Course Identification

Translational Cancer Research-From Bench to Bedside
20233192

Lecturers and Teaching Assistants

Prof. Zvi Livneh
N/A

Course Schedule and Location

2023
Second Semester
Monday, 11:15 - 13:00, Wolfson Auditorium
24/04/2023
21/07/2023

Field of Study, Course Type and Credit Points

Life Sciences: Lecture; Elective; Regular; 2.00 points

Comments

Moed A will take place at FGS room A (instead C)

Prerequisites

No

Restrictions

100

Language of Instruction

English

Attendance and participation

Expected and Recommended

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

100%
Part of the final grade may be for assignments

Evaluation Type

Examination

Scheduled date 1

08/08/2023
WSoS, Rm C
1000-1200
N/A

Scheduled date 2

23/08/2023
WSoS, Rm C
1000-1200
N/A

Estimated Weekly Independent Workload (in hours)

2

Syllabus

 

Please notice: The order of the lectures is not final; Name of speakers will be soon finalized

Translational vs basic research and course overview

Why epidemiology? Introduction, inter-individual variability; dirty data, descriptive epidemiology

Principles of cancer epidemiology (Cancer burden, cancer research history, principles of cancer epidemiology (descriptive, analytical); study design: prospective & case-control studies; randomized trials)

Biostatistics for translational cancer research-1 Hypothesis testing, Sample size, Sources of variations, confounding, biases

Biostatistics for translational cancer research-2 Relative Risk, Odds Ratio, logistic regression, survival data, Measures of diagnostic and prognostic accuracy, sensitivity, specificity, ROC curves

Overview of cancer prevention Primary prevention-Etiology (associations), Secondary prevention-early detection; Tertiary prevention-prognosis and survival

Biomarkers in translational and clinical research Omics, liquid biopsy; immuno-assays and functional assays; a case study of biomarkers for lung cancer

Analysis of Omics data Lots of information for small number of samples: False Discovery Ratio, biological pathway driven analysis

Big Data management and utilization for translational cancer research Challenges and limitations of big data analysis

Imaging in translational research

Cancer Screening Advantages and disadvantages in screening; biases, cost-effectivenes);  Tools for screening: imaging, biomarkers;

Cancer Drugs development – from idea to drug Phases of drug development, regulation, trialsA case study

Targeted cancer therapies Challenges, tumor heterogeneity; drug targets; Immunotherapy; cost.

Choosing right models for translational cancer research Animal models: human vs syngeneic, GEMMs, PDXs, humanized mouse models/non-animal alternatives (3D cultures, organoids); Including examples.

IRB@ WIS; Helsinki approvals

Ethical considerations in translational clinical research/Helsinki declaration; stem cells; animal models

Technology transfer at WIS- from academia to industry – success stories

'Public Trial' on a hot topic related to translational cancer research, with students acting as defense and plaintiff attorneys, witnesses, and jury.

Learning Outcomes

Upon successful completion of this course students should be able to:
[1] Understand the rationale of epidemiology and biostatistics in preclinical and clinical translational research.
[2] Interpret and review data sets by recognizing appropriate clinical research design.
[3] Understand strategies of translational research for new diagnostics and therapeutics.
[4] Understand the underlying ethical principles that form the foundation of human subjects protection regulations.

Reading List

Schuster DP, Powers WJ. Translational and Experimental Research. Lippincott Williams and Wilkins. Philadelphia PA, USA. 2005.

Website

N/A