MIT CompBio Lecture 22 - Cancer Genomics (Fall 2019)

MIT Computational Biology: Genomes, Networks, Evolution, Health
compbio.mit.edu/6.047/
Prof. Manolis Kellis
Full playlist with all videos in order is here: • Machine Learning in Ge...
All slides from Fall 2019 are here: stellar.mit.edu/S/course/6/fa...
Outline for this lecture:
0. Introduction: oncogenes, tumor suppressors, hallmarks
- Hallmarks of cancer, tumor-suppressors, proto-oncogenes/oncogenes, mutator phenotype, oncoviruses, and fusion oncogenes.
- Exome sequencing lessons: recurrence and heterogeneity
1. Recurrence: common signatures across types/patients/tumors/clones
- Evolutionary dynamics: clonal heterogeneity, computational models
- WGS lessons: non-coding drivers and convergence
2. Background mutation rate: regions, chromatin states, patients, plexi
- Convergence: mutations  enhancers  genes  pathways
3. Beyond mutations: epigenomics, functional heterogeneity
- Epigenomic alterations: reprogramming
- Single-cell sequencing: functional heterogeneity
4. Tumor immunology, microenvironment, immunotherapy
- Tumor-microenvironment interactions, cancer immunoediting.
- Neo-antigens, immune suppression, immunotherapy.

[@Zakariah1971]

Excellent

[@h.imamura7344]

Thank you for providing the lectures and slides. Hideo Imamura

[@haoxianglei8527]

good time to review!

[@jessicadoamaral9684]

Very useful! Thank you