Simona Cristea Profile picture
Dec 7 27 tweets 11 min read
Can we outsmart #cancer and stop it before it even starts?

Our brand new paper🔥@NatureComms reveals a novel stem-like cell population directly related to #breast tumor initiation.

Let's dig in🧵🧵 Image
First, quick background.

Sadly, everybody reading this knows breast cancer.

It is the most commonly diagnosed cancer in women, with a staggering 1 in every 8 women in the world receiving this diagnosis throughout their lifetimes.
Multiple factors have been shown to modulate breast cancer risk.

You might already know that:

An active lifestyle🏃‍♀️, a good diet 🥦 or breastfeeding 🤱 are protective, while high breast density, radiation exposure or hormone replacement therapy are detrimental. Image
Unfortunately, what you might not know is that the absolute risk reduction from such protective lifestyle factors is depressingly modest.

But, make no mistake and prepare to be shocked😳.

Breast cancer is one of the very few cancers that can be effectively prevented!
Enter Pregnancy🤰

A single full-term early pregnancy (< 25 yrs) decreases the lifelong risk of hormone receptor positive breast cancer (85% of all breast cancers) by an unbelievable 40%.

Later first pregnancies (> 30 yrs) are still protective, but less so. Image
Unfortunately, in practice, preventing breast cancer is not that easy. On the contrary.

We all know that full-term early pregnancies are not feasible as a population-level breast cancer prevention strategy.
There’s more:

The lifelong breast cancer risk of BRCA1/2 germline mutation carriers 🧬 is even further increased‼️ by pregnancies, reaching an unbelievable 80% for BRCA1+ carriers with one child. Image
The natural question now becomes:

Can we mimic the protective effect of early🤰with a 💊?

Let's try!

But in order to do this, we need to first map out the mechanisms by which pregnancy decreases breast cancer risk.
Past data @LabPolyak shows that p27+ (CDKN1B+) progenitors with high TGFB pathway activity are decreased after pregnancy.

Therefore, TGFB could regulates the proliferation & pool size of hormone-responsive mammary epithelial progenitors which are cell of origin in breast cancer. Image
If so,modulating the TGFB pathway could modulate breast cancer risk.

Let's test this.

1.Strategy🧭
Deplete p27+ progenitors via inhibition of TGFB. Decreasing these progenitors could prevent tumors.

2.Intervention⚡️
Short treatment with TGFB Receptor1 inhibitor in 2 rat models
In a mind-boggling experiment, after treating rats with the inhibitor (TGFBRi) for 10 days, we expose them to a potent carcinogen.

90% of untreated rats develop tumors, whereas only 40% of treated rats do!

‼️In other words: 50% of rats are tumor-free because of the treatment😯 Image
Digging deeper:

1. The treated rats have fewer tumors which develop later.

2. The mammary glands of tumor-free animals are histologically normal.

Hence: This treatment 💊 has a long-term cancer preventive effect without perturbing normal mammary physiology.

Why is this?
Enter molecular #scRNAseq data 🧬

We find that the TGFBRi treatment promotes epithelial features (shifted keratin distribution), and that all 3 main breast mammary gland epithelial populations (basal, luminal progenitor, mature luminal) are heavily perturbed by the treatment. Image
Surprisingly, in the single cell data, the TGFBRi treatment induces cell cycle proliferation of progenitors, as shown by unique groups of cells with strong expression of proliferation and cell-cycle markers popping up after treatment. Image
The most striking treatment-induced change is how a totally novel population with both epithelial basal & secretory features emerges right after treatment.

We term them Secretory Basal Cells (SBCs).

We identify SBCs in both rat strains and create a SBC characteristic signature. Image
We characterize SBCs in great detail, via experiments & computational analyses.

SBCs have strong mammary epithelial stem cell features. They are enriched in Terminal End Buds, a specialized structure consisting of stem cells & guiding pubertal mammary development & cancer risk. Image
Again surprisingly, SBCs are enriched in tissues from the mammary gland of high-risk conditions (women without any pregnancy-nulliparous vs. women with pregnancies-parous), as well as in tissues from BRCA1/2+ carriers.

Hence,SBCs are positively associated with breast cancer risk Image
Interactome analysis shows a central role for SBCs in the mammary epithelium.

SBCs are the most active cell type (highest number of connections/cell) and they most actively regulate insulin-IGF signaling, a critical pathways for mammary gland development & breast cancer risk. Image
Finally, we also validate the epithelial nature and presence of the SBC subpopulation experimentally in rat organoid data from both control and TGFBRi-treated rats.

In treated rats, this population is expanded, confirming SBC enrichment following treatment. Image
Let's recap📚

1. A novel breast epithelial population (SBC) emerges right after a TGFBRi short-term treatment which prevents tumors in 2 rat models.

2. SBCs are associated with increased proliferation.

3. SBCs are stem-like.

4. SBCs are enriched in high-risk cancer conditions
Taken together, these observations seem counter-intuitive🤔

But, biology is complex. What we believe is actually happening:

Treatment💊
⬇️
Transient increase📈in progenitor proliferation
⬇️
Long-term depletion of the progenitor pool
⬇️
Lifelong decrease📉in breast cancer risk Image
Take home messages‼️

1. Breast cancer is one of the few cancers for which a potent natural prevention strategy does exist.

Understanding the underlying mechanisms by which this happens is an immense opportunity still hidden in plain sight.
2. Breast cancer can be prevented by targeting TGFB-responsive mammary epithelial progenitors in 2 different rat models.

