Engineers at MIT and the University of California at San Diego (UCSD) have devised a new way to detect cancer that has spread to the liver, by enlisting help from probiotics — beneficial bacteria similar to those found in yogurt.

Many types of cancer, including colon and pancreatic, tend to metastasize to the liver. The earlier doctors can find these tumors, the more likely that they can successfully treat them.

“There are interventions, like local surgery or local ablation, that physicians can perform if the spread of disease in the liver is confined, and because the liver can regenerate, these interventions are tolerated. New data are showing that those patients may have a higher survival rate, so there’s a particular need for detecting early metastasis in the liver,” says Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Electrical Engineering and Computer Science at MIT.

Using a harmless strain of E. coli that colonizes the liver, the researchers programmed the bacteria to produce a luminescent signal that can be detected with a simple urine test. Bhatia and Jeff Hasty, a professor of biology at UCSD, are the senior authors of a paper describing the new approach this week in the journal Science Translational Medicine. Lead authors are MIT postdoc Tal Danino and UCSD postdoc Arthur Prindle.

Microbial help

Previous studies had shown that bacteria can penetrate and grow in the tumor microenvironment, where there are lots of nutrients and the body’s immune system is compromised. Because of this, scientists have been trying for many years to develop bacteria as a possible vehicle for cancer treatment.

The MIT and UCSD researchers began exploring this idea a few years ago, but soon expanded their efforts to include the concept of creating a bacterial diagnostic.

To turn bacteria into diagnostic devices, the researchers engineered the cells to express the gene for a naturally occurring enzyme called lacZ that cleaves lactose into glucose and galactose. In this case, lacZ acts on a molecule injected into the mice, consisting of galactose linked to luciferin, a luminescent protein naturally produced by fireflies. Luciferin is cleaved from galactose and excreted in the urine, where it can easily be detected using a common laboratory test.

At first, the researchers were interested in developing these bacteria for injection into patients, but then decided to investigate the possibility of delivering the bacteria orally, just like the probiotic bacteria found in yogurt. To achieve that, they integrated their diagnostic circuits into a harmless strain of E. coli called Nissle 1917, which is marketed as a promoter of gastrointestinal health.

In tests with mice, the researchers found that orally delivered bacteria do not accumulate in tumors all over the body, but they do predictably zero in on liver tumors because the hepatic portal vein carries them from the digestive tract to the liver.

“We realized that if we gave a probiotic, we weren’t going to be able to get bacteria concentrations high enough to colonize the tumors all over the body, but we hypothesized that if we had tumors in the liver they would get the highest dose from an oral delivery,” says Bhatia, who is a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science.

This allowed the team to develop a diagnostic specialized for liver tumors. In tests in mice with colon cancer that has spread to the liver, the probiotic bacteria colonized nearly 90 percent of the metastatic tumors.

In the mouse experiments, animals that were given the engineered bacteria did not exhibit any harmful side effects.

More sensitive detection

The researchers focused on the liver not only because it is a natural target for these bacteria, but also because the liver is hard to image with conventional imaging techniques like CT scanning or magnetic resonance imaging (MRI), making it difficult to diagnose metastatic tumors there.

With the new system, the researchers can detect liver tumors larger than about one cubic millimeter, offering more sensitivity than existing imaging methods. This kind of diagnostic could be most useful for monitoring patients after they have had a colon tumor removed because they are at risk for recurrence in the liver, Bhatia says.

Andrea Califano, a professor of biological sciences at Columbia University, says the study is “seminal and thought-provoking in terms of clearing a new path for investigating what can be done for early detection of cancer,” adding that the therapeutic possibilities are also intriguing.

“These bacteria could be engineered to cause genetic disruption of cancer cell function, deliver drugs, or reactivate the immune system,” says Califano, who was not involved in the research.

The MIT team is now pursuing the idea of using probiotic bacteria to treat cancer, as well as for diagnosing it.

The research was funded by the Ludwig Center for Molecular Oncology at MIT, a Prof. Amar G. Bose Research Grant, the National Institutes of Health through the San Diego Center for Systems Biology, and the Koch Institute Support Grant from the National Cancer Institute.

By Anne Trafton | MIT News Office

Engineers at MIT and the University of California at San Diego (UCSD) have devised a new way to detect cancer that has spread to the liver, by enlisting help from probiotics — beneficial bacteria similar to those found in yogurt.

Many types of cancer, including colon and pancreatic, tend to metastasize to the liver. The earlier doctors can find these tumors, the more likely that they can successfully treat them.

“There are interventions, like local surgery or local ablation, that physicians can perform if the spread of disease in the liver is confined, and because the liver can regenerate, these interventions are tolerated. New data are showing that those patients may have a higher survival rate, so there’s a particular need for detecting early metastasis in the liver,” says Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Electrical Engineering and Computer Science at MIT.

Using a harmless strain of E. coli that colonizes the liver, the researchers programmed the bacteria to produce a luminescent signal that can be detected with a simple urine test. Bhatia and Jeff Hasty, a professor of biology at UCSD, are the senior authors of a paper describing the new approach this week in the journal Science Translational Medicine. Lead authors are MIT postdoc Tal Danino and UCSD postdoc Arthur Prindle.

Microbial help

Previous studies had shown that bacteria can penetrate and grow in the tumor microenvironment, where there are lots of nutrients and the body’s immune system is compromised. Because of this, scientists have been trying for many years to develop bacteria as a possible vehicle for cancer treatment.

The MIT and UCSD researchers began exploring this idea a few years ago, but soon expanded their efforts to include the concept of creating a bacterial diagnostic.

