Biology subjects

Mustjoki, S.

Publications and source records attributed to Mustjoki, S..

22 records · Page 2Linked to original sources

bioRxiv2019

Inferring immunological control mechanisms from TKI dose alterations in CML patients

Recent clinical findings in chronic myeloid leukemia (CML) patients suggest that the risk of molecular recurrence after stopping tyrosine kinase inhibitors (TKI) treatment substantially depend on an individual, leukemia-specific immune response. However, it is still not possible to prospectively identify patients that will most likely remain in a long-term treatment free remission (TFR). Here, we use a mathematical model for CML, which explicitly includes an anti-leukemic (presumably immunological) effect and apply it to a set of patients (n=60) for whom BCR-ABL/ABL time courses had been quantified before and after TKI stop. We demonstrate that such a feedback control is conceptually necessary to explain long-term remission as observed in about half of the patients. Based on simulation results we classify the patient data sets into three different groups according to their predicted immune system configuration. While one class of patients requires a complete CML eradication to achieve TFR, other patients are able to control the leukemia after treatment cessation. Among them, we identified a third class of patients, which only maintains TFR if an optimal balance between leukemia abundance and immunological activation is achieved before treatment cessation. Further, we demonstrate that the immune response classification of the patients cannot be obtained solely from BCR-ABL measurements before treatment cessation. However, our results strongly suggest that changes in the BCR-ABL dynamics arising after system perturbations, such as TKI dose reduction, holds the information to predict the individual outcome after treatment cessation.

systems biology↗

bioRxiv2019

Immunogenomic landscape of hematological malignancies

Understanding factors that shape the immune landscape across hematological malignancies is essential for immunotherapy development. Here, we integrated over 8,000 transcriptomes and over 1,000 samples with multilevel genomic data of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival. Infiltration of cytotoxic immune cells was associated with distinct microenvironmental responses and driver alterations in different cancers, such as TP53 in acute myeloid leukemia and DTX1 in diffuse large B cell lymphoma. Epigenetic modification of CIITA regulating antigen presentation, cancer type-specific immune checkpoints such as VISTA in myeloid malignancies, and variation in cancer antigen expression further contributed to immune heterogeneity. Prognostic models highlighted the significance of immunological properties in predicting survival. Our study represents the most comprehensive effort to date to link immunology with cancer subtypes and genomics in hematological malignancies, providing a resource to guide future studies and immunotherapy development.

immunology↗

bioRxiv2019

TCRGP: Determining epitope specificity of T cell receptors

T cell receptors (TCRs) can recognize various pathogens and consequently start immune responses. TCRs can be sequenced from individuals and methods analyzing the specificity of the TCRs can help us better understand individuals immune status in different diseases. We have developed TCRGP, a novel Gaussian process method to predict if TCRs recognize certain epitopes. This method can utilize CDR sequences from TCR and TCR{beta} chains and learn which CDRs are important in recognizing different epitopes. We have experimented with with epitope-specific data against 29 epitopes and performed a comprehensive evaluation with existing prediction methods. On this data, TCRGP outperforms other state-of-the-art methods in epitope-specificity predictions. We also propose a novel analysis approach for combined single-cell RNA and TCR{beta} (scRNA+TCR{beta}) sequencing data by quantifying epitope-specific TCRs with TCRGP in phenotypes identified from scRNA-seq data. With this approach, we find HBV-epitope specific T cells and their transcriptomic states in hepatocellular carcinoma patients.

bioinformatics↗

bioRxiv2018

Characterization of novel TMEM173 mutation with additive IFIH1 risk allele

TMEM173 encodes for STING that is a transmembrane protein activated by pathogen or self-derived cytosolic nucleic acids causing its translocation from ER to Golgi, and further to vesicles. Monogenic STING gain-of-function mutations cause early-onset type I interferonopathy, with disease presentation ranging from fatal vasculopathy to mild chilblain lupus. Molecular mechanisms causing the poor phenotypegenotype correlation are presently unclear. Here we report a novel gain-of-function G207E STING mutation causing a distinct phenotype with alopecia, photosensitivity, thyroid dysfunction, and STING-associated vasculopathy with onset in infancy (SAVI) -features; livedo reticularis, nasal septum perforation, facial erythema, bacterial infections and skin vasculitis. Single residue polymorphisms in TMEM173 and an IFIH1 T946 risk allele modify disease presentation in the affected multigeneration family, explaining the varying clinical phenotypes. The G207E mutation causes constitutive activation of inflammation-related pathways in HEK cells, as well as aberrant interferon signature and inflammasome activation in patient PBMCs. Protein-protein interactions further propose impaired cellular trafficking of G207E mutant STING. These findings reveal the molecular landscape of STING and highlight the complex additive effects on the phenotype.\n\nBRIEF SUMMARYNovel gain-of-function mutation in TMEM173, associated with single residue polymorphisms in TMEM173 and IFIH1, causes a distinct clinical phenotype with some shared features of SAVI.

immunology↗