Engineering
- Ion Transport and Channel Regulation
- Neonatal and fetal brain pathology
- Adipose Tissue and Metabolism
- Machine Learning in Materials Science
- Ubiquitin and proteasome pathways
- Gene expression and cancer classification
- Mitochondrial Function and Pathology
Tampere University
2018-2025
Tampere University Hospital
2024-2025
Universitat de Barcelona
2014-2018
The immunosuppressive microenvironment in glioblastoma (GBM) prevents an efficient antitumoral immune response and enables tumor formation growth. Although understanding of the nature immunosuppression is still largely lacking, it important for successful cancer treatment through system modulation. To gain insight into GBM, we performed a computational analysis to model relative cell content type each GBM sample from Cancer Genome Atlas RNA-seq data set. We uncovered high variability...
Abstract The tumor immune microenvironment (TiME) of human central nervous system (CNS) tumors remains to be comprehensively deciphered. Here, we employed flow cytometry and RNA sequencing analysis for a deep data-driven dissection diverse TiME uncover noncanonical cell types in CNS by using seven from five patients. Myeloid subsets comprised classical microglia, monocyte-derived macrophages, neutrophils, two myeloid subsets: CD3 + myeloids CD19 myeloids. T lymphocyte included...
Background & Aims: Patients with colorectal cancer have heterogeneous clinical responses to chemotherapy, although guidelines advise little variability in treatment selection based on molecular tumor features. Precision oncology research typically utilizes patient-derived organoids (PDTO) predict outcomes, but such efforts are often not directed towards identification of factors underlying differential therapy. Methods: Bulk RNA-sequencing was performed treatment-naive PDTOs, and gene...
Abstract Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated mechanisms through which cells escape treatment, but their relation toward tumor microenvironment (TME) remains elusive. Here we present comprehensive landscape of prostate TME at multiple points in standard timeline employing single-cell RNA-sequencing spatial transcriptomics data from 120 patients. We identify club-like as key epithelial...
The proprotein convertase enzyme FURIN promotes the proteolytic maturation of pro-proteins and thereby it serves as an important factor for maintaining cellular homeostasis. In T cells, is critical regulatory cell dependent peripheral immune tolerance intact helper polarization. enzymatic activity directly associated with its expression levels, but genetic determinants cell-type specific Furin gene regulation have remained elusive. By exploring histone acetyltransferase p300 binding patterns...
Abstract Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated mechanisms through which cells escape treatment, but their relation toward tumor microenvironment (TME) remains elusive. Here we present comprehensive landscape of prostate TME at multiple points in standard timeline employing single-cell RNA-sequencing spatial transcriptomics data from 110 patients. We identify club-like as key epithelial...
25 Background: The brain tumor immune microenvironment (TiME) is characterised by suppression of tumor-infiltrating leukocytes. lymphocyte niche activity particularly downregulated within this TiME milieu. Methods: Here, using data-driven approaches in flow cytometry and RNA sequencing analysis, we aimed at dissecting leukocyte cell types infiltrating human TiME. Results: Unsupervised clustering provided T subsets including double-negative (CD3 + CD4 - CD8 ) cells (DNT). Our DNT phenotype...
Abstract Purpose Extent of brain tumor resection continues to be one the central decisions taken during standard care in glioma patients. Here, we aimed evaluate most essential molecular factors, such as IDH (isocitrate dehydrogenase) mutation gliomas classification with patient-derived organoids (PGOs) using differential mobility spectrometry (DMS). Methods prospectively recruited 12 patients, 6 IDH-mutated and wild-type tumors, from which PGOs were generated ex-vivo . Altogether, 320 DMS...
The immunosuppressive microenvironment in glioblastoma (GBM) prevents efficient antitumoral immune response and thus enables tumor formation growth. An understanding of the nature immunosuppression is still largely lacking although it important for successful cancer treatment through system modulation. To gain insight into GBM, we performed a computational analysis to model relative cell content type each GBM sample from Cancer Genome Atlas RNA-seq dataset. As result, uncovered high...
<div>Abstract<p>The immunosuppressive microenvironment in glioblastoma (GBM) prevents an efficient antitumoral immune response and enables tumor formation growth. Although understanding of the nature immunosuppression is still largely lacking, it important for successful cancer treatment through system modulation. To gain insight into GBM, we performed a computational analysis to model relative cell content type each GBM sample from The Cancer Genome Atlas RNA-seq data set. We...
<p>Tables contain immune system related Gene ontology and KEGG pathway enrichments for identified response gene clusters.</p>
<p>Tables contain statistically significant associations between cluster activities and mutations or copy number variations in genes.</p>
<p>Table contains immune response related gene clusters identified in clustering analysis and used other analyses.</p>
<p>Table contains copy number variation of genes adjacent to CDK4 (AGAP2, MARCH9, TSPAN31) in samples with amplification.</p>
<p>File contains supplementary figures S1-S12. Figures include the concept, results and validation of regression analysis, estimated cell proportions for all non-malignant reference cells tissues, immune subgroups in separate GBM cohort, different associations between subgroups, genetic aberrations, relative or cluster. Furthermore, showing gene expression HLA genes as well protein levels glioma lines patient-derived cultures are included.</p>
<p>Tables contain GEO sample accession numbers for reference cells, genes which mutation and copy number variation data was downloaded primer sequences used qRT-PCR analysis.</p>
<p>Tables contain results from Ingenuity Pathway Analysis for immune system related gene clusters.</p>
<p>Tables contain immune subgroup for each sample and results from statistical testing all probes Illumina Infinium Human DNA Methylation 450 array. Statistical was done between the following groups: IDH1 mutated sampels; wild type samples with CDK4-MARCH9 locus amplification; Other samples.</p>
<p>Table contains copy number variation of genes adjacent to CDK4 (AGAP2, MARCH9, TSPAN31) in samples with amplification.</p>
<p>Tables contain statistically significant associations between cluster activities and mutations or copy number variations in genes.</p>
<p>Table contains immune response related gene clusters identified in clustering analysis and used other analyses.</p>
<p>Tables contain results from Ingenuity Pathway Analysis for immune system related gene clusters.</p>
<p>Tables contain GEO sample accession numbers for reference cells, genes which mutation and copy number variation data was downloaded primer sequences used qRT-PCR analysis.</p>