July 24, 2025 • 23 mins
🎙️ Episode 85: Genomic landscape of virus-associated cancers
🧬 In this episode of PaperCast Base by Base, we explore the comparative genomic analysis of virus-positive and virus-negative tumors across nine cancer types linked to five oncogenic viruses uncovering epidemiological patterns, mutational signatures, and therapeutic implications.
🔍 Study Highlights:
The authors aggregated genomic data from 1,971 tumors spanning nine virus-associated cancers and performed comprehensive analyses of mutation burden and driver mutations across virus-positive and virus-negative cases. They identified that virus-positive tumors generally have a lower somatic mutation load but frequent mutations in RNA helicases DDX3X and EIF4A1 and distinct mutation signatures compared to virus-negative tumors. Epidemiological analysis revealed higher male incidence and geographic disparities for virus-positive cancers, while immunotherapy response data indicated improved outcomes for virus-positive gastric cancer and head and neck squamous cell carcinoma. Comparative copy number and structural variant analyses highlighted recurrent chromosomal losses and translocations associated with viral infection status.
🧠 Conclusion:
These findings provide a pan-cancer perspective on the distinct genomic and clinical landscapes of virus-associated malignancies and suggest RNA helicase mutations and viral status as potential biomarkers for targeted therapies.
📖 Reference:
Nam Y, Gomez K, Reynier JB, Khamnei C, Aitken M, Zheng V, Lhakhang T, Casula M, Palmieri G, Cossu A, Levine A, Tiacci E, Rabadan R. Genomic landscape of virus-associated cancers. Nature Communications. 2025;16:5887. doi:10.1038/s41467-025-60836-9.
📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:14):
Welcome to Base by Base, the paper cast that brings genomics
to you, wherever you are. Today, we're kicking off a deep
dive into a truly compelling mystery.
Did you know that a significant portion of human cancer,
somewhere between say 15% to 20%globally, are actually linked to
infections and maybe 8% to 10% are caused directly by viruses,
(00:34):
these things often called oncoviruses?
Yeah. And what's really astonishing, I
think, is the sleeper agent nature of these links.
You know, a tumor might not evenemerge until years, sometimes
decades after the initial infections.
Wow. Exactly.
I mean, imagine cervical cancer developing maybe 25, even 30
years after an HPV infection, orliver cancer popping up 10 to 30
years after hepatitis B or C. These viruses definitely play
(00:57):
the long game. And that raises A fascinating
and really critical question, doesn't it?
How can a virus like Epstein Barr, EBV, which infects, well,
most of the global population, end up causing cancer in only
this tiny fraction of individuals?
And what really happens inside our cells when these viruses
finally, you know, push things towards malignancy?
(01:18):
This deep dive is all about uncovering the unique
characteristics that distinct biological blueprint of these
virus associated cancers. We're really looking for the
hidden pathways that make them tick differently.
Before we go any deeper though, we really have to acknowledge
the incredible research that brings us these kinds of
insights. It's the sort of work that
genuinely push at the boundariesof what we know.
(01:39):
Absolutely. Today we're celebrating the the
really groundbreaking efforts ofthe research team led by Raul
Rabadon and his colleagues. And we should definitely mention
Uninom and Karen Gomez, who contributed equally to this huge
undertaking. They're from top institutions
like Columbia University, the National Research Council in
Italy, and the Institute for Advanced Study.
(02:01):
Their comprehensive analysis, honestly, it's profoundly
advanced our understanding of the fundamental differences
between virus positive and virusnegative cancers.
It really feels like a game changer.
So let's unpack this a bit. We've known about oncoviruses
for a while, right? Yeah.
But what was this sort of big picture problem this study was
trying to tackle? What were we still missing?
(02:21):
That's exactly right. Arcoviruses aren't exactly new
to science. We know of seven that are
officially linked to human cancers.
Things like human papilloma virus, HPV, Epstein Bar virus,
EBV, hepatitis, B&C, human herpes virus 8, HTLV 1, and
Merkel cell polyoma virus. But here's the puzzle.
The exact factors that actually drive a normal infected cell to
(02:44):
become malignant, while they remain largely unknown.
And we especially lack understanding about what factors
are common across these different types of virus
associated cancers. And why is getting that common
understanding so crucial, you know, on a global scale?
Well, because these cancers represent a really substantial
global health burden and they disproportionately affect
developing countries where the incidence rates can be
(03:06):
significantly higher. So identifying those
commonalities across these various virus associated cancers
could potentially unlock entirely new broad strategies
for prevention and treatment. It could impact millions
worldwide. Understood.
So if we look at the oncoviruseswe know about what are some of
the general patterns that researchers have already
(03:27):
observed over time? Well, first, they all tend to
cause persistent long term infections.
The tumors often appear years like we said, even decades after
the initial exposure. That's pattern one.
OK, persistence. Second, these viruses produce
specific proteins, viral proteins that directly
contribute to turning a normal cell cancerous.
The classic example you know is HP VS E6 and E7 oncoproteins.
(03:50):
Right, I've heard of those. Yeah, they famously shut down
critical tumor suppressor gene like P53 and RB.
They basically disarm the cells natural brakes against
uncontrolled growth. Got it.
And 3rd, and this is a really critical point, the viral
infection itself isn't always enough to cause cancer.
Think about EBV. Something like 90 to 95% of
(04:11):
people worldwide are infected HPV.
