Computer models show promise for personalizing chemotherapy

Computers have revolutionized many fields, so it isn’t surprising that they may be transforming cancer research. Computers are now being used to model the molecular and cellular changes associated with individual tumors, allowing scientists to simulate the tumor’s response to different combinations of chemotherapy drugs.  

Modeling big data to improve personalized cancer treatment was the focus of a recent episode of the Sirius radio show “The Future of Everything.” On hand was Sylvia Plevritis, PhD, a professor of biomedical data science and of radiology at Stanford, who discussed her work with Stanford professor and radio show host Russ Altman, MD, PhD.  

Plevritis and her colleagues are using multi-omics data — including measures of gene expression, protein function, metabolic processes and more — to extensively profile individual tumors of individual patients.

They are analyzing this data to better understand how tumors become drug-resistant. She explained in the podcast that tumors are often heterogeneous — not every cell has the same gene mutations — but chemotherapy drugs typically target specific genetic mutations. Tumors are also driven by complex mechanisms beyond genetic mutations. So her lab is comprehensively characterizing the different cell types in a tumor and how these different cell types respond to individual drugs. By better understanding the complexity of what drives the tumor’s response, they hope to identify the underlying mechanisms of drug resistance.

The goal, Plevritis said, is to more accurately estimate the response of the entire tumor to a given set of drugs without having to run clinical trials on every drug combination. Using their modeling, they hope to identify the most promising drug combinations to make clinical trials more efficient, she said.

The research team tested their computational model by measuring the multi-omics profile of human cancer cells in a dish, before and after exposing the cells to specific drugs. Their model then identified the minimum combination of drugs with the maximum effect. This work used archived cell samples, so their modeling results didn’t impact the patients’ treatment. But they compared their model’s prediction to what drugs the patients actually received.

They determined that the best chemotherapy cocktail for most of the patients would have been just one or two of the drugs that they received. For about 10 percent of the patients, they predicted that a totally different drug would have been the most effective, Plevaritis said in the podcast.

Thus, their computational model may be able to divide patients into different groups, based on tumor characteristics, and match those groups with specific chemotherapy cocktails that would be most effective for them. Plevaritis’ team is currently setting up a study to validate their computational predictions for a group of patients with acute myeloid leukemia, in parallel with a combination drug therapy trial, she said.

As a member of the Cancer Intervention Surveillance Network Modeling consortium, Plevritis is also using computational models to evaluate the impact of cancer screening guidelines — such as the recommended frequency of mammograms for general breast cancer screening — on mortality rates. For example, policy organizations like the U.S. Preventive Service Task Force often ask the consortium to simulate thousands of different screening policies — and rank their potential impact — to use as part of their selection criteria, she said.

One outcome of this work is an online decision tool for women who are at high risk for developing breast cancer because they carry a mutation in the BRCA1 or BRCA2 gene. Plevritis said about 45,000 people worldwide have used the tool, and her team has received a lot of positive feedback.

“It’s been very satisfying to get these emails and this feedback from individuals who feel that this complex information was distilled in a way that they can make sense of it,” Plevritis said.

Image of acute promyelocytic leukemia cells by Ed Uthman

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

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The future hope of “flash” radiation cancer therapy

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The goal of cancer therapy is to destroy the cancer cells while minimizing side effects and damage to the rest of the body. Common types of treatment include surgery, chemotherapy, targeted therapy and radiation therapy. Often combined with surgery or drugs, radiation therapy uses high-energy X-rays to harm the DNA and other critical processes of the rapidly-dividing cancer cells.

New innovations in radiation therapy were the focus of a recent episode of the Sirius radio show “The Future of Everything.” On hand was Stanford’s Billy Loo, MD, PhD, a professor of radiation oncology, who spoke with Stanford professor and radio host Russ Altman, MD, PhD.

