Welcome to MOOC course on Introduction to
Proteogenomics.
Today we have scientist Dr. Suman Thakur from
Center for Cellular and Molecular Biology,
CCMB Hyderabad.
Dr. Thakur will talk to you about mass spectrometry
based quantitative proteomics and how it can
help the cancer research.
He will also talk about why quantitative proteomics
is very important, in which way various tools
available for doing quantitative proteomics
have helped to understand different diseases.
Dr. Thakur will focus on why we are not getting
clinically relevant biomarkers for all the
cancers and why one drug cannot cure all the
cancers.
He will talk about different specifications
for mass spectrometry based columns.
For example: the gradients, the column length
and other type of mass spectrometry parameters.
How it could be optimized to obtain good results.
He will also talk about why the number of
proteins decreases in labelled analysis as
compared to the liberal free quantitative
analysis.
He will then talk about anti-cancer compound
screening and how the proteomics, cell biology
and animal studies together could only help
to find out the clinically relevant information.
So, let us welcome Dr. Suman Thakur for today铆s
lecture.
Mass spectrometry based quantitative proteomics
in cancer.
So, anyhow you are well trained and thanks
to all the previous speaker who has set the
stage and I should just move it.
So, all you know proteogenomics; so, genomics
is here, proteomics is here, middle transcriptomics,
metabolomics for us the all are different
subject.
But, for body all are happening; billion year,
trillion year of evolution has made this.
So, this is not a one day anything maybe this
is new subject for us.
But what is here?
So, biology change thousand year before also
question what is life, today is also question
what is life?
Most probably thousand years later will be
also question what is life, what is evolution?
But, what change that we have to understand?
Technology; so, technology drives biology,
you get new technology in your hand or you
try to answer different question.
If you want to do something in life you have
to ask question.
What is the question?
Find a specific anti-cancer compound for particular
cancer without side effects, is it possible
to find a drug without side effect?
That is the reason you asked question what
is not easily possible.
Second find earlier stage and cancer biomarker,
cancer is a such a word till you discuss in
symposium and lecture hall it is fine.
If you see any patient your near and dear
you will be second very badly.
So, that is a bad word is a cancer basically
is a disease still after so, many years 100
years of research we are not able to cure
it, we are still in the middle.
So, what you need?
Earlier stage every doctor ask earlier stage.
But, what is the question?
Common cause, there are different organs in
the body, different types of cancer are there.
If all are there then cancer should be common,
this question you can ask and to we try to
ask this question and I thought take select
11 or 10 cancer cell liner.
It is very nice to we have to get clear this
is the cell line, same thing we are trying
to repeat on the tissue also.
So, you take HeLa, cervical cancer, Jurkat,
leukemia, HePG2 liver cancer, GAMG brain tumor,
MCF breast cancer, A549 lung cancer, LNCAP
prostate, RKO colon, U2OS bone and K562 again
myeloid.
So, different type of cancer are there.
Why not one drug is there for all the cancer?
Impossible origin is different, metastasis
different so, that mean it is very complex.
Then you have to take if you want to do anything
in the proteomics, we have to select one control
and this is non-cancerous cell line.
So, we thought we will take this 10 cancerous
cell line and very childish way you think,
you get 5000 proteins within L 10 or 11 you
will have also almost whole human proteome;
practically it is not possible.
Or, you do different fractionation and you
come to 10,000 protein in each cell line is
still you will not able to cross 11,000, 12,000
maximum 13,000.
So, what is the matter in; that means, all
proteins in all the cancer are same, only
quantitation is getting changed.
Someplace someone is expressed someplace someone
is expressed.
So that means, what?
Expression level, quantitation.
So, finally, what came?
Quantitation is important in the experimental
and it is happening inside the body.
But, how you will do this?
This is very simple, we want cancer full proteome
that is one or few proteins protein chemistry.
We will see some lab is full 20 years has
been focused on one protein.
But some lab will not like one protein.
Why one protein?
We should have thousand protein, but what
you will do with thousand proteins.
Again what is missed whatever is your interest
that you have miss.
