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CARES courses

One week courses (online) - preliminary description

Epigenetics in cancer research, organized by Helena Carén, UGOT

The course will introduce the concepts of epigenetics (DNA methylation, chromatin structure and histone modifications and non-coding RNA), how it is involved in diseases, can be used in clinical diagnostics and how epigenetic analyses are planned and performed.

 Aims

The course will cover the following topics:
(1) The current state of knowledge on epigenetics in health and disease, specifically in cancer
(2) The potential of using epigenetics in cancer diagnostics
(3) Epigenetic therapy as an emerging strategy for treating cancer and
(4) How to design and carry out epigenetic experiments

The course will consist of lectures, a lab exercise and a discussion session where students have the opportunity to discuss their own projects, focusing on epigenetic questions.

Learning outcomes: After completion of the course, the student should be able to:

  • Demonstrate an advanced knowledge of the concept of epigenetics and its role in health and disease
  • Discuss experimental strategies and tools for epigenetic analyses
  • Demonstrate ability to be able to design, carry out and interpret an epigenetic screen
  • Critically analyse, explain, discuss and present scientific topics and research issues in epigenetic

Liquid biopsy, organized by Anders Ståhlberg, UGOT

The development of ultrasensitive technologies enable the detection and quantification few analytes in complex matrices, such as liquid biopsy. In cancer management and research, liquid biopsy analysis can be used in screening, diagnostics, monitoring treatment efficacy as wells as early detection of minimal residual disease and relapse. This course outline the potentials and limitations of liquid biopsy analysis in cancer management. Practical and theoretical aspects of sampling, preanalytical steps, biomarker analysis, data analysis and clinical interpretation will be included within the application areas of cancer. We have a specific focus on DNA and RNA analysis, as well as on clinical utility. The course will be given in a digital format, including lectures, theoretical exercises and group discussions


Translational cancer research, organized by UGOT

The course will convey an enhanced knowledge about translational cancer research, as well as empower the student to make an informed decision of suitable methods for his/her own research situation. 

Aims

The course will provide an introduction to bench-to-bedside research. A survey of descriptions of different examples of projects with a strong translational edge will be provided. The role of different competences required to finalize a translational project including medical doctors, pre-clinical investigators and industry will be exemplified. Different work flows such as biobanking, sequencing data, biomarker discovery, animal modeling, clinical chemistry and immunology, drug and diagnostics development and early clinical trials will be described by national and international experts. In parallel, the students will perform a literature review of translational research of particular interest, with the aim of designing a new project.

Learning outcomes: After completion of the course, the student should be able to: compare and contrast the position of translational research in relation to basic and clinical research by

  • Reflect on some of the hindrances (the valley of death) - structural or individual – to overcome to become successful in translational research
  • Relate the knowledge about translational research to his/her own research

Medical Bioinformatic, organized by Gottfrid Sjödahl and Karin Engström, LU

Time: Spring 2022 - Preliminary five days during week 11-12 2022

Objectives: The aim of the course is to provide participants with a basic understanding of bioinformatics concepts and methods.

Content: The course will provide awareness, from theoretical as well as practical perspectives, of bioinformatics resources and tools available in the different phases of a study, from the planning phase to the analysis, interpretation and presentation of data. Through the presentation of key concepts/terms and examples of bioinformatics work processes, the course gives a broad introduction to bioinformatics. It highlights resources that can facilitate self-directed learning in bioinformatics and provides information about the local, national and international support available with regard to bioinformatics.

Learning outcomes: On completion of the course, the participants shall be able to:

  • explain key concepts and terms in bioinformatics
  • use bioinformatics tools to analyse, organise and interpret large-scale data
  • identify resources for further learning in bioinformatics

Design: The course consists of five whole days that are compulsory and based on the active participation of doctoral students. The teaching will be a mixture of different forms, including lectures, group exercises and individual practical exercises. Independent study of selected texts is also included. Participants are expected to have access to a laptop. Furthermore, the course includes one compulsory assignment, in which the doctoral student is to reflect on a research situation (from their own research, if possible) where bioinformatic analyses can be used, discuss it in a group discussion and finally propose in writing how bioinformatics can be used to enrich the previously described research situation.

Assessment: For a Pass on the course, participants must have actively participated in all course components and submitted the compulsory assignment.


Clinical trial in cancer (online)

The course will run during the whole 18 month period and cover the following aspects in clinical trial in cancer:

  • Good Clinical Practice (ICH GCP)
  • Clinical trial design
  • Ethics
  • National regulation in clinical trials
  • Strategies and tools for recruitment
  • Clinical trial protocol
  • Administration of clinical trials
  • Statistics and power in study design
  • Data analysis and management
  • Result and evaluation
  • Register-based randomised clinical trials
  • Health economy and clinical research

The course consists of approximately 17 modules with online lectures and assignments.