To turn bacteria into diagnostic devices, the researchers engineered the cells to express the gene for a naturally occurring enzyme called lacZ that cleaves lactose into glucose and galactose. In this case, lacZ acts on a molecule injected into the mice, consisting of galactose linked to luciferin, a luminescent protein naturally produced by fireflies. Luciferin is cleaved from galactose and excreted in the urine, where it can easily be detected using a common laboratory test.

At first, the researchers were interested in developing these bacteria for injection into patients, but then decided to investigate the possibility of delivering the bacteria orally, just like the probiotic bacteria found in yogurt. To achieve that, they integrated their diagnostic circuits into a harmless strain of E. coli called Nissle 1917, which is marketed as a promoter of gastrointestinal health.

In tests with mice, the researchers found that orally delivered bacteria do not accumulate in tumors all over the body, but they do predictably zero in on liver tumors because the hepatic portal vein carries them from the digestive tract to the liver.

“We realized that if we gave a probiotic, we weren’t going to be able to get bacteria concentrations high enough to colonize the tumors all over the body, but we hypothesized that if we had tumors in the liver they would get the highest dose from an oral delivery,” says Bhatia, who is a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science.

This allowed the team to develop a diagnostic specialized for liver tumors. In tests in mice with colon cancer that has spread to the liver, the probiotic bacteria colonized nearly 90 percent of the metastatic tumors.

In the mouse experiments, animals that were given the engineered bacteria did not exhibit any harmful side effects.

More sensitive detection

The researchers focused on the liver not only because it is a natural target for these bacteria, but also because the liver is hard to image with conventional imaging techniques like CT scanning or magnetic resonance imaging (MRI), making it difficult to diagnose metastatic tumors there.

With the new system, the researchers can detect liver tumors larger than about one cubic millimeter, offering more sensitivity than existing imaging methods. This kind of diagnostic could be most useful for monitoring patients after they have had a colon tumor removed because they are at risk for recurrence in the liver, Bhatia says.

Andrea Califano, a professor of biological sciences at Columbia University, says the study is “seminal and thought-provoking in terms of clearing a new path for investigating what can be done for early detection of cancer,” adding that the therapeutic possibilities are also intriguing.

“These bacteria could be engineered to cause genetic disruption of cancer cell function, deliver drugs, or reactivate the immune system,” says Califano, who was not involved in the research.

The MIT team is now pursuing the idea of using probiotic bacteria to treat cancer, as well as for diagnosing it.

The research was funded by the Ludwig Center for Molecular Oncology at MIT, a Prof. Amar G. Bose Research Grant, the National Institutes of Health through the San Diego Center for Systems Biology, and the Koch Institute Support Grant from the National Cancer Institute.

By Anne Trafton | MIT News Office

Sangeeta Bhatia has been named the recipient of the 2015 Heinz Award for Technology, the Economy, and Employment.

The Heinz Family Foundation, which administers the award, cites Bhatia, the John J. and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, for her seminal work in tissue engineering and disease detection. She is also recognized for her passion in promoting the advancement of women in science, technology, engineering, and mathematics (STEM) fields. The award includes an unrestricted prize of $250,000.

The Heinz Awards pay tribute to the memory of the late U.S. Senator H. John Heinz III by celebrating his belief that individuals have both the power and responsibility to change the world for the better. In his honor, the Heinz Family Foundation annually recognizes individuals for their extraordinary contributions to arts and humanities; environment; human condition; public policy; and technology, the economy, and employment.

“John Heinz believed that individuals have the power and responsibility to improve the human condition. I believe this wholeheartedly and feel enormously privileged to have received training in engineering, biology, and medicine that enables my team to do interdisciplinary work that impacts human health,” says Bhatia, who also is a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science. “This type of recognition helps to bring science into the public eye so that everyone can appreciate the dedication and innovation that is happening in laboratories all over the country.”

Bhatia’s team pioneered the fabrication of artificial human microlivers, which are being used by many biopharmaceutical companies to test the toxicity of drug candidates. Bhatia is also using microlivers in the lab to model malaria infection and test drugs that can eradicate malaria parasites completely — even the parasite reservoirs that remain in the liver after a patient’s symptoms subside. Bhatia hopes to eventually develop implantable liver tissue as a complement or substitute for whole-organ transplant.

In her study of cancer and the tumor microenvironment, Bhatia and her laboratory have developed synthetic biomarkers that are paving the way for simple, low-cost cancer diagnostics. Their engineered nanoparticles interact with tumor proteins in the body and release hundreds of these biomarkers, which can be detected in urine. One application relies on a paper-strip urine test that can reveal the presence of cancer within minutes in mouse models. This point-of-care, low-budget technology holds great promise for earlier cancer detection in the developing world and other settings with limited medical infrastructure.

Aside from her work in developing new solutions for liver disease and cancer, Bhatia is an advocate for bringing more women into STEM fields — especially at a young age. While a graduate student at MIT, Bhatia helped start Keys to Empowering Youth (KEYs), a program that engages middle school girls with science and engineering through hands-on activities and mentorship from MIT students. Bhatia continues to advise KEYs and MIT’s Society of Women Engineers chapter, which manages the program.

“I’m hopeful that the visibility associated with this award can inspire young girls by showing them what a rewarding profession — and life — STEM can yield,” she says.

