Making science more sustainable!

Well done to our MSci student Katarina Pedersen on making a video for Cancer Research Demsytified about her thesis project, wherein she tested different methods for making biomedical research more sustainable. Katarina did a great job on the video & her project! You can watch here:

This is an extremely important endeavour, as biomedical labs are incredibly wasteful – we power through WAY too much single use plastic, we incinerate way too many bags of hazardous waste, and we use inefficient methods that could really use some improvement!

Katarina wrote an excellent editorial on this topic which you can read here:….

You can find out more about UCL sustainability here:…

And you can find out about the LEAF calculators which Katarina used for her research project here:…

As always, for more content like this – just search Cancer Research Demystified in your favourite social media platform! Thank you!

We NEED to make in vitro research more sustainable!

Our team member Katarina Pedersen recently pushed an editorial on sustainability in cell culture research. You can read it here!

Cell culture is the bread and butter of cancer research, but the methods we use to culture those cells are currently completely unsustainable – from huge volumes of single use plastic, to excessive incineration of waste, the whole procedure desperately needs shaking up. In the editorial, we offer some tips and resources for researchers on how to make their work more sustainable, and we implore laboratory suppliers to get serious about offering sustainable alternatives.

As well as being a timely and important piece of writing, this also represents Katarina’s first publication – a key research milestone! Well done Katarina!

Cancer Roundup: Cannabinoids, Immuno-Oncology, Spatial Biology & Summer Events!

This is the first in our new series of ‘Cancer Roundup’ videos, where we’ll take you through some advances in cancer research that have been discussed in the last month or so, in both the mainstream media and in the academic community, as well as one type of new cancer technology that has caught our eyes, and any local cancer research news we can update you on.

We feel we’ve covered most of the basics on this channel, and it’s time to focus on new & exciting areas of cancer research, as they emerge.

Please let us know if you enjoy this new format & thanks for engaging with us!


This month’s news story on cannabinoids

This month’s science story on immuno-oncology models

This month’s new ‘toy’ (technology), on spatial biology

This month’s local news, on our twinned summer events

Full programme announced – Join us on July 27th!

Novel spatial, molecular & imaging approaches to analyse 3D tissue models


14:00-14:10 Introduction and welcome

Dr Susan Heavey, UCL

Academic session:

14:10-14:35 Mass Spectrometry Imaging in Combination with 3D Tissue Models for Early Stage Efficacy and Safety Testing of Drugs and Toxicants

Prof. Malcolm Clench, Sheffield Hallam University

14:35 – 15:00 Imaging organoid responses to drugs

Prof. Trevor Dale, Cardiff University

15:00 – 15:15 Novel methods for investigating stiffness in 3D in vitro models

Ms Auxtine Micalet, UCL

15:15 – 15:40 A technological roadmap for 3D multi-omics and imaging for human disease modelling

Prof Je Hyuk Lee, Cold Spring Harbour Laboratory

15:40 – 16:10 Brainstorming session – what are our unmet needs for endpoint analyses, as 3D tissue model researchers?

Industry session:

16:10 – 16:30 SpheroMatrices: a spheroid tissue microarray (microTMA) platform for multiplexed analysis of 3D microtissue experiments

Dr Simon Plummer, Micromatricies

16:30 – 16:50 Morphology Driven High-Plex Spatial Analysis of Tissue Microenvironments 

Dr. Anthony Zucca, NanoString Technologies inc.

16:50 – 17:05 Unlocking Spatial Biology with Orion

Dr Tad George, RareCyte, Inc

17:05 – 17:20 Multiplex tissue imaging approaches for deep phenotyping with single-cell resolution

Dr Roslyn Lloyd, Akoya Bioscience

17:20 – 17:40 Spatially map and quantify the whole transcriptome in the tissue context with Visium spatial solutions

Dr Cristophe Fleury, 10X Genomics

17:40 – 18:00 Round table discussion – where do we see the future of spatial biology going?

Please note this is the second of a paid of twinned summer events from our centre – you can find out about the first event at the link below!

Novel spatial, molecular & imaging approaches to analyse 3D tissue models

Announcing a summer webinar for your viewing pleasure!

