rna seq - pdx models

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Whole Transcriptome Profiling of Cancer Tumors in Mouse PDX Models http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&p ath%5B%5D=8014 Based on breast cancer samples taken from the publication “Whole transcriptome profiling of patient-derived xenograft models as a tool to identify both tumor and stromal specific biomarkers” (James R. Bradford et. al.; DOI: 10.18632/oncotarget.8014)

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Page 1: Rna seq - PDX models

Whole Transcriptome Profiling of Cancer Tumors in Mouse PDX Models

http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path%5B%5D=8014

Based on breast cancer samples taken from the publication “Whole transcriptome profiling of patient-derived xenograft models as a tool to identify both tumor and stromal specific biomarkers” (James R. Bradford et. al.; DOI:

10.18632/oncotarget.8014)

Page 2: Rna seq - PDX models

Introduction

• Dataset: 21 samples from 3 subtypes of breast cancer in 3 different mouse models.• Goals: identify a clear signal showing transcriptional differences between cancer subtypes

1) Identify differences in expression between cancer subtypes and between mouse models 2) Select representative genes that could be considered as biomarker candidates

PDX Mouse Species

XID: Characterized by the absence of the thymus, mutant

B lymphocytes, and no T-cell function.

NOD SCID: Severe combined

immunodeficiency, with no mature T cells and B cells.

Athymic Nude: Lacks the thymus and is unable to

produce T-cells

 Breast TN: Survival rates are lower for this cancer than ER+ cancer types.

Breast ER+: Treatment often includes Hormone Therapy and has a more positive outlook in the short term.

Breast HER2+: Tends to be a more aggressive cancer type than ER+.  

Breast Cancer Subtypes

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Project Accession Number

Page 5: Rna seq - PDX models

What is a FastQ file?What is a FastQ File?

FASTA Format:Text Based File without the Quality Score

Page 6: Rna seq - PDX models

Step 1: RNA-seq pipeline prepares all annotated and non-annotated genomic element estimation of

expression levels

Removing genomic elements that did not have any expression (all zeros) in the RSEM table. This includes both the isoform and gene tables.

Quantile NormalizationPrincipal Component

Analysis

Step 2: RSEM output tables of genes and isoforms are prepared for Machine Learning

Analysis

1. Mapping by Bowtie2 using the original GTF (Mouse and Human Genome Combined)

2. RSEM Expression Table: Quantification of Gene and Isoform Level Abundance

3. Outputs include Genes Table and Isoform Table

Factor Regression Analysis

Visualization of T-Bioinfo Bioinformatics Functions

Lets First Build Our RNA-seq Pipeline!

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When your RNA-seq pipeline is complete….

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Quantile Normalization

Before Normalization

After Normalization

Gene Name Sample Names

Multi-Sample Normalization is considered a standard and necessary part of RNA-seq Analysis. - Unwanted Technical Variation

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Biological Databases- Great for Annotation!

https://david.ncifcrf.gov/http://www.ensembl.org

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Now back to the T-BioInfo Platform! 1. Start a PCA Pipeline2. Analyze our PCA Visualization 3. Create a Scatter Plot Image from our Results4. Utilize DAVID and ENSEMBL to investigate Biological Meaning 5. Learn about other Machine Learning Methods6. Understand a “real” RNA-seq project timeline

T-Bio.Info Platform: http://tbioinfopb1.pine-biotech.com:3000PCA Visualization:

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Triple_NEG ER+ HER2+

PC1:22.16%, PC2:9.22%

Estrogen Receptor

Triple Negative

-8 -6 -4 -2 0 2 4 6

-6

-4

-2

0

2

4

6

8

Breast Cancer Genes

PCA of Human Tumor By Samples and By Genes

Visualization Link:

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• Extracellular Matrix Remodeling

• Cell Migration • Tumor Growth• Angiogenesis

ERR1084798_Triple_NEG

ERR1084799__Triple_NEG

ERR1084800__Triple_NEG

ERR1084801__Triple_NEG

ERR1084802__Triple_NEG

ERR1084803__Triple_NEG

ERR1084804__Triple_NEG

ERR1084807__Triple_NEG

ERR1084808__Triple_NEG

ERR1084809__Triple_NEG

ERR1084810__Triple_NEG

ERR1084768__Triple_NEG

ERR1084767_HER2

ERR1084811_ER+

ERR1084811_ER+

ERR1084806_ER+

ERR1084763_ER+

ERR1084764_ER+

ERR1084765_ER+02468

1012

Matrix Metalloprotease 14 Expression in Breast Cancer Samples

Breast Cancer Samples

Leve

l of E

xpre

ssio

n

Upregulated in Triple Negative Cancer Samples

Defining the Breast Cancer Subtypes

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• Estrogen Regulated Proteins

• Oncogenic• Bone

Metastasis

TFF3 is a promoter of angiogenesis in Breast Cancer . This protein is secreted from mammary carcinoma cells to promote angiogenesis.

TFF3 also promotes angiogenesis by direct functional effects on endothelial cellular processes promoting angiogenesis.

TFF3 stimulates angiogenesis to co-coordinate with the growth promoting and metastatic actions of TFF3 in mammary carcinoma to enhance tumor progression and dissemination. 