Around 80% of individuals will get an infection by age 45.
Wow, that high. Exactly.
Yet only a tiny, tiny fraction of those infected people ever
actually develop cancer. This strongly suggests that
other factors may be genetic, may be environmental.
Perhaps immune factors are also at play, pushing that infected
(04:34):
cell towards malignancy. And this study then really dives
into those very factors you justmentioned.
It's searching for those deeper connections beyond just is the
virus there or not? Precisely.
The team pulled together just anenormous amount of data.
Nearly 2000 tumors across 9 different cancer types linked to
five different viruses. Their whole mission was to
identify common patterns in epidemiology.
You know who gets them and where, but also the unique
(04:56):
genomic changes inside these cancers and even how these
tumors respond to therapy. It's a true big data approach to
tackle a massive biological puzzle.
That sounds like quite an undertaking.
So how did the researchers actually get to the bottom of
these differences between the virus positive and the virus
negative tumors? What kind of sophisticated tools
(05:16):
did they use for such a widespread analysis?
Yeah, this was a colossal comparative analysis.
They aggregated somatic mutationdata from 1971 tumors and this
was a mix of data types, whole exome sequencing, targeted DNA
sequencing, whole genome sequencing pulled from a range
of previously published studies,plus they generated brand new
(05:39):
data specifically for Kaposi sarcoma.
This allowed them to compare genetic changes across a really
wide spectrum of cancers, but using a consistent methodology,
which is key. So they were really scrutinizing
the the genetic changes within the tumor cells themselves,
looking deep inside. Yes, absolutely.
Deep genomic analysis are reallythe core of their work.
(05:59):
For instance, they map mutation signatures.
These are like unique fingerprints left on the DNA by
different kinds of damage processes.
Underprints. OK, Yeah.
Imagine each type of DNA damage,say from smoking or UV light,
leaves its own characteristic pattern, its own mark.
They were able to read those marks to understand the
underlying causes of the mutations.
Interesting. They also looked at things like
(06:20):
structural variants and copy number changes in the
chromosomes, basically big rearrangements or changes in how
many copies of certain genes there are.
Right. And they analyzed chromosomal
instability signatures. These tell you how often
chromosomes are being sort of missegregated or lost during
cell division, which indicates Achaotic cellular environment
(06:41):
that often promotes cancer. So a sign of instability.
Exactly. And finally, they zoomed right
in on recurrently mutated genes.They were searching for specific
genes that were altered much more frequently in the virus
positive versus the virus negative tumors, looking for
those key genetic switches that might be different.
That's a lot of genomic detective work, but did they
also look at how these genetic differences might play play out
(07:03):
clinically, especially, you know, in terms of how patients
respond to treat? Absolutely.
That was a crucial part of theirmethodology.
They evaluated how the virus status correlated with the
response to immunotherapy, specifically the PDL 1
inhibitors, which are a major class of cancer drugs now.
Right, the checkpoint inhibitors.
Exactly. And they did this by
(07:24):
meticulously analyzing data from32 different clinical trials.
That's an impressive scope. So they weren't just looking at
the genetic blueprint, they wereconnecting it to real world
patient outcomes. That's a powerful combination,
connecting the lab bench directly to the patient's
bedside, essentially. Indeed, and to really understand
the why behind that immunotherapy response, they
(07:47):
also delved deep into the tumor's immune microenvironment.
The neighborhood around the tumor.
Precisely. They looked at things like PDL
one expression which is kind of like a don't attack me flag that
cancer cells can wave to hide from the immune system.
They also studied the infiltration of CD 8 + T cells.
These are the immune system's direct killer cells, the ones
that actually attack cancer. The.
(08:08):
Frontline soldiers. You got it, and they analyzed T
cell receptor clonal selection. This basically tells you how
focused and effective the immunesystem's search and destroy
mission is against those specific cancer cells.
This kind of holistic approach allowed them to connect the dots
across different levels, from the DNA itself to the broader
(08:28):
immune system's interaction withthe tumor.
OK, so after all that meticulousanalysis, wading through all
that data, what? Were the most.
Striking, maybe even surprising discoveries that emerged from
their deep dive. Well, the findings were quite
remarkable actually, and they illustrated some really distinct
trends that truly differentiate these virus associated cancers.
Let's start with who gets these cancers?
(08:50):
Did they find any clear demographic patterns?
Yes. One very notable observation was
a higher frequency of virus positive tumors in males across
the board. Really virus associated cancers
showed a greater male to female ratio compared to their non
viral counterparts. This trend was particularly
clear in things like gastric cancer and Hodgkin lymphoma.
(09:11):
Interesting. And geography plays a role too,
right? It's not just about sex
differences. Yeah.
Exactly right. There are notable geographic
hotspots. For example, EBV positive
Hodgkin lymphoma is more common in places like North Africa, the
Middle East, and South America, whereas EBV positive
nasopharyngeal carcinoma is highly concentrated in China and
(09:31):
Southeast Asia. And these disparities aren't
just random. They reflect real differences in
risk factors like how common theoncovirus is in that population,
but also local lifestyle factorsthat can influence cancer risk.
OK, now shifting gears to the very heart of the cell, the DNA
itself. What did the genomic analysis
reveal about the differences in mutations between these virus
(09:53):
positive and virus negative tumors?
Right, this is where it gets really, really interesting.
Generally speaking, virus positive tumors had a lower
count of somatic mutations. Those are the non inherited ones
that accumulate over time compared to their virus negative
counterparts. Lower mutation count.
