Identification of silencers in the human genome >>

Project description

The candidate will be actively involved in identifying silencers in an unbiased way to gain a more general understanding of the biology of silencers. We aim to identify a general pattern of epigenetic modifications of silencers, unique combination of sequence motifs, responsible regulatory TFs, biological pathways that are regulated by silencers, diseases that might be related to mutations in silencers, and finally better manipulation strategies of silencers.

About the group

The research group of Baoxu Pang is at the Department of Cell and Chemical Biology of the Leiden University Medical Center (LUMC). The research is supported by an ERC starting grant. The main focus of the group is to develop and use state-of-the-art technologies to study the non-coding regulatory part of the genome, especially the silencers, so as to define the essential genomic elements for cell survival, development, drug response, and other important biological pathways. We have developed a unique high-throughput system to study the silencer regions of the genome (Nature Genetics. 52, 254–263, 2020; Nature Reviews Molecular Cell Biology, Pang et al., in press 2022). In addition, we have also developed another unique screening system using CRISPR/Cas9 to study the function of other non-coding regulatory regions.

Profile of the candidate

The successful candidate should be fluent in English, self-motivated, collaborative, and with a strong background in molecular biology, cell biology, and genetics (e.g. cell culture, cloning, CRISPR-Cas9 editing).

Application

Interested candidates should submit their curriculum vitae and contact information of three references, together with any questions via e-mail to: b.pang@lumc.nl 

Dr Baoxu Pang
Principal investigator
Department of Cell and Chemical Biology
https://ccb.lumc.nl/about-the-pang-lab-177

Project description

Salmonella and other bacterial pathogens introduce factors in host cells to control infection and intracellular survival. We showed earlier (Kuijl et al. Nature 2007) that inhibition of the host kinase AKT1 was sufficient to eliminate intracellular bacteria, in fact defining the first antibiotic active through manipulation of host rather than pathogen proteins. Salmonella and other bacteria appeared to activate AKT1 during their infection cycle. Since AKT is also often activated in cancer, we wondered whether bacteria, through this mechanism, could contribute to cancer induction. Indeed, Salmonella infection was able to transform cells into cancer cells, when the cells already harbor one or two defined pretransforming mutations. This explains the link between chronic S.Typhi infections and the increased risk of gallbladder carcinoma, as observed in India. In fact, our lab results were confirmed in gallbladder carcinoma samples from India. These experiments (Scanu et al., Cell Host Microb 2015) also included a mouse experiment that showed that infection of APC+/- mice with another salmonella serovar, S.typhimurium, induced colon cancer. Since thise serovar is known from food poisoning, we wondered whether such food poisoning would increase the risk of colon cancer and started a nation-wide epidemiological study. We then showed that serious infections with –again- another salmonella serovar, S.enteritidis increases the risk of colon cancer almost 3-fold. We are studying these and other bacterial infections for their potential role in cancer induction by combining epidemiology, infection model systems and cell biology. This may yield clinical guidelines for patients with such infections to be enrolled in nation-wide cancer screening programs. This work is now a collaborative effort between the Dutch Health Institute (RIVM) and our lab, which providing unique epidemiological and clinical isolates for studying this connection. It is also supported by a shared grant from the Dutch Cancer Society KWF.

About the group

The research group is led by Prof. Dr. Jacques Neefjes. Prof. Dr. Neefjes is the head of the Department of Cell and Chemical Biology, LUMC, and is an internationally renowned expert who has made outstanding contributions to the field of cell biology of antigen presentation by MHC class I and MHC class II molecules, and his discoveries are broadly applied in modern immunotherapy approaches internationally. Prof. Neefjes is a member and the domain chairperson of the Dutch Royal Society of Sciences and Arts, EMBO, Norwegian Academy of Science and Letters, European Academy of Cancer Sciences, Academia Europaea. He received NWO Spinoza Prize,

van Loghem Career Award from the Dutch Immunology Society, Josephine Nefkens Award for cancer research and Ceppellini Award from the European Federation of Im-munogeneticists. Prof. Neefjes has obtained various Dutch and European grants, including European Research Council Advanced Grants. He has published 286 articles with > 30,000 cita-tions, including papers in Nature, Cell, Cancer Cell, Immunity and others, with an H-index of 92.