This offers preclinical evidence for the design of breast cancer prevention strategies initially targeting women at high risk of developing breast cancer 🧬
However, our results are still very preliminary.

There are immense challenges ahead on the way to clinical implementation⛰️

We’re thinking about these issues a lot and doing follow-up studies and experiments.
We believe cancer prevention is the future.

Cancers are evolutionary beasts. Fighting them is hard. Current cancer treatments are complicated & often don't work.

This is why stopping cancer before it starts is the way forward.

This is real & possible.
All #Bioinformatics #DataScience code and materials to support these results is on GitHub github.com/csimona/tumor-…

The raw and preprocessed genomics data is on GEO 0-www-ncbi-nlm-nih-gov.brum.beds.ac.uk/geo/query/acc.…

Preprocessed #RStats objects can be downloaded from Zenodo zenodo.org/record/7293642…
Finally, here is the link to the @NatureComms paper. Read it and get it touch!

This was a monumental effort spanning many years together with @LabPolyak @nellage & so many wonderful colleagues @DanaFarber @harvardmed @dfcidatascience

Thank you all!

nature.com/articles/s4146…

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More from @simocristea

Dec 9
#singlecell analysis is revolutionizing medicine and changing the way we look at disease.

New perspective article just out🚨@NatureMedicine reflecting on @humancellatlas: informative for both #singlecell lovers❤️& skeptiks🤔

Let's map out where the field stands & what is next🧵 Image
First, some context.

The genomics single cell field has started out 1-2 decades ago with a huge promise:

"Find the missing link between genes, diseases and therapies. This will bring completely novel therapeutics to the market & cure disease."
The underlying logic is straigtforward:

1. the cell is the main unit of living organisms
⬇️
2. cells break down in disease
⬇️
3. understanding cells helps understand how & why they break
⬇️
4. this helps with engineering new therapeutics
⬇️
5. new therapeutics will cure disease
Read 13 tweets
Dec 5
Can't keep up with all the interesting #ChatGPT prompts?

Nothing to worry about! I curated a 🧵for you with key messages & relevant tweets on where our new academic companion #ChatGPT excels or fails in writing #Bioinformatics code, academic grants & tutorials👇
1. Our new friend is very good with writing #Python and #RStats code.

1.1 Here, it teaches us plotting with pandas & matplotlib, together with explanatory text.

If you are in the process of learning/improving your Python skills, #ChatGPT is of real help.
1.2 It is amazing that it can also debug code really well. It finds bugs, explains them, then fixes them!

Read 28 tweets
Nov 21
New🔥TCR #CRISPR✂️ cancer #immunotherapy paper just out in @Nature by PACT Pharma & UCLA.

Why all the 📸headlines & press coverage?

This small proof-of-concept study can give us a glimpse into the future of cancer therapy.

Let’s unpack the details & relevance of this study👇🧵
First things first:

Here’s the link to the paper, which has been made public by @Nature in an unedited form (before official publication), due to its perceived immediate relevance to the research & clinical cancer communities.

nature.com/articles/s4158…
A. The context ✍️ of this work:

Most cancerous lesions have mutations in the 🧬of their cells.

Cancer cells (literally) display small pieces of cellular mutated proteins (called peptides) on their surface.

These peptides, called neoantigens, are important therapeutic targets.
Read 21 tweets
Nov 7
New🔥 #DataScience #Bioinformatics resource: 850,000‼️ #scRNAseq cells from 226 samples across 10 cancer types draw a map of the tumor microenvironment, in particular fibroblasts.

Let’s see👇what are the main contributions of this work & what this means for #cancer #Genomics🧵 Image
But first, some background.

Cancers are (unfortunately) complex ecosystems,consisting of various types of cells.

Malignant cells represent only a fraction of the tumor. The rest is made of the tumor microenvironment/TME (fibroblasts + immune cells), with complicated dual roles. Image
Understanding the essence of this duality is key in understanding why most cancer therapies fail.

TME cells are plastic & can easily change states.

The same TME cells can either promote or suppress tumor development, depending on very subtle factors totally not well understood.
Read 22 tweets
Nov 1
#GraphNeuralNetworks are way too cool to be left unexplored!

In a nutshell, GNNs are an exciting merger between graph theory (math) & #DeepLearning (coding).

Here's my detailed resource stack of best GNN theory explainers, videos & coding tutorials I used for my own learning.
1. This is a great place to start if you either: want to learn the basics, or enjoy reading about basic concepts explained in a well structured way.

It walks us through graphs in real world, what graphs & GNNs consist of, and how GNNs do prediction.

distill.pub/2021/gnn-intro/
2. Further, this next tutorial walks us through graphs & GNNs in an intuitive manner, while also going quite deep into the specific mathematical terminology of the field.

I like this one a lot because it also includes hands-on PyTorch code at every step.
theaisummer.com/graph-convolut…
Read 15 tweets
Oct 31
It’s that time of the year🎃when students are deciding if to apply for #PhDpositions👻

Even though #Academia is far from perfect:doing a #PhD is valuable.

It develops unique & important skills that will stay with you forever

These PhD skills are totally☹️not discussed enough👇 Image
1. Ability to work interdependently🔁(independently & with others).

Doing a PhD requires individual planning, as well as collaborating and working within teams. The ability to dive really deep into both these areas *simultaneously* is one of the defining features of a PhD.
2. Self-motivation & drive

Doing a PhD can also be hard & frustrating😮‍💨. You'll sometimes find yourself working alone, with no clear goals on the project, and no end in sight.

Making it work somehow nurtures your ability to motivate yourself when faced with hard situations.
Read 12 tweets

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