Radiation has been used to treat cancer for over a century, but today’s technologies target the tumor with far greater precision and speed than the old days. Loo explained that modern radiotherapy now delivers low-dose beams of X-rays from multiple directions, which are accurately focused on the tumor so the surrounding healthy tissues get only a small dose while the tumor gets blasted. Radiation oncologists use imaging — CT, MRI or PET — to determine the three-dimensional sculpture of the tumor to target.

“We identify the area that needs to be treated, where the tumor is in relationship to the normal organs, and create a plan of the sculpted treatment,” Loo said. “And then during the treatment, we also use imaging … to see, for example, whether the radiation is going where we want it to go.”

In addition, oncologists now implement technologies in the clinic to compensate for motion, since organs like the lungs are constantly moving and patients have trouble lying still even for a few minutes. “We call it motion management. We do all kinds of tricks like turning on the radiation beam synchronized with the breathing cycle or following tumors around with the radiation beam,” explained Loo.

Currently, that is how standard radiation therapy works. However, Stanford radiation oncologists are collaborating with scientists at SLAC Linear Accelerator Center to develop an innovative technology called PHASER. Although Loo admits that the acronym was inspired because he loves Star Trek, PHASER stands for pluridirectional high-energy agile scanning electronic radiotherapy. This new technology delivers the radiation dose of an entire therapy session in a single flash lasting less than a second — faster than the body moves.

“We wondered, what if the treatment was done so fast — like in a flash photography — that all the motion is frozen? That’s a fundamental solution to this motion problem that gives us the ultimate precision,” he said. “If we’re able to treat more precisely with less spillage of radiation dose into normal tissues, that gives us the benefit of being able to kill the cancer and cause less collateral damage.”

The research team is currently testing the PHASER technology in mice, resulting in an exciting discovery — the biological response to flash radiotherapy may differ from slower traditional radiotherapy.

“We and a few other labs around the world have started to see that when the radiation is given in a flash, we see equal or better tumor killing but much better normal tissue protection than with the conventional speed of radiation,” Loo said. “And if that translates to humans, that’s a huge breakthrough.”

Loo also explained that their PHASER technology has been designed to be compact, economical, reliable and clinically efficient to provide a robust, mobile unit for global use. They expect it to fit in a standard cargo shipping container and to power it using solar energy and batteries.

“About half of the patients in the world today have no access to radiation therapy for technological and logistical reasons. That means millions of patients who could potentially be receiving curative cancer therapy are getting treated purely palliatively. And that’s a huge tragedy,” Loo said. “We don’t want to create a solution that everyone in the world has to come here to get — that would have limited impact. And so that’s been a core principle from the beginning.”

This is a reposting of my Scope blog post, courtesy of Stanford School of Medicine.

The future of genomics: A podcast featuring Stanford geneticists

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Image by Pat Lyn

Every living organism on Earth has a genome, the complete set of DNA containing all of the information needed to develop and maintain the organism. Humans inherit three billion long strings of DNA called chromosomes from each parent, so your genome can help identify your personal ancestry. But genomes can also identify the movement of human populations based on who is similar to whom.

Carlos Bustamante, PhD, a professor of biomedical data science, of genetics and of biology at Stanford, discusses the blossoming uses of genomes on a recent episode of “The Future of Everything” radio show.

For example, Bustamante told host Russ Altman, MD, PhD, a professor of bioengineering, of genetics, of medicine and of biomedical data science, about the genomic fingerprints of the history of slavery in the United States. As part of an international collaboration, he studied the DNA of modern individuals and individuals from slave cemeteries, tracing their history to particular tribal groups in Africa.

“A lot of that history has been lost and African Americans want to reclaim parts of that history using DNA,” Bustamante said. “What’s interesting, at least in the United States, is that most of the slave ships went first to the Caribbean and Brazil. Only a couple hundred thousand people came in straight to the Port of Charleston. So the history of the slave trade is actually written in the DNA of the Caribbean, Brazilian and U.S. African descendant populations.”

But that is only one of the many genomic applications discussed on the episode. Another important use is predicting disease risks. Genetic tests are now available for many hereditary conditions, including cancer risk assessment, at Stanford.