The group applies cell biological and chemical tools for fundamental research, as well as translational research on cancer in three broad themes:

  1. The cell biology of the endosomal system and MHC class II antigen presentation;
  2. The role of bacterial infections in cancer induction, and
  3. The cell biology of anti-cancer drugs, especially the anthracycline family.

Lab webpage: https://ccb.lumc.nl/about-the-neefjes-lab-172

Your profile

The successful candidate should be fluent in English, self-motivated, collaborative, and with a strong background in molecular biology, cell biology, and genetics (e.g. cell culture, cloning, CRISPR-Cas9 editing).

Application

Interested candidates should submit their curriculum vitae and contact information of three references, together with any questions via e-mail to: J.J.C.Neefjes@lumc.nl

Prof Jacques Neefjes
Department head Cell and Chemical Biology

<< The role of bacterial infections in cancer induction

Unraveling the epigenomic mechanisms mediating the impact of non-coding variants on human disease >>

Project description

Over 90% of genetic variants that are known to influence the risk of human disease occur in non-coding regions of the genome. Hence, the mechanisms by which these variants influence disease risk involve the regulation of the genome. Indeed, many disease variants are known to impact on the epigenome as is evident from genetic studies of DNA methylation. However, specific mechanisms remain to be elucidated for the vast majority of variants. In this project you will develop a systematic approach that combines bioinformatics and genome engineering to uncover the epigenomic mechanisms that mediate the impact of disease variants. Specifically, you will perform bioinformatics analyses to develop hypotheses for the mechanisms of specific variants by mining existing databases on genome-wide association studies and regulatory quantitative trait loci (DNA methylation, transcription factor binding etc.), and performing analyses in large scale population resources. Next, you will test these hypotheses by designing and executing experiments that involve editing of the genome and epigenome in cell lines of different origin.

About the groups

You will work between the research groups lead by prof. dr. Bas Heijmans at the department of Biomedical Data Sciences and dr. Lucia Daxinger at the department of Genetics. Prof. Heijmans is an internationally recognized expert in population epigenomics who adopts innovative analyses of multiple omics data in human cohorts to identify molecular profiles and biological processes involved complex diseases and aging. Dr. Daxinger is well-known for her work on the discovery of epigenetic regulators and unraveling the molecular basis of epigenetic diseases using state-of-the-art experimental approaches. Both research groups provide a stimulating research environment with high-level facilities and an excellent international position which form an ideal starting-point for a PhD student. You will have to opportunity to present your work during (international) conferences and follow diverse courses to develop (transferable) skills.

Profile of the candidate

You hold a MSc degree in biomedical sciences, life sciences, or a related discipline and have a proven interest in epigenomic mechanisms in disease. You have hands-on experience with a range of molecular biology techniques, desirably including the application of CRISPR, and cell culture. In addition, you have practical knowledge of analyzing omics data using the software R. You enjoy working in a multidisciplinary team, and possess excellent writing and presenting skills. Proficiency in English is required (IELTS 7 or above). Please, note that applications without a personal statement of interest will not be considered.

Application

For more information about this position, please contact Dr Lucia Daxinger, email: l.clemens-daxinger@lumc.nl, or Prof Bas Heijmans, email: bas.heijmans@lumc.nl.

Project description

LncRNAs are transcripts that are not translated into proteins. They can regulate a multitude of cellular functions including transcription, translation and RNA splicing. Using transcriptional profiling of TGF-β stimulated cancer cells and a genetic screen, we identified lncRNAs that are potently induced by TGF-β and that regulate TGF-b/SMAD signaling. In this project you will elucidate their mechanism of action and determine their possible role in cancer progression using CRISPR Cas9, biochemical, cell biological and bioinformatic techniques, in vitro and in vivo models, and analysis of misexpression in clinical samples. A few selected interested lncRNA will be explored for therapeutic targeting.

