Lecture 13: Modern technologies in pathology Flashcards
What is Histopathology and how is it used in treatment
It shows tissue and cell morphology as well as fine details which can be informative about health and disease, allowing pattern recognition.
This is important in the diagnosis, prognosis and direction of treatment
What is Immunohistochemistry used for
Allows identification of specific proteins in/on cells therefore can help identify cell state and type. This can lead to potential treatments
What was the Central Dogma
The flow of information contained in the DNA (genome) to coding mRNA (transcriptome) to a protein (proteome) and finally metabolites that result from that proteins action (metabolome)
What are non coding RNAs (microRNAs)
RNAs not made into proteins but rather used to modulates how genes are used in cells. This breaks central dogma process and can drive disease or help with diagnosis
How is next generation sequencing achieved
- Genomic DNA is cut in fragments
- known fragments of DNA are added on to the end
- Fragments are plated onto glass slide and amplified via PCR reaction using fluorescently tagged nucleotides
- The lights from these nucleotides can be converted into the sequence
- Fragments must be aligned and assembled into a genome by bioinformatic technicians
- Genomes of different cells from the same organism can be compared to find mutations
What is the exome
Small part (1%) of the genome that encodes for protein
How can single gene sequencing used to help patients with disease
- To find out if the disease is because of somatic or germline mutations
- To identify the specific dysfunctional protein causing the disease allowing correct drug prescribing
How can next generation (whole genome) sequencing help patients with disease - Genomic medicine
- By researching the genetic changes that drive cancers, comparing the genetic changes in the individual patients tumour allows more sensible stratification of targeted therapies
- again mapping genes relating to enzyme cascades can help to detemine correct drug treatment
- Circulating tumour DNA in blood can identify the mutations indicating cancer relapse after surgery
How has analysing of cancer changed with the introduction of genomics
Previous cancer classification of tumours looked at morphology by
histopathologists and single gene changes.
Now focus + whole genomic context of cancer: driver mutation, with corrobating genomic changes to back this up, drugs that can hit this target, response seen in the clinic and absence of resistance mechanisms?
What is the major limitation behind the slow progress of this technology changing medicine
Our incomplete molecular understanding of disease - technology is waiting for us to catch up
What are main applications of AI in medicine
- Neural networks can be trained to recognise cancers/ disease in xray helping diagnosis
- Neural networks can be trained to recognise patterns in DNA stacks to identify mutations
- Used to distill valuable information from data about individuals/ populations to make diagnoses/ public health interventions
What features of AI are useful in medicine- how does it work
Deep learning which allows computers to complete tasks based on existing relationships of data.
There is a neural network method modelled on the human bain structure with multiple hidden layers
What provides the examples that AI learns from
Large scale research banks which such as tissue and genomic banks which collect information along with other big data sources.
What are the inequities in Genomics data collection and consequences of this
There is a strong bias against indigenous populations in big data used to train AI. This could lead to the benefits not being served to these populations because AI learns only the characteristic variants of caucasian population
What are the challenges of rapid expansion of direct to consumer testing
The veracity of direct to consumer testing may not be as high because the results can be for recreational purposes
