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Complete college aantekeningen (complete lecture notes) Tumor Biology & Clinical Behaviour (TBCB) €10,44   In winkelwagen

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Complete college aantekeningen (complete lecture notes) Tumor Biology & Clinical Behaviour (TBCB)

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Complete college aantekeningen (complete lecture notes) Tumor Biology & Clinical Behaviour (TBCB)

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  • 14 december 2021
  • 67
  • 2020/2021
  • College aantekeningen
  • Saskia cillessesen en aart mookhoek
  • Alle colleges
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Tumor Biology & Clinical Behaviour Week 1
Introduction to histopathology and staging of tumors

• Cytology = individual cells or small clumps of cells
o Fine needle aspiration

• Histology
o Thick needle biopsy
o Often multiple biopsies are taken

Tissue biopsies (specimen) are “fixed” with formalin so they can work on it for a longer period of
time.

Specimen Handling: How to diagnose cancer (Cancer Diagnostics)

Registration, Description, Grossing (selecting samples from a tissue (not too many slides to look at),
Processing, Embedding (with paraffin to dissect it more easily), Sectioning, Staining.

Some general histologic properties of malignant tumors

1. Loss of differentiation
➢ Worse prognosis
➢ Anaplasia
2. Pleomorphism
➢ If cells look different from one another
3. Disorderly architecture
➢ No formation of tubules/lumen anymore in medullary carcinoma
4. Abnormal mitotic activity
➢ Atypical mitotic figure
5. Invasion and metastasis

Angioinvasion = tumor cells invade the blood vessels which allows them to metastasize.

Microscopic classification: Tumor type and tumor grade (differentiation state 1-5 → 5 is really poorly
differentiated). They do this because of: growth rate, different risk factors, prognosis, etc.

Main tumor groups:

• Carcinoma
o Most common tumor
o Epithelial
• Sarcoma
o Mesenchymal (muscle/fat/nerves etc)
• Lymphoma
o Lymphocyte system
o T cell/B cell/ NK cell phenotype
• Haemopoietic neoplasms
o Leukemia
• Brain tumors
• Germ cell tumors

,Laboratory techniques tools session

Micro-array CGH (Comparative Genomic Hybridization) to analyse Copy Number Variations (CNVs ➔
numerical changes). Isolate DNA from tissue samples (breast cancer).




Wikipedia

Array-based methods have been accepted as the most efficient in terms of their resolution and high-
throughput nature and the highest coverage (choose an array with over 2 million probes) and they
are also referred to as virtual karyotype.

Microarray CGH steps:

1. Isolate mRNA from tumor tissue and normal tissue
2. Copy the mRNA into labelled cDNA (red/green)
3. Mix and add cDNA of tumor and normal tissue to the different wells
➢ The different wells contain different nucleotide sequences
4. cDNA (of tumor tissue and/or normal tissue) will bind to these sequences (=Hybridization)
5. Green, Red or Yellow colour appears
➢ Red = higher expression of gene from tumor tissue hybridize
➢ Green = higher expression of gene from normal tissue hybridize
➢ Yellow = equal numbers hybridize

,Bioinformatics: Intro to practical

NextGen Sequencing:

1. DNA fragmentation
2. Ligation of adapters to A-tailed DNA ends
3. Single stranded DNA binds to flow cell
4. Bridge formation and amplification
5. Clusters of single stranded DNA are now generated withing every channel of the flow cell
6. DNA sequencing (labelled bases)
7. Base calling via a detector

FASTQ File = outcome of sequencing analysis.




4th lane gives the quality score (Phred score). Ranges from 3 (B) to 40 (h). B means 0.40 chance of
the based being called wrong. h has a probability (of a base call being wrong) of 0.0001. h is the
highest/best score.




Data Quality Control by FastQc. This is what you want →
It doesn’t start really optimal but later it becomes optimal.
Stays optimal for a while.

After NGS, you need to remove the adapter sequences again. Adapter – Sequence – Adapter.
Trim/cut low quality reads from the end.



Alignment of the data with SAM
= Sequence Alignment Map.

Contains information about how
sequence reads map to a reference
genome

, Proteomics identification and quantification by mass spectrometry LC-MS

Liquid Chromatography Mass Spectrometry gives unbiased data and it’s easy. Only downside:
Stochastic sampling / missing value problem




Protein digestion: <100% sequence coverage. The protein structure changes

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