Bhatia will receive her award on May 13 at a ceremony in Pittsburgh. There, she will be honored along with the Heinz Award recipients in the four other categories: Roz Chast, a best-selling illustrator and cartoonist (arts and humanities); Frederica Perera, an environmental health researcher at Columbia University (environment); William McNulty and Jacob Wood, founders of Team Rubicon (human condition); and Aaron Wolf, a geoscientist and professor at Oregon State University (public policy).

By Kevin Leonardi | Karen Shaner

Sangeeta Bhatia has been named the recipient of the 2015 Heinz Award for Technology, the Economy, and Employment.

The Heinz Family Foundation, which administers the award, cites Bhatia, the John J. and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, for her seminal work in tissue engineering and disease detection. She is also recognized for her passion in promoting the advancement of women in science, technology, engineering, and mathematics (STEM) fields. The award includes an unrestricted prize of $250,000.

The Heinz Awards pay tribute to the memory of the late U.S. Senator H. John Heinz III by celebrating his belief that individuals have both the power and responsibility to change the world for the better. In his honor, the Heinz Family Foundation annually recognizes individuals for their extraordinary contributions to arts and humanities; environment; human condition; public policy; and technology, the economy, and employment.

“John Heinz believed that individuals have the power and responsibility to improve the human condition. I believe this wholeheartedly and feel enormously privileged to have received training in engineering, biology, and medicine that enables my team to do interdisciplinary work that impacts human health,” says Bhatia, who also is a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science. “This type of recognition helps to bring science into the public eye so that everyone can appreciate the dedication and innovation that is happening in laboratories all over the country.”

Bhatia’s team pioneered the fabrication of artificial human microlivers, which are being used by many biopharmaceutical companies to test the toxicity of drug candidates. Bhatia is also using microlivers in the lab to model malaria infection and test drugs that can eradicate malaria parasites completely — even the parasite reservoirs that remain in the liver after a patient’s symptoms subside. Bhatia hopes to eventually develop implantable liver tissue as a complement or substitute for whole-organ transplant.

In her study of cancer and the tumor microenvironment, Bhatia and her laboratory have developed synthetic biomarkers that are paving the way for simple, low-cost cancer diagnostics. Their engineered nanoparticles interact with tumor proteins in the body and release hundreds of these biomarkers, which can be detected in urine. One application relies on a paper-strip urine test that can reveal the presence of cancer within minutes in mouse models. This point-of-care, low-budget technology holds great promise for earlier cancer detection in the developing world and other settings with limited medical infrastructure.

Aside from her work in developing new solutions for liver disease and cancer, Bhatia is an advocate for bringing more women into STEM fields — especially at a young age. While a graduate student at MIT, Bhatia helped start Keys to Empowering Youth (KEYs), a program that engages middle school girls with science and engineering through hands-on activities and mentorship from MIT students. Bhatia continues to advise KEYs and MIT’s Society of Women Engineers chapter, which manages the program.

“I’m hopeful that the visibility associated with this award can inspire young girls by showing them what a rewarding profession — and life — STEM can yield,” she says.

Bhatia will receive her award on May 13 at a ceremony in Pittsburgh. There, she will be honored along with the Heinz Award recipients in the four other categories: Roz Chast, a best-selling illustrator and cartoonist (arts and humanities); Frederica Perera, an environmental health researcher at Columbia University (environment); William McNulty and Jacob Wood, founders of Team Rubicon (human condition); and Aaron Wolf, a geoscientist and professor at Oregon State University (public policy).

By Kevin Leonardi | Karen Shaner

Correctly diagnosing a person with cancer — and identifying the specific type of cancer — makes all the difference in successfully treating a patient.

Today your doctor might draw from a dozen or so similar cases and a big book of guidelines. But what if he or she could instead plug your test results and medical history into a computer program that has crunched millions of pieces of similar data?

That sort of future is looking increasingly possible thanks to researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). Working with a team from Massachusetts General Hospital (MGH), PhD student Yuan Luo and MIT Professor Peter Szolovits have developed a computational model that aims to automatically suggest cancer diagnoses by learning from thousands of data points from past pathology reports. The work has been published this month in the Journal of the American Medical Informatics Association.

Better lymphoma diagnoses

The researchers focused on the three most prevalent subtypes of lymphoma, a common cancer with more than 50 distinct subtypes that are often difficult to distinguish. According to Ephraim Hochberg, director of the Center for Lymphoma at MGH and one of the paper’s co-authors, upwards of 5 to 15 percent of lymphoma cases are initially misdiagnosed or misclassified, which can be a significant problem since different lymphomas require dramatically different treatment plans.

For example, Hochberg recently saw a patient who had been mistakenly told that her lymphoma was incurable. If he hadn’t accurately diagnosed her and put her on an aggressive plan, it might have been too late to counteract the cancer.

Lymphoma classification has long been a source of debate for pathologists and clinicians. There were at least five different sets of guidelines until 2001, when the World Health Organization (WHO) published a consensus classification. In 2008 the WHO revised its guidelines in a labor-intensive process that involved an eight-member steering committee and over 130 pathologists and hematologists around the world. In addition, only around 1,400 cases from Europe and North America were reviewed to cover 50 subtypes, meaning that on average a subtype’s diagnosis criteria was based on what happened to only a limited number of people.

Meanwhile, large medical institutions like MGH often archive decades of pathology reports. This got the MIT researchers thinking about whether they could tap into these resources to develop automated tools that could improve doctors’ understanding of how to diagnose lymphomas.

“It is important to ensure that classification guidelines are up-to-date and accurately summarized from a large number of patient cases,” says Luo, who is first author on the paper. “Our work combs through detailed medical cases to help doctors more comprehensively capture the subtle distinctions between lymphomas.”

