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Adaptive immune system uses T cell receptors (TCRs) to recognize pathogens and to consequently initiate 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 disorders. For this task, we have developed TCRGP, a novel Gaussian process method that predicts if TCRs recognize specified epitopes. TCRGP can utilize the amino acid sequences of the complementarity determining regions (CDRs) from TCRα and TCRβ chains and learn which CDRs are important in recognizing different epitopes. Our comprehensive evaluation with epitope-specific TCR sequencing data shows that TCRGP achieves on average higher prediction accuracy in terms of AUROC score than existing state-of-the-art methods in epitope-specificity predictions. We also propose a novel analysis approach for combined single-cell RNA and TCRαβ (scRNA+TCRαβ) sequencing data by quantifying epitope-specific TCRs with TCRGP and identify HBV-epitope specific T cells and their transcriptomic states in hepatocellular carcinoma patients.
Motivation T cells play an essential role in adaptive immune system to fight pathogens and cancer but may also give rise to autoimmune diseases. The recognition of a peptide-MHC (pMHC) complex by a T cell receptor (TCR) is required to elicit an immune response. Many machine learning models have been developed to predict the binding, but generalizing predictions to pMHCs outside the training data remains challenging. Results We have developed a new machine learning model that utilizes information about the TCR from both α and β chains, epitope sequence, and MHC. Our method uses ProtBERT embeddings for the amino acid sequences of both chains and the epitope, as well as convolution and multi-head attention architectures. We show the importance of each input feature as well as the benefit of including epitopes with only a few TCRs to the training data. We evaluate our model on existing databases and show that it compares favorably against other state-of-the-art models.
Motivation: T cells use T cell receptors (TCRs) to recognize small parts of antigens, called epitopes, presented by major histocompatibility complexes. Once an epitope is recognized, an immune response is initiated and T cell activation and proliferation by clonal expansion begin. Clonal populations of T cells with identical TCRs can remain in the body for years, thus forming immunological memory and potentially mappable immunological signatures, which could have implications in clinical applications including infectious diseases, autoimmunity and tumor immunology.Results: We introduce TCRconv, a deep learning model for predicting recognition between TCRs and epitopes. TCRconv uses a deep protein language model and convolutions to extract contextualized motifs and provides state-of-the-art TCR-epitope prediction accuracy. Using TCR repertoires from COVID-19 patients, we demonstrate that TCRconv can provide insight into T cell dynamics and phenotypes during the disease.
Abstract A sorption-enhanced process for hydrogenation of CO2 to methanol was designed and investigated by mathematical modelling and techno-economic analysis. The modelling methodology combined dynamic modelling of the cyclic reactor operation with pseudo-steady state modelling of the overall process. With continuous adsorption of water in the sorption-enhanced process, highly pure methanol (>99%) was produced without downstream distillation. The dynamic reactor cycle was designed and optimized to maximize the methanol production rate. The cycle and the process were modelled in two reactor configurations: adiabatic and isothermal. Under the default cost assumptions for the raw materials (CO2 50 €/t, hydrogen 3000 €/t) the adiabatic configuration was found more competitive in terms of the overall methanol production cost, at 1085 €/t compared to 1255 €/t for the isothermal case. The cost estimate for the adiabatic case was found comparable to a reference process representing conventional CO2 hydrogenation to methanol (1089 €/t). In addition to the methanol process, the developed modeling method has potential in the design of other sorption-enhanced processes.
Abstract The ambitious CO2 emission reduction targets for the transport sector set in the Paris Climate Agreement require low-carbon energy solutions that can be commissioned rapidly. The production of gasoline, kerosene, and diesel from renewable methanol using methanol-to-olefins (MTO) and Mobil’s Olefins to Gasoline and Distillate (MOGD) syntheses was investigated in this study via process simulation and economic analysis. The current work presents a process simulation model comprising liquid fuel production and heat integration. According to the economic analysis, the total cost of production was found to be 3409 €/tfuels (273 €/MWhLHV), corresponding to a renewable methanol price of 963 €/t (174 €/MWhLHV). The calculated fuel price is considerably higher than the current cost of fossil fuels and biofuel blending components. The price of renewable methanol, which is largely dictated by the cost of electrolytic hydrogen and renewable electricity, was found to be the most significant factor affecting the profitability of the MTO-MOGD plant. To reduce the price of renewable fuels and make them economically viable, it is recommended that the EU’s sustainable transport policies are enacted to allow flexible and practical solutions to reduce transport-related emissions within the member states.