ERR1084809_Tr

iple_NEG

ERR1084803_Tr

iple_NEG

ERR1084810_Tr

iple_NEG

ERR1084808_Tr

iple_NEG

ERR1084807_Tr

iple_NEG

ERR1084766_Tr

iple_NEG

ERR1084802_Tr

iple_NEG

ERR1084804_Tr

iple_NEG

ERR1084768_Tr

iple_NEG

ERR1084800_Tr

iple_NEG

ERR1084801_Tr

iple_NEG

ERR1084799_Tr

iple_NEG

ERR1084798_Tr

iple_NEG

ERR1084763_ER

+

ERR1084764_ER

+

ERR1084806_ER

+

ERR1084805_ER

+

ERR1084811_ER

+

ERR1084765_ER

+

ERR1084775_ER

+02468

1012

Trefoil Factor 3 in Breast Cancer

Breast Cancer Samples

Leve

l Of E

xpre

ssio

n

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Upregulated in Estrogen Receptor + Samples

Significance of Hormones to Breast Cancer- Endocrine Therapy

ERR1084811_ER+

ERR1084805_ER+

ERR1084806_ER+

ERR1084763_ER+

ERR1084764_ER+

ERR1084765_ER+

ERR1084775_ER+

ERR1084767_HER2

ERR1084766_Triple_NEG

ERR1084768_Triple_NEG

ERR1084800_Triple_NEG

ERR1084802_Triple_NEG

ERR1084803_Triple_NEG

ERR1084804_Triple_NEG

ERR1084807_Triple_NEG

ERR1084808_Triple_NEG

ERR1084809_Triple_NEG

ERR1084810_Triple_NEG

0

2

4

6

8

10

12

Estrogen Receptor Expression in Breast Cancer Samples

Breast Cancer Samples

Leve

l Of E

xpre

ssio

n

Estrogen Stimulates the cell proliferation of the Breast cancer cell

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Progesterone receptor testing is a standard part of testing for breast cancer diagnosis

ERR1084768_Triple_NEG

ERR1084775_Triple_NEG

ERR1084798_Triple_NEG

ERR1084799_Triple_NEG

ERR1084800_Triple_NEG

ERR1084801_Triple_NEG

ERR1084802_Triple_NEG

ERR1084804_Triple_NEG

ERR1084807_Triple_NEG

ERR1084808_Triple_NEG

ERR1084809_Triple_NEG

ERR1084810_Triple_NEG

ERR1084767_HER2

ERR1084811_ER+

ERR1084805_ER+

ERR1084806_ER+

ERR1084763_ER+

ERR1084764_ER+

ERR1084765_ER+012345678

Progesterone Receptor Expression in Breast Cancer Samples

Breast Cancer Sample

Leve

l of E

xpre

ssio

n Progesterone receptors, when activated by progesterone, actually attached themselves to the estrogen receptors, which caused the estrogen receptors to stop turning on the cancer promotion gene.

Then they actually turned on the genes that promote death of cancer cells (called apoptosis), and the growth of healthy cells!

Upregulated in Estrogen Receptor Cancer

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Factor Regression Analysis

A0B0 Triple Neg/ Athymic Nude

A0B1 Triple Neg-/SCID

A1B0 ER+/ Athymic Nude

A1B1 ER+/ SCID

Factor A: Triple Negative vs. ER+

Factor Table (2 factors, 2 levels each)

Triple Negative Samples ER+ Samples

Selecting Human Genes Under the Influence of Either Triple Negative Breast Cancer or Estrogen Positive Breast Cancer

* Will have either large table for Factor analysis or visualization table

Gene Expression Key

*No Significant Mouse Genes

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Tumor – Stroma Association Study

•Expression Table (alignment of reads on comprised genome)•Separate Human and Mouse genes/isoforms/exons•BiAssociation: Links between Human and Mouse

genes/isoforms/exons•P-clustering of all selected correlated/anti-correlated

genes/isoforms/exons •Results: Network of associations between stroma and

tumor genes/isoforms/exons

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Tumor Samples enriched with immune processes

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Batch Effect- Enrichment of mitochondrial and ribosomal genes

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RNA-Seq Experiment Overview Based on Breast Cancer Samples taken from the publication “Whole transcriptome profiling of patient-derived

xenograft models as a tool to identify both tumor and stromal specific biomarkers” (James R. Bradford et. al.; DOI: 10.18632/oncotarget.8014)

HER2 ER+TNBC

NOD SCID XID Athymic CB17 SCID

1. Ribosomal Depleted RNA2. Fragment RNA3. TruSeq RNA Sample

Preparation Kit4. Concatenated Genome

(Mouse/Human) 5. Indexed with star align

Secondary Analysis

Tertiary Analysis Gene Summary and Ontology Report

1. Mapping using TopHat2. Finding Isoforms using Cufflinks3. GTF file of isoforms using Cuffmerge4. Mapping Bowtie-2t on new transcriptome

Cancer Subtypes

Mouse Species

Page 21: Rna seq - PDX models

Thanks for Listening!

Any Questions? Contact: [email protected]

T-Bioinfo Platform : http://tbioinfopb1.pine-biotech.com:3000

Pine Biotech Website: http://pine-biotech.com

Pine Biotech Education Website: http://edu.t-bio.info