Doctor-friendly models

Luo emphasizes that such machine-learning models need to be not only accurate but also interpretable to clinicians. The WHO guidelines’ criteria are outlined via a panel of test results that are themselves relations among medical concepts such as tumor cells and surface antigens. In order to capture the relations, the researchers converted sentences from pathology reports into a graph representation where graph nodes are medical concepts and graph edges are syntactic/semantic dependencies. As described in their previous paper, they then collected frequently occurring subgraphs that correspond to relations that specify test results.

“Clinicians’ diagnostic reasoning is based on multiple test results simultaneously,” Luo says. “Thus it is necessary for us to automatically group subgraphs in a way that corresponds to the panel of test results. This makes the model interpretable to clinicians instead of being a black-box, as they often complain about many other machine learning models.”

The core contribution of this work is to use a technique called Subgraph Augmented Non-negative Tensor Factorization (SANTF). In SANTF, data from the 800 or so medical cases are organized as a three-dimensional table where the dimensions correspond to the set of patients, the set of frequent subgraphs, and the collection of words appearing in and near each data element mentioned in the reports. This scheme clusters each of these dimensions simultaneously, using the relationships in each dimension to constrain those in the others. By examining the resulting clusters, the researchers can link test result panels to lymphoma subtypes.

“The promise of Luo’s work, if applied to very large data sets, is that the criteria that would then help to identify these clusters can inform doctors about how to understand the range of lymphomas and their clinical relationships to each other,” Peter Szolovits says.

“Most natural-language processing in clinical reporting has focused on identifying important phrases or attributes, and not the more difficult task of recognizing relationships and concepts,” explains Professor Wendy Chapman, chair of the department of biomedical informatics at the University of Utah. “Medical experts with years of experience are able to understand not just the words, but the deeper implications. This research gets us a step closer to developing robust computer models that can achieve that level of comprehension.”

On top of that, the SANTF model does not require labeled training data, which makes it possible to automate the process of knowledge discovery. Szolovits is confident that that the team’s model can help doctors make more accurate lymphoma diagnoses based on more comprehensive evidence — and could even be incorporated into future WHO guidelines.

“Our ultimate goal is to be able to focus these techniques on extremely large amounts of lymphoma data, on the order of millions of cases,” says Szolovits. “If we can do that, and identify the features that are specific to different subtypes, then we’d go a long way towards making doctors’ jobs easier — and, maybe, patients’ lives longer.”

By Adam Conner-Simons | CSAIL

Correctly diagnosing a person with cancer — and identifying the specific type of cancer — makes all the difference in successfully treating a patient.

Today your doctor might draw from a dozen or so similar cases and a big book of guidelines. But what if he or she could instead plug your test results and medical history into a computer program that has crunched millions of pieces of similar data?

That sort of future is looking increasingly possible thanks to researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). Working with a team from Massachusetts General Hospital (MGH), PhD student Yuan Luo and MIT Professor Peter Szolovits have developed a computational model that aims to automatically suggest cancer diagnoses by learning from thousands of data points from past pathology reports. The work has been published this month in the Journal of the American Medical Informatics Association.

Better lymphoma diagnoses

The researchers focused on the three most prevalent subtypes of lymphoma, a common cancer with more than 50 distinct subtypes that are often difficult to distinguish. According to Ephraim Hochberg, director of the Center for Lymphoma at MGH and one of the paper’s co-authors, upwards of 5 to 15 percent of lymphoma cases are initially misdiagnosed or misclassified, which can be a significant problem since different lymphomas require dramatically different treatment plans.

For example, Hochberg recently saw a patient who had been mistakenly told that her lymphoma was incurable. If he hadn’t accurately diagnosed her and put her on an aggressive plan, it might have been too late to counteract the cancer.

Lymphoma classification has long been a source of debate for pathologists and clinicians. There were at least five different sets of guidelines until 2001, when the World Health Organization (WHO) published a consensus classification. In 2008 the WHO revised its guidelines in a labor-intensive process that involved an eight-member steering committee and over 130 pathologists and hematologists around the world. In addition, only around 1,400 cases from Europe and North America were reviewed to cover 50 subtypes, meaning that on average a subtype’s diagnosis criteria was based on what happened to only a limited number of people.

Meanwhile, large medical institutions like MGH often archive decades of pathology reports. This got the MIT researchers thinking about whether they could tap into these resources to develop automated tools that could improve doctors’ understanding of how to diagnose lymphomas.

“It is important to ensure that classification guidelines are up-to-date and accurately summarized from a large number of patient cases,” says Luo, who is first author on the paper. “Our work combs through detailed medical cases to help doctors more comprehensively capture the subtle distinctions between lymphomas.”

Doctor-friendly models

Luo emphasizes that such machine-learning models need to be not only accurate but also interpretable to clinicians. The WHO guidelines’ criteria are outlined via a panel of test results that are themselves relations among medical concepts such as tumor cells and surface antigens. In order to capture the relations, the researchers converted sentences from pathology reports into a graph representation where graph nodes are medical concepts and graph edges are syntactic/semantic dependencies. As described in their previous paper, they then collected frequently occurring subgraphs that correspond to relations that specify test results.

“Clinicians’ diagnostic reasoning is based on multiple test results simultaneously,” Luo says. “Thus it is necessary for us to automatically group subgraphs in a way that corresponds to the panel of test results. This makes the model interpretable to clinicians instead of being a black-box, as they often complain about many other machine learning models.”