So, finally, if you want to make a drug or
target, you will target on one protein.
So, what proteomics has given you?
Completely back cycle to find the target and
come back on the one protein are make the
drug test, same things we are trying also
to do.
But before that I will go with little bit
problem is there.
There is nothing everything is good, good,
good, good in life, but mostly we talk good,
good, good thing.
If you go to see us the biomarker things different
disease same marker, same disease different
marker; all you will get confused and you
will end up with the nothing.
So, bottom line what we need?
Need unique biomarker that is the whole thing
and field should grow it or maybe you need
set of biomarker.
Just like if someone is telling no this is
this disease then again you go to cross check,
you go to verification that is thing has to
be done.
Why all these things is happening?
Answer is a billion year of evolution, you
cannot easily search find in one day directly
sort it.
It has to be systematic a study or if you
are by luck, you are hitting in the dark it
got hit; both are happening together and both
example I will show you how we fail, how we
pass.
We thought instead of 15 centimetre make half
a meter column, think little bit weird everyone
will tell you crazy, it works you are best;
if did not works you still carry with the
tag crazy ok.
So now, 15 centimetre 50 centimetre column
it is long column, make bead side everyone
using 5 micrometre, 3 micrometre, half.
What will happen?
HPLC pressure will vary increase, to increase
the pressure simple you just school knowledge
Charles law, Boyle's law.
Heat it, down the temperature down that increase
the temperature, down the pressure and somehow
you will manage with old HPLC.
This 50 centimetre column long run and 5000
protein came that time in one single shot.
This was just example, same technique we have
developed; now recently we have published
how long gradient we can use and after 12
hour if you are using the gradient recently
published in 2018 there is no use; so, it
is saturated.
So, need of fixation how long gradient, how
long this and that.
Now, this technique you should use in SILAC
that I am going to tell about the cancerous
cell.
So, this is just introduction; now I show
you label free quantitation 5000 protein comes
in one run, but when you do SILAC you get
less protein.
Why?
Because now 2 peak is needed to identify and
quantify a protein.
So, you increase the complexity; so, if you
increase the complexity sensitivity has to
be compromise or your protein number has to
be compromised.
But, we know all the way how to increase the
number also.
What if in 1 hour you got 3700, make triplicate
know then quantify, here bioinformatics you
like or dislike bioinformatics you have to
use ok.
So, now this is the place 1 into 8 hour you
got 3,000.
Now, run triplicate you get 4222 because which
one peak has come in this run another peak
came in this run by bioinformatics you merge
and you can increase that.
So, this way you are showing, but there is
the way triplicate, 4, 5 times, 6 times how
many time?
This is showing almost in triplicate on 4
almost you are getting close.
So, there is no need of going to unnecessary
too much ok.
You have to keep your temptation and limitation
that is also very important otherwise you
are doing only one thing.
Now, same thing we did with all these 11 cell
line and then we try to find is there any
common thing is there or we have to a stop
on 11; first we did one then gone 5 then 11.
Now, we are planning to have 25 or 50 cell
line to get complete idea, but we cannot decide
in one it is very costly affair and we are
selected in the broad range.
Now, by this if you do deep proteome you will
get 10,000 protein in each cell line by fractionation,
but we thought we should go single shot also
and we should see in one run.
There is no comparison between any fractionation,
4 fractionation you might know by bioinformatics
1 run direct result and see, that both approach
we have use.
Now, you see what happens here, it is single
shot; one shot whatever came.
This is CID SILAC, you know CID and HCD?
You would have heard high energy, today铆s
is the era of HCD ok.
Now, you take HEK 293 light plus heavy ok.
So, HEK is there light and heavy, now you
are comparing that.
There should be theoretically any difference,
in quantitation up regulation down regulation?
It should not, that is the reason when you
quantify identify 4200 and quantify 91 percent
in 4.
But, when you did in 1 I told you already
comes, here you quantified only 78 percent,
here 89 percent, here 91 percent.
So, what happens when you do multiple run?
You are going to quantify more, but now I
am increasing 5 cell line.