About the group

    The mission of our Department of Cell and Chemical Biology is to unravel the molecular details of the working of cells in their normal function and the perturbed functioning in diseased cells. We help translate our knowledge and technologies to clinical practice. Studies in our research group are aimed at elucidating how the cytokine TGF-β controls the phenotypic plasticity of cancer cells, activates cancer associated fibroblasts (CAFs) and suppresses immune responses. We are an well-funded group with access to various advanced life cell imaging and microscopy equipment, omics technologies and animal models.

    Your profile

    Enthusiastic and motivated molecular cell biologist (master student or PhD student) with talent for experimental cancer research and also enjoys to work as part of a team.

    Application

    Interested candidates should submit their curriculum vitae and motivation letter to Prof Peter ten Dijke (Member of EMBO and Netherlands Academy of Science), Chemical Signaling Laboratory, Dept. Cell and Chemical Biology. Email: p.ten_dijke@lumc.nl

    https://ccb.lumc.nl/about-the-ten-dijke-lab-34

    << Long non coding RNAs (lncRNAs) in cancer progression; mechanism of action and therapeutic targeting

    Understanding the role of autoreactive B cells and autoantibodies in autoimmune rheumatic diseases (ARD) >>

    Project description

    The department of Rheumatology is looking for a CSC PhD candidate interested in the role and function of autoreactive B cells and autoantibodies in autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), anca-associated vasculitis (AAV) and systemic sclerosis (SSc). The department of Rheumatology is recognized as a Center of Excellence by EULAR.

    Despite considerable improvements in the treatment of ARDs, they remain chronic diseases that cause significant loss in the patients’ quality of life with increased morbidity and mortality. Current medication mostly treat the consequences of disease by inhibiting inflammation but do not achieve cure. In part, this is due to a lack of knowledge of the molecular pathways underlying autoimmunity.

    You role:

    • You will develop and apply flow cytometry and BCR sequencing techniques to study autoreactive B cells in the context of disease development and progression in ARDs
    • You will characterize levels and isotypes of disease-specific autoantibodies and investigate their functional properties in relation to disease development and progression.
    • You will be working on translational projects in a multidisciplinary team of basic scientists, technicians and clinicians.

    About the groups

    The Department of Rheumatology aims to reach prevention and/or cure of ARDs by mapping (early) disease pathogenesis and to implement novel therapeutic interventions. In our approach, we focus on autoreactive B cells since these cells are at the center stage of initiating and maintaining disease in RA, SLE, AAV and SSc. Therefore, mechanistic insight into the initiation of these autoimmune responses is of great importance to design preventive strategies and/or interventions aiming to restore immune homeostasis against autoantigens. Available PhD projects will therefore focus on the mechanisms underlying the emergence and activation of autoreactive B cell responses and their secreted products, autoantibodies. Together with the PhD candidate we will create a detailed innovative and cutting edge research project to apply to the CSC.

    Your profile

    • MSc degree in biomedical sciences, biopharmaceutical sciences or Life Science & Technology or similar subjects.
    • You have strong interest and practical experience with cellular immunology and/or autoimmunity and translational science
    • Experience in cell culture, ELISA and (spectral) flow cytometry will be preferred.
    • You have excellent communication skills and have fluent English language skills, both oral and written.

    Application

    Please send your CV along with a motivation letter to Dr Cynthia Fehres (c.m.fehres@lumc.nl). If you have any further questions, please contact Dr Fehres.

    Project description

    Obesity induces adipose tissue inflammation, which contributes to insulin resistance and progression towards type 2 diabetes. The crosstalk between adipocytes and macrophages within fat tissue is central in this process but remains incompletely understood. We will investigate the unexplored role of complex carbohydrate structures, called glycans, located on adipocyte cell surface and/or secretory proteins in glycan-receptor mediated macrophage pro-inflammatory activation. For this purpose, state-of-the-art approaches combining (bio)chemical and genetic tools will be used to modify adipocyte glycan structures, and their impact on macrophage functions and adipocyte insulin sensitivity will be assessed in vitro using both co-culture model and organoids.