The core contribution of this work is to use a technique called Subgraph Augmented Non-negative Tensor Factorization (SANTF). In SANTF, data from the 800 or so medical cases are organized as a three-dimensional table where the dimensions correspond to the set of patients, the set of frequent subgraphs, and the collection of words appearing in and near each data element mentioned in the reports. This scheme clusters each of these dimensions simultaneously, using the relationships in each dimension to constrain those in the others. By examining the resulting clusters, the researchers can link test result panels to lymphoma subtypes.

“The promise of Luo’s work, if applied to very large data sets, is that the criteria that would then help to identify these clusters can inform doctors about how to understand the range of lymphomas and their clinical relationships to each other,” Peter Szolovits says.

“Most natural-language processing in clinical reporting has focused on identifying important phrases or attributes, and not the more difficult task of recognizing relationships and concepts,” explains Professor Wendy Chapman, chair of the department of biomedical informatics at the University of Utah. “Medical experts with years of experience are able to understand not just the words, but the deeper implications. This research gets us a step closer to developing robust computer models that can achieve that level of comprehension.”

On top of that, the SANTF model does not require labeled training data, which makes it possible to automate the process of knowledge discovery. Szolovits is confident that that the team’s model can help doctors make more accurate lymphoma diagnoses based on more comprehensive evidence — and could even be incorporated into future WHO guidelines.

“Our ultimate goal is to be able to focus these techniques on extremely large amounts of lymphoma data, on the order of millions of cases,” says Szolovits. “If we can do that, and identify the features that are specific to different subtypes, then we’d go a long way towards making doctors’ jobs easier — and, maybe, patients’ lives longer.”

By Adam Conner-Simons | CSAIL

Four MIT graduate students and an alumnus are among 30 new recipients nationwide of the Paul and Daisy Soros Fellowships for New Americans.

The four current or incoming MIT graduate students who have won Soros Fellowships are Stephanie Speirs, whose mother emigrated from Korea, and who will pursue an MBA at the MIT Sloan School of Management; Yakir Reshef, from Israel, and Andre Shomorony, from Brazil, both of whom are currently enrolled in the Harvard-MIT Health Sciences and Technology (HST) program; and Krzysztof Franaszek, from Poland, who will enroll in HST this spring.

In addition, alumnus Allen Lin ’11, MEng ’11, whose parents are Taiwanese immigrants, will use his Soros Fellowship to pursue a PhD in systems biology at Harvard University.

The Soros Fellowships, established in 1997, award $90,000 for immigrants and children of immigrants to complete graduate studies in the United States. Applicants may propose graduate work in any discipline, and are selected for their potential to make significant contributions to American society, culture, or their academic field.

This year’s 30 winners were selected from a pool of 1,200 applicants. Including this year’s winners, 18 MIT students and alumni have won Soros Fellowships since 2010.

Krzysztof Franaszek


Photo: Christopher Smith

Krzysztof Franaszek emigrated from Poland with his parents; his father, a theoretical physicist, and his mother, a neuropharmacologist, both now work at federal research institutions in Maryland. With an interest in biological science and technology, Franaszek completed his undergraduate degree in cell biology and economics at the University of Maryland; as an undergraduate, he was named as a Howard Hughes Medical Institute Undergraduate Research Fellow.

Franaszek, who aspires to establish a biotechnology and medical research company to develop treatments for age-dependent diseases, is pursuing training as a physician-scientist. With a Gates-Cambridge Scholarship, he is currently completing a PhD in pathology at Cambridge University, focusing on how molecular genetics techniques can combat viral diseases; Franaszek’s Soros Fellowship will allow him to pursue an MD through the HST.

Allen Lin


Photo: Christopher Smith

Alumnus Allen Lin, whose parents emigrated from Taiwan, grew up in New Jersey. He came to MIT with an interest in complex systems; as an undergraduate, he immersed himself in the study of synthetic biology, computer science, technology policy, and public health.

In 2011, Lin was named a Marshall Scholar; as an MIT undergraduate, he also received a Barry M. Goldwater Scholarship and a Department of Homeland Security Scholarship for his research.

Lin holds three degrees from MIT, all awarded in 2011: a bachelor’s in electrical engineering and computer science (EECS), and in biological-chemical engineering, and a master’s in EECS. Following his graduation, Lin’s Marshall Scholarship allowed him to complete an MPhil in technology policy at Cambridge University, followed by an MS in public health at the London School of Hygiene and Tropical Medicine.

The Soros Fellowship will support Lin’s PhD studies in systems biology at Harvard. His research focuses on developing cost-effective vaccines and treatments for infections, particularly HIV, that disproportionally affect marginalized populations. 

Yakir Reshef


Photo: Christopher Smith

HST graduate student Yakir Reshef, whose father is Romanian and mother is Iraqi, was born in Israel and spent his early childhood in a suburb of Jerusalem. He then moved to Kenya with his parents, who work in the medical and public health fields, before the family settled in Maryland.

Passionate about math and computer science, Reshef majored in mathematics as an undergraduate at Harvard, where he developed a method to detect associations between pairs of variables in large data sets. This research resulted in a publication in the journal Science. After completing his undergraduate work, Reshef returned to Israel as a Fulbright Scholar, conducting research in mathematics and computer science at the Weizmann Institute of Science.

Reshef, who aims to use his computational knowledge to analyze medical data and improve outcomes for patients, is now training as a physician-scientist. The Soros Fellowship will support his studies in HST, through which he plans to obtain an MD and a PhD in computer science.