Yes, lower count. This was a pretty consistent
finding across most of the cancers they studied, like head
(10:13):
and neck squamous cell carcinomaand primary central nervous
system lymphoma. It strongly suggests a different
pathway to malignancy is being used.
But there's always an exception that kind of proves the rule,
isn't there. You know it in hepatocellular
carcinoma, that's a type of liver cancer, and also in
Birkett lymphoma, the virus positive cases actually showed a
(10:34):
greater total mutation load. Oh, OK, so the opposite.
The opposite. Yeah.
These cases where virus positivetumors actually have more
mutations are really intriguing.It suggests that maybe in some
scenarios the virus isn't just reducing the need for mutations,
but it might actually be causingsome DNA damage itself.
Or perhaps, like in Birkett lymphoma, specific viral
(10:56):
proteins like EBNA one can directly substitute for the need
for those classic cancer drivinggene mutations.
OK, that makes sense. Any other surprising mutational
insights that really stood out? Yes, the mutation signatures,
those fingerprints we talked about were quite distinct.
For example, HPV positive head and neck cancers showed a much
higher presence of something called APOBEC mutations.
(11:18):
Yeah, these suggest that the HPVproteins might actually be kick
starting some of our own cellular enzyme enzymes that
normally fight viruses. But in this context, they
ironically end up causing more mutations in the host DNA.
It's like a defense mechanism gone wrong.
Like friendly fire. Kind of, yeah.
In contrast, if you look at Merkel cell carcinoma, the virus
positive tumors had significantly fewer UV light
(11:41):
related mutations compared to the virus negative ones.
This strongly implies that the virus itself is taking over the
primary cancer initiation role, reducing the need for sun use to
DNA damage to get the cancer started.
And what about the specific genes that were frequently
mutated? Were there clear patterns there
too, beyond the overall count orthe signatures?
Yes, and this is a truly key finding.
(12:03):
Virus negative tumors had significantly higher odds
mutations in common well known tumor suppressor genes like TP
53 and CDK and two a the. Usual suspects.
Exactly the usual suspects. These are genes we often
immediately associate with cancer development, acting as
those crucial breaks on cell growth.
But in stark contrast, the viruspositive tumors showed increased
(12:24):
mutations and a specific set of RNA helicase genes, particularly
DDX 3X and eif 4A1. RNA helicases.
That sounds specific. It is.
And DDX 3X mutations, very interestingly were strongly
associated with EBV positive bricate lymphoma.
And here's a really striking detail. 96% of the truncating
(12:45):
DDX 3X mutations, those are the ones that essentially break the
gene and cause a loss of its function, occurred in males. 96%
in males. That male bias in DDX 3X,
especially with the loss of function mutation.
That's really fascinating. So it points to very distinct
genetic pathways being active depending on whether a virus is
present. Precisely, it strongly suggests
that the virus itself is providing alternative oncogenic
(13:07):
mechanisms, alternative ways to drive cancer.
This essentially reduces the needle for the cells to acquire
mutations in those traditional tumor suppressors like TP 53.
The virus is doing some of that oncogenic work if you will, and
that loss of function for DDX 3Ximplies it can no longer do its
normal job, which might include keeping the cell in check.
So losing it could act as a major accelerant for certain
(13:30):
virus associated cancers, particularly it seems in men.
The clinical implications of that finding, thinking about
treatment, seem truly significant.
What does this mean for how doctors might approach patient
care based on virus status? Right.
This is perhaps one of the most immediately impactful findings
for patients and for clinicians.The study found a really
(13:51):
significant association between virus positivity and a higher
treatment response rate to thosePDL 1 immunotherapies.
High response. Higher response.
This was especially evident in gastric cancer and head and neck
squamous cell carcinoma. And this finding is particularly
surprising because as we said, virus positive tumors generally
have that lower total mutation burden.
(14:13):
Typically, a high mutation burden is thought to correlate
with a better immunotherapy response because more mutations
mean more targets for the immunesystem.
Right, that's the usual thinking, exactly.
So this study kind of flips thatconventional wisdom on its head,
at least for these specific virus associated cancers.
So why the better response then if it's not simply due to a
higher mutation burden? What's happening differently in
(14:35):
the immune system in these cases?
That's the $1,000,000 question, isn't it?
And the researchers really dug into it.
What they observed in the virus positive gastric and head and
neck cancers was increased CD 8 + T cell infiltration.
More killer T cells getting intothe tumor.
Exactly. And higher T cell receptor
clonal selection. What this combination means is
(14:56):
that the immune system, specifically those powerful
killer T cells, seems to be moreactively recruited to the tumor
and more specifically targeted against those virus associated
tumor cells. So the immune system is already
more engaged. It seems so.
This pre-existing, more robust immune activity likely makes
them more susceptible to immunotherapy.
(15:16):
The immunotherapy drug then justacts like a switch or maybe like
taking the foot off the brake tofully reactivate and boost that
already present response. So connecting all these dots,
what does this all mean when we look at the bigger picture of
how cancer develops and how we might treat it?
Well, I think the study profoundly highlights that virus
associated cancers really are a distinct biological entity.
(15:38):
They're not just cancers that happen to have a virus hanging
around. They have their own unique
epidemiological patterns, a verydifferent genomic landscape,
and, crucially, unique therapeutic vulnerabilities.
