Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

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Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst
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Transcript of Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Page 1: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Half Hairpin Analysis in Cancer Cells

Katie Stackpole

Lucien Barnes

Isabel Vanderslice

Andrew Borst

Page 2: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Cancer in the US

• Second leading cause of death in the US

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Lung and BronchusUterus

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Breast Cancer

• Second most common form of cancer in women, behind skin cancer

• Most common cause of death in Hispanic women

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Colon Cancer

• 72,007 men and 69,398 women were diagnosed with colorectal cancer.

• 26,781 men and 26,224 women died from colorectal cancer.

• Third most common type of cancer in men, and third leading cause of death from cancer.

Page 5: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Cancer Proliferation Gene Discovery Through Functional Genomics Michael R. Schlabach,1* Ji Luo,1* Nicole L. Solimini,1* Guang Hu,1* Qikai Xu,1 Mamie Z. Li,1 Zhenming Zhao,1 Agata Smogorzewska,1,2 Mathew E. Sowa,3 Xiaolu L. Ang,3 Thomas F. Westbrook,1 Anthony C. Liang,1 Kenneth Chang,4 Jennifer A. Hackett,1 J. Wade Harper,3 Gregory J. Hannon,4 Stephen J. Elledge1 Retroviral short hairpin RNA (shRNA)–mediated genetic screens in mammalian cells are powerful tools for discovering loss-of-function phenotypes. We describe a highly parallel multiplex methodology for screening large pools of shRNAs using half-hairpin barcodes for microarray deconvolution. We carried out dropout screens for shRNAs that affect cell proliferation and viability in cancer cells and normal cells. We identified many shRNAs to be antiproliferative that target core cellular processes, such as the cell cycle and protein translation, in all cells examined. Moreover, we identified genes that are selectively required for proliferation and survival in different cell lines. Our platform enables rapid and cost-effective genome-wide screens to identify cancer proliferation and survival genes for target discovery. Such efforts are complementary to the Cancer Genome Atlas and provide an alternative functional view of cancer cells.

Page 6: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Key Terms

• DNA barcoding: Uses a short genetic marker to identify species along the DNA

• shRNA: RNA with a tight hairpin turn that can be used to silence gene expression via the RNAi pathway

• HHRNA: 3’ half of the shRNA stem, eliminates probe self-annealing during microarray hybridization

• Dropout: Cell colonies that have shown lower proliferation after being introduced to shRNA– Gene that was knocked down was necessary for cellular

proliferation

• Knock-down: The reduced expression of a gene.

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Roadmap of Lecture

• Central Goal: Producing a high throughput screen to display what genes are not required for cancer cells

• Methods: Retroviral transformation, HHRNA Production, HHRNA microarray hybridization, Cell viability assay

• Results: Show cell viability when genes are knocked down, also shows validation of shRNA by using siRNA

• Discussion: MDM2, PRPS2, and BUB1 shown to be required genes for cancer cells (with exceptions)

Page 8: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Figure 1: Overview of the pool-based dropout screen with barcode microarrays

Page 9: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Figure 1 B: Schematic of HH barcode hybridization

insertion region is unique in genome due to inclusion of loop

190 bp HH DNA barcode

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1 C: Comparison between HH amplicons and full-hairpin PCR amplicons on an HH probe microarray

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Retroviral transformation with MSCV

2nd generation Elledge-Hannon human and mouse shRNA libraries

pMSCV -Puro-M1uI-shRNA library

- 1841 shRNAs targeting 1272 genes “cherry-picked”, cloned as pools into pMSCV-PM-PheS

- Retroviruses produced by transfection of MSCV-PM-shRNA, pCG-gag/pol, and pVSV-G plasmids using TransIT-293 into 293T cells. Retroviral supernatant was isolated

- Human cells were infected 3 times. Viruses removed and uninfected cells selected against using puromycin

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Controls and Verifications

-BUB1 (using siRNA and shRNAs to confirm knockdown because of similarity

between processes)

-EIF 3510 and RBX1 (essential for viability in all cell lines)

-Included shRNA in screen and others from library

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Cell Viability Assay

-Cells infected in triplicate with retroviruses-Replace media 24 hrs later-On days 2, 6, or 9 post-infection using CellTiter-Glo reagent (glows in presence of ATP)

-Read on plate readerPromega CellTiter-Glo reagent

Page 14: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Analogous to a continually expressed RNAi BUT

- like a hybrid of microRNA and siRNA because it comes from nucleus but cuts

mRNA target instead of simply sequestering it.

- may effect development - can test multiple genes at

once (as in this study)

MUCH more high through-put than gene deletions

Comparisons to Other Techniques

Main difference in new method: using HHRNA instead of shRNA eliminates probe self annealing, allowing barcodes to be identified by 20 bp hybridization to a plate rather than sequencing of a 60bp barcode.

siRNA

microRNA

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Results:

Page 16: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

• The meaning of log 2

Most of the data in this paper uses log base 2 to normalize the results.

How this works: up-regulation by a factor of 2 has an expression ratio of 2, and down-regulation by a factor of 2 has an expression ratio of ½.

What is?

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Dropout and Enrichment

“For each cell line, shRNAs were ranked on the basis of their mean normalized log2 Cy3/Cy5 ratios. The shaded rectangle indicates the log2 ratio range within which an shRNA's abundance was considered unchanged.”

The healthy human cells (HMEC) were much more affected than the cancerous cells.

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Necessary Genes

Healthy cells need more of their genes to survive than cancer cells (antiproliferative shRNAs identified in the screen).