And not just viewing – we’ll be hoping to engage you in round table discussions and brainstorming sessions about the future of this exciting field! We’re still confirming the last couple of talk titles before announcing the full programme, but as readers of my blog you can register early here!

About this event

Advances in bioengineering have lead to a wide array of biomimetic 3D tissue models being used to study human health and disease. To best utilize and understand these exciting new models, it is key that we employ effective endpoint analysis that goes beyond traditional imaging or molecular approaches. In recent years, a range of new methods have been developed to interrogate the complex molecular microenvironment and architecture of 3D tissue models, many of which fall under the umbrella of ‘spatial biology’ – recognized recently as Nature’s method of the year 2020!

The aim of this virtual workshop is to meet with academic and industry leaders, to discuss new advances in endpoint analysis of 3D tissue models, including spatial transcriptomics, mass-spectrometry imaging, and highly multiplexed immunofluorescence. New approaches such as these allow us to better understand the biology underpinning our 3D tissue models, and we will compare and contrast their utility during round table discussions. We will share expertise, build networks and consider the future directions of this emerging field.

When the full programme is available I’ll post it here so you can get excited, and I look forward to seeing you on Tuesday 27th July!

How to select the best Spatial Transcriptomics platform for your work!

In recent years, spatial transcriptomics has gone from being a long-shot futuristic technology that many were sceptical of, to one of the trendiest and mostly widely attempted omics methods on the market. Having once been the handywork of a few isolated academic labs developing methodologies in-house, it is now commercially available from a wide range of competing companies, with kits, specialised pieces of equipment, and bespoke analysis pipelines at the ready.

Data in this image is adapted from
Image source:

Assuming you like the idea of seeing thousands of genes spatially resolved across your cells or tissue samples (and who wouldn’t?), and assuming you’ve got some funding at your disposal, how can you decide which method to paint your molecular picture with?

You will need to take into account the usual considerations when planning your research, as well as some methodology-specific and sample-specific requirements:

-Usual considerations: cost, equipment needed, time etc.

-Sample type (live cells / fixed cells / frozen sections / FFPE)

-Sample type (auto fluorescence?)

-Targeted or transcriptome-wide?

-Spatial resolution: anatomical features? Subcellular?

-Has it been demonstrated outside of originator’s lab?

Fortunately, the experts have already pulled together much of the method-specific requirements, which you can see summarised in the table below! Be sure to read the full paper (linked below the table), written by Michaela Asp, Joseph Bergenstråhle, and Joakim Lundeberg.

Table source:

With such exciting methods already available, I look forward to further development in this area, specifically:

•cBioportal/Cancertool for spatial datasets?

•Larger cohorts – spatial equivalent of TCGA?

•Automated spatial transcriptomics?

•High content spatial transcriptomics?

•Combining with spatial proteomics?

•Combining with spatial metabolomics?

•Combining with spatial epigenomics?

This is an exciting area with rapidly accelerating development, so I’m sure it won’t be long before these development become easily accessible. One preprint already seems to show improvement in several of these areas:

“Here, we advance the application of ST at scale, by presenting Spatial Multiomics (SM-Omics) as a fully automated high-throughput platform for combined and spatially resolved transcriptomics and antibody-based proteomics.”

Are you using spatial transcriptomics yet? What is your method of choice?

Internet friends: help me answer a question!

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I’m currently working on a new video for Cancer Research Demystified, where I’m going to attempt to answer this lofty question. What is the biggest challenge in cancer research today?

For the video, I’ll summarise a few different perspectives on this: the patients, the advocates, the funders, the institutions, the public, and the researchers ourselves. The most common answer so far is of course ‘there’s more than one!’ so I’ll cover as many as I can, and give my two cents on what could be considered the one single greatest challenge.

The NCRI cover their top priorities here – (of which there are of course more than one!) and you can see similar lists from many other groups. But what is the biggest one?! I’ve been asking around on Twitter, Instagram and Facebook, and I’ve gotten 24 responses so far, mostly from other cancer researchers, but some from patients & funders too. Before I compile, compare & contrast these, I wanted to ask you too – what do you think is the single greatest challenge in cancer research today? I’ll give you a head start by saying that the answers I’m getting are falling into two few common themes: biology & barriers.

