Samenvatting week 1
Introduction to histopathology and staging of tumors
Cytology = individual cells / small clumps (fine needle aspiration). Histology = thick needle biopsy.
The biopsy (specimen) is fixed with formalin / FFPE (embedding). Grossing is selecting tissue slides.
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.
Histological properties of malignant tumors are
Loss of differentiation (anaplasia)
Pleomorphism (cells look different from one another)
Disordered architecture
Abnormal mitotic activity
Invasion and metastasis
TNM stage for tumor type & grade to find growth rate, risk factors, prognosis etc.
T-stage: degree of expansion of the primary tumor
N-stage: presence and abundance of metastasis to the local lymph nodes
M-stage: presence or absence of metastasis
Carcinoma (epithelial), Sarcoma (mesenchymal; muscle/fat/nerves), Lymphoma (T/B/NK cell),
Leukemia (haematopoietic neoplasm), brain tumor, germ cell tumor.
Conclusion
Tumor cells often don’t differentiate, they look different among each other, their
architecture and mitotic activity is abnormal and they invade/metastasize
T = degree of expansion of primary tumor, N = presence/abundance of metastasis to local
LNs, M = presence/absence of metastasis.
Carcinoma is in epithelium, sarcoma in muscle/fat/nerves (mesenchymal), lymphoma is in
lymphocytes (T/B/NK), leukemia in leukocytes (blood tumor)
,Bioinformatics: Intro to practical
NGS process:
1. DNA fragmentation
2. Ligation of adapters (to A tailed DNA ends)
3. ssDNA binds to flow cell
4. Bridge formation
5. Amplification
6. Clusters (of ssDNA) form
7. DNA sequencing with labelled bases
8. Base calling (detector)
FASTQ file (outcome NGS) gives the Phred score (quality score) which determines the accuracy.
Phred score ranges from 3 (B) to h (40):
B = chance of 0.40 that the base is called wrong 40% wrong
h = chance of 0.0001 that the base is called wrong 0.01% wrong
o h is the best score highest accuracy
Data Quality Control is done by FastQc. This gives the sequence quality per base.
Doesn’t start and end optimal. After NGS you cut these low quality ends + the adapters (a – s – a)
Lastly you map the reads to the reference genome alignment of your data with SAM (Sequence
Alignment Map). Now you can find where the sequences occur in the genome.
Conclusion
NGS = DNA fragmentation, adapter ligation to ssDNA, binds to flow cell, forms bridge,
amplification, cluster formation, sequencing, base calling
FASTQ file gives the Phred score for the accuracy B is low, h is high
FastQc gives the sequence quality per base
Low quality sequencing at the beginning/end trim these together with adapters
, Proteomics identification and quantification by mass spectrometry
Liquid Chromatography-Mass Spectrometry (LC-MS) can identify isotopes with different masses.
They have the same amount of protons but a different amount of neutrons.
Cell/tissue/biofluid protein mixture protein in-gel digestion with Trypsin (after R and K*) LC
to separate peptides by hydrophobicity electrospray ionization (peptides bombarded with e-)
peptide ions (= with charge) go into MS machine database searching identification validation.
* Trypsin doesn’t cut when a P follows RP or KP
The complexity increases when proteins are cut into peptides. Also less peptides discovered after
digestion because some peptides are too small/large to be detected by LC-MS. Some proteins don’t
have R/K or are hydrophobic/hydrophilic. This results in <100% sequence coverage.
Liquid Chromatography generic phase
Reversed phase C18 chromatography to separate the peptides based on hydrophobicity.
Stationary phase
o Nonpolar or hydrophobic (C18 modified cilica beads)
Mobile phase
o Polar or hydrophilic
Mass Spectrometry discovery phase
After your peptides got a charge (ionization) they go into the MS apparatus. Here the ions are
accelerated through electric plates and enter a magnetic field this bends the ion pathways this
is measured with a detector graph intensity (y, %) vs atomic mass or m/z (x, u or -).
Higher mass means that the ion is bent less. This gives the different mass spectrum. Higher masses
more to the right. Higher peak means more isotopes with this amount of neutrons.
X = atomic mass or m/z
Y = graph intensity (%)
= quantitation
= spectral counting
If you knock 1 e- off,
you’ll have a charge of +1