I am mixing 5 cell line together, then I am
trying to see what is happening.
One thing you see if one cell line give me
4299 protein, mind tells 5 cell line will
give more.
Correct or not?
Simple thinking, do not think too much; answer
is no then we thought 11 cell line will give
more, answer is again no.
See this pattern is continuing single run
is giving less, triplicate is giving more
and here you are getting more.
But, when you are increasing the cell line
nothing is changing that shows your technology
has limitation.
Of course, 5 cell line when you put you have
more protein 11 cell line when you put you
have more protein, but technology has limitation.
That means, still our so called well developed,
well costly mass spec need to develop less
or more?
Very more.
Very more.
So, still price will increase, development
will continue.
Now, see now this is same CID, here compare
HEK 293 versus HEK 293.
So, there is theoretically there is no difference
ok.
When no difference so, what happen in your
in quantitation we do not take less than 2
fold ok.
See majority of things is falling in this
less than 2 fold and whatever it is showing
1 percent that is almost a error ok.
Now, I have taken 5 cell line, in 5 cell line
I am taking HeLa versus Jurkat, HeLa, HePG2,
GAMG, MCF7.
So, this HeLa is inside that 5 cell line,
but I am able to quantify and see 2 fold that
is falling only 84 percent; that means, others
are changing ok.
Here is the very less change, here you can
see more change; that means, different cell
line has different things correct.
Now, here I took 11 cell line, it is coming
almost same so; that means, because my technology
is also coming close and result is also coming
close.
So, I cannot comment on that clear, but that
is shows me 5 cell line has more protein or
different protein compared to that.
And, if theoretically same 2 cell line if
you compare where is up regulation and down
regulation, if you there you get up regulation
down regulation; that means, better to stop
the experiment ok.
So, that is shows your control things are
going in right direction, but this HeLa is
inside the 5 cell line and 11 cell line.
With this you plot, you have learn all the
R and all these things today.
By plot you can see the 5 cell line is not
that much sharp, 11 cell line is more that
much sharp; that means, quantitation is better
when you have multiple cell line.
A chances to find that protein is very high.
Same things you do with HCD 1 5 11 cell line
and you will get different type of things
and we are fine here, but this HeLa is again
inside that.
Now, HeLa compared with Jurkat you will get
only 70 percent, no changes almost.
But, HeLa with 5 cell line, HeLa with 11 cell
line you are getting more to cover it; now
it is different you are comparing.
Again you see that HeLa with Jurkat your line,
your graph is not density plot is not so sharp,
here it is better and 11 cell line better.
So, this has given me indication in my 11
cell line or higher a stock I will able to
cover more protein of that.
If that mix is ready that proper things is
ready; that means, I will have more chance
to quantify because, in human I cannot label
SILAC ok.
It is only possible in cell culture ok.
Now, you see here, here we have taken 1 cell
line HCC 1599 breast cancer, this is not mix
present in the mix of 5 and 11.
Now, you see here chances of getting quantification
is more or less, because it is not inside
you will get different things.
So, this concept is coming clearly how you
make the mix, do you need a master mix, do
you need this.
And, whole analysis idea is still we are doing
that what common protein is there in all the
type of cancer, where it is getting click
or where it is getting a start that is still
under the way.
Most probably next time I will show you more
and better, same things I am trying also to
go with the tissue now.
When 11 cell line we can take, now we know
what is going to happen, now 11 tissue or
20 tissue we are trying to do, all cancerous
tissue and we are looking what is the common.
And, can we find one common place where all
these get trigger that will help, will we
do not know what will happen.
With this you again say this density plot
always 11 cell line is coming better ok, you
all have learned R.
And, with this I will move towards the little
bit cancer drug discovery that is the my favourite
hard work of PhD student and it is somehow
giving result.
So, what is there?
Development of anti-cancer compound, use cell
biology, mouse model and human model you have
to go finally, clinical trial.
So, that is the what simple cancer means tumor,
break the cluster, induce cell death, apoptosis
and reduce cancer cell proliferation.
