Gene regulation in cancer 11/14/07
Overview The hallmark of cancer is uncontrolled cell proliferation. Oncogenes code for proteins that help to regulate cell growth and differentiation. A mutation in an oncogene causes uncontrolled cell growth. Tumor suppressors suppress cell division or promote apoptosis (regulated cell-death).
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Signal Steroid receptor TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Signal TF Steroid receptor
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Signal * TF Steroid receptor
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Kinase Signal TF Steroid receptor Nuclear TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Kinase TF Signal Steroid receptor Nuclear TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Signal Kinase * TF Steroid receptor Nuclear TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Signal Kinase * TF Steroid receptor Nuclear TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Signal Kinase * TF Steroid receptor Nuclear TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus TF Signal Steroid receptor Nuclear TF Latent cytoplasmic TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus TF Signal Steroid receptor Nuclear TF Latent cytoplasmic TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Signal TF * Steroid receptor Nuclear TF Latent cytoplasmic TF
Different paths leading to transcription factor activation extra-cellular cytoplasm nucleus Signal TF * Steroid receptor Nuclear TF Latent cytoplasmic TF
Transcription factors in cancer Oncogenes Steroid receptors –Estrogen receptors (breast cancer) and androgen receptors (prostate cancer) Nuclear proteins –JUN Latent cytoplasmic factors –STAT Tumor suppressors p53, RB, etc.
Example: STAT pathway Darnell 2000
P53: overview Known as the “guardian of the genome” The first discovered tumor suppressor Inactivated in most types of tumors. 10,000 tumor related mutations have been identified from human to clam.
P53: overview Sequence-specific transcription factor (both an activator and a repressor)
Vousden and Lane 2007
(Vogelstein et al. 2000)
p53 pathway Oren 2003
Different biological outcomes
p53 activation Nuclear protein Activated by phosphorylation. Contain multiple phosphorylation sites.
Different activation of different subsets of genes. Oren 2003
Life and death choices of p53 How do p53 choose which set of genes to activate?
Life and death choices of p53 How do p53 choose which set of genes to activate? –Different modifications –Different partners –Others?
What genes are regulated by p53?
Gene expression profiling Ovarian cancer cell line (p53 is inactivated) Expression p53 by infection with adenovirus Label the DNA from the two cell lines differently and hybridize using a 2-color microarray Measure gene expression by microarray (60,000 cDNAs) at multiple time points. Monitor whether genes are activated or repressed (fold change > 2.5). Mirza et al. 2003
Target genes Differentially expressed genes can be due to direct or indirect regulation. How to identify direct targets? Mirza et al. 2003
Target genes Differentially expressed genes can be due to direct or indirect regulation. How to identify direct targets? Use known motif information, scan genome for motif sites. These sites are viewed as target genes. 294 repressed genes contain p53 motif sites; 67 activated genes contain p53 motif sites Mirza et al. 2003
Identifying p53 targets by CHIP-chip Cawley et al Affymetrix tiling array chr 21 and bp resolution on average
Identifying p53 targets by CHIP-chip Cawley et al Data analysis Apply Wilcoxon rank-sum test to probes in each sliding window P-value cutoff at p53 sites identified.
Cawley et al. 2004
Distribution of TFBS Cawley et al. 2004
Novel transcript related to TFBS Cawley et al. 2004
Novel transcript related to TFBS Cawley et al. 2004
Co-expression between coding and non-coding RNA Cawley et al. 2004
Can tiling array data be used to obtain a better motif?
CHIP-PET: A new method for detecting TFBS (Wei et al. 2006)
counts Detected 122 novel target genes.7
Motif finding from CHIP-PET data (Wei et al. 2006)
Expression profile from multiple tumors 193 tumors with p53 wild-type 58 tumors with p53 mutant Measure gene expression for each tumor tissue
Expression profile from multiple tumors 193 tumors with p53 wild-type 58 tumors with p53 mutant Measure gene expression for each tumor tissue Idea: For p53 target genes, differential expression should be observed.
Gene expression profile of p53 wild-type vs mutant tumors (Wei et al. 2006)
Gene expression profile of p53 wild-type vs mutant tumors (Wei et al. 2006)
Clinical implications
p53 network (Vogelstein et al. 2000)
Oren 2003
Reading List Oren 2003 –A review of p53 pathway Mirza et al –Gene expression profile of p53 Cawley et al –Map p53 binding sites using high resolution tiling array Wei et al –Use CHIP-PET to map p53 binding sites, rediscovered p53 motif; linked p53 targets with gene expression profile