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Serum microRNA biomarkers for early detection of ovarian cancer

Biofluids microRNA NGS Services and microRNA PCR Services

Prof. Dipanjan Chowdhury
Prof. Dipanjan Chowdhury

Prof. Dipanjan Chowdhury is Associate Professor at the Dana Farber Cancer Institute, part of the Harvard Medical School in Boston, United States. He is investigating the role of microRNAs in DNA repair. Over the years, his lab has used Exiqon's microRNA NGS and qPCR Services in several different projects.

What is the main focus of the research conducted in your lab?

The crux of my research interest is genome stability and DNA repair. DNA repair is relevant for both cancer therapy and the process of oncogenesis.

How did you come to be interested in microRNAs?

I started my lab back in 2007 when microRNAs were a relatively new class of molecules and at that time no one was looking at the role of microRNAs in DNA repair. So we wanted to understand the role of microRNAs in the relatively well-studied process of DNA repair.

How has the approach to microRNA research changed over the years?

Back in 2007, understanding of microRNA functions was still in its infancy. We started with lab-based experiments: finding a microRNA, and then asking if it is clinically relevant. Nowadays we do things the other way around, we first start with the patient samples, we identify the clinically relevant microRNAs, and then investigate the mechanism by which they impact the process we are studying.

Now with so much greater availability of clinical samples, and new technologies enabling sequencing from very small amounts of material, we can take the research to a new level.

We started off studying tumor-based microRNAs, and indeed we still do, but the serum based microRNAs are going to be much more powerful as biomarkers, as it’s ultimately a blood-based non-invasive test.

Of all your projects involving microRNA, which do you find most exciting and why?

We are doing a lot in the realm of serum microRNAs as biomarkers. I think the most exciting study in my lab using Exiqon’s Biofluids microRNA NGS and qPCR Services is to find out if we can use serum microRNAs for early detection of ovarian cancer. Ovarian cancer is the most lethal gynecological disease in the United States. Early detection of ovarian cancer is crucial for the best patient outcomes. Unfortunately there is no early detection test for ovarian cancer, and the symptoms of ovarian cancer are very weak. So we set out to identify microRNAs in serum indicative of ovarian cancer, with a view to developing a blood based test for ovarian cancer.

What were the results of your project to identify serum biomarkers for ovarian cancer using Exiqon’s microRNA NGS and qPCR Services?

We sent 180 patient serum samples to Exiqon for small RNA sequencing. The patients had ovarian cancer in different stages, benign tumors or no tumor. It's really exciting because we have identified a set of microRNAs that are very promising: the serum microRNA signature can distinguish benign vs malignant disease – and can even distinguish stage I cancer vs benign disease. This is a big deal because when the patient comes to the clinic there is currently no way of telling whether or not the patient has ovarian cancer, until they do the surgery and the biopsy, which is an extremely invasive procedure. Using the microRNA biomarkers we can also distinguish early disease from late disease.


"It's really exciting because the serum microRNA signature can even distinguish stage I ovarian cancer from benign disease."


Could you tell us about your projects on serum microRNA biomarkers to assess the impact of total body irradiation?

We published a paper last year (ref. 2) using mouse models where we used Exiqon' s microRNA qPCR Services to identify two serum microRNAs that can help us predict the outcome of total body irradiation. In today’s world, with the current political climate and terrorist threat, we have to plan how to respond to a nuclear disaster. Right now there is no test to identify whether or not a person has been exposed to radiation. Based on the microRNA biomarkers in serum, we can actually identify which animals were exposed to the radiation, and we can predict the impact of radiation exposure i.e. whether or not the exposure will be lethal.


"We have to plan how to respond to a nuclear disaster. Right now there is no test to identify if a person has been exposed to radiation."


We have recently done a similar study with Exiqon's microRNA qPCR Services using existing blood samples from macaques – these animals are individuals (not inbred), so they are the closest you can get to the real human situation. This study is actually very powerful because the microRNA biomarkers we identified in mouse are evolutionarily conserved and did hold true in macaque. These microRNA biomarkers could be used to identify individuals most likely to benefit from drugs to mitigate the effect of radiation.

Did the macaque study on serum microRNAs reveal any new information?

What’s interesting about the macaque study is that the same dose of irradiation is lethal for some animals but not for others. This highlights that individuals respond differently to the same dose of irradiation, and we could predict the response to irradiation using just two microRNA biomarkers. It's incredible!