Analyzing antigen-specific T cell responses at scale has been challenging. Here, we analyze three types of T cell receptor (TCR) repertoire data (antigen-specific TCRs, TCR-repertoire, and single-cell RNA + TCRαβ-sequencing data) from 515 patients with primary or metastatic melanoma and compare it to 783 healthy controls. Although melanoma-associated antigen (MAA) -specific TCRs are restricted to individuals, they share sequence similarities that allow us to build classifiers for predicting anti-MAA T cells. The frequency of anti-MAA T cells distinguishes melanoma patients from healthy and predicts metastatic recurrence from primary melanoma. Anti-MAA T cells have stem-like properties and frequent interactions with regulatory T cells and tumor cells via Galectin9-TIM3 and PVR-TIGIT -axes, respectively. In the responding patients, the number of expanded anti-MAA clones are higher after the anti-PD1(+anti-CTLA4) therapy and the exhaustion phenotype is rescued. Our systems immunology approach paves the way for understanding antigen-specific responses in human disorders.
Common variable immunodeficiency (CVID) and other late-onset immunodeficiencies often co-manifest with autoimmunity and lymphoproliferation. The pathogenesis of most cases is elusive, as only a minor subset harbors known monogenic germline causes. The involvement of both B and T cells is, however, implicated. To study whether somatic mutations in CD4+ and CD8+ T cells associate with immunodeficiency, we recruited 17 patients and 21 healthy controls. Eight patients had late-onset CVID and nine patients other immunodeficiency and/or severe autoimmunity. In total, autoimmunity occurred in 94% and lymphoproliferation in 65%. We performed deep sequencing of 2,533 immune-associated genes from CD4+ and CD8+ cells. Deep T-cell receptor b-sequencing was used to characterize CD4+ and CD8+ T-cell receptor repertoires. The prevalence of somatic mutations was 65% in all immunodeficiency patients, 75% in CVID, and 48% in controls. Clonal hematopoiesis-associated variants in both CD4+and CD8+ cells occurred in 24% of immunodeficiency patients. Results demonstrated mutations in known tumor suppressors, oncogenes, and genes that are critical for immune- and proliferative functions, such as STAT5B (2 patients), C5AR1 (2 patients), KRAS (one patient), and NOD2 (one patient). Additionally, as a marker of T-cell receptor repertoire perturbation, CVID patients harbored increased frequencies of clones with identical complementarity determining region 3 sequences despite unique nucleotide sequences when compared to controls. In conclusion, somatic mutations in genes implicated for autoimmunity and lymphoproliferation are common in CD4+ and CD8+ cells of patients with immunodeficiency. They may contribute to immune dysregulation in a subset of immunodeficiency patients.
BACKGROUND. Relatlimab plus nivolumab (anti-lymphocyte-activation gene 3 plus anti-programmed death 1 [anti-LAG-3+anti-PD-1]) has been approved by the FDA as a first-line therapy for stage III/IV melanoma, but its detailed effect on the immune system is unknown. METHODS. We evaluated blood samples from 40 immunotherapy-naive or prior immunotherapy-refractory patients with metastatic melanoma treated with anti-LAG-3+anti-PD-1 in a phase I trial using single-cell RNA and T cell receptor sequencing (scRNA+TCRαβ-Seq) combined with other multiomics profiling. RESULTS. The highest LAG3 expression was noted in NK cells, Tregs, and CD8+ T cells, and these cell populations underwent the most significant changes during the treatment. Adaptive NK cells were enriched in responders and underwent profound transcriptomic changes during the therapy, resulting in an active phenotype. LAG3+ Tregs expanded, but based on the transcriptome profile, became metabolically silent during the treatment. Last, higher baseline TCR clonality was observed in responding patients, and their expanding CD8+ T cell clones gained a more cytotoxic and NK-like phenotype. CONCLUSION. Anti-LAG-3+anti-PD-1 therapy has profound effects on NK cells and Tregs in addition to CD8+ T cells. TRIAL REGISTRATION. ClinicalTrials.gov (NCT01968109) FUNDING. Cancer Foundation Finland, Sigrid Juselius Foundation, Signe and Ane Gyllenberg Foundation, Relander Foundation, State funding for university-level health research in Finland, a Helsinki Institute of Life Sciences Fellow grant, Academy of Finland (grant numbers 314442, 311081, 335432, and 335436), and an investigator-initiated research grant from BMS.