It builds strongly on previous work by showing these
commonalities across a really broad range of cancer types, not
just looking at one cancer in isolation.
(15:58):
That male predominance you mentioned earlier for virus
associated cancers, that really stood out.
Any more thoughts on why that might be the case?
It's a fascinating question. It could very well be linked to
some kind of immunological predisposition.
We know that females generally exhibit a more robust immune
response to infections overall. This is influenced by a complex
(16:19):
mix of factors, you know, from genes on the X chromosome to
hormonal differences. This potentially stronger immune
surveillance in females might offer some protective advantage
against the virus persisting long enough or triggering the
changes needed for cancer development.
OK. That makes sense.
And the lower overall mutation burden in most of these virus
positive tumors, that's quite a departure from what we often
(16:42):
think about with many other cancers driven by environmental
damage or aging. What's the leading hypothesis
there again? Yeah.
What's really fascinating here is the hypothesis that the viral
proteins themselves are providing much of the necessary
oncogenic activity, the hits needed to turn a cell cancerous.
This then reduces the selective pressure for the host cell to
(17:02):
acquire numerous additional somatic mutations to become
fully malignant. So the virus is essentially
driving the car, meaning you don't need as many individual
engine modifications, so to speak.
That's a good analogy, Yeah. The virus is doing a lot of the
driving. Let's delve just a bit more into
those. Specific.
RNA helicase gene mutations. You mentioned DDX 3X and EIK
4A1. Why are they so significant
(17:25):
specifically in virus associatedcancers?
What are these genes normally do?
Right. So these are NA halocases.
You can think of them as molecular unravelers or maybe
rewinders in our cells. They're crucial for reading and
processing our genetic code stored in RNA.
They play key roles in really fundamental cellular processes
and also, interestingly, in innate immunity, the body's
(17:47):
first line of defense against pathogens.
DDX 3X in particular, is complex.
It can act as both a tumor suppressor and surprisingly
sometimes as an oncogene, depending on the cellular
context. It's frequent mutation in these
cancers, especially that striking male bias for the
truncating loss of function mutations strongly suggests that
losing DDX 3X function might be a really key step in the
(18:10):
development of certain virus associated cancers like EVD
positive Birkitt lymphoma. It really opens up new avenues
for understanding their specificpathogenesis and maybe
developing therapies that targetthis pathway.
And circling back to the immunotherapy response, that
positive signal and virus positive cancers, that feels
like a potential paradigm shift for how we treat these specific
cancers. What does this mean for patients
(18:32):
and doctors moving forward? It really is a powerful
implication. The increased T cell
infiltration and the focused clonal T cell response in virus
positive gastric and head and neck cancers strongly suggest
that the high immunogenicity, the ability to provoke an immune
response of the viral antigens, the viral proteins within these
(18:53):
tumors actually primes the immune system to recognize and
attack them from the start. So the immune system sees the
viral bits as foreign. Exactly.
Immunotherapy then acts like this potent switch, reactivating
and supercharging that pre-existing immune response,
making it far more effective than it might be in a tumor
without those viral flags. This could genuinely mean that
(19:13):
assessing a patient's virus status becomes a critical
biomarker for predicting whetherthey're likely to respond well
to immunotherapy. So a new tool for doctors?
A new tool? Absolutely.
Imagine we now have a new, perhaps unexpected biomarker to
help guide potentially life saving immunotherapy decisions,
especially in cancers where maybe it wasn't previously
considered as effective. Now with any study this broad,
(19:36):
are there any limitations to keep in mind or clear next steps
needed for this line of research?
Oh, absolutely. As with any comprehensive study
like this, there are always nuances.
This analysis, for instance, focused on the most
significantly differentially mutated genes across the entire
pan cancer cohort they studied. What that means is some known
(19:56):
associations that occur in specific cancer types might not
have met the stringent statistical threshold needed for
pan cancer significance in this analysis.
For example, mutations in the promoter region, which are known
to be common in HPV positive head and neck cancers, weren't
captured here because the study primarily focused on mutations
within the protein coding parts of genes, the exons, and
(20:19):
generally excluded promoter regions.
So technical limitations based on the analysis.
Scope, exactly. So future studies will
definitely need to incorporate larger, perhaps even more
diverse cohorts. And they'll need to look at
additional genetic factors like those promoter mutations and
also epigenetic genetic factors,changes that affect gene
activity without changing the DNA sequence itself, to further
(20:40):
expand and refine our understanding.
There's always more to learn, more layers to peel back.
So ultimately, this study reallypaints a picture of two quite
distinct models for how cancer can develop, doesn't it?
Yes, I think that's a great way to put it.
One model is where accumulated random mutations, perhaps from
aging or exposure to environmental carcinogens, drive
(21:01):
the process forward in the absence of a viral infection.
That's kind of the classic view for many cancers.
And the other model highlighted here is where a viral infection
first establishes A persistent latent state and then specific
subsequent mutations, often in these different genes like the
RNA helicases DDX 3X and eif 4A1contribute to the final
(21:22):
malignant transformation. This fundamental distinction is
absolutely critical if we want to develop more targeted, more
effective therapies that are tailored to the unique biology
driving these different cancer pathways.
So if our listeners take just one key thing away from this
deep dive today, what should it be?
I'd say it's that our understanding of cancer just got
significantly richer. This study clearly reveals that
(21:45):
virus associated cancers are a truly distinct category.