This raises a challenge, however, because our knowledge of DNA is primarily based on people of European descent. As Bustamante explained, this occurred because European countries were the first to recognize the potential impact that DNA sequencing could have on health care, once the cost of DNA sequencing technology plummeted.

“They invested quickly and by the year, say 2009, they’d done about a thousand studies and 95 percent of the participants in those studies were of European descent — be they from the countries in Europe or in Iceland.”

Since humans are 99.9 percent identical in their genetic makeup, maybe this doesn’t sound like a problem. But Bustamante said the differences may be important because they could help lead to improvements in health care. He described this lack of diversity as both a problem and an opportunity.

Take blond hair, for example. Bustamante explained that two main populations have blond hair: Europeans and Melanesians from the Solomon Islands. When the scientists started a research project, they hypothesized that a European went to Melanesia and had a lot of kids. But that isn’t what the genetics showed.

“The genetics of blond hair in Europe are different than the genetics of blond hair in Melanesia. They look the same, but it turns out that the underlying genes are different,” he said. “And why is that interesting? From the point of view of medical genetics, if this is true for blond hair — which is about as simple a trait as you can get — what about diabetes? Why would we assume the genetic basis of diabetes is the same in every population, when we know diabetes actually presents differently in different populations?”

He also argued that new drug discovery would be more successful if it was based on genetic leads. Cholesterol lowering drugs called PCSK9 inhibitors, for instance, were found by studying families with naturally high or low levels of cholesterol. Successes like these are the reason he thinks it’s important to study diverse populations.

“If we spread our bets across different human populations, we’re much more likely to find interesting biology that then benefits everybody,” he said. “Because these cholesterol lowering drugs aren’t just good for those people with high cholesterol for genetic reasons. That’s the key. You can mimic it in others and it benefits everybody.”

Of course, the potential for genomics goes beyond human applications. Altman and Bustamante also discuss plant and animal uses, including designing your dream dog.

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

4 H’s and 4 T’s Walk Into a Bar…”: A joke? No, an episode from a medical education podcast

Photo by Patrick Breitenbach

Medical school is jam packed with information to memorize as well as with high-stakes exams and expectations, creating a cauldron of stress and tension. Enter the mnemonic-filled Humerus Hacks podcast, part of a growing movement to make medical education more entertaining and accessible.

I recently learned about Humerus Hacks from its Australian founders and hosts Karen Freilich, MBBS, education coordinator at The Nookie Project, and Sarah Bush, MBBS, medical intern at Western Health. They started the bimonthly podcast to liven up their studies, but have continued it after graduating from medical school despite hectic intern schedules. Each 10- to 40-minute episode is filled with humor and casual conversation, which should be no surprise given episode titles like, “4 H’s and 4 T’s Walk Into a Bar…” (Which, for non-cardiologists, is a reference to potential causes of cardiac arrest.)

What inspired you to create a podcast?

Freilich: “Sarah and I have been mates since we were ten years old, and study buddies since day one of med school. We were both constantly overwhelmed by the sheer quantity of information we had to learn, especially when it came to learning the tongue-twisting names of medications. We began breaking down our curriculum into funny snippets to make it easier to learn, but also more enjoyable to study.

The tables turned in our penultimate year of medicine, when I was commuting over two hours daily to placement and Sarah hurt her back and couldn’t properly sit down at a desk to study. We raked through the medical podcast world to find something aimed at our level that wouldn’t put us to sleep, and there wasn’t too much out there. And so, Humerus Hacks was born. We picked the name because it was dorky, fun and medical — just like us.”

How did you learn to make podcasts?

Bush: “As an avid podcast devourer, going through at least four hours of content a day during my commutes about town, I became interested in the sound engineering — and turn’s out its super simple! We opted for high quality microphones, although we didn’t figure out how to use them properly until episode 3 or 4. And I learnt how to edit using Audacity. And then I just give it to a podcast hosting company, and voila!”

Why do you format the episodes as conversations?