Three things are there target, different compound
we have a screen, there are you would heard
a company a screen 10,000 15,000 compound
library and then come to one target.
We thought how can we do a smartly.
Here this is a childhood cancer, mostly happened
in childhood time before 5 year.
Why it happens?
It is very tough to tell, no one knows.
It can happen in 1 eye, it can happen in 2
eye and both the eye can be affected.
There is the drug with very high side effect
carboplatin, etoposide and vincristine mostly
natural towards ok.
So, we thought nature maybe have something,
with this now how to think about the cancer,
how much unfortunately this retinoblastoma
is very high in India or developing country
India, Africa and all this.
Why?
There is no answer of that, but if you look
all these things you will see 10 percent of
pediatric patients have retinoblastoma ok.
In that also highest incidence of retinoblastoma
is in Africa and India.
Why?
No one knows.
This is the cancer related with the gene,
because you are in proteogenomics and this
cancer is related with the gene retinoblastoma
RB, you would have heard cancer suppressor
gene and this is directly link with that ok.
So, this is some time hereditary, sometime
environmental, but then sometime no one understand
why it happen ok.
Now, people are a still thinking which place
it is just getting a start and recently one
in 2014 paper came that they tells it is mostly
a starting with the cone precursor cell ok.
So, this is the little bit evidence has come.
So, this is below 14 years says non-hereditary,
60 percent hereditary is 40 percent.
So, wonderful model system to a study the
cancer where genes genetics is also involved,
environment is also involved, but no one has
any answer.
Now, this is terrible make is not good to
see too much ok, in 6 months times this become
terrible ok.
If you did not get treatment then very tough
and that is the problem happened in developing
country, when you get you see leukocoria you
can characterise if a doctor will see a normal
person will quickly figure out there is something
in the eye.
This is the step where you understand there
is something leukocoria stable tell.
I have mouse glioblastoma mouse in lab we
see that directly it ok, but if it get bigger
if they get tumor bigger than head size.
Now, you can understand how this happened,
if timely there is nothing in nucleation is
only that a chances to having metastasis is
very very high.
So, what you should do?
Now, this is the chain if and most of the
time what happened children parents not able
to take to the hospital, no one takes care
it gets different aggressive a stage than
it is almost nothing.
Now so, what we need?
We need a need for the development of safe
better and effective manner.
What you need at this time?
You need some drug ok, whatever drug is there
that is also not able to cure, it has very
side effect.
Then this one of the student Kamakshi PhD
student has done this work.
How?
Now, we thought to break the cluster and now
idea is that find a drug and find mode of
action.
In science mode of action is more important.
Drug needs patient, mode of action will give
you patient help and to make the another drug
better.
So now, simple concept break the cluster you
say this is cluster forming cell ok.
So now, when you are started giving this control
cluster is there, you give we have screens
few compounds, several compounds.
And, then we came to this compound, this break
the cluster, but this is not a big deal.
You put Surf excel, Wheel anything it will
break the cluster.
So, this is nothing conclusive, but indication
is there ok.
Now, if you got what a biologists will do
quickly go and do cytotoxicity ok.
So, we did cytotoxicity and somehow we found
Y79 cancer retinoblastoma cancer cell line
is giving 18 micro molar IC 50.
But, if you got 18 micro molar in the cancerous
cell, it is also possible this will kill your
normal cell ok.
If it is killing normal cell then how can
this will be drug?
First argument you ask yourself and you confirm
here.
Now, what we did?
We took ARP 90, it is also retinal epithelial
cell and here you see IC 50 is 165 micro molar;
that means, there is it is not killing.
Normal.
Normal cell.
We are looking for this, we are looking a
compound which has potential to kill only
cancerous cell, not to normal cell that is
the whole point came here.
So now, you see this is our slide, anyhow
there is nothing hard to tell fact this experiment
we do did very late.
First we did because, we do not have cell
line we try to arrange cell line, it took
lot of time later we did, but somehow it worked.
Now, here proteomics played the role.
Now, I told you, you put Surf excel also it
will work ok.