T cell large granular lymphocytic leukemia (T-LGLL) is a rare lymphoproliferative disorder of mature, clonally expanded T cells, where somatic-activating STAT3 mutations are common. Although T-LGLL has been described as a chronic T cell response to an antigen, the function of the non-leukemic immune system in this response is largely uncharacterized. Here, by utilizing single-cell RNA and T cell receptor profiling (scRNA+TCRαβ-seq), we show that irrespective of STAT3 mutation status, T-LGLL clonotypes are more cytotoxic and exhausted than healthy reactive clonotypes. In addition, T-LGLL clonotypes show more active cell communication than reactive clones with non-leukemic immune cells via costimulatory cell–cell interactions, monocyte-secreted proinflammatory cytokines, and T-LGLL-clone-secreted IFNγ. Besides the leukemic repertoire, the non-leukemic T cell repertoire in T-LGLL is also more mature, cytotoxic, and clonally restricted than in other cancers and autoimmune disorders. Finally, 72% of the leukemic T-LGLL clonotypes share T cell receptor similarities with their non-leukemic repertoire, linking the leukemic and non-leukemic repertoires together via possible common target antigens. Our results provide a rationale to prioritize therapies that target the entire immune repertoire and not only the T-LGLL clonotype.
Immunological control of residual leukemia cells is thought to occur in patients with chronic myeloid leukemia (CML) that maintain treatment-free remission (TFR) following tyrosine kinase inhibitor (TKI) discontinuation. To study this, we analyzed 55 single-cell RNA and T cell receptor (TCR) sequenced samples (scRNA+TCRαβ-seq) from patients with CML (n = 13, N = 25), other cancers (n = 28), and healthy (n = 7). The high number and active phenotype of natural killer (NK) cells in CML separated them from healthy and other cancers. Most NK cells in CML belonged to the active CD56dim cluster with high expression of GZMA/B, PRF1, CCL3/4, and IFNG, with interactions with leukemic cells via inhibitory LGALS9–TIM3 and PVR–TIGIT interactions. Accordingly, upregulation of LGALS9 was observed in CML target cells and TIM3 in NK cells when co-cultured together. Additionally, we created a classifier to identify TCRs targeting leukemia-associated antigen PR1 and quantified anti-PR1 T cells in 90 CML and 786 healthy TCRβ-sequenced samples. Anti-PR1 T cells were more prevalent in CML, enriched in bone marrow samples, and enriched in the mature, cytotoxic CD8 + TEMRA cluster, especially in a patient maintaining TFR. Our results highlight the role of NK cells and anti-PR1 T cells in anti-leukemic immune responses in CML.
The prevalence and functional impact of somatic mutations in nonleukemic T cells is not well characterized, although clonal T-cell expansions are common. In immune-mediated aplastic anemia (AA), cytotoxic T-cell expansions are shown to participate in disease pathogenesis. We investigated the mutation profiles of T cells in AA by a custom panel of 2533 genes. We sequenced CD4+ and CD8+ T cells of 24 AA patients and compared the results to 20 healthy controls and whole-exome sequencing of 37 patients with AA. Somatic variants were common both in patients and healthy controls but enriched to AA patients’ CD8+ T cells, which accumulated most mutations on JAK-STAT and MAPK pathways. Mutation burden was associated with CD8+ T-cell clonality, assessed by T-cell receptor beta sequencing. To understand the effect of mutations, we performed single-cell sequencing of AA patients carrying STAT3 or other mutations in CD8+ T cells. STAT3 mutated clone was cytotoxic, clearly distinguishable from other CD8+ T cells, and attenuated by successful immunosuppressive treatment. Our results suggest that somatic mutations in T cells are common, associate with clonality, and can alter T-cell phenotype, warranting further investigation of their role in the pathogenesis of AA.
