Karimi Cancer Genetics 2022 PDF

A brief introduction to cancer NGS and bioinformatics 7BBG2014 Bioinformatics, interpretation and data quality in genome analysis Dr Mohammad M. Karimi Senior Lecturer in Bioinformatics [email protected]...

A brief introduction to cancer NGS and bioinformatics 7BBG2014 Bioinformatics, interpretation and data quality in genome analysis Dr Mohammad M. Karimi Senior Lecturer in Bioinformatics [email protected] November 2022  Outline A brief introduction to cancer How can genetic data help understand cancer and guide treatment? Bioinformatics – data and analysis Outlook  What is cancer? Cancer is when abnormal cells divide in an uncontrolled way - The life cycle (division, maturation and death) of cells is carefully orchestrated by molecular signals - If any of these signals are faulty or missing, cells may start to grow and multiply too much and form a lump called a tumour. A primary tumour is where the cancer starts.  Types of cancer There are more than 200 different kinds of cancer Five main types, based on what type of tissue they start in: - Carcinoma – cancer that begins in the skin or in tissues that line or cover internal organs - Sarcoma – cancer that begins in the connective or supportive tissues such as bone, cartilage, fat, muscle or blood vessels - Leukaemia – cancer that starts in blood forming tissue such as the bone marrow and causes abnormal blood cells to be produced and go into the blood - Lymphoma and myeloma – cancers that begin in the cells of the immune system - Brain and spinal cord cancers – these are known as central nervous system cancers  How cancer grows Tumours can be either benign or cancerous (malignant) Benign tumours typically grow slowly, don't spread widely in the body and are made up of cells that are quite similar to normal cells They are usually only problematic if they: - grow very large - become uncomfortable or painful - are visible and unpleasant to look at - press on other body organs - take up space inside the skull (such as a brain tumour) - release hormones that affect how the body works  How cancer grows Cancerous or malignant tumours are made up of cancer cells who: - Usually grow faster than benign tumours - Spread into surrounding tissues and cause damage - May spread to other parts of the body in the bloodstream or through the lymph system to form secondary tumours (metastasis)  How cancer grows Blood supply and cancer - Like all tissues tumours need oxygen and nutrients - As the tumour gets bigger, its centre gets further and further away from the blood vessels Angiogenesis: the tumour sends out signals (angiogenic factors) that encourage new blood vessels to grow into the tumour - Without these, can't grow much bigger than a pin head Once established, allows the tumour to grow rapidly Cancer cells break off and travel with the blood stream - May spread the cancer to other tissues (metastasis)  How are cancer cells different? Normal cells - Produce when and where it's needed - Stick together in the right place in the body - Self destruct when they become damaged or too old - Become specialised (mature) Cancer cells - Don't stop growing and dividing - Ignore signals from other cells - Don't stick together - Don't specialise - Don't repair themselves or die, i.e. have faulty DNA repair and cell self- destruct (apoptosis) mechanisms - Look different, e.g. large variation in cell size and abnormal shapes Cancer Tumours Heterogeneity  How Many Cancers are Genetic? Sporadic (~85%) Familial (~10%) Hereditary (~5%)  Sporadic Cancer Many patients may have a similar Family History Age of diagnosis typically later in life Usually not inherited Can be reassuring Might be attributed to somatic mutations Hereditary Cancer  Several affected family members  Earlier than average age of onset  Multiple generations are affected on one side of the family  A particular pattern of cancers noted  Individuals with more than one primary tumour site  5-10% of Cancer Cases  Hereditary Breast and Ovarian Cancer Other genes BRCA1 BRCA2 5-10% Sporadic Hereditary Most cases caused by a mutation in BRCA1 or BRCA2 gene BRCA1 / 2 are tumour suppressor genes, which are involved in the repair of DNA Accounts for about 5% of breast cancer cases and about 12% of ovarian cancer cases  The genetic basis of cancers There are 4 main types of genes involved in the cell life cycle. Most tumours have faulty copies of more than 1 of these types. Oncogenes: genes that encourage the cell to multiply - Most normal cells divide only rarely, but cancerous genes divide often Tumour suppressor genes: genes that stop the cell multiplying - Mutations in tumour suppressor genes mean that a cell no longer understands the instruction to stop growing - The best known tumour suppressor gene is p53. This gene is damaged or missing in most cancers DNA repair genes: genes that repair other damaged genes Apoptosis genes: genes that tell a cell when to die - Normal cells are programmed to self-destruct when too old or damaged (apoptosis) - Complex process with many genes involved. Damage to these genes can cause cancer to