What If a Simple Blood Test Could Detect Cancer? | Hani Goodarzi | TED

Summary

Scientists have identified 'orphan non-coding RNAs' or oncRNAs, a new class of small RNAs not coding for proteins, which are unique to cancer cells. These oncRNAs can be detected in blood samples, forming a molecular barcode for each cancer type. Leveraging AI, partial oncRNA barcodes in blood can be used to reconstruct the full barcode, aiding in early cancer detection and identification. This breakthrough has the potential to revolutionize cancer screening, making it more precise, sensitive, and accessible.

Takeaways

• 🔍 **Early Cancer Detection**: Identifying cancer in its earliest stages is crucial for treatment and saving lives.
• 🧬 **RNA's Role**: RNA, particularly non-coding RNAs, plays a significant role in cancer detection.
• 🌟 **Discovery of oncRNAs**: A new class of non-coding RNAs, termed oncRNAs, has been discovered that is specific to cancer cells.
• 🔬 **Transformation in Detection**: The discovery of oncRNAs has revolutionized the approach to non-invasive cancer detection from blood samples.
• 🧐 **Cancer Cell Biology**: oncRNAs provide insights into the biology of cancer cells, offering a window into tumor behavior.
• 🧬 **Genomic Reprogramming**: Cancer cells reprogram their genomic machinery, leading to the activation of silent parts of the genome and the creation of oncRNAs.
• 📖 **Digital Molecular Barcode**: oncRNAs act as a unique digital molecular barcode for different types or subtypes of cancer.
• 🩸 **Blood Sample Detection**: oncRNAs can be detected in blood samples, indicating the presence of cancer.
• 🤖 **AI and Machine Learning**: Machine learning and AI are used to reconstruct the full oncRNA barcode from partial information in blood samples.
• 🏥 **Clinical Application**: Preliminary studies have shown the potential of using oncRNAs to detect residual disease in breast cancer patients post-treatment.
• 🌐 **Future of Cancer Screening**: The speaker envisions a future where blood detection of cancers is precise, sensitive, and accessible.

Q & A

What is the significance of detecting cancer at its earliest stages?

Detecting cancer early is crucial because it is when it is most treatable, potentially saving countless lives by allowing for more effective interventions.

How does RNA relate to the detection of cancer?

RNA, particularly messenger RNA, is transcribed from DNA and serves as a template for protein synthesis. The discovery of a new class of non-coding RNAs, called oncRNAs, has transformed cancer detection approaches.

What are oncRNAs and why are they significant in cancer research?

OncRNAs, short for orphan non-coding RNAs, are small RNAs that do not code for proteins. They are significant because they are uniquely expressed in cancer cells and can serve as molecular barcodes for identifying the type or subtype of cancer.

How do oncRNAs change the approach to cancer detection?

OncRNAs allow for non-invasive detection of cancer through blood samples. They provide a digital molecular barcode that captures the identity of cancer cells, which can be detected and analyzed to identify the presence and type of cancer.

How do cancer cells hijack the cell's machinery to their advantage?

Cancer cells hijack the cell's machinery by increasing the expression of genes that promote tumor growth and spread, while silencing or down-regulating genes that normally keep cancer in check.

What is the role of genomic reprogramming in cancer cells?

Genomic reprogramming in cancer cells involves the activation of parts of the genome that are normally silent in healthy cells, leading to the production of oncRNAs, which are unique to cancer.

How can oncRNAs found in blood samples be used for cancer detection?

Although only a subset of oncRNAs are secreted into the blood, their presence can be detected in blood samples. Machine learning and AI can use this partial information to reconstruct the full oncRNA barcode and identify the type of cancer.

What is the potential impact of oncRNA-based cancer detection on clinical practice?

OncRNA-based detection can help identify residual disease in patients post-treatment, guiding clinicians on who needs additional treatment or monitoring. This can lead to more targeted and effective cancer care.

How does the speaker envision the future of cancer screening with oncRNAs?

The speaker envisions a future where blood detection of cancers becomes a reality, leveraging AI and oncRNA molecular barcodes to create a precise, sensitive, and accessible cancer screening method.

What is the significance of the preliminary study conducted on breast cancer patients?

The preliminary study on breast cancer patients demonstrated the potential of using oncRNAs to detect residual disease post-treatment, which is a significant step towards bringing this technology to clinical use.

Outlines

00:00

🧬 Early Cancer Detection with OncRNAs

The speaker discusses the importance of early cancer detection and introduces a new approach using a class of non-coding RNAs called oncRNAs. These RNAs, which do not code for proteins, are found in higher concentrations in cancer cells and can be detected in blood samples, offering a non-invasive method for cancer screening. The discovery of oncRNAs has revolutionized cancer detection by providing a unique molecular barcode for different types of cancer, allowing for early diagnosis and a deeper understanding of cancer biology.