Rheumatoid arthritis (RA) is a complex autoimmune disease targeting synovial joints. Traditionally, RA is divided into seropositive (SP) and seronegative (SN) disease forms, the latter consisting of an array of unrelated diseases with joint involvement. Recently, we described a severe form of SN-RA that associates with characteristic joint destruction. Here, we sought biological characteristics to differentiate this rare but aggressive anti-citrullinated peptide antibody-negative destructive RA (CND-RA) from early seropositive (SP-RA) and seronegative rheumatoid arthritis (SN-RA). We also aimed to study cytotoxic CD8+ lymphocytes in autoimmune arthritis. CND-RA, SP-RA and SN-RA were compared to healthy controls to reveal differences in T-cell receptor beta (TCRβ) repertoire, cytokine levels and autoantibody repertoires. Whole-exome sequencing (WES) followed by single-cell RNA-sequencing (sc-RNA-seq) was performed to study somatic mutations in a clonally expanded CD8+ lymphocyte population in an index patient.A unique TCRβ signature was detected in CND-RA patients. In addition, CND-RA patients expressed higher levels of the bone destruction-associated TNFSF14 cytokine. Blood IgG repertoire from CND-RA patients recognized fewer endogenous proteins than SP-RA patients’ repertoires. Using WES, we detected a stable mutation profile in the clonally expanded CD8+ T-cell population characterized by cytotoxic gene expression signature discovered by sc-RNA-sequencing. Our results identify CND-RA as an independent RA subset and reveal a CND-RA specific TCR signature in the CD8+ lymphocytes. Improved classification of seronegative RA patients underlines the heterogeneity of RA and also, facilitates development of improved therapeutic options for the treatment resistant patients.
Abstract Background: Relatlimab plus nivolumab (anti–lymphocyte-activation gene 3 plus anti–programmed death 1 [anti–LAG-3+anti–PD-1]) has been approved by the FDA as a first-line therapy for stage III/IV melanoma, but its detailed effect on the immune system is unknown. Methods: We evaluated blood samples from 40 immunotherapy-naive or prior immunotherapy–refractory patients with metastatic melanoma treated with anti–LAG-3+anti–PD-1 in a phase I trial using single-cell RNA and T cell receptor sequencing (scRNA+TCRαβ-Seq) combined with other multiomics profiling. Results: The highest LAG3 expression was noted in NK cells, Tregs, and CD8+ T cells, and these cell populations underwent the most significant changes during the treatment. Adaptive NK cells were enriched in responders and underwent profound transcriptomic changes during the therapy, resulting in an active phenotype. LAG3+ Tregs expanded, but based on the transcriptome profile, became metabolically silent during the treatment. Last, higher baseline TCR clonality was observed in responding patients, and their expanding CD8+ T cell clones gained a more cytotoxic and NK-like phenotype. Conclusion: Anti–LAG-3+anti–PD-1 therapy has profound effects on NK cells and Tregs in addition to CD8+ T cells. Trial registration: ClinicalTrials.gov (NCT01968109) Funding : Cancer Foundation Finland, Sigrid Juselius Foundation, Signe and Ane Gyllenberg Foundation, Relander Foundation, State funding for university-level health research in Finland, a Helsinki Institute of Life Sciences Fellow grant, Academy of Finland (grant numbers 314442, 311081, 335432, and 335436), and an investigator-initiated research grant from BMS.
