Cancer Transcriptomics

Question 1

What is the transcriptome informing of

Answer 1

1. Analysis of the entire collection of RNA sequences in a cell
   - > which genes are turned on
2. Different cells show different patterns of gene expression- Liver genes are expressed specifically in the liver
3. Transcriptome actively changes
4. By collecting and comparing transcriptomes of different types of cells, we can a deeper understanding of what constitutes a “normal” cell function; what changes occur in a diseased cell, etc.
5. Some molecular features can only be observed at the mRNA level– Alternative isoforms, fusion transcripts, RNA editing

Question 2

The amount of RNA molecules is estimated at what?

Answer 2

roughly 10 to power of 7 per cell.

Question 3

What are methods to quantify mRNA expression levels?

Answer 3

1. PCR methods
   - RT-PCR. qPCR, etc.
   - Quantification of single gene
2. RNA in situ
   - RNAscope
   - Quantification and localisation of single gene
3. Probe-based
   Relative (microarray) or absolute (nanoString) of pre-selected genes
4. RNA-sequencing
   Absolute quantification of all types of RNA species

Question 4

What are the different RNA preparation methods?

Answer 4

1. Total RNA:
Broad transcript representation 
Abundant RNAs dominate
High unprocessed RNA
High genomic DNA

2. rRNA reduction
Broad transcript representation
Abundant RNAs de emphasised
High unprocessed RNA 
High genomic DNA

3. cDNA capture
Limited transcript representation (targeted)
Abundant RNAs de emphasised
Low unprocessed RNA
Low genomic DNA

4. PolyA selection 
Limited transcript representation (polyA)
Abundant RNAs de emphasised
Low unprocessed RNA
Low genomic DNA

Question 5

How can sequencing depth limit research questions?

Answer 5

Dependent on capture method

Absolute minimum of 10 million reads
- Variation in genes with above-median expression stabilises at about 10 million reads per sample among technical replicates (Wang et al. 2011)

40 to 60 million reads
- Can identify alternative splicing with high confidence

> 100 million reads
Quantify low-abundant transcripts
Identify fusion genes
FFPE material

To attain high quality RNA data 150 million reads per sample recommended

Question 6

What is the goal of RNA-sequencing experiments?

Answer 6

• Compare expression of genes between different samples

- Compare expression of genes with other genes within the same sample

Question 7

What is needed to achieve the goal of RNA sequencing experiments?

Answer 7

1. Quantification
   - ’Counting’ the number of reads mapped to a gene
   - Technical problems with simply ‘counting’ (technical biases)

• Between samples- samples with higher reads have higher counts
• Across genes- longer genes have higher counts
  2. Normalisation

Process of removing variation

Question 8

To address technical biases, what needs to be performed across samples and across features?

Answer 8

Normalisation

Question 9

What variety of normalisation methods exist?

Answer 9

1. RPKM - reads per kilobase of transcript per million reads of library
   Corrects for total library coverage
   Corrects for gene length
   Comparable between different genes within the same dataset
2. FPKM - fragments per kilobase of transcripts per million reads per library
   Only relevant for paired end libraries
   Read- pairs are not independent
3. TPM - transcripts per million
   Normalised to transcript copies instead of reads
   Corrects for cases where the average transcript length differs between samples
   Compare samples of different origin

Question 10

What are the challenges in RNA-sequencing?

Answer 10

1. Sample purity, quantity and quality
   RNA is fragile compared to DNA (easily degraded)
2. Mapping strategies
   Small exons may be separated by large introns
   Aligning RNA-sequencing reads to genome is challenging
3. Relative abundance of RNA species vary wildly (between 105 to 107)
   Since RNA-sequencing works by random sampling, a small fraction of highly expressed genes may consume the majority of reads
   Ribosomal and mitochondrial genes
4. RNA species come in a wide range of sizes
   Small RNAs must be captured separately
   PolyA selection of large RNAs may result in 3’ end bias

Question 11

What is used in the downstream analysis of single‐cell RNA‐seq?

Answer 11

t-distributed stochastic neighbour embedding (t-SNE) plots

a dimensionality reduction step for visualising the data in two dimensions

Question 12

What is transcript-omics?

Answer 12

Investigation of gene expression patterns based on the relative
amount of mRNA under a given condition

Question 13

What does transcript-omics in translational science involve?

Answer 13

Compare normal tissue with diseased tissue

Classification of different tissue types or cellular populations

Gene expression pattern related to specific clinical characteristics

Long list of gene signatures capturing different phenotypes, responses to drugs, etc.

Question 14

What does a single sample predictor involve?

Answer 14

Extract RNA and analyse this and investigate expression level. Can align expression pattern of known subgroups from previous research. If similar expression seen as previous research, can predict patient survival

Question 15

What is the Nanostring Prosigna?

What is the Nanostring Prosigna used for?

Answer 15

FDA cleared assay for subtyping breast cancer

Predict patient’s Risk of Recurrence
- estimates the probability of distant
recurrence over 10 years

• PAM50, intrinsic subtype, nodal status, tumour size and proliferation score. Intrinsic subtypes provide valuable prognostic information to guide clinical decisions

Question 16

How was the effectiveness of the MammaPrint Test by Agendia measured?

Answer 16

Gene expression signature of 70 genes

• Invasive Breast Cancer Stage I and II
• > 3 positive lymph nodes
• Hormone-receptor-positive AND negative

Calculate a recurrence score

• Low risk: 10% risk of recurrence in 10 years without any additional treatment
• High risk: ~30% risk of recurrence in 10 years without any additional treatment

Microarray In Node negative and 1-3 positive lymph node Disease may
Avoid ChemoTherapy..MINDACT trial
- 7,000 patients were accrued (93 institutes , 9 countries)
- 46% of women with breast cancer who are at high clinical risk

might NOT require chemotherapy.

Question 17

What is the Oncotype Dx test?

Answer 17

Genomic test that analyses activity of group of genes that can affect how a cancer like likely to behave and respond to treatment- 21 genes

Used to help clinicians calculate woman’s risk of early stage oestrogen receptor positive breast cancer, HER2-negative breast cancer coming recurrence and how well she is to benefit from chemotherapy after breast cancer surgery.

Question 18

What is the Oncotype Dx test?

Answer 18

Genomic test that analyses activity of group of genes that can affect how a cancer like likely to behave and respond to treatment- 21 genes

Used to help clinicians calculate woman’s risk of early stage oestrogen receptor positive breast cancer, HER2-negative breast cancer coming recurrence and how well she is to benefit from chemotherapy after breast cancer surgery.

Question 19

What did the Trial Assigning Individualised Options for Treatment….TAILORx find when investigating the effectiveness of the Oncotype Dx test?

Answer 19

10,000 patients

100 institutes in USA & Canada

73% of patients with high clinical risk had Recurrence Score results 0-25 and may
have been overtreated without the Recurrence Score result

43% of patients with Recurrence Score results 26-100 had low clinical risk and may have been undertreated without the Recurrence Score result