    As a PhD student, you will be the main driver of this project under the direct supervision the principal investigator. You will perform the experiments with the help of other lab members, analyze the data in a critical way and assemble the results in a suitable format for scientific communications (abstract, poster, presentation, journal article). For this purpose, you will be extensively train for acquiring all the technical and cognitive skills necessary for achieving the abovementioned tasks/goals. Altogether, we offer a multifaceted scientific project with excellent technical facilities, a place in a dynamic and committed team, as well as strong local and international scientific collaborations.

    About the group

      The main research of Guigas’ group at the Leiden University Medical Center (LUMC) is focused on the emerging field of immunometabolism, aiming to identify new druggable molecules and/or molecular targets involved in the immune regulation of metabolic homeostasis in the context of obesity and type 2 diabetes.

      Recent publications of the group on related topic:

      Embgenbroich M, et al. Soluble mannose receptor induces pro-inflammatory macrophage activation and metaflammation. Proceedings of the National Academy of Sciences of the United States of America, 118(31):e2103304118, 2021.

      Van der Zande JP et al. The helminth glycoprotein omega-1 improves metabolic homeostasis in obese mice through type-2 immunity-independent inhibition of food intake. FASEB Journal, 35(2):e21331, 2021.

      Your profile

      • Good English communication skills
      • Significant interest in immunology and/or metabolism
      • Motivated and ambitious, with a team player spirit
      • Previous laboratory experience(s) (flow cytometry and/or mice studies would be a plus)

      Application

      You are welcome to apply at the latest on December 15th, 2022. Please send your CV (in English) along with a motivation letter to Dr Bruno Guigas (b.g.a.guigas@lumc.nl). If you have any further questions, please contact Dr Bruno Guigas (b.g.a.guigas@lumc.nl) or global@lumc.nl.

      << Unravelling the role of adipocyte glycans in the crosstalk with macrophages during obesity

      Multi omics network analysis for Huntington’s disease >>

      Project description

      The Biosemantics group in collaboration with the NeuroD group at the Human Genetics department and the Huntington Research group at the Neurology department from the LUMC is looking for an enthusiastic CSC PhD candidate interested in multi omics analysis and network analysis in biomedical data. You will work in the Biosemantics group of the Human Genetics department within the LUMC and collaborate closely with the NeuroD and Neurology group.  

      Huntington’s disease (HD) is a rare neurodegenerative disorder with a prevalence of about 1 in 100.000 individuals in the western population. The cause of HD, the mutated HTT protein, has been known since 1993. However, the mechanisms that lead to disease pathogenesis are not fully understood. Despite years of research and the plethora of experiments that have resulted in large quantities of data, we are still lacking a complete picture of the disease. A meta analysis of all those datasets could help to identify disease signatures and biomarkers that could be targeted for altering the disease course.

      A comprehensive understanding of disease mechanisms requires the analysis and interpretation of molecular interactions at multiple levels. Previous studies have highlighted the importance of integrating multiple omics datasets to obtain a clearer picture of the system under study. Rare diseases such as HD can benefit from the study of multi-omics analysis because we are able to investigate the interplay between different biomolecules on different molecular levels, in contrast to studying singular omics that can offer a single layer of information.

      In this project we will perform a meta-analysis of datasets that are publicly available and leverage the information that has been published previously by HD studies. Extensive research into HD has resulted in various experiments that produced different types of omics data (transcriptomics , proteomics, metabolomics, and genomics) in different tissues (brain, blood, muscle) and different model organisms (mouse, pig, sheep, fly). The meta-analysis of omics data will result in extending our knowledge on the pathological mechanisms that are implicated in HD on a systems level. We will achieve this by applying network analysis on a selection of those multi-omic data sets. The selection will be on the basis of the quality of the study, data availability, sample size and will be performed in close collaboration with HD experts. We will investigate network analysis methods, by an extensive literature study on methods for creating multiplex networks (such as Mogamun) by integrating different types of omics data that come from different experiments. 