They're characterized by unique epidemiology, who gets them
where, and perhaps why. They often have a lower overall
mutation burden, but with specific crucial driver
mutations in genes like DDX 3X and EIF 4A1.
And importantly, they show greater responsiveness to
(22:06):
certain immunotherapies. And this distinct biology offers
completely new pathways not justfor understanding how cancer
develops, but, crucially, for improving treatment strategies
for potentially millions of people around the globe.
Exactly. And it leaves us with a really
important question to ponder. What does this mean for how we
should approach cancer prevention and treatment going
forward, especially in those parts of the world where these
(22:28):
viral infections are most prevalent?
It's a question that could genuinely change lives.
This episode was based on an Open Access article under the
CCBY 4 Point O license. You can find a direct link to
the paper and the license in ourepisode description.
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(22:51):
makes a huge difference in helping others discover the
show. Thanks for listening and join us
next time as we explore more science base by Base.
Welcome to Base by Base, the paper cast that brings genomics
to you, wherever you are. Today, we're kicking off a deep
dive into a truly compelling mystery.
Did you know that a significant portion of human cancer,
somewhere between say 15% to 20%globally, are actually linked to
infections and maybe 8% to 10% are caused directly by viruses,
(00:34):
these things often called oncoviruses?
Yeah. And what's really astonishing, I
think, is the sleeper agent nature of these links.
You know, a tumor might not evenemerge until years, sometimes
decades after the initial infections.
Wow. Exactly.
I mean, imagine cervical cancer developing maybe 25, even 30
years after an HPV infection, orliver cancer popping up 10 to 30
years after hepatitis B or C. These viruses definitely play
(00:57):
the long game. And that raises A fascinating
and really critical question, doesn't it?
How can a virus like Epstein Barr, EBV, which infects, well,
most of the global population, end up causing cancer in only
this tiny fraction of individuals?
And what really happens inside our cells when these viruses
finally, you know, push things towards malignancy?
(01:18):
This deep dive is all about uncovering the unique
characteristics that distinct biological blueprint of these
virus associated cancers. We're really looking for the
hidden pathways that make them tick differently.
Before we go any deeper though, we really have to acknowledge
the incredible research that brings us these kinds of
insights. It's the sort of work that
genuinely push at the boundariesof what we know.
(01:39):
Absolutely. Today we're celebrating the the
really groundbreaking efforts ofthe research team led by Raul
Rabadon and his colleagues. And we should definitely mention
Uninom and Karen Gomez, who contributed equally to this huge
undertaking. They're from top institutions
like Columbia University, the National Research Council in
Italy, and the Institute for Advanced Study.
(02:01):
Their comprehensive analysis, honestly, it's profoundly
advanced our understanding of the fundamental differences
between virus positive and virusnegative cancers.
It really feels like a game changer.
So let's unpack this a bit. We've known about oncoviruses
for a while, right? Yeah.
But what was this sort of big picture problem this study was
trying to tackle? What were we still missing?
(02:21):
That's exactly right. Arcoviruses aren't exactly new
to science. We know of seven that are
officially linked to human cancers.
Things like human papilloma virus, HPV, Epstein Bar virus,
EBV, hepatitis, B&C, human herpes virus 8, HTLV 1, and
Merkel cell polyoma virus. But here's the puzzle.
The exact factors that actually drive a normal infected cell to
(02:44):
become malignant, while they remain largely unknown.
And we especially lack understanding about what factors
are common across these different types of virus
associated cancers. And why is getting that common
understanding so crucial, you know, on a global scale?
Well, because these cancers represent a really substantial
global health burden and they disproportionately affect
developing countries where the incidence rates can be
(03:06):
significantly higher. So identifying those
commonalities across these various virus associated cancers
could potentially unlock entirely new broad strategies
for prevention and treatment. It could impact millions
worldwide. Understood.
So if we look at the oncoviruseswe know about what are some of
the general patterns that researchers have already
(03:27):
observed over time? Well, first, they all tend to
cause persistent long term infections.
The tumors often appear years like we said, even decades after
the initial exposure. That's pattern one.
OK, persistence. Second, these viruses produce
specific proteins, viral proteins that directly
contribute to turning a normal cell cancerous.
The classic example you know is HP VS E6 and E7 oncoproteins.
(03:50):
Right, I've heard of those. Yeah, they famously shut down
critical tumor suppressor gene like P53 and RB.
They basically disarm the cells natural brakes against
uncontrolled growth. Got it.
And 3rd, and this is a really critical point, the viral
infection itself isn't always enough to cause cancer.
Think about EBV. Something like 90 to 95% of
(04:11):
people worldwide are infected HPV.
Around 80% of individuals will get an infection by age 45.
Wow, that high. Exactly.
Yet only a tiny, tiny fraction of those infected people ever
actually develop cancer. This strongly suggests that
other factors may be genetic, may be environmental.
Perhaps immune factors are also at play, pushing that infected
(04:34):
cell towards malignancy. And this study then really dives
into those very factors you justmentioned.
It's searching for those deeper connections beyond just is the
virus there or not? Precisely.
The team pulled together just anenormous amount of data.
Nearly 2000 tumors across 9 different cancer types linked to
five different viruses. Their whole mission was to
identify common patterns in epidemiology.
You know who gets them and where, but also the unique
(04:56):
genomic changes inside these cancers and even how these
tumors respond to therapy. It's a true big data approach to
tackle a massive biological puzzle.