05:01

🔎 Machine Learning and AI in OncRNA Detection

The speaker explains how machine learning and AI are used to reconstruct the full molecular barcode of oncRNAs from partial information obtained from blood samples. This technology enables the detection and identification of cancer types or subtypes with high precision. A preliminary study with breast cancer patients demonstrated the effectiveness of this method in detecting residual disease post-treatment, guiding clinical decisions on additional treatment or monitoring. The speaker envisions a future where blood-based cancer detection becomes a standard part of cancer screening, made possible by the integration of AI and oncRNA molecular barcodes.

Keywords

💡Cancer Detection

Cancer detection refers to the identification of cancerous cells or tumors in the body at an early stage. In the video, the speaker discusses the importance of catching cancer early when it is most treatable. The theme revolves around innovative methods for detecting cancer, specifically through the analysis of RNA, which is a central focus of the video's narrative.

💡RNA

RNA, or ribonucleic acid, is a molecule essential in various biological roles, including coding, decoding, regulation, and expression of genes. In the context of the video, RNA is highlighted as a key to understanding and detecting cancer due to its role in protein synthesis and its presence in cancer cells. The speaker mentions that RNA has become well-known due to the COVID-19 pandemic and its relevance in the development of vaccines.

💡Messenger RNA (mRNA)

Messenger RNA is a type of RNA that conveys genetic information from DNA to the ribosome, where it directs the synthesis of proteins. The video explains that while typical mRNA is involved in protein production, the newly discovered oncRNAs do not code for proteins, which is a departure from the usual function of mRNA.

💡Non-coding RNA

Non-coding RNA refers to RNA molecules that do not code for proteins. In the video, the speaker introduces oncRNAs as a class of non-coding RNAs that have been pivotal in transforming cancer detection methods. These oncRNAs are unique to cancer cells and are not found in healthy cells, making them a significant biomarker for cancer.

💡OncRNAs

OncRNAs, short for 'orphan non-coding RNAs,' are a newly discovered class of small non-coding RNAs that are unique to cancer cells. The video emphasizes that these oncRNAs provide a 'digital molecular barcode' for cancer cells, which can be detected in blood samples, thus revolutionizing the approach to cancer detection and understanding.

💡Genomic Recipes

The term 'genomic recipes' is used metaphorically in the video to describe the complex genetic instructions within cells that guide the expression of genes. Cancer cells are said to 'hack' these recipes to promote their growth and survival, which results in the production of oncRNAs, a key concept in the video's discussion on cancer detection.

💡Cancer-emergent RNAs

Cancer-emergent RNAs are RNA molecules that are produced as a consequence of the genetic reprogramming that occurs in cancer cells. The video explains that these RNAs are not present in healthy cells but are activated in cancer cells, leading to the creation of oncRNAs that can be detected in blood samples.

💡Digital Molecular Barcode

A 'digital molecular barcode' refers to the unique pattern of oncRNAs that can be detected in cancer cells. The video describes how this barcode is specific to the type or subtype of cancer and can be used to identify the presence and nature of cancer through the detection of oncRNAs in blood samples.

💡Machine Learning and AI

Machine learning and artificial intelligence are mentioned in the video as tools that can be used to analyze partial oncRNA barcodes detected in blood samples. These technologies help in reconstructing the full barcode present in the tumor and matching it against known oncRNA patterns to detect and identify cancer types.

💡Blood Detection of Cancers

Blood detection of cancers is a method discussed in the video where oncRNAs are detected in blood samples to identify the presence of cancer. This approach is highlighted as a major frontier in cancer screening, offering a non-invasive and accessible way to detect cancers early.

Highlights

Catching cancer at its earliest stages can save countless lives.

The challenge is identifying a small group of rogue cancer cells in a healthy body.

RNA, particularly non-coding RNAs, may be key to early cancer detection.

Messenger RNA serves as a template for protein synthesis, with more mRNA correlating to more protein.

A new class of non-coding RNAs, called oncRNAs, has been discovered.

OncRNAs do not code for proteins and have transformed cancer detection approaches.

These RNAs are found in cancer cells and can be detected in blood non-invasively.

Cancer cells hijack cellular machinery to increase the expression of genes that promote tumor growth.

Genomic reprogramming in cancer cells leads to the activation of normally silent parts of the genome.

The activation results in the creation of oncRNAs, which are unique to cancer cells.

OncRNAs provide a digital molecular barcode that captures the identity of cancer cells.

OncRNAs are not confined to cancer cells; some are released into the blood.

The presence of oncRNAs in blood samples can indicate the presence of cancer.

Machine learning and AI can reconstruct the original oncRNA barcode from partial information in blood.

This technology can detect the presence of disease and identify its type or subtype.

A preliminary study showed the potential of oncRNAs in detecting residual disease in breast cancer patients post-treatment.

The technology helps clinicians determine which patients need additional treatment or monitoring.

The speaker envisions a future of precise, sensitive, and accessible blood detection of cancers.

Blood detection of cancers is presented as a reality, not just a hope, for the future of cancer screening.