      We will perform active subnetwork search, to identify the most “active” subnetworks in this large multi omic network. Active subnetworks are assumed to be highly associated with HD and being key drivers of change in the multi-layer system. To our knowledge a comprehensive multi-omic analysis in the field of HD and in general in the field of rare diseases is lacking.

      • You will perform a large-scale multi-omic data integration, to leverage published information to identify disease signatures and biomarkers in HD patients on a multi-omics scale.
      • You will improve the understanding of the natural history of this disease, the mechanisms that are implicated in disease pathogenesis and aid the development of therapeutics to be applied to the right HD subgroup.
      • You will be part of a multidisciplinary team consisting of clinicians, biologists and computer scientists, and will have the opportunity to work with various HD experts, also internationally.

      Your profile

      • You hold a master’s degree in computer science, or bioinformatics or an equivalent combination of biomedical science and computer science.
      • You have a good understanding of multi omics analysis and network analysis methods.
      • You have a strong interest in translational research on rare and genetic diseases.
      • You are able to collaborate in a multidisciplinary and international team.
      • You have a good command of the English language.
      • You have excellent communication skills and affinity with conveying technical information to collaborators with a life science or health care background.

      Application

      You are welcome to apply at the latest 1 December 2022. Please send your CV (in English) along with a motivation letter to Dr Eleni Mina (e.mina@lumc.nl) . If you have any further questions, please contact Dr Eleni Mina (e.mina@lumc.nl).

      Project description

      The Biosemantics group in collaboration with the NeuroD group at the Human Genetics department and the Huntington Research group at the Neurology department from the LUMC is looking for an enthusiastic CSC PhD candidate interested in applying machine learning in biomedical data. You will work in the Biosemantics group of the Human Genetics department within the LUMC and collaborate closely with the NeuroD and Neurology group.  

      You will work on the Enroll-HD data, a worldwide large longitudinal observational study for Huntington’s disease (HD), a rare neurodegenerative disorder. Enroll-HD is an integrated clinical research platform operating in the field of neurology that encompasses more than 20.000 participants in different clinical sites worldwide, including baseline and follow up visits for each patient. Enroll-HD is collecting information regarding the clinical aspects of HD, covering motor, cognitive, and behavioural domains as well as information regarding the medication and nutritional supplements that patients are receiving.

      In addition, we will integrate Enroll-HD data with data from other biomarker and imaging studies, e.g. HDClarity and TRACK-HD, to integrate the clinical data with biosamples (e.g. CSF, serum) and imaging samples (3T MRI, fMRI, DTI) from the same participants.

      The goal of this project is to investigate and better characterize disease progression in HD, extend our knowledge as to the factors that contribute to disease progression, and make personalized predictions regarding the disease status at a particular time point in the future. Our predictions will assist in making decisions that pertain to medical interventions at the right time point and to the quality of everyday life of HD patients based on these predictions (e.g. ability to work or drive a car until a certain age).

      This is a project that is highly translational in nature. The applicability of the data analysis results will be used to develop a more accurate prognosis and prediction of onset  for the HD patients in our outpatient clinic while assisting in the discovery and development of new therapeutics for HD.

      • You will work with longitudinal clinical data and their integration with -omics and imaging data to better understand HD and study disease progression by applying machine learning methods. You will compare and validate different machine learning techniques with the conservative way of analysing longitudinal clinical data, thereby pioneering this field of neurodegenerative diseases.
      • You will contribute to the development of a more accurate prognosis and prediction of onset for the HD patients in our outpatient clinic at the LUMC.
      • You will contribute to the development of new therapeutics as well as to the selection of the right participants for clinical trials
      • You will be part of a multidisciplinary team consisting of clinicians, biologists and computer scientists, and will have the opportunity to work with various HD experts, also internationally.