That sounds like quite an undertaking.
So how did the researchers actually get to the bottom of
these differences between the virus positive and the virus
negative tumors? What kind of sophisticated tools
(05:16):
did they use for such a widespread analysis?
Yeah, this was a colossal comparative analysis.
They aggregated somatic mutationdata from 1971 tumors and this
was a mix of data types, whole exome sequencing, targeted DNA
sequencing, whole genome sequencing pulled from a range
of previously published studies,plus they generated brand new
(05:39):
data specifically for Kaposi sarcoma.
This allowed them to compare genetic changes across a really
wide spectrum of cancers, but using a consistent methodology,
which is key. So they were really scrutinizing
the the genetic changes within the tumor cells themselves,
looking deep inside. Yes, absolutely.
Deep genomic analysis are reallythe core of their work.
(05:59):
For instance, they map mutation signatures.
These are like unique fingerprints left on the DNA by
different kinds of damage processes.
Underprints. OK, Yeah.
Imagine each type of DNA damage,say from smoking or UV light,
leaves its own characteristic pattern, its own mark.
They were able to read those marks to understand the
underlying causes of the mutations.
Interesting. They also looked at things like
(06:20):
structural variants and copy number changes in the
chromosomes, basically big rearrangements or changes in how
many copies of certain genes there are.
Right. And they analyzed chromosomal
instability signatures. These tell you how often
chromosomes are being sort of missegregated or lost during
cell division, which indicates Achaotic cellular environment
(06:41):
that often promotes cancer. So a sign of instability.
Exactly. And finally, they zoomed right
in on recurrently mutated genes.They were searching for specific
genes that were altered much more frequently in the virus
positive versus the virus negative tumors, looking for
those key genetic switches that might be different.
That's a lot of genomic detective work, but did they
also look at how these genetic differences might play play out
(07:03):
clinically, especially, you know, in terms of how patients
respond to treat? Absolutely.
That was a crucial part of theirmethodology.
They evaluated how the virus status correlated with the
response to immunotherapy, specifically the PDL 1
inhibitors, which are a major class of cancer drugs now.
Right, the checkpoint inhibitors.
Exactly. And they did this by
(07:24):
meticulously analyzing data from32 different clinical trials.
That's an impressive scope. So they weren't just looking at
the genetic blueprint, they wereconnecting it to real world
patient outcomes. That's a powerful combination,
connecting the lab bench directly to the patient's
bedside, essentially. Indeed, and to really understand
the why behind that immunotherapy response, they
(07:47):
also delved deep into the tumor's immune microenvironment.
The neighborhood around the tumor.
Precisely. They looked at things like PDL
one expression which is kind of like a don't attack me flag that
cancer cells can wave to hide from the immune system.
They also studied the infiltration of CD 8 + T cells.
These are the immune system's direct killer cells, the ones
that actually attack cancer. The.
(08:08):
Frontline soldiers. You got it, and they analyzed T
cell receptor clonal selection. This basically tells you how
focused and effective the immunesystem's search and destroy
mission is against those specific cancer cells.
This kind of holistic approach allowed them to connect the dots
across different levels, from the DNA itself to the broader
(08:28):
immune system's interaction withthe tumor.
OK, so after all that meticulousanalysis, wading through all
that data, what? Were the most.
Striking, maybe even surprising discoveries that emerged from
their deep dive. Well, the findings were quite
remarkable actually, and they illustrated some really distinct
trends that truly differentiate these virus associated cancers.
Let's start with who gets these cancers?
(08:50):
Did they find any clear demographic patterns?
Yes. One very notable observation was
a higher frequency of virus positive tumors in males across
the board. Really virus associated cancers
showed a greater male to female ratio compared to their non
viral counterparts. This trend was particularly
clear in things like gastric cancer and Hodgkin lymphoma.
(09:11):
Interesting. And geography plays a role too,
right? It's not just about sex
differences. Yeah.
Exactly right. There are notable geographic
hotspots. For example, EBV positive
Hodgkin lymphoma is more common in places like North Africa, the
Middle East, and South America, whereas EBV positive
nasopharyngeal carcinoma is highly concentrated in China and
(09:31):
Southeast Asia. And these disparities aren't
just random. They reflect real differences in
risk factors like how common theoncovirus is in that population,
but also local lifestyle factorsthat can influence cancer risk.
OK, now shifting gears to the very heart of the cell, the DNA
itself. What did the genomic analysis
reveal about the differences in mutations between these virus
(09:53):
positive and virus negative tumors?
Right, this is where it gets really, really interesting.
Generally speaking, virus positive tumors had a lower
count of somatic mutations. Those are the non inherited ones
that accumulate over time compared to their virus negative
counterparts. Lower mutation count.
Yes, lower count. This was a pretty consistent
finding across most of the cancers they studied, like head
(10:13):
and neck squamous cell carcinomaand primary central nervous
system lymphoma. It strongly suggests a different
pathway to malignancy is being used.
But there's always an exception that kind of proves the rule,
isn't there. You know it in hepatocellular
carcinoma, that's a type of liver cancer, and also in
Birkett lymphoma, the virus positive cases actually showed a
(10:34):
greater total mutation load. Oh, OK, so the opposite.
The opposite. Yeah.
These cases where virus positivetumors actually have more
mutations are really intriguing.It suggests that maybe in some
scenarios the virus isn't just reducing the need for mutations,
but it might actually be causingsome DNA damage itself.