Andre Shomorony


Photo: Christopher Smith

Andre Shomorony grew up in Rio de Janeiro, in a family with Jewish and European roots. When Shomorony was 15, his parents, who were engineers in Brazil, decided to move with their three sons to Florida. The transition was difficult: Shomorony had to learn English, and adapt to a new culture, while his parents struggled to find stable employment.

Despite these difficulties, Shomorony won a full scholarship to Yale University through QuestBridge, an organization that supports low-income, high-achieving students. When his father developed pancreatic cancer, Shomorony turned his interests toward biomedical research. At Yale, he studied the development of techniques to generate tissues for use in transplantation, stem-cell therapy, and reconstructive surgery — work that resulted in a paper in the journal Chemistry Letters on which he was first author. He has since worked at Boston Children’s Hospital, developing a technique for noninvasive, extracorporeal blood filtration to treat sepsis.

Driven by his interests in research, clinical work, and serving underrepresented patient populations, Shomorony enrolled in HST, pursuing an MD while conducting biomedical engineering research. Ultimately, he wants to use his background in biomedical engineering to improve surgical procedures. As an aspiring physician, he intends to work at the intersection of reconstructive plastic surgery, otolaryngology, and surgical oncology.

Stephanie Speirs


Photo: Christopher Smith

Born in Hawaii, Stephanie Speirs was raised by a single mother who emigrated from Korea. Growing up with two siblings, Speirs gained an appreciation for hard work at an early age, earning money to help her mother with expenses. Through these early experiences, she became committed to domestic and international social change.

Speirs received her bachelor’s degree from Yale, and then earned a master’s degree from Princeton University in public affairs and international development. Her interest in government led Speirs to work as a field organizer for Barack Obama’s 2008 presidential campaign; she then went on to work at the National Security Council (NSC), developing policy for the Middle East. In her work at the NSC, Speirs traveled to Yemen and Pakistan, where she focused on economic development.

Speirs’ passion for international development led her to become a fellow at Acumen, a nonprofit venture capital fund that works to reduce poverty in the developing world. In addition, Speirs co-founded Solstice Initiative, a nonprofit whose mission is to give low-income households access to solar energy.

The Soros Fellowship will allow Speirs to complete her MBA at MIT Sloan, giving her the business knowledge to continue developing Solstice Initiative, and furthering her work as an agent of social change.

By Nora Delaney | GECD: Global Education

Four MIT graduate students and an alumnus are among 30 new recipients nationwide of the Paul and Daisy Soros Fellowships for New Americans.

The four current or incoming MIT graduate students who have won Soros Fellowships are Stephanie Speirs, whose mother emigrated from Korea, and who will pursue an MBA at the MIT Sloan School of Management; Yakir Reshef, from Israel, and Andre Shomorony, from Brazil, both of whom are currently enrolled in the Harvard-MIT Health Sciences and Technology (HST) program; and Krzysztof Franaszek, from Poland, who will enroll in HST this spring.

In addition, alumnus Allen Lin ’11, MEng ’11, whose parents are Taiwanese immigrants, will use his Soros Fellowship to pursue a PhD in systems biology at Harvard University.

The Soros Fellowships, established in 1997, award $90,000 for immigrants and children of immigrants to complete graduate studies in the United States. Applicants may propose graduate work in any discipline, and are selected for their potential to make significant contributions to American society, culture, or their academic field.

This year’s 30 winners were selected from a pool of 1,200 applicants. Including this year’s winners, 18 MIT students and alumni have won Soros Fellowships since 2010.

Krzysztof Franaszek


Photo: Christopher Smith

Krzysztof Franaszek emigrated from Poland with his parents; his father, a theoretical physicist, and his mother, a neuropharmacologist, both now work at federal research institutions in Maryland. With an interest in biological science and technology, Franaszek completed his undergraduate degree in cell biology and economics at the University of Maryland; as an undergraduate, he was named as a Howard Hughes Medical Institute Undergraduate Research Fellow.

Franaszek, who aspires to establish a biotechnology and medical research company to develop treatments for age-dependent diseases, is pursuing training as a physician-scientist. With a Gates-Cambridge Scholarship, he is currently completing a PhD in pathology at Cambridge University, focusing on how molecular genetics techniques can combat viral diseases; Franaszek’s Soros Fellowship will allow him to pursue an MD through the HST.

Allen Lin


Photo: Christopher Smith

Alumnus Allen Lin, whose parents emigrated from Taiwan, grew up in New Jersey. He came to MIT with an interest in complex systems; as an undergraduate, he immersed himself in the study of synthetic biology, computer science, technology policy, and public health.

In 2011, Lin was named a Marshall Scholar; as an MIT undergraduate, he also received a Barry M. Goldwater Scholarship and a Department of Homeland Security Scholarship for his research.

Lin holds three degrees from MIT, all awarded in 2011: a bachelor’s in electrical engineering and computer science (EECS), and in biological-chemical engineering, and a master’s in EECS. Following his graduation, Lin’s Marshall Scholarship allowed him to complete an MPhil in technology policy at Cambridge University, followed by an MS in public health at the London School of Hygiene and Tropical Medicine.

The Soros Fellowship will support Lin’s PhD studies in systems biology at Harvard. His research focuses on developing cost-effective vaccines and treatments for infections, particularly HIV, that disproportionally affect marginalized populations. 

Yakir Reshef


Photo: Christopher Smith

HST graduate student Yakir Reshef, whose father is Romanian and mother is Iraqi, was born in Israel and spent his early childhood in a suburb of Jerusalem. He then moved to Kenya with his parents, who work in the medical and public health fields, before the family settled in Maryland.