      Your profile

      • You hold a master’s degree in computer science, or bioinformatics or an equivalent combination of biomedical science and computer science.
      • You have a good understanding of machine learning and you have a strong interest in applying machine learning algorithms on biomedical data.
      • You have a strong interest in translational research on rare and genetic diseases.
      • You are able to collaborate in a multidisciplinary and international team.
      • You have a good command of the English language.
      • You have excellent communication skills and affinity with conveying technical information to collaborators with a life science or health care background.

      Application

      You are welcome to apply at the latest 1 December 2022. Please send your CV (in English) along with a motivation letter to Dr Eleni Mina (e.mina@lumc.nl) . If you have any further questions, please contact Dr Eleni Mina (e.mina@lumc.nl).

      << Machine learning for Huntington’s disease

      Complement protein C1q as a regulator of the T cell response >>

      Project description

      While the complement system has long been appreciated for its role in innate immunity, it has recently been discovered that specific complement proteins regulate adaptive immune responses. This proposal focusses on C1q, the recognition molecule in the classical pathway of complement activation. In both human and mouse, genetic deficiency of C1q leads to the autoimmune disease Systemic Lupus Erythematosus (SLE). Initially, it was suggested that SLE was caused by defective clearance of apoptotic cells in the absence of C1q. However, current findings indicate that C1q suppresses adaptive immune responses, independent of complement activation, by binding to cellular receptors. Overexpression of C1q in tumors was reported to dampen effector T cell responses. Moreover, in human and in mouse models of emphysema, C1q was reported to enhance Treg function and limit Th17 differentiation. In the mouse, we found that C1q is essential for antigen cross presentation by conventional dendritic cells (cDCs) and others reported that C1q regulates the metabolic state of  CD8 T cells. Our own recent work revealed that in patients with tuberculosis (TB), an infectious disease caused by an intracellular pathogen, C1q levels are greatly increased. In light of the aforementioned results, we postulate that  increased levels of C1q may dampen T cell responses against the infection.

      We hypothesize that C1q is a fluid-phase regulator of CD4 and CD8 T cell responses.

      The aim of the project is to delineate the role of C1q in modulating the T cell response, to reveal the underlying mechanisms and to therapeutically modulate these C1q functions in mouse models of autoimmunity and cancer.

      • You will perform human and mouse profiling studies using CyTOF and flow cytometry to compare the peripheral blood cell composition of C1q deficient versus controls
      • You will study the biochemical interactions of C1q and complement proteins in their binding to and internalization in immune cells.
      • Mouse experimental studies will be employed to study the role of C1q in T cell biology in models of T cell driven autoimmunity and T cell mediated anti-tumor therapy.
      • You will conduct detailed human cellular experiments to study the role of C1q and C1q Receptors in subsets of T cells and dendritic cells.

      Your profile

      • You have a background in biology, (bio)chemistry or (bio)medicine and a special interest in complement and immune regulation
      • You are interested in working in a multidisciplinary research team consisting of biologists and medical doctors see: About the Leendert Trouw Group – Immunology (lumc.nl)
      • You are highly ambitious, motivated and goal-oriented.
      • You are systematic, analytical and accurate in your work.
      • You are a team player with excellent organization skills.
      • To achieve your goals, you combine creativity with dedication and perseverance.

      Application

      You are welcome to apply at the latest 1st December 2022. Please send your CV (in English) along with a motivation letter to Leendert Trouw, L.A.Trouw@LUMC.nl

      Project description

      Background: Tumor-antigen loaded dendritic cells (DC) have been used as vaccines in hundreds of cancer immunotherapy trials, but not given significant treatment benefits. In most trials, monocytederived (mo)DC were used, because they are easy to obtain. It has been proposed that the unsatisfactory performance of moDC in cancer immunotherapy is due to their suboptimal intrinsic capacity to induce T-cell responses. From extensive studies in mouse, it is clear that classical (c) type 1 DC (cDC1) and cDC2 lineages, that are discerned into migratory and lymph node-resident subpopulations play a key role in initiating T-cell response. Our group has recently demonstrated that among human progenitor-derived DC, the cDC1 has superior ability to relay CD4+ T-cell help for crosspresenting cell-associate tumor antigen and cross-priming anti-tumor cytotoxic T lymphocyte (CTL) response (Nat. Communications under revision).