Immuunijärjestelmä on elimistömme puolustusjärjestelmä taudinaiheuttajilta. Autoimmuunisairauksissa immuunijärjestelmämme ei toimi odotetusti aiheuttaen erilaisia oireita ja jopa vahingoittaen terveitä soluja ja kudoksia. Näiden sairausten puhkeamisen syy on usein heikosti tunnettu, mutta monien sairausten on osoitettu olevan yhteydessä T-soluihin ja HLA-geenialueeseen. RNA-sekvensointi on suurtehosekvensointimenetelmä, jota käytetään usein geeniekspressioiden analysointiin. Nykyaikaiset työkalut mahdollistavat myös T-solureseptorien ja HLA-tyypitysten määrittämisen RNA-sekvensointidatasta. Tämä mahdollistaa edellä mainitun datan käyttämisen tutkimuksiin, jotka tarkastelevat immuunijärjestelmämme hankittua vastustuskykyä erilaisin ja yksityiskohtaisimmin tutkimuskysymyksin. Diplomityössä keräsimme lähes kaksi tuhatta julkisesti ladattavissa olevaa RNA-sekvensointidatanäytettä Sequence Read Archive -tietokannasta. Nämä näytteet olivat kymmenistä projekteista, jotka sisälsivät potilasnäytteitä tulehduksellisista suolistosairauksista ja keliakiasta. Määritimme laskennallisesti näytteissä esiintyvät T-solureseptorit ja HLA-tyypitykset tutkiaksemme niiden piirteitä eri sairauksissa. Tarkastelimme tämän lisäksi sekvensointiparametrien vaikutusta suorittamaamme analyysiin. Käytimme datan analysointiin valmiiksi kehiteltyjä metodeja: MiXCR:iä T-solureseptorien määrittämiseen, PHLAT:ia HLA-tyypitykseen, VDJtoolsia ja GLIPH2:a T-solureseptorien laskennalliseen tarkasteluun ja klusterointiin, sekä TCRGP:tä ennustamaan mitä T-solureseptorit tunnistavat. Diplomityön tulokset osoittavat heikompien sekvensointiparametrien ja kudosnäytteiden käytön vähentävän T-solureseptorien laskennallista saantia. Havaitsemme myös näytteiden erilaisen solutason koostumuksen vaikutuksen T-solureseptorien V-geenialueiden käytössä. Tietojoukkomme vaihtelevuudesta huolimatta löysimme kuitenkin T-solureseptoreiden yhtäläisyyksiin pohjautuvia monien näytteiden T-solureseptoreja kattavia klustereita. Osoitimme myös, etteivät näytteiden vaihtelevat prosessointitavat luo systemaattisia vinoumia TCRGP:n tuloksiin, ja uskommekin sen olevan sopiva työkalu autoreaktiivisten T-solureseptorien tunnistamiseen mahdollisen sopivan datan löytyessä. Totesimme HLA-tyypitysten olevan yhdenmukaisia vertailemalla tuloksia potilaskohtaisesti eri näytteistä. Osoitimme tilastollisella analyysillä näytteiden ilmentävän eri sairauksiin jo muissa tutkimuksissa yhdistettyjä riskialleeleja. Diplomityössä esittelemme tämän analyysin mahdollisuuksia keräämällä uuden tietojoukon ja toistamalla sen avulla aiemmin esitettyjä ilmiöitä. Diplomityön analyysi luo myös perustan muidenkin näytekokonaisuuksien analysointiin ja diplomityössä käytetyn tietojoukon laajentamiseen.
Cancer cells can evade natural killer (NK) cell activity, thereby limiting anti-tumor immunity. To reveal genetic determinants of susceptibility to NK cell activity, we examined interacting NK cells and blood cancer cells using single-cell and genome-scale functional genomics screens. Interaction of NK and cancer cells induced distinct activation and type I interferon (IFN) states in both cell types depending on the cancer cell lineage and molecular phenotype, ranging from more sensitive myeloid to less sensitive B-lymphoid cancers. CRISPR screens in cancer cells uncovered genes regulating sensitivity and resistance to NK cell-mediated killing, including adhesion-related glycoproteins, protein fucosylation genes, and transcriptional regulators, in addition to confirming the importance of antigen presentation and death receptor signaling pathways. CRISPR screens with a single-cell transcriptomic readout provided insight into underlying mechanisms, including regulation of IFN-γ signaling in cancer cells and NK cell activation states. Our findings highlight the diversity of mechanisms influencing NK cell susceptibility across different cancers and provide a resource for NK cell-based therapies.