But, when the surf excel concentration will
go, it will come again cell closer ok.
Now, when this compound this never comes close
so, that was one benefit.
Now, you took the give the treatment with
this compound to different cell both and now
you do proteomics.
I have shown you how to do it ok.
Now, you do proteomics and now you are start
comparing what happened after doing proteomics.
When you look the proteomics, what you found
cell adhesion related proteins are down regulated
in E4, E4 is nothing it is my lab number,
room number.
So, that is from it.
So, now all cell adhesion related protein.
So, cell is not getting attached, it is getting
detached and cell adhesion protein is getting
down regulated; that means, something is going
towards the cell adhesion.
No one is going to believe proteomics, if
you are not doing antibody or some validation
at least reviewer ok.
We all believe ok, reviewer will ask you.
Now, we have done antibody experiment and
we have moved forward.
Now, if it is really anti-cancer all oncogene
and cancer related protein should be down
regulated, perfectly hit ok.
So; that means, it is anti-cancer, now you
have to talk about the mechanism.
What happens if all mitochondrial protein
you will see that is going up regulated in
the treatment.
So, mechanism in somewhere related to mitochondria.
Who is telling proteomics, now this much indication
is enough for biologist to kill the or make
the project work ok, that is the proteomics
played the role.
Now, you do whole analysis, cluster, networking
all you have learned you know also must do
this is very useful.
When you do you saw tumor suppressor protein
TUSC3 is getting up regulated, that is the
logic.
Suppressor protein should go up, cancer related
protein should go down, but we found this
transcription factor and caspase14 came up.
So, that we do not have anything铆s ok, clue
about that.
You quickly look this compound is binding
with DNA or not, control take a ethidium bromide
and just you look it is not binding.
Quickly next experiment Tm, Tm is changing
somehow; no need to find quickly mechanism
one by one, one by one.
Third you are in CCMB, all are well trained
here ok.
Now, third quickly look does E4 after alter
cell cycle, here we found an little bit very
different and strange result.
You see this sub G1 population is getting
very high with the concentration dose dependency
ok; that means, you change the dose IC 50
is 18.
If you increase this dose and here you find
the mechanism sub G1 population is getting
very high, here you seen same concept thing
in 24 and 48 hour result is wonderful.
Something confusion is there, this pattern,
this pattern is same; this pattern, this pattern
is changing in the S phase, no answer we have
ok.
This happens; that means, different dose is
working at different different time point
a different things ok, but this gives sub
G 1 population is altering the circle.
So, what is the conclusion?
E4 perturbs the cell cycle and cause the cell
death.
If this we know, then next what we should
do?
Quickly do apoptosis and quickly we are showing
again with the concentrates increasing the
concentration what you are doing?
You are able to go to late apoptosis more.
So, this is working in the time and dose dependent
manner that is we come, you can conclude anything
more than this.
Now, E4 cause cell by apoptosis, now you go
another experiment DNA fragmentation, run
the gel quickly do it or do tunnel as a little
bit fancy and you can see that DNA fragmentation
is also going up by higher concentration.
So, we are trying to find the mode of action,
mode of mechanism and question answer is here.
E4 cause apoptosis by DNA fragmentation dose
and time dependent manner, even not binding
with the that.
So, now detection of intracellular ROS, we
have saw mitochondrial thing, we have saw
ROS protein.
So, with this we found that this is also making
sense and mitochondrial membrane potential
assay we have done; with this we came to that
it is something is happening.
We are not sure ok, something is happening
towards the mitochondrial cell.
So, compound E4 induce ROS generation mechanism
and leads to mitochondrial membrane depolarization,
this indicates that ok.
So, what proteomics told mitochondria result
came by other biological technique, same or
different that is we need.
So, with this now no one is going to believe
your cell culture only publication ok, if
you want to move mouse experiment you have
to do.
So, this is xenografted mouse, you take the
cell line, inject in the mouse, make the tumor,
leave the month time to establish, inject
the compound.
And, if it reduce supervisor will move next
stage and a student will go happy another
year for move ok.