Does one of these jump out at you as being a bigger challenge than the others? Do you have something to add? Comment below or DM me on Twitter/Facebook/Instagram/Reddit/LinkedIn and I’ll discuss your thoughts (anonymised if via DM) in our upcoming video!

Human tissue models for the replacement of mice in cancer research: Are we there yet?

I recently came across a review which asked if it’s time for peer reviewers to request ‘organ on a chip’ models instead of animal validation studies, and it got me thinking – are we there yet?

As cancer researchers, if we submit an article for publication that contains only data from cell lines, we’re often asked by peer reviewers to carry out animal studies – usually in mice. This review suggests that it might be nearly time for reviewers to ask for human tissue work instead – maybe some of our newest human tissue models are good enough to replace these types of animal studies?

Personally, I’m a big advocate for human tissue work in cancer research. Anyone who collaborates with me knows that I favour ex vivo / 3D culture of human tumours over mouse models. Of course there are ethical considerations here around reducing the number of animals used for research, but my opinion stems mostly from the science – because of the very simple fact that mice are not humans. The differences between mouse biology and human biology are too wide ranging, with far too many variables to feasibly take into account. Frankly, neither have been characterized rigorously enough to pick apart their similarities and normalize for their differences.

Of course, to date, mouse xenografts (and more recently, patient derived xenografts) are pretty much the best models we’ve got in terms of testing new cancer drugs in a better model than cell lines, without the ethical risks of testing them in living humans too early.

As such, many scientists like me around the world have been developing a huge range of human tissue models, usually removed from a cancer patient at biopsy or surgery, and donated for research. The idea being that one day we’ll get these cells or tissues to survive outside the body while changing as little of their biology as possible, and treat them with experimental drugs for research. Ultimately, replacing animal models.

Roughly speaking, these types of models fall into three categories: explant cultures, organoids/tumouroids, and ‘organ on a chip’ models.

Explant cultures involve taking a small piece of donated human tissue, and trying to keep it alive for a few days in an incubator, helped along by different nutrients and materials. One of the main benefits of explants is that the tissue stays whole, rather than the scientist isolating out particular cell types. The original architecture of the tissue, and range of different cell types within it can remain somewhat intact (this isn’t perfect, but it’s improving). I’ve been using a version of explants for the last five years, testing new drugs in prostate cancer, as part of my fellowship project ‘SCREEN’, kindly funded by Prostate Cancer UK.

Organoids, or specifically within our field of cancer research – ‘tumouroids’, represent human tumour cells that are grown in 3D outside of the human body, including multiple key cell types and environmental factors. Here the structure of the tissue does not remain intact as with explants, but key molecular signals added by scientists can induce the cells to organise themselves in the same way that the original tumour would have done in the human. These can be cultured for longer than explants generally, and offer more flexibility for the researcher to tweak particular aspects of their behaviour.

Organ on a chip models can be based on either of the above, but include additional extras like midrofluidics (a system that allows for nutrients to flow over and around the cells in the same way blood would in the body), which can encourage blood vessels to grow and feed the tumour, as they would in a human. These are getting ever closer replicating human tumours outside of humans.

But are any of these good enough to replace mouse experiments yet? My gut says no – but we really are very very close.

One of the issues with this branch of cancer research is that there are just so many different types of models being investigated. Yes, they do fall roughly within three categories, but within each of these categories, there are dozens if not hundreds of iterations being researched around the world. In my view, to properly validate them, we need a consensus – not a new model every five minutes! This consensus will be difficult to achieve, as within the structure of academic research we are encouraged to generate new intellectual property (IP), and we’re generally taught that to get a model validated and used in the clinic, we need to either commercialize it ourselves, or licence it to a company who will develop it for us. This is the approach that will get us the next grant, the next paper, the next promotion – i.e. more cred, and potentially personal financial gain. So why would we bother to further develop, independently validate and rigorously characterize someone else’s model, when we could be changing it slightly to add our own ‘unique selling point’ and branding it as our own?

My hope is to reject this way of thinking. Over the first few years of my new lab, I am to compare and contrast the leading models from around the world in a fully independent setting, where I’m not backing any horse in the race – where I have no allegiance to one human tissue model over another – and just purely try to see if the best one(s) reflect how humans actually respond to anti-cancer treatments. If we can pull this unbiased validation and rigorous characterization off, then I truly believe the peer reviewer mentioned in the paper linked above should absolutely be asking researchers to validate their research in these human models rather than animal models.