Or perhaps, like in Birkett lymphoma, specific viral
(10:56):
proteins like EBNA one can directly substitute for the need
for those classic cancer drivinggene mutations.
OK, that makes sense. Any other surprising mutational
insights that really stood out? Yes, the mutation signatures,
those fingerprints we talked about were quite distinct.
For example, HPV positive head and neck cancers showed a much
higher presence of something called APOBEC mutations.
(11:18):
Yeah, these suggest that the HPVproteins might actually be kick
starting some of our own cellular enzyme enzymes that
normally fight viruses. But in this context, they
ironically end up causing more mutations in the host DNA.
It's like a defense mechanism gone wrong.
Like friendly fire. Kind of, yeah.
In contrast, if you look at Merkel cell carcinoma, the virus
positive tumors had significantly fewer UV light
(11:41):
related mutations compared to the virus negative ones.
This strongly implies that the virus itself is taking over the
primary cancer initiation role, reducing the need for sun use to
DNA damage to get the cancer started.
And what about the specific genes that were frequently
mutated? Were there clear patterns there
too, beyond the overall count orthe signatures?
Yes, and this is a truly key finding.
(12:03):
Virus negative tumors had significantly higher odds
mutations in common well known tumor suppressor genes like TP
53 and CDK and two a the. Usual suspects.
Exactly the usual suspects. These are genes we often
immediately associate with cancer development, acting as
those crucial breaks on cell growth.
But in stark contrast, the viruspositive tumors showed increased
(12:24):
mutations and a specific set of RNA helicase genes, particularly
DDX 3X and eif 4A1. RNA helicases.
That sounds specific. It is.
And DDX 3X mutations, very interestingly were strongly
associated with EBV positive bricate lymphoma.
And here's a really striking detail. 96% of the truncating
(12:45):
DDX 3X mutations, those are the ones that essentially break the
gene and cause a loss of its function, occurred in males. 96%
in males. That male bias in DDX 3X,
especially with the loss of function mutation.
That's really fascinating. So it points to very distinct
genetic pathways being active depending on whether a virus is
present. Precisely, it strongly suggests
that the virus itself is providing alternative oncogenic
(13:07):
mechanisms, alternative ways to drive cancer.
This essentially reduces the needle for the cells to acquire
mutations in those traditional tumor suppressors like TP 53.
The virus is doing some of that oncogenic work if you will, and
that loss of function for DDX 3Ximplies it can no longer do its
normal job, which might include keeping the cell in check.
So losing it could act as a major accelerant for certain
(13:30):
virus associated cancers, particularly it seems in men.
The clinical implications of that finding, thinking about
treatment, seem truly significant.
What does this mean for how doctors might approach patient
care based on virus status? Right.
This is perhaps one of the most immediately impactful findings
for patients and for clinicians.The study found a really
(13:51):
significant association between virus positivity and a higher
treatment response rate to thosePDL 1 immunotherapies.
High response. Higher response.
This was especially evident in gastric cancer and head and neck
squamous cell carcinoma. And this finding is particularly
surprising because as we said, virus positive tumors generally
have that lower total mutation burden.
(14:13):
Typically, a high mutation burden is thought to correlate
with a better immunotherapy response because more mutations
mean more targets for the immunesystem.
Right, that's the usual thinking, exactly.
So this study kind of flips thatconventional wisdom on its head,
at least for these specific virus associated cancers.
So why the better response then if it's not simply due to a
higher mutation burden? What's happening differently in
(14:35):
the immune system in these cases?
That's the $1,000,000 question, isn't it?
And the researchers really dug into it.
What they observed in the virus positive gastric and head and
neck cancers was increased CD 8 + T cell infiltration.
More killer T cells getting intothe tumor.
Exactly. And higher T cell receptor
clonal selection. What this combination means is
(14:56):
that the immune system, specifically those powerful
killer T cells, seems to be moreactively recruited to the tumor
and more specifically targeted against those virus associated
tumor cells. So the immune system is already
more engaged. It seems so.
This pre-existing, more robust immune activity likely makes
them more susceptible to immunotherapy.
(15:16):
The immunotherapy drug then justacts like a switch or maybe like
taking the foot off the brake tofully reactivate and boost that
already present response. So connecting all these dots,
what does this all mean when we look at the bigger picture of
how cancer develops and how we might treat it?
Well, I think the study profoundly highlights that virus
associated cancers really are a distinct biological entity.
(15:38):
They're not just cancers that happen to have a virus hanging
around. They have their own unique
epidemiological patterns, a verydifferent genomic landscape,
and, crucially, unique therapeutic vulnerabilities.
It builds strongly on previous work by showing these
commonalities across a really broad range of cancer types, not
just looking at one cancer in isolation.
(15:58):
That male predominance you mentioned earlier for virus
associated cancers, that really stood out.
Any more thoughts on why that might be the case?
It's a fascinating question. It could very well be linked to
some kind of immunological predisposition.
We know that females generally exhibit a more robust immune
response to infections overall. This is influenced by a complex
(16:19):
mix of factors, you know, from genes on the X chromosome to
hormonal differences. This potentially stronger immune
surveillance in females might offer some protective advantage
against the virus persisting long enough or triggering the
changes needed for cancer development.
OK. That makes sense.
And the lower overall mutation burden in most of these virus
positive tumors, that's quite a departure from what we often
(16:42):
think about with many other cancers driven by environmental
damage or aging. What's the leading hypothesis
there again? Yeah.
