1. "What genetic material was used in this research?"
2. How does the completion of this research advance the treatment of cancer?
in typed please and this is the research "The Mystery of Metastasis"
Transcribed Image Text: The Mystery of Metastasis: Can a Tumor's Genetic
Mutations Predict Whether and Where Cancer Will
Spread?
O mskcc.org/newsimystery-metastasis-can-tumor-s-genetic-mutations-predict-whether-and-where-cancer-will-spread
Thursday, February 3, 2022
Scientists at Memorial Sloan Kettering are using computational methods to understand where cancer
cells (like those above) will metastasize.
Several years ago, in a lab meeting, one of Nikolaus Schultz's postdoctoral fellows posed a
question: "Do you think it's possible to predict, based on the genomie profile of an individual
tumor, which organs it might metastasize to?"
And just like that, a research project was born.
Dr. Schultz is a computational oncologist in the Department of Epidemiology and
Biostatistics at Memorial Sloan Kettering Cancer Center. He also serves as Head of
Knowledge Systems in the Marie-Josée and Henry R. Kravis Center for Molecular Oncology.
In these dual roles, he has gained a wealth of experience sequencing the DNA in patients
tumors and using this information to help physicians guide treatment.
Every person with advanced cancer who is treated at MSK undergoes genetic sequencing of
their tumor withMSK-IMPACT™, a tool that looks for mutations in 400-plus cancer-
associated genes. Since sequencing started in 2014, MSK has compiled genetic tumor profiles
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from more than 50,000 patients. This vast
repository represents a goldmine for
biologists interested in asking questions
about the relationships between tumor
mutations and cancer progression.
Dr. Schultz and Francisco Sanchez-Vega –
the curious postdoc who originally posed the
question about metastasis and who is now an
Assistant Attending Computational
Oncologist at MSK – realized that they could
use computational techniques to search this
mountain of data for clues. Specifically, they
MSK computational oncologists Francisco
Sanchez-Vega and Nikolaus Schultz
could ask whether particular mutations (or
groups of mutations) correlate with the spread of cancer to particular organs, across many
different types of cancer.
That was six years ago. Now, in a paper published February 3, 2022, in the journal Cell, Drs.
Schultz and Sanchez-Vega and their team, including postdoctoral researchers Bastien
Nguyen and Christopher Fong, and 71 other MSK scientists present the results of their
investigation.
To the question of whether it's possible to look at an individual tumor and, based on its
genomic profile alone, predict its precise future metastatic trajectory, the answer is clearly
no.
"While we found some gene mutations to be slightly more common in tumor samples with
specific metastatic transitions, we found no single gene that, when mutated, will predict with
absolute certainty whether or not a tumor will metastasize to a particular organ," Dr. Schultz
says.
The study was revealing in other ways: "At a very high level, what the data are telling us is
that metastatic disease is genomically different from primary disease," Dr. Schultz says.
For example, in many cancer types, metastatic tumors have more of what geneticists call
DNA copy-number changes compared with primary tumors. A DNA copy-number change is
when a particular segment of DNA is present in greater or fewer than the normal number of
copies. These copy-number changes, when observed in primary tumors, were an indicator of
metastatic potential, Dr. Schultz points out.
In addition, he notes, some cancer-driving mutations were detected at different frequencies
in metastases compared with primary tumors across a variety of cancer types.
Transcribed Image Text: Making the Data Available to Other Researchers
Dr. Schultz likens the extensive dataset his team has curated to The Cancer Genome Atlas
(TCGA) project, in which he was also involved. "An important goal of TCGA was to assemble
a valuable dataset and get it out into the world so that others could mine it," he says.
To help researchers mine these new data for insights, the team is making them publicly
available through the cBioPortal for Cancer Genomics asMSK-MET (Memorial Sloan
Kettering – Metastatic Events and Tropisms).
The dataset includes information on genetic changes and clinical outcomes from 25,000
patients across 50 different cancer types.
A Shift in Perspective
Because no single mutation or set of mutations stood out as reliable predictors of metastatic
behavior across tumor types, the new study may add support to an emerging framework in
cancer science that views metastasis – the cause of 90% of cancer deaths – as not primarily
driven by genetic mutations. Rather, epigenetic changes that occur in cancer cells as a
consequence of their interactions with normal cells in the surrounding environment could be
more to blame. (Epigenetic changes are ones that alter what genes are turned on or off in a
cell without altering the DNA sequence as a mutation would.) These changes may underlie
the ability of metastatic cells to adapt to otherwise hostile tissue environments.
To the question of whether it's possible to look at an individual tumor and, based on its
genomic profile alone, predict its precise future metastatic trajectory, the answer is clearly
no.
Recent discoveries from other investigators at MSK – including Joan Massagué, Karuna
Ganesh, Charles Sawyers, Kat Hadjantonakis, and Dana Pe'er – have pointed to a kind of
epigenetically driven "identity switching" that enables cancer cells to assume more
developmentally primitive states and thereby grow in new parts of the body.
Exploring the ramifications of these and other findings will be the focus of MSK's new Marie-
Josée and Henry R. Kravis Cancer Ecosystems Project, which launches today.
Further Opportunities for Data Mining and Extending Personalized
Medicine
Currently, genetic sequencing of tumors with MSK-IMPACT can inform whether or not a
specific patient should receive a specific drug based on a single genomic alteration. For
example, if someone is found to have a mutation in the BRAF gene, they might be a good
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candidate for a targeted drug called vemurafenib.
But Dr. Schultz points out that there is potentially much more information to be found in the
mass of sequencing data and associated patient clinical data that could inform treatment
decisions.
"When properly mined, this data could tell us a lot more about prognosis of these patients,
whether or not their tumors will metastasize, maybe even to what tissues," he says. "This
information might determine how these patients get monitored in the future. We can learn
about what treatments they might be more sensitive to or less sensitive to. I think that there's
enormous potential for personalized medicine that goes beyond the single biomarker, and
therefore justification to keep sequencing more patients with broader sequencing panels to
increase our power to make new discoveries."
Key Takeaways
• Genomic data from 25,000 patients with 50 different kinds of cancer allowed
researchers to ask whether DNA mutations in a tumor could predict whether and where
it would metastasize, or spread.
• While some mutations were slightly more common in tumors prone to certain
metastatic events, no single mutation or group of mutations could predict with absolute
certainty where a particular tumor would metastasize.
• The researchers found that some mutations, called DNA copy-number changes, were
more common in metastatic tumors than in primary tumors, and these changes were
predictive of metastatic potential when found in primary tumors.
• The dataset is being made publicly available to other researchers who wish to explore
the relationship between genomic events and cancer progression.
This study was supported by the MSK Cancer Center Support Grant (P30 CAoo8748), the
MSK MIND initiative, Cycle for Survival, the Alan and Sandra Gerry Metastasis and
Tumor Ecosystems Center, the Fund for Innovation in Cancer Informatics (ICI), the
Robertson Foundation, a Prostate Cancer Foundation Challenge Award, and the Marie-
Josée and Henry R. Kravis Center for Molecular Oncology.