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CARES Overview of Course

1. 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


2. Cancer epidemiology organized by Helena Jernström, LU

Aims

The overall aim of the course is that you after the course should have gained knowledge of epidemiological methodology in order to suggest appropriate methods for planning and evaluating common types of epidemiological studies. The course should make you more knowledgeable about, and make you able to critically assess, statistical and epidemiological methods used, including gene-environment interactions. The students should have passed the compulsory statistics course at the respective medical faculty or equivalent prior to taking this course.

Learning outcomes: The students should be able to:

  • Use epidemiological concepts, to critically evaluate different types of research designs commonly used in epidemiological studies e.g. cohort, case-control, and ecological studies
  • Critically analyze epidemiological scientific papers
  • Identify details of data collection that are related to the reliability, validity and bias of the results of your research and their ethical implications for the study participants and the scientific community
  • Understand genetic/molecular epidemiology and gene environment interaction


3. The human genome and high-content methods, organized by Sofia Gruvberger and Lao Saal, LU

The course will cover the human genome project, genetic markers, tumor genome evolution, and the myriad of high-throughput, high-content methods employed to study the tumor genome, including screening-, microarray-, and next-generation sequencing methods.

Aims

The course will provide an introduction to public databases, web-portals, and tools for interrogating the human genome, and describe the generation of high-content datasets. The application of these methods in cancer diagnosis, drug design and testing, and studies of interaction, gene regulation, epigenetics, genomics, and transcriptomics will be reviewed. Furthermore, third- and fourth-generation methods on the horizon will be described.

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

  • Explain fundamental principles with regards to mapping of the human genome
  • Analyze and handle information and raw data from the most common genome databases
  • Compare and contrast different methods for analysis of DNA copy number, geneexpression, epigenetic marks, and sequence variation
  • Relate the knowledge about the human genome and high-content methods to his/her own


4. High-throughput sequencing: Applications in cancer research, organized by Helena Persson and Henrik Liljebjörn, LU

This one-week, full time course is aimed at PhD students in oncology with an interest in high throughput sequencing technology and its applications. The course consists of lectures, computer exercises and discussions designed to provide the students with a basic understanding of what high-throughput sequencing is, what its applications are in basic and clinical cancer research, and how such sequencing data is analysed and interpreted.

Aims

This course is designed to provide the students with a basic understanding of what high throughput sequencing is, what its applications are in basic and clinical cancer research, and how such sequencing data is analysed and interpreted. The course will consist of lectures on sequencing technologies, DNA and RNA sequencing, as well as key concepts in data analysis such as quality control, commonly used file formats, data standards, and sequence alignment strategies. These concepts will also be dealt with in computer exercises on basic command line and batch system usage, sequence alignments etc. Particular emphasis will be given to evaluation and critical assessment of findings from sequence data.

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

  • Explain basic principles behind high-throughput sequencing (HTS) technologies including the weaknesses and strengths of different approaches
  • Explain how HTS data can be used to study genetic variation, quantify gene expression, characterize gene and transcript structure, analyse gene regulation and assemble whole genomes
  • Explain the steps involved in common HTS data analyses such as sequence alignment, sequence variant detection, annotation and interpretation of functional variants, and data visualization
  • Explain the key concepts of alignment and de novo assembly


5. Single-cell tumor biology and tumor heterogeneity organized by Anders Ståhlberg, UGOT

This course targets scientists entering the field of single cell analysis and teach different preparation and quantification methods at the single-cell level with a specific focus on tumor biology.

Aims

This course will provide the students with solid understanding of single-cell biology.The course will also include practical exercises about single-cell collection, sample preparation and data analysis. The course will focus on latest state-of-art technologies in gene expression profiling, but single-cell DNA, DNA methylation and protein analysis will be covered by lectures. Furthermore, the course will also cover practical exercises about single cell data analysis that partly differ from traditional population analysis. Finally, the course will include a couple of applications in tumor biology that will illustrate the pros and cons of applying single-cell analysis.

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

  • Perform single-cell analysis on tumor material
  • Analyze and interpret single-cell data
  • Reflect and discuss the importance of tumor subpopulations and tumor heterogeneity


6. Mouse models and imaging modalities in cancer research, organized by Chris Madsen and Kristian Pietras, LU

The course will convey an enhanced knowledge about the generation and use of mouse models in cancer research, as well as empower the student to make an informed decision of suitable models for his/her own research situation.

Aims

The course will provide an introduction to the generation and use of mouse models of human cancer. A survey of the state-of-the-art technology in the field, such as conditionality, inducibility and imaging, will be provided by national and international experts. In addition, the use of mouse models in various applications related to cancer research, such as studies of metastasis or experimental therapy, will be reviewed. In parallel, the students will perform a literature review of mouse models of particular interest, with the aim of designing new and improved mouse models of cancer.

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

  • Compare and contrast different categories of mouse models of cancer and analyze the pros and cons of models within each category
  • Reflect on state-of-the-art technology in the generation and use of novel mouse models of cancer
  • Compare and contrast different types of in vivo imaging modalities
  • Relate the knowledge about mouse models of cancer to his/her own research


7. Translational cancer research, organized by Jonas Nilsson, 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


8. Proteomics in cancer research, organized by Jörgen Berström at Proteomics Core Facility UGOT

The analysis of the proteome can provide a better understanding of the underlying molecular mechanisms of disease states and the progression of a disease. Global quantitative proteomics are used in the study of differential expressed proteins and enable the discovery of potential cancer biomarkers for diagnosis and monitoring as well as targets for treatment. Also identification of protein binding partners and the analysis of protein modifications, such as phosphorylation that play a significant role in the mechanisms of cell regulation in normal and cancer cells, are frequently performed in cancer project. The aim of the course is to present proteomic strategies that can be employed in cancer research. Invited speakers will highlight cutting-edge proteomic research in the cancer field. In a separate section NMR based methodology for analysis of protein structure and cancer metabolomics with identification and follow up of biomarkers.

Learning outcomes: After the course the students should be able to

  • Explain the principles and methods on how proteins can be identified and quantified by mass spectrometry
  • Understand the importance protein expression, post-translational modifications, and complex formation in healthy and diseased tissue
  • Explain the basics of the software methods used in protein studies
  • Independently analyze data using the main databases for proteomics research
  • Explain the basics of NMR based protein analysis and NMR use in cancer metabolomics
  • Interpret and use data from NMR based analysis

 

 

CARES Contact Information

Pia Berntsson, PhD, Scientific Coordinator
Medicon Village
Building 406: 311E1 (HS 90)
Scheelevägen 2
SE-223 81 Lund
+46 46 222 31 01

Ulrika Lantz Carlsson, Administrator
University of Gothenburg
Box 425
SE-405 30 Gothenburg
+46 31 786 6792
 

Steering Committee

Håkan Axelson (Director LU)
Jonas Nilsson (UGOT)
Kristian Pietras (LU)
Lao Saal (LU)
Pierre Åman (Director UGOT)

Page Manager: Veronica Norell|Last update: 12/15/2017
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