What's really fascinating here is the hypothesis that the viral
proteins themselves are providing much of the necessary
oncogenic activity, the hits needed to turn a cell cancerous.
This then reduces the selective pressure for the host cell to
(17:02):
acquire numerous additional somatic mutations to become
fully malignant. So the virus is essentially
driving the car, meaning you don't need as many individual
engine modifications, so to speak.
That's a good analogy, Yeah. The virus is doing a lot of the
driving. Let's delve just a bit more into
those. Specific.
RNA helicase gene mutations. You mentioned DDX 3X and EIK
4A1. Why are they so significant
(17:25):
specifically in virus associatedcancers?
What are these genes normally do?
Right. So these are NA halocases.
You can think of them as molecular unravelers or maybe
rewinders in our cells. They're crucial for reading and
processing our genetic code stored in RNA.
They play key roles in really fundamental cellular processes
and also, interestingly, in innate immunity, the body's
(17:47):
first line of defense against pathogens.
DDX 3X in particular, is complex.
It can act as both a tumor suppressor and surprisingly
sometimes as an oncogene, depending on the cellular
context. It's frequent mutation in these
cancers, especially that striking male bias for the
truncating loss of function mutations strongly suggests that
losing DDX 3X function might be a really key step in the
(18:10):
development of certain virus associated cancers like EVD
positive Birkitt lymphoma. It really opens up new avenues
for understanding their specificpathogenesis and maybe
developing therapies that targetthis pathway.
And circling back to the immunotherapy response, that
positive signal and virus positive cancers, that feels
like a potential paradigm shift for how we treat these specific
cancers. What does this mean for patients
(18:32):
and doctors moving forward? It really is a powerful
implication. The increased T cell
infiltration and the focused clonal T cell response in virus
positive gastric and head and neck cancers strongly suggest
that the high immunogenicity, the ability to provoke an immune
response of the viral antigens, the viral proteins within these
(18:53):
tumors actually primes the immune system to recognize and
attack them from the start. So the immune system sees the
viral bits as foreign. Exactly.
Immunotherapy then acts like this potent switch, reactivating
and supercharging that pre-existing immune response,
making it far more effective than it might be in a tumor
without those viral flags. This could genuinely mean that
(19:13):
assessing a patient's virus status becomes a critical
biomarker for predicting whetherthey're likely to respond well
to immunotherapy. So a new tool for doctors?
A new tool? Absolutely.
Imagine we now have a new, perhaps unexpected biomarker to
help guide potentially life saving immunotherapy decisions,
especially in cancers where maybe it wasn't previously
considered as effective. Now with any study this broad,
(19:36):
are there any limitations to keep in mind or clear next steps
needed for this line of research?
Oh, absolutely. As with any comprehensive study
like this, there are always nuances.
This analysis, for instance, focused on the most
significantly differentially mutated genes across the entire
pan cancer cohort they studied. What that means is some known
(19:56):
associations that occur in specific cancer types might not
have met the stringent statistical threshold needed for
pan cancer significance in this analysis.
For example, mutations in the promoter region, which are known
to be common in HPV positive head and neck cancers, weren't
captured here because the study primarily focused on mutations
within the protein coding parts of genes, the exons, and
(20:19):
generally excluded promoter regions.
So technical limitations based on the analysis.
Scope, exactly. So future studies will
definitely need to incorporate larger, perhaps even more
diverse cohorts. And they'll need to look at
additional genetic factors like those promoter mutations and
also epigenetic genetic factors,changes that affect gene
activity without changing the DNA sequence itself, to further
(20:40):
expand and refine our understanding.
There's always more to learn, more layers to peel back.
So ultimately, this study reallypaints a picture of two quite
distinct models for how cancer can develop, doesn't it?
Yes, I think that's a great way to put it.
One model is where accumulated random mutations, perhaps from
aging or exposure to environmental carcinogens, drive
(21:01):
the process forward in the absence of a viral infection.
That's kind of the classic view for many cancers.
And the other model highlighted here is where a viral infection
first establishes A persistent latent state and then specific
subsequent mutations, often in these different genes like the
RNA helicases DDX 3X and eif 4A1contribute to the final
(21:22):
malignant transformation. This fundamental distinction is
absolutely critical if we want to develop more targeted, more
effective therapies that are tailored to the unique biology
driving these different cancer pathways.
So if our listeners take just one key thing away from this
deep dive today, what should it be?
I'd say it's that our understanding of cancer just got
significantly richer. This study clearly reveals that
(21:45):
virus associated cancers are a truly distinct category.
They're characterized by unique epidemiology, who gets them
where, and perhaps why. They often have a lower overall
mutation burden, but with specific crucial driver
mutations in genes like DDX 3X and EIF 4A1.
And importantly, they show greater responsiveness to
(22:06):
certain immunotherapies. And this distinct biology offers
completely new pathways not justfor understanding how cancer
develops, but, crucially, for improving treatment strategies
for potentially millions of people around the globe.
Exactly. And it leaves us with a really
important question to ponder. What does this mean for how we
should approach cancer prevention and treatment going
forward, especially in those parts of the world where these
(22:28):
viral infections are most prevalent?
It's a question that could genuinely change lives.
This episode was based on an Open Access article under the
CCBY 4 Point O license. You can find a direct link to
the paper and the license in ourepisode description.
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