Passionate about math and computer science, Reshef majored in mathematics as an undergraduate at Harvard, where he developed a method to detect associations between pairs of variables in large data sets. This research resulted in a publication in the journal Science. After completing his undergraduate work, Reshef returned to Israel as a Fulbright Scholar, conducting research in mathematics and computer science at the Weizmann Institute of Science.

Reshef, who aims to use his computational knowledge to analyze medical data and improve outcomes for patients, is now training as a physician-scientist. The Soros Fellowship will support his studies in HST, through which he plans to obtain an MD and a PhD in computer science.

Andre Shomorony


Photo: Christopher Smith

Andre Shomorony grew up in Rio de Janeiro, in a family with Jewish and European roots. When Shomorony was 15, his parents, who were engineers in Brazil, decided to move with their three sons to Florida. The transition was difficult: Shomorony had to learn English, and adapt to a new culture, while his parents struggled to find stable employment.

Despite these difficulties, Shomorony won a full scholarship to Yale University through QuestBridge, an organization that supports low-income, high-achieving students. When his father developed pancreatic cancer, Shomorony turned his interests toward biomedical research. At Yale, he studied the development of techniques to generate tissues for use in transplantation, stem-cell therapy, and reconstructive surgery — work that resulted in a paper in the journal Chemistry Letters on which he was first author. He has since worked at Boston Children’s Hospital, developing a technique for noninvasive, extracorporeal blood filtration to treat sepsis.

Driven by his interests in research, clinical work, and serving underrepresented patient populations, Shomorony enrolled in HST, pursuing an MD while conducting biomedical engineering research. Ultimately, he wants to use his background in biomedical engineering to improve surgical procedures. As an aspiring physician, he intends to work at the intersection of reconstructive plastic surgery, otolaryngology, and surgical oncology.

Stephanie Speirs


Photo: Christopher Smith

Born in Hawaii, Stephanie Speirs was raised by a single mother who emigrated from Korea. Growing up with two siblings, Speirs gained an appreciation for hard work at an early age, earning money to help her mother with expenses. Through these early experiences, she became committed to domestic and international social change.

Speirs received her bachelor’s degree from Yale, and then earned a master’s degree from Princeton University in public affairs and international development. Her interest in government led Speirs to work as a field organizer for Barack Obama’s 2008 presidential campaign; she then went on to work at the National Security Council (NSC), developing policy for the Middle East. In her work at the NSC, Speirs traveled to Yemen and Pakistan, where she focused on economic development.

Speirs’ passion for international development led her to become a fellow at Acumen, a nonprofit venture capital fund that works to reduce poverty in the developing world. In addition, Speirs co-founded Solstice Initiative, a nonprofit whose mission is to give low-income households access to solar energy.

The Soros Fellowship will allow Speirs to complete her MBA at MIT Sloan, giving her the business knowledge to continue developing Solstice Initiative, and furthering her work as an agent of social change.

By Nora Delaney | GECD: Global Education

Many years of research have shown that for students from lower-income families, standardized test scores and other measures of academic success tend to lag behind those of wealthier students.

A new study led by researchers at MIT and Harvard University offers another dimension to this so-called “achievement gap”: After imaging the brains of high- and low-income students, they found that the higher-income students had thicker brain cortex in areas associated with visual perception and knowledge accumulation. Furthermore, these differences also correlated with one measure of academic achievement — performance on standardized tests.

“Just as you would expect, there’s a real cost to not living in a supportive environment. We can see it not only in test scores, in educational attainment, but within the brains of these children,” says MIT’s John Gabrieli, the Grover M. Hermann Professor in Health Sciences and Technology, professor of brain and cognitive sciences, and one of the study’s authors. “To me, it’s a call to action. You want to boost the opportunities for those for whom it doesn’t come easily in their environment.”

This study did not explore possible reasons for these differences in brain anatomy. However, previous studies have shown that lower-income students are more likely to suffer from stress in early childhood, have more limited access to educational resources, and receive less exposure to spoken language early in life. These factors have all been linked to lower academic achievement.

In recent years, the achievement gap in the United States between high- and low-income students has widened, even as gaps along lines of race and ethnicity have narrowed, says Martin West, an associate professor of education at the Harvard Graduate School of Education and an author of the new study.

“The gap in student achievement, as measured by test scores between low-income and high-income students, is a pervasive and longstanding phenomenon in American education, and indeed in education systems around the world,” he says. “There’s a lot of interest among educators and policymakers in trying to understand the sources of those achievement gaps, but even more interest in possible strategies to address them.”

Allyson Mackey, a postdoc at MIT’s McGovern Institute for Brain Research, is the lead author of the paper, which appears the journal Psychological Science. Other authors are postdoc Amy Finn; graduate student Julia Leonard; Drew Jacoby-Senghor, a postdoc at Columbia Business School; and Christopher Gabrieli, chair of the nonprofit Transforming Education.

Explaining the gap

The study included 58 students — 23 from lower-income families and 35 from higher-income families, all aged 12 or 13. Low-income students were defined as those who qualify for a free or reduced-price school lunch.

The researchers compared students’ scores on the Massachusetts Comprehensive Assessment System (MCAS) with brain scans of a region known as the cortex, which is key to functions such as thought, language, sensory perception, and motor command.

