Translational Cancer Research

Faculty of Medicine | Lund University

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Overview of Courses

Fall 2016

1. High-throughput sequencing: Applications in cancer research organized by Helena Persson and Henrik Lilljebjörn (29 August-2 September 2016)

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.

2. Cancer epidemiology organized by Helena Jernström (3-7 October 2016)

The course provides a broad introduction to epidemiology and its applications in research, internationally, nationally, and regionally at Lund University. It introduces the basic concepts of measures of disease occurrence (prevalence, incidence rates, and cumulative incidence), measures of association (odds ratio and risk ratio), common designs for epidemiological studies (cross-sectional, cohort, and case control). The course will also cover the basics of causation (using DAGs), including the role of bias, effect modification, and intermediate variables.

3. The human genome and high-content methods organized by Sofia Gruvberger and Lao Saal (24-28 October 2016)

The aim of the course is to provide a broad introduction to the human genome, the cancer genome, and the high-content methods that may be harnessed in cancer research. The course lectures will cover various types of changes to the genome that contribute to tumorigenesis, and the basic principles of methods from microarrays and next-generation sequencing to high-throughput screening, among others. Furthermore, through computer lab exercises, the student will be familiarized with the wealth of available data on normal and cancer genomes, how the most common public resources and tools can be used in practice, and factors to consider in making an informed decision on which high-content method is appropriate for a given research question.

Spring 2017

 

4.  Bioinformatics I: DNA copy number changes in solid tumors, organized by Johan Staaf and Göran Jönsson (6-10 February 2017)

The course provides an introduction to human genome, with focus on DNA alterations in the human solid tumors. In particular, the students will deal with DNA copy number alterations and the methods that are available for identifying and characterizing such changes in order to link these changes to the disease. The course is divided in one theoretical and one practical part. The practical part of the course will be based on computer exercises employing bioinformatic analyses in combination with genome and gene databases. 

5. Clinical shadowing organized by Ana Carneiro (spanning week 4-12 2017)

The aim of this course is to provide students with a clinical experience within medical and radiation oncology. The students will have the opportunity to gain insight into clinical practice by attending multidisciplinary conferences, and internal therapeutic conferences.  During the course students will also be given the chance to review clinical study protocols with members of the team and understand the challenges associated with clinical/translational research. Through these experiences, students will gain a sense of the bidirectional nature of translational cancer research and will be given the opportunity of networking with clinicians working within their specific research topic.

Please note that this course is not a hands-on experience and activities are scattered during the indicated period. Due to privacy related questions students may not be allowed to shadow all clinical activities.

6. Bioinformatics II: : transcriptomics organized by Johan Vallon-Christersson, (13-17 March 2017).  

The course will consist of lectures on gene expression technologies and on key concepts in data analysis such as quality control, data formats, and analysis methods. The main part of the course consists of practical work of analysing gene expression data. The practical part includes step-by-step introduction to basic analysis as well as a more project-oriented exercise in which commonly used analysis strategies are performed. Practical steps include data file preparation, loading and visualising data, filtering and basic data transformations, investigating differential expressed genes, creating gene lists, performing hierarchical clustering and sample classification. Special emphasis will be on analysis strategies commonly used in cancer research.

Fall 2017

7. Proteomics organized by Peter James, LU (18-22 September 2017)

Cellular processes at the protein level are the main targets for the treatment of a disease. Proteins and their modifications are often used for medical analysis of those processes involved in the development of a disease like cancer. The main effectors that perform these processes are mostly proteins though miRNA are now implicated. A basic understanding of how to analyze proteins and how proteins interact is crucial for the development and application of new tools in this area. We will study and discuss proteomics within these criteria and discuss how to use proteomics tools to create a scientific basis for cancer research processes.

8. Tumor biology and targeted therapy, organized by Ramin Massoumi (9-13 October 2017).

A series of lectures will cover tumor biology, motility in tumor invasion and metastasis, cancer stem cells, tumor immunology, epigenetics, targeted cancer therapy, and mechanism of tumor cell drug resistance. Furthermore, small group activity with a plenary discussion based on the highly selected and relevant PBL-cases will provide a missing link in the postgraduate training program of translational cancer research for clinical and pre-clinical PhD students.

9.  Animal models organized by Kristian Pietras LU (21-25 November 2017)

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. Also, the use of mouse models in various applications related to cancer research, such as studies of metastasis or experimental therapy, will be reviewed. Mouse models of particular interest will be highlighted. In parallel, literature studies of mouse models of specific indications will be performed by the students, with the aim of designing new and improved mouse models.

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