Transcripts

Catching cancer at its earliest stages,

when it's most treatable, can save countless lives.

But the million-dollar question is:

in an otherwise healthy body made up of trillions of cells,

how can we zero in on a small group of rogue cancer cells?

The answer, I think,

may be rooted in something that, thanks to the pandemic,

we have all come to know quite well, and that is RNA.

I think these days, everyone has a basic understanding of how RNA works.

Again, thanks to the COVID vaccines.

But basically, RNA is transcribed from DNA in the cell,

and messenger RNA specifically serves as a template for protein synthesis.

So usually the more mRNA you have in the cell,

the more protein you get.

But our discovery is a little bit different.

We have found a new class of RNAs

that have changed how we think about cancer detection.

These are relatively small RNAs,

and they don't actually code for any protein.

So they're non-coding.

And since we found them, we got to name them.

And we have called them orphan non-coding RNAs

or oncRNAs for short.

These oncRNAs have not only changed

and transformed our approach to cancer detection

from blood non-invasively,

but they've also helped open a window into the tumor itself for us.

So leveraging these RNAs,

we are not only detecting cancer earlier,

we are actually peering into its biology.

So with that short introduction, let me break down the science for you.

As you may know, every cell in our body shares the same genetic code

as every other cell.

It's as if our cells have access to the same pantry,

but then they use different recipes

to mix the same ingredients into different dishes.

It's actually the diversity in genomic recipes

that gives us the more than 200 cell types we have in our bodies,

each with their own distinct role and function,

like skin cells, for example, or neurons.

And as you can imagine,

there is a complex machinery in place in the cell that governs this process

and tells the cell for each of its 20,000 genes

how much of them it needs to express

to be a healthy, well-functioning cell.

Now, cancer cells, being the resourceful survivalists that they are,

they actually hijack components of this machinery to their advantage.

And they do this to increase the expression of genes

that will help the tumor grow and spread throughout the body,

or silence or down-regulate genes whose job is to keep cancer in check.

Another way of putting this

is that cancer cells are basically hacking that original genomic recipe

that I told you about.

Now a few years ago, we made an interesting discovery

that is actually a consequence of this genomic reprogramming

that happens in cancer cells, is actually a hallmark of cancer.

Basically, parts of the genome that is normally silent

and inactive in healthy cells

becomes activated in cancer.

And a direct consequence of this activation

is the birth of a new kind of RNA.

That we only see these RNAs in cancer,

but not really in healthy cells.

Now over the past few years,

we have spent a lot of time basically mapping these cancer-emergent RNAs

across human cancers.

And as I told you earlier,

we have come to name them oncRNAs.

Now, what is even more interesting

is that which oncRNAs I see in a given sample is not random.

It's actually tied back to the type or subtype of cancer

that I'm looking at.

So collectively, oncRNAs actually provide a digital molecular barcode

that captures cancer cell identity.

And it's actually unique to the type or subtype of cancer.

But how are these molecular barcodes actually useful?

So it turns out oncRNAs are not actually confined to cancer cells.

Some of them are nicely packaged and released into the blood.

And this is something that healthy cells do as well with other small RNAs.

And with all of this introduction, I hope you know where I'm going with this.

Basically, if oncRNAs are only expressed in cancer cells,

and some of them do in fact find their way into the bloodstream,

doesn't it mean that we should be able to detect them

in blood samples from cancer patients?

The answer, turns out, is yes, but with an asterisk.

So the oncRNAs that we detect in blood samples from patients

actually form a partial barcode.

And it's only a partial barcode

because only a subset of oncRNAs

are actually secreted from cancer cells into the blood.

And even a smaller subset can be reliably detected

in a small volume of blood.

However, thanks to the magic of machine learning and AI,

we can actually use this partial information

to reconstruct the original barcode that resides in the tumor.

And we can match that deconstruction

against our catalog of oncRNA barcodes across cancers

to not only --

to not only detect the presence of the disease,

but also identify its type or subtype.

And actually, as we grow,

fundamentally increase the number of these oncRNA catalogs that we have built,

we can go deeper and deeper into the biology of the disease as well.

Now, with help from our clinical collaborators at UCSF,

we have come a step closer to actually bringing this platform to the clinic.

In a preliminary study across 200 breast cancer patients,

we have actually shown that we can use oncRNAs

to detect residual disease in patients

after they have received treatment,

and knowing which patients have remaining disease,

tells clinicians who needs additional treatment or monitoring

after the surgery.

And this way, patients receive more treatment

only when it's needed.

I truly believe that the next decade is the decade of cancer screening.

And as you can imagine, blood detection of cancers

is a major frontier in that war.

And I hope to have convinced you today that leveraging powerful AI

built on top of molecular barcodes of oncRNAs,

we can envision a future that’s precise and sensitive,

but more importantly,

very accessible.

Blood detection of cancers is not just the hope,

but it's actually a reality.

Thank you.

(Applause)