Doktabörse

Computational single cell analytics for tailored cell therapy

Angebot: Doktorarbeit
Beginn: möglich ab 24.06.2021
Institut: Abteilung für Klinische Pharmakologie
Arbeitsgruppe: Immunpharmakologie

Beschreibung

CAR (Chimeric Antigen Receptor) T cells are genetically engineered immune cells that express an artificial T cell receptor, giving them the ability to bind surface proteins in a highly specific manner. By designing T cells to target tumor antigens, CAR T cell therapies have emerged as a powerful novel approach to fight hematologic cancers (Miliotou and Papadopoulou, 2018). However, developing immunotherapeutically efficient CAR T cells requires the identification of tumor-specific surface antigens, a challenging task in hematological malignancies such as AML (Mardiana and Gill, 2020). Single cell RNA sequencing (scRNAseq) offers the unique potential to scrutinize surface protein expression in an unprecedented resolution: Massive single cell expression atlases provide detailed information about the transcriptomic anatomy of healthy and malignant cells that cannot be overserved from bulk sequencing approaches (see figure and Wagner et al., 2016).
Objective
By combining our expertise in biomedical data analysis and immunopharmacology, we want to identify novel candidates for CAR T cell therapy. Using state of the art machine learning approaches, we find new targetable surface protein coding genes that are differentially expressed in malignant cells. Single cell expression atlases will then be explored to validate these candidates in silico by investigating possible off-target effects and comparing them to previously used CARs.
Milestones
● Acquire background knowledge of scRNAseq and CAR T cell immunotherapy
● Analyze publicly available scRNAseq data using the computational resources at the Helmholtz Center Munich
● Compile possible targets and scRNAseq expression data for particular cancers
● Validate and compare target expression among candidates
● Design experimental validation
Requirements
● Strong Interest in biomedical data analysis
● Experience with python programming
● Computationally inclined and interested in solving
interdisciplinary problems
References
Mardiana, S., and Gill, S. (2020). CAR T Cells for Acute Myeloid Leukemia: State of the Art and Future Directions. Front. Oncol. 10, 697.
Miliotou, A.N., and Papadopoulou, L.C. (2018). CAR T-cell Therapy: A New Era in Cancer Immunotherapy. Curr. Pharm. Biotechnol. 19, 5–18.
Wagner, A., Regev, A., and Yosef, N. (2016). Revealing the vectors of cellular identity with single-cell genomics. Nat. Biotechnol. 34, 1145–1160.

Für den Zeitraum des Projektes stehen regelmäßige Event-Teilnahmen an.
Doctoral candidates will be integrated into the i-Target: "Immunotargeting of Cancer" training network (lead: Prof. Dr. med. Sebastian Kobold). Regular meetings Monday afternoon (5 p.m.) as well as (bi)annual workshops.
Regular (lab)meetings with supervisiors and principial investigators (Dr. Carsten Marr, Prof. Sebastian Kobold)

Neben der Doktormutter/dem Doktorvater ist eine separate Person für die Betreuung zuständig.
Close bioinformatic supervision guaranteed by experienced PhD Student (Moritz Thomas, Helmholtz Centre of Computational Biology) and immunological, oncological supervision by resident and postdoctoral fellow (Adrian Gottschlich, Division of Clinical Pharmacology).

Über das Modul 6 hinaus sind weitere Freisemester nötig.
one additional semester.
Total scope Modul 6 + at least one extra semester.

Für die Arbeit an diesem Projekt stehen ggf. Fördermöglichkeiten zur Verfügung.
MMRS, i-Target funding or alternative ressources are available for suitable candidates.