Freilich: “We wanted to create content that was funny and enjoyable to listen to. We always aim to include banter and tangents, because that’s what keeps learning interesting. Before an episode, we often write down the three most important things we want the listeners to learn that episode. If our listeners can learn those things, and be entertained at the same time, then we’ve done our job.”

You mentioned that you’ve had feedback from patients. Isn’t your podcast for medical students?

Freilich: “Doctors, nurses and other health practitioners often have jargon so deeply ingrained that it makes it hard for them to explain a health topic simply. We didn’t initially intend to incorporate patients in our listenership, and we are still surprised and quite honored that people have used our podcast as a way to further understand their condition. It’s great that Humerus Hacks can help improve access to medical education.”

What is your favorite Humerus Hacks episode?

Bush: “My favorite is definitely the murmurs rap (at time 9:20) about ejection and pansystolic murmurs, because it has helped me out in real life diagnosis. And it has the added benefit of teaching people how to beat box: start by saying boots and cats, and we’ll go from there. Also I get to rap, which is always fun and embarrassing.”

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

Engineering better opioids: A podcast featuring Stanford bioengineer Christina Smolke

Obtaining compounds from nature, such as opioids from poppies or taxol from yew trees, is hard and time-consuming. So researchers, including Stanford’s Christina Smolke, PhD, are working to synthesize medically useful compounds by reengineering nature.

Smolke, a professor of bioengineering, describes her efforts to engineer yeast to make opioids on a recent episode of the “Future of Everything” radio show.

“These are compounds in nature that the opioid poppy has evolved to make. And to date, our chemists have not been able to develop efficient processes to make these compounds,” Smolke told show host Russ Altman, MD, PhD, a professor of bioengineering, of genetics, of medicine and of biomedical data science. “So we still farm this drug crop of opioid poppy to produce these molecules and the raw materials to make these molecules. And there are many limitations that come about from doing that.” These limitations include environmental and geopolitical risks, she said.

Smolke explained that she tackled this research even though many experts in the field viewed it as impossible — because it involved reengineering a complicated set of reactions and mix of enzymes that work together within the opioid poppy to build the opioid molecules. Over 10 years, her research team developed the very challenging platform technology to “prove that it could be used with any compound found in nature.”

“The final yeast strain that made the initial opioids molecules had 23 different enzymes put into it. So one of the challenges was identifying the enzymes from the opioid poppy and then moving them into yeast,” Smolke said.

But the trickiest part, she explained, was getting them to work in yeast, which is a very different organism than opioid poppies. The researchers had to modify each of the enzymes to create a yeast strain that could churn out opioid molecules.

There is more work to do though, including creating yeast that are more efficient at making the opioid compounds, as well as using the technology to make better opioids with less side effects so they are less addictive. Luckily, Smolke expects her new research projects to go more quickly now that they’ve developed the basic tools.

“We’re probably around 5 years away from molecules coming from yeast-based platforms to actually be in the medications that you’re taking,” Smolke explained. “Some of that lag is due to the engineering that we have to do to make the processes efficient enough so they can be scaled up at a commercial setting. And others are [due to] regulatory approvals.”

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

Tagging Along on a Fantasy Field Trip

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The Field Trip Podcast icon, courtesy of Kara Platoni.

Looking back, the only school field trip that I remember was our trip to the San Francisco Exploratorium. I enjoyed the fun interactive science exhibits, but what I remember best is the tactile dome. I entered into total darkness and spent the next hour feeling, crawling and sliding my way through a 3-D maze. The purpose of the tactile room is to explore a disorienting world in which you can only rely on touch. For a kid, the challenge is to do that as quickly as possible.

However, that field trip is tame compared to what Kara Platoni, Eric Simons, and Casey Miner have in mind. They’ve launched a new podcast, The Field Trip, that broadcasts their real world science adventures. To add a little more intellectual rigor, they also interview an expert guest in their radio studio for each episode. Beginning on May 14, a new episode will air weekly each Monday through June 4.

For more information on the podcast series, check out my KQED Quest blog.