HMEC (healthy human breast tissue) compared to the other three types of cancerous tissue shows the number of required genes as a darker color of orange.

The cancer cells had better survival rates than healthy cells when genes were randomly interfered with.

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Several RNAs, one gene• “(C) Antiproliferative

shRNAs and genes that scored in the screen for each cell line are shown.

• (D) Summary of the common shRNAs (blue) and genes (red) identified in the screen.

• (DLD-1 and HMEC have more overlapping genes than shRNAs because, in some cases, different sets of shRNAs targeting the same gene scored in each line).”

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A Control• “Validation of selected

shRNAs from the screen that reduce viability of all four cell lines. All viability reductions were significant (P < 0.05), except where indicated by “#”.”

*FF is a negative control with shRNA targeting firefly luciferase, and shows that shRNA doesn’t affect a cell if the cell doesn’t contain a gene related to that shRNA, because the cell viability didn’t change.

This data shows that the shRNA works to interfere with genes that are present, but does not affect survival if those genes are not.

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Importance of certain genes• “Examples of core cellular

modules required in all four cell lines. Shown are the APC/C (top left), the COP9 signalosome (top right), the eIF3 translation initiation complex (bottom left), and E3 ubiquitin ligases (bottom right).”

This shows which genes within a known pathway are crucial to only one type of cell, to two cells, three, or to all four cells.

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Some genes are crucial for all cells…but some are even more so than others?

• “For each shRNA, the normalized log2 Cy3/Cy5 ratio (i.e., its relative abundance in the end sample versus initial sample) is given.”

• For example, the gene PLK1 is required by all four cell types, but it is most important to the HCT116 cells.

• This is important because knowing which genes are crucial to a particular cancer could lead to research of a specialized treatment.

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Discussion - What does this all mean?

Cats are awesome….regardless of what Dr. Young says.

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Cancer Cell Line Similarity

• High degree of similarity for gene knock-down susceptibility between the two colon-cancer cell lines (DLD-1, HCT116).

DLD-1: 114 shRNAs (88 genes; about 1.4% of genome)

HCT116: 202 shRNA (115 genes; about 3.9% of genome)

IN ENGLISH: The two colon cancer cell lines required similar genes for successful proliferation. Without these genes, the two lines died.

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Normal Human Mammary Epithelial Cells vs. Cancerous Cells

• 695 genes essential for HMEC survival– Reflects ability of cells to

respond to various stresses.

• The relatively few number of genes required for cancer cell proliferation demonstrates the ability for these cells to evade growth inhibitory cues. These thousands of snowmen are analogous to

the uncontrolled proliferation of cancer cells.

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Genes selectively required for proliferation or survival of cancer cells.

DLD-1: Colon Cancer

HCT116: Colon Cancer

HCC1964: Breast Cancer

HMEC: Normal Human Mammary Epithelial Cells

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Gene Knock-down Susceptibility

• Differs largely between cancer cells isolated from different tissue cultures.

• PRPS2 encodes nucleoside synthesis (dNTPs) in cells.

• Down-regulation of this gene proves to be inhibatory in DLD-1 (colon cancer) cells than in HCC1954 (breast cancer) cells

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MDM2 Gene Essentiality

• MDM2: E3 ubiquitin ligase for p53

• Large negative log2 ratio indicates that knocked-down gene is essential for growth

• Positive log2 ratios indicate knocking-down that gene helped with growth

Page 29: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

BUB1 – Interesting…

• BUB1: Spindle Checkpoint Kinase

• The spindle checkpoint blocks the entry of a cell undergoing mitosis into anaphase until all chromosomes are properly attached to the meiotic or mitotic spindle. – It is a cell-cycle regulator

The spindle checkpoint stagnates mitosis until all spindle microtubules are attached to the chromosomal centromere at the metaphase plate.

Page 30: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

BUB1 more Necessary in Cancerous Breast Tissue.

• Enhanced sensitivity of HCC1954 (breast cancer) cells to BUB1 (spindle checkpoint kinase) knockdown. – ENGLISH: More breast

cancer cells died when BUB1 was knocked-down than in normal HMEC cells. Both shRNA and siRNA knockdown Both shRNA and siRNA knockdown

of BUB1 reduce HCC1954 cell of BUB1 reduce HCC1954 cell viability but have little/no effect on viability but have little/no effect on

HMEC viability.HMEC viability.

Page 31: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

BUB1 is more Necessary in Cancerous Breast Tissue.

Again: • Large negative log2 ratio

indicates that knocked-down gene is essential for growth

• Positive log2 ratios indicate knocking-down that gene helped with growth.

• Small negative log2 ratios (> -1) indicate knocked-down gene wasn’t very inhibitory for cellular proliferation.

Page 32: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.

Enhanced Sensitivity to BUB1 Knockdown in breast cancer tissue. Why?

• Breast cancer cells (HCC1954) are near-tetraploid in nature. – BUB1 is putatively used to

maintain genomic stability.

• “Non-oncogene addiction”– Tendency of cancerous cells to

become dependent on non-oncogenes for proliferation.

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In summary…

It is now possible to easily identify specific anti-proliferative genes for numerous cancer cell

lines.

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Genetic Cancer Genome Project

• Goal: Generating cancer lethality signatures for different cancer types and thus identifying cancer type–specific lethal genes representing potential drug targets.

Page 35: Half Hairpin Analysis in Cancer Cells Katie Stackpole Lucien Barnes Isabel Vanderslice Andrew Borst.