Using magnetic resonance imaging (MRI), they discovered differences in the thickness of parts of the cortex in the temporal and occipital lobes, whose primary roles are in vision and storing knowledge. Those differences correlated to differences in both test scores and family income. In fact, differences in cortical thickness in these brain regions could explain as much as 44 percent of the income achievement gap found in this study.

Previous studies have also shown brain anatomy differences associated with income, but did not link those differences to academic achievement.

“A number of labs have reported differences in children’s brain structures as a function of family income, but this is the first to relate that to variation in academic achievement,” says Kimberly Noble, an assistant professor of pediatrics at Columbia University who was not part of the research team.

In most other measures of brain anatomy, the researchers found no significant differences. The amount of white matter — the bundles of axons that connect different parts of the brain — did not differ, nor did the overall surface area of the brain cortex.

The researchers point out that the structural differences they did find are not necessarily permanent. “There’s so much strong evidence that brains are highly plastic,” says Gabrieli, who is also a member of the McGovern Institute. “Our findings don’t mean that further educational support, home support, all those things, couldn’t make big differences.”

In a follow-up study, the researchers hope to learn more about what types of educational programs might help to close the achievement gap, and if possible, investigate whether these interventions also influence brain anatomy.

“Over the past decade we’ve been able to identify a growing number of educational interventions that have managed to have notable impacts on students’ academic achievement as measured by standardized tests,” West says. “What we don’t know anything about is the extent to which those interventions — whether it be attending a very high-performing charter school, or being assigned to a particularly effective teacher, or being exposed to a high-quality curricular program — improves test scores by altering some of the differences in brain structure that we’ve documented, or whether they had those effects by other means.”

The research was funded by the Bill and Melinda Gates Foundation and the National Institutes of Health.

By Anne Trafton | MIT News Office

Many years of research have shown that for students from lower-income families, standardized test scores and other measures of academic success tend to lag behind those of wealthier students.

A new study led by researchers at MIT and Harvard University offers another dimension to this so-called “achievement gap”: After imaging the brains of high- and low-income students, they found that the higher-income students had thicker brain cortex in areas associated with visual perception and knowledge accumulation. Furthermore, these differences also correlated with one measure of academic achievement — performance on standardized tests.

“Just as you would expect, there’s a real cost to not living in a supportive environment. We can see it not only in test scores, in educational attainment, but within the brains of these children,” says MIT’s John Gabrieli, the Grover M. Hermann Professor in Health Sciences and Technology, professor of brain and cognitive sciences, and one of the study’s authors. “To me, it’s a call to action. You want to boost the opportunities for those for whom it doesn’t come easily in their environment.”

This study did not explore possible reasons for these differences in brain anatomy. However, previous studies have shown that lower-income students are more likely to suffer from stress in early childhood, have more limited access to educational resources, and receive less exposure to spoken language early in life. These factors have all been linked to lower academic achievement.

In recent years, the achievement gap in the United States between high- and low-income students has widened, even as gaps along lines of race and ethnicity have narrowed, says Martin West, an associate professor of education at the Harvard Graduate School of Education and an author of the new study.

“The gap in student achievement, as measured by test scores between low-income and high-income students, is a pervasive and longstanding phenomenon in American education, and indeed in education systems around the world,” he says. “There’s a lot of interest among educators and policymakers in trying to understand the sources of those achievement gaps, but even more interest in possible strategies to address them.”

Allyson Mackey, a postdoc at MIT’s McGovern Institute for Brain Research, is the lead author of the paper, which appears the journal Psychological Science. Other authors are postdoc Amy Finn; graduate student Julia Leonard; Drew Jacoby-Senghor, a postdoc at Columbia Business School; and Christopher Gabrieli, chair of the nonprofit Transforming Education.

Explaining the gap

The study included 58 students — 23 from lower-income families and 35 from higher-income families, all aged 12 or 13. Low-income students were defined as those who qualify for a free or reduced-price school lunch.

The researchers compared students’ scores on the Massachusetts Comprehensive Assessment System (MCAS) with brain scans of a region known as the cortex, which is key to functions such as thought, language, sensory perception, and motor command.

Using magnetic resonance imaging (MRI), they discovered differences in the thickness of parts of the cortex in the temporal and occipital lobes, whose primary roles are in vision and storing knowledge. Those differences correlated to differences in both test scores and family income. In fact, differences in cortical thickness in these brain regions could explain as much as 44 percent of the income achievement gap found in this study.

Previous studies have also shown brain anatomy differences associated with income, but did not link those differences to academic achievement.

“A number of labs have reported differences in children’s brain structures as a function of family income, but this is the first to relate that to variation in academic achievement,” says Kimberly Noble, an assistant professor of pediatrics at Columbia University who was not part of the research team.

In most other measures of brain anatomy, the researchers found no significant differences. The amount of white matter — the bundles of axons that connect different parts of the brain — did not differ, nor did the overall surface area of the brain cortex.

The researchers point out that the structural differences they did find are not necessarily permanent. “There’s so much strong evidence that brains are highly plastic,” says Gabrieli, who is also a member of the McGovern Institute. “Our findings don’t mean that further educational support, home support, all those things, couldn’t make big differences.”

In a follow-up study, the researchers hope to learn more about what types of educational programs might help to close the achievement gap, and if possible, investigate whether these interventions also influence brain anatomy.

“Over the past decade we’ve been able to identify a growing number of educational interventions that have managed to have notable impacts on students’ academic achievement as measured by standardized tests,” West says. “What we don’t know anything about is the extent to which those interventions — whether it be attending a very high-performing charter school, or being assigned to a particularly effective teacher, or being exposed to a high-quality curricular program — improves test scores