“We can predict the response to irradiation using just two serum microRNA biomarkers. It’s incredible!”


There also appears to be gender differences as well – females seem to be more radiation sensitive – which is a new observation. There is currently no systematic study on the gender aspect of radiation sensitivity because animal studies usually include only one gender to minimize variability. We were lucky that this macaque cohort included both genders. One microRNA basically showed us the gender bias. These are really interesting observations and also raise so many questions: where are these serum microRNAs coming from? What are they doing? Where are they going?

Can serum microRNAs also be useful biomarkers for radiation therapy?

We are looking at radiation therapy and whether serum microRNAs can predict the later development or type of secondary tumors. We have a mouse model where mice are irradiated at a certain dose and go on to develop lymphomas or sarcomas 4-5 months later. We have identified two microRNAs, present in serum one week after radiation, that predict whether the secondary tumor will be a lymphoma or sarcoma. That data provided us with the basis for a project we are currently working on, using human patient samples.

What were some specific challenges in your projects?

One of the biggest issues when developing any biomarker is the sample numbers, and having access to clinical samples with all the relevant clinical data available. You have to look at hundreds of samples from different cohorts to really make sure you are on the right track.

Another challenge is sample amount. It’s very hard to get hold of these clinical samples and sometimes the amount we receive is very limited. The QC checks that Exiqon do for biofluid samples are good to do, but I would like it if the QC could be done using less material.
Another big issue with serum microRNAs is normalizers. It’s not simple – there’s no GAPDH, there’s no actin. We’ve spent a lot of time figuring out what is the best normalizer. To be honest, it’s not as simple as just run NormFinder and identify the best normalizers.

How did you overcome the challenge of normalization in serum?

You really need to run these algorithms, identify 10 or 12 candidate normalizer microRNAs, and then actually test them to see which do not change. In the mouse serum study we spent a long time doing it, and the same with the macaque and the human projects.

What has been your experience validating microRNA NGS results by qPCR? Did you find a good agreement between the two platforms?

14 serum microRNAs identified as ovarian cancer biomarkers by Exiqon's Biofluids microRNA NGS Services were subsequently validated using Exiqon’s microRNA qPCR Services. The first validation project was done using 120 serum samples (the same samples that were used for sequencing).

Overall we found good agreement between the two platforms, however we did identify some microRNAs by NGS which were not identified by qPCR. This could be due to different thresholds applied during the NGS and qPCR analysis, or different sensitivity levels of the platforms.

Nevertheless, the microRNAs that were successfully validated by qPCR still constituted a statistically significant signature for ovarian cancer, so the qPCR validation essentially refined the signature. Ultimately, any diagnostic test will be based on qPCR and not NGS.

We have also sent serum samples to Exiqon from an independent cohort of 226 patients for analysis by qPCR, and those results have literally arrived from Exiqon today so it’s exciting.

Why did you choose to use Exiqon’s Services?

We have worked with Exiqon for many years. Working with Exiqon has been very critical; I think the Exiqon microRNA qPCR platform is very good. I’ve tried many platforms, trust me! I am totally neutral, but I do think the LNA™ qPCR platform is very good – particularly with regard to specificity, which is crucial.


“Working with Exiqon has been critical.”


"I've tried many platforms and I’m totally neutral, but I do think the LNA™ qPCR platform is very good."


I believe you have conducted some of the experiments in your own lab, and some at Exiqon Services. What factors do you consider when deciding whether to send samples to Exiqon for analysis, or perform the analysis in your own lab?

Honestly, we send all the human samples to Exiqon, and any precious samples with limited amount of material available we always send to Exiqon. We feel that Exiqon are the professionals so we prefer Exiqon to handle those samples. In our lab we mainly handle tissue culture based samples.

My lab is relatively small by choice, so I prefer that Exiqon takes care of the samples they know how to handle best – and it’s easier for me to send samples to Exiqon than have one person spend a month doing it in our lab. We would rather spend our time doing the functional analysis.

The ovarian cancer project, the macaque project – these projects have literally not been touched by anyone in my lab; we just got the samples and shipped them to Exiqon, and I really like that, honestly, because we send the serum to Exiqon and Exiqon does everything. If it's good, it’s good, and if it’s not good it's Exiqon's fault, so I can blame Exiqon (which hasn’t happened so far, so it's all good!).