So, like this happens.
What is the most important things, if you
give take control because after 1200 ethical
does not permit you to keep the tumor size.
And, if you give treatment it is completely
demolished.
This results gives very nice, even I like
this is first experiment you see because experiment
you have to plan very well.
Give injection only on Monday, student will
not feel bad; Monday come inject nicely wait
for next Monday and you see the ones how dose
dependency go.
So, this proof clear that do not give too
much pressure, then they will not think.
So, this gives clear that how things are working.
If it is really working, what is the next
stage?
Again use your proteomics, now we are sitting
here, we have this tools technique knowledge.
We took the tumor from both after treatment
that do full proteomics, do histological staining,
quickly show where is the apotheosis is happening.
And histology of tumor, thus you can see treatment
yeah just this.
And now I told you one word side effect, there
should not be a side effect ok.
So now, when histology of liver, we do we
do not see any change.
Only compound when you inject, when tumor
form when tumor form any compound injected
we do not see in histology any change and
no mouse has died that is the biggest with
this.
With this you see similar thing in a spleen,
you saw similar thing in lung, heart and kidney.
That is gives the now here two and a half
years after hard work of system and paper
work finally, we got knock out mouse retinoblastoma
where gene is knockout RB- p53-.
So, mouse will get automatically retinoblastoma,
here we have started treating and we are getting
potential very good result.
And, I will show you most probably next time
whenever we meet.
With this I showed you how things will go,
similar concept we have used for leukemia.
Very nice IC 50 1 1 minute, I will show you
the concept is repeating that you got late
apoptosis.
What is the interesting thing here got, when
you injected this is another compound, but
similar line in 5 minute it reach after injection
to brain and if you leave for 45 days this
compound get from body out also.
So, this is another compound working for leukemia,
this is very nice.
Third is melanoma all you know, what I saw
how to come the mechanism.
This is the last, here there is no cluster;
if it is working there is no cluster.
And when cluster is there, still compound
is working you find mode of action and mechanism
which signalling pathway very simple.
All the known target drug you take, make the
slide and even you find this is the target.
And then you do all your experiment and you
will find by antibody ok, this is happening.
I told you in biology antibody is very important.
Now, you see BCL2 is the down regulated, PAK3
is down regulated.
And, if this is really apoptosis all caspases
should be down regulated or up regulated?
Up regulated.
Up regulated biology is like this ok, only
mass spec is not enough; you need mass spec
and parallel this.
When you reach this, by this anyone can tell
there is the apoptosis, caspase is up.
There is something is going.
If you have this data you make your models
ok, how mechanism is working.
When you go to this mechanism, you saw we
saw Caspase 8, 3, 7, poly ADP ribose polymerase,
Caspase 9 FF, Cyto c, Bcl2, Bax.
So, this is the mode of that and mostly it
is going towards the Akt signalling pathway
ok.
Now, use your knowledge, here experience is
experience ok; then you see it is Akt, FoxO1,
Bcl 2, p 53, Bax, apoptosis.
This is the chain, it is coming down regulated
and up regulated.
So finally, we are coming it is towards the
Akt signalling pathway.
With this thank you all of you, your patience
and for time.
For today铆s lecture by Dr. Suman Thakur,
I hope you got a complete image understanding
about why getting a single biomarker for cancer
is tough; why many biomarkers have not been
able to reach to the transitional work so
far in the clinics.
Dr. Suman Thakur showed you how multiple cancer
cell lines having same protein, but different
amount.
This is the reason a labelling technique like
SILAC or iTRAQ can be helpful.
He also showed a complete overview how cell
biology can be used to get the drug screening
strategy and enable modern experiment can
help in validation.
I hope you are gathering different facts from
different scientists, clinicians and trying
to understand that what are the latest advancements
in the field.
And also what are the gaps from the clinical
as well as its successful translation.
In this way by integration of cell biology,
various type of omic based technologies and
clinical strategies together only we can made
some success in this area.
The next lecture is by Dr. David Fenyo, who
will talk about predictive analysis.
Thank you.