      Therefore, therapeutic vaccination with cDC1 is expected to yield benefit in new clinical trials. The cDC1 subset is very scarce, constituting less than 0.01% of peripheral blood mononuclear cells. For this reason, the development of protocols to generate cDC1 in good yield from progenitors in vitro would greatly benefit cancer immunotherapy.

      Aim: We aim to develop optimal protocols to generate the ex vivo equivalents of human cDC1 cells in large scale in vitro from blood-derived progenitor cells. We will validate the identity of the cDC1 generated by transcriptomics and by functional analyses, using ex vivo cDC1 as a reference. We will assess their response to specific innate stimuli and/or CD40 stimulation, as well as their ability to crosspresent tumor cell-associated antigen and to prime an optimal CTL response, in comparison with moDC.

      Approach: We can efficiently generate primary human DC in vitro from a specific hematopoietic progenitor that we have identified. We typically generate over 100.000 DC from 500 blood-derived progenitors. Preliminary data indicated that the in vitro generated DC are able to relay CD4+ T-cell help for priming tumor antigen-specific CTL response, and they resemble blood derived cDC subsets rather than moDCs according to bulk transcriptomics. However, the yield of cDC1-like cells is still suboptimal.

      In this project, we aim to optimize cDC1 yield making use of our specific culture conditions with a mesenchymal stem cell (MSC) feeder layer and specific cytokines in combination with a Notch ligand (DL1) that reportedly stimulates cDC1 differentiation. We will set up a 3D culture system to enable largescale cDC1 production. We will perform single cell mRNA-Seq to compare in vitro generated DCs with ex vivo cDC1. We will study response to activation stimuli, cross-presentation and priming capacity of the in vitro generated DCs as compared to the ex vivo DC subsets. For this purpose, we will use a unique in vitro DC-T cell coculture system that we have developed.

      Expected outcome: This work is expected to deliver a protocol to generate in large yield from bloodderived progenitors human cDC1s that match the ex vivo counterpart and to demonstrate whether in vitro generated cDC1-like cells are the optimal DC type to prime tumor-specific CTL responses. This project supports the further interest in developing human cDC1-based vaccines for antitumor therapy.

      In brief, the potential candidate PhD student will aim to develop protocols for efficient in vitro generation of human cDC1-like cells and to examinate the function ability of in vitro generated cDC1-like cells using a newly developed reliable in vitro human DC-T co-culture platform. With the aid of intensive multicolor (up to 35-40 antibodies) flow cytometry (Aurora) and cutting-edge CITE single-cell RNA-Seq technology, candidate PhD student will first identify and isolate in vitro generated cDC1-like cells and then study the function (both at cellular and transcriptional levels) of these cDC1-like cells that geneated under different conditions.

      About the group

      You will work in the research team led by Dr. Yanling Xiao (MD & PhD). The department of Immunology provides stimulating environment wherein many researches are performed in international collaborations.

      Your profile

      • Master’s degree in biomedical science, oncology or related subjects in clinical medicine.
      • Knowledge of DC and T-cell biology with interests in tumor immunology and cancer immunotherapy. Experience in cell culture and flow cytometry will be preferred. Interested in meta-analysis. Knowledge on programming languages (R or Python) and experience in handling OMICS will be preferred.
      • Must demonstrate fluent English language skills both oral and written (TOEFL, or equivalent, may be required).

      Application

      You are welcome to apply at the latest 1 December 2022. Please send your CV (in English) along with a motivation letter to Dr. Xiao (y.xiao@lumc.nl). 

      << Creating protocols for efficient in vitro generation of human classical type 1
      dendritic cells and examination of their ability to prime anti-tumor immunity

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