"We send all the human samples to Exiqon, for the professionals to handle. We send the serum and Exiqon does everything."


What are the next steps in the ovarian cancer project?

Now we are trying to get more samples to solidify the results we have for early detection of ovarian cancer in serum. We would also like to find out more about the 14 microRNAs we have identified as biomarkers of ovarian cancer: do they have a role, what are they doing? Once the clinical application has been demonstrated in further cohorts, we can begin to go after the biological questions and really find out what these microRNAs are doing. It’s exciting times.

What are the future perspectives for the ovarian cancer project?

It would be very exciting to analyze serum samples from patients before they develop cancer. There are some very precious collections of blood samples taken from thousands of individuals, and a small number of them ended up getting cancer. If we can sequence these samples, maybe we can develop a blood based microRNA test that predicts ovarian cancer before onset of the disease – that's the ultimate diagnostic. This will be one of the most important things – if we can do it, it will be a huge breakthrough. We are cautiously optimistic because we definitely have a test that distinguished benign vs malignant disease. I genuinely believe this is going to make a difference.


“Maybe we can develop a blood based microRNA test that predicts ovarian cancer before onset of the disease – that's the ultimate diagnostic.”


In your opinion, how large is the potential for microRNA biomarkers?

There's certainly a huge potential for microRNA biomarkers. I also believe a lot of the potential has been untapped because there’s a lot of mis-information and wrong data out there. Many of the problems have to do with platforms, and not taking care with the analysis – like the issue of normalizers for serum microRNAs for example. This diffuses the enthusiasm for the field for outsiders or clinicians who want to use it.

So it’s really very important for us to do it right, repeat it, and really convince people that microRNA biomarkers have the potential. I really believe that the blood based microRNAs (plasma or serum) have a huge potential as biomarkers. And for many cancers they have not really been looked at in a very rigorous way, so there is definitely a huge potential in this area.

What are the advantages of microRNAs, from a biomarker perspective?

I think microRNAs are great biomarkers – there's not many things that are that stable, so small, you can detect them easily – PCR based detection is so much easier than finding antibodies. With one PCR you can detect any microRNA. So you just need to analyze different microRNAs, but using the same overall tools and technique.

How do you see these ovarian cancer microRNA biomarkers being developed into a test for the benefit of patients?

The big picture here is to come up with a blood test that can be part of a woman's annual physical check-up. So as you go and get your cholesterol and sugar levels checked, you can have the microRNA levels checked too, to see if you are at risk of developing ovarian cancer. We’ve developed an algorithm where you punch in the levels of each of the 14 microRNAs, and this gives you a score for the probability of having ovarian cancer.

There is certainly a lot of interest from clinicians here. If this pans out, the application for this test will be very broad. I will be very happy to see these microRNAs put to use in the clinic for the benefit of patients.

When and where will we read more about your studies?

We have two papers currently under review – one on the microRNA signature for early detection of ovarian cancer in human serum, and the other on the macaque study looking at serum microRNA biomarkers to predict the impact of total body irradiation.

References

Dinh et al. Circulating miR-29a and miR-150 correlate with delivered dose during thoracic radiation therapy for non-small cell lung cancer. Radiat Oncol. 2016 Apr 27;11:61. PMID: 27117590.
Acharya et al. Serum microRNAs are early indicators of survival after radiation-induced hematopoietic injury. Sci Transl Med. 2015 May 13;7(287):287ra69. PMID: 25972001.
Moskwa et al. miR-182-mediated downregulation of BRCA1 impacts DNA repair and sensitivity to PARP inhibitors. Mol Cell. 2011 Jan 21;41(2):210-20. PMID: 21195000.
Choi et al. MicroRNAs down-regulate homologous recombination in the G1 phase of cycling cells to maintain genomic stability. Elife. 2014 Apr 30;3:e02445. PMID: 24843000.
Moskwa et al. A functional screen identifies microRNAs that induce radioresistance in glioblastomas. Mol Cancer Res. 2014 Dec;12(12):1767-78. PMID: 25256711.
Choi et al. Platinum and PARP Inhibitor Resistance Due to Overexpression of MicroRNA-622 in BRCA1-Mutant Ovarian Cancer. Cell Rep. 2016 Jan 26;14(3):429-39. PMID: 26774475.

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