It’s worth mentioning that I also tweeted this paper and got varying responses. While one person replied a jokey ‘I wonder what reviewer 3 wrote in the report :)’, another expressed caution:

And I agree somewhat – we still don’t have strong enough validation in my mind to fully replace animal studies. But should reviewers be requesting more human work incrementally as our models get better and better? Yes, I think so. They’re certainly worth carrying out in addition to animal studies – just maybe not instead of animal studies just yet.

Dr Dania Movia from Trinity College Dublin commented on the frustration of human tissue researchers still being required to validate their findings in animals instead of humans – why do we think of mice as a gold standard for how human biology behaves? It makes no sense, and I couldn’t agree more! While mouse models bring some valuable extra data that human models don’t have perfect yet, they’re certainly imperfect in a lot of other ways, and not the right place to validate a human model.

Check out the review linked at the top of this blog if you’d like to read a more technical summary of where the field is at (though the review is not specific to cancer research). And let me know what you think! Are we ready to replace animal models with human models today? Will be there in a year, in a decade, or ever?

Guidelines for reporting research

A quick blog this week as I’m in the midst of lots of teaching & grant writing! On this week’s teaching agenda I’ve got research reporting, research presentation skills, in vitro, in vivo, and in silico research, acute & chronic inflammation, image analysis and drug efficacy. I thought I’d share with you some of the resources we are using in one of these lessons (not compiled by me), as frankly – they’re quite useful!

Research reporting – something we all need to get right!

According the declaration of Helsinki, researchers and authors have a duty to make their results available publicly using accepted guidelines for ethical reporting.

Naturally we’ll be teaching our students general tips on which types of content should be included in the different sections of a general research paper. We also discuss why it’s important to report our research fully, and what can go wrong when we don’t!

We also give the students a list of guidelines for specific types of research reports. Some of these are slightly peripheral to my own research interests, and I found them quite interesting, so I thought you might too! If you’re new to research reporting, perhaps a bit rusty, or trying to remember one of those many many reporting acronyms, then here’s an overview that might be helpful for you.

EQUATOR have also developed a wizard that can be useful to help decide on how to report your research. This tool asks what type of research you are conducting, and identifies useful checklists to make sure you are include the required information in your report:

The list! (Courtesy of Prof Kurinchi Gurusamy):

•Consolidated Standards Of Reporting Trials (CONSORT)
–Design, analysis and interpretation of the RCT.

•Strengthening the Reporting of Observational studies in Epidemiology (STROBE)
–Reporting of observational studies

•Standards for Reporting Studies of Diagnostic Accuracy (STARD)
–Reporting of diagnostic accuracy studies

•Quality assessment of diagnostic accuracy studies (QUADAS 2)
–Quality assessment of diagnostic accuracy studies

•Transparent Reporting of a multivariable prediction model for Individual Prognosis Or
Diagnosis (TRIPOD)
–Reporting of prediction models

•Consolidated Health Economic Evaluation Reporting Standards (CHEERS)
–Reporting practices for economic evaluations of interventional studies

•Consolidated criteria for reporting qualitative research (COREQ)
–Reporting of qualitative data from interviews and focus groups

•Standards for reporting qualitative research: a synthesis of recommendations (SRQR)
–Reporting of qualitative data

•Consensus-based Clinical Case Reporting Guideline Development (CARE)
–Reporting of case reports

•Standards for Quality Improvement Reporting Excellence (SQUIRE)
–Reporting of quality improvement in health care

•Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)
–Reporting systematic reviews and meta-analyses

•Enhancing transparency in reporting the synthesis of qualitative research (ENTREQ)
–Reporting of systematic reviews of qualitative research

•Animals in Research: Reporting In Vivo Experiments (ARRIVE)
–Reporting of animal research

•Statistical Analyses and Methods in the Published Literature (SAMPL)
–Reporting of statistical methods and analyses of all types of biomedical research

Hopefully you’ll find this list as handy as I did – many thanks to Prof Gurusamy for compiling it & hopefully you’ll forgive the short blog this week – I’m off to continue my grant!!