develop Hallmarks of cancer Hanahan2011 Aims of Genetic Counselling Help patients to… Understand the information about the genetic condition Appreciate inheritance patterns and risk of recurrence Understand and prioritize available treatment options Make informed choices appropriate to their personal and family situation Make the best possible adjustment to the condition and risk  Using tumour genetic data to treat cancer Cancers display great heterogeneity in progression and in what genetic factors contribute to the primary cancer tumour Knowledge of the genetic alterations in a specific patient can help determine a treatment plan Some treatments—particularly, some targeted therapies— only work for tumours with specific driver mutations that cause the cells to divide out of control Example: mutations in the EGFR gene - Makes cells divide rapidly - Found some people’s lung cancer cells - Can use EGFR inhibitors to slow tumour growth Caveats: genetic heterogeneity within the tumour means that - Tumours often contain multiple driver mutations - May develop immunity to any single targeted treatment - Important to combine multiple treatments  Tumour profiles Sample tumour and non-tumour tissue (e.g. blood) from patient Profile of genetic differences between tumour and normal tissue - Whole or targeted exome DNA resequencing to identify potential driver variants (single nucleotide variants or small insertions/deletions). - Whole transcriptome (RNA-seq) processing pipeline analyses tumour RNA-seq data to find small variants and gene fusions and compute gene expression Combine with databases of known nucleotide and structural genetic variants associated with different cancers, and known gene-drug interactions - E.g. COSMIC, GDI and Cancer Cell Line Encyclopedia Complex profiles allow personalised treatment - Identify potential druggable genetic variants in the cancer - Identify genetic variants that may reduce efficiency of certain drugs - Genetic risk factors for different side effects  Studying Cancers with Sequencing Rizzo2012 Bioinformatics pipelines for tumour profiling Many pipelines exist for implementing tumour profiling using NGS resequencing and RNA-seq data Example: Galaxy implementation by Jeremy Goecks et al. - Location: http://usegalaxy.org/cancer - Exome pipeline - RNA-seq pipeline - Integrated variant analyses pipeline Outputs: - Rare and deleterious mutations - Druggable rare and deleterious mutations - Potential drugs associated with the druggable mutations Goecks et al. 2015 Cancer Medicine 4(3):392–403 Bioinformatics pipelines for tumour profiling Goecks et al. 2015 Cancer Medicine 2015, 4(3):392–403  Pancreatic cell line data (MIA PaCa2) From inside track out: 1 mapped read coverage 2 mapped read coverage after PCR duplicates removed 3 called variants 4 rare and deleterious variants 5 rare, deleterious, and druggable variants 6 rare and deleterious variants in highly expressed genes 7 rare, deleterious, and druggable variants in highly expressed genes. Goecks et al. 2015  PAC tumour data From inside track out: 1 mapped read coverage 2 mapped read coverage after PCR duplicates removed 3 called variants 4 rare and deleterious variants 5 rare, deleterious, and druggable variants 6 rare and deleterious variants in highly expressed genes 7 rare, deleterious, and druggable variants in highly expressed genes. Goecks et al. 2015  PAC tumour data From inside track out: 1 mapped read coverage 2 mapped read coverage after PCR duplicates removed 3 called variants 4 rare and deleterious variants 5 rare, deleterious, and druggable variants 6 rare and deleterious variants in highly expressed genes 7 rare, deleterious, and druggable variants in highly expressed genes. Goecks et al. 2015 Shared mutations in three pancreatic cell lines Goecks et al. 2015 Network analysis to promote understanding of Cancer  Pathway discovery Stimulate receptor 31% of pathway is activated BioCarta EGF Signaling Pathway Phosphorylation data from Alejandro Wolf-Yadlin  Clinical data Age, sex, cancer stage, survival Kaplan–Meier plot Wikipedia  Interactive tools for cancer data cBioPortal TumorPortal Cancer Regulome Cancer Genomics Browser StratomeX  Pathway and function enrichment Database for Annotation, Visualization and Integrated Discovery (DAVID) Molecular Signatures Database (MSigDB)  Gene expression data Gene Expression Omnibus (GEO) ArrayExpress  Protein interaction networks iRefIndex and iRefWeb Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) High-quality INTeractomes (HINT)  Transcriptional regulation Encyclopedia of DNA Elements (ENCODE) DNA binding motifs - TRANSFAC - JASPAR - UniPROBE  miRNA binding miRBase TargetScan  More to explore Galaxy resources for tumour DNA and gene expression analyses - Goecks et al. 2015 Cancer Medicine 2015, 4(3):392–403 - usegalaxy.org/cancer Cancer Research UK - Further information about different cancers - www.cancerresearchuk.org/about-cancer Cancer in the 100,000 Genomes Project - How the 100,000 Genomes Project aims to improve cancer care for NHS patients through personalised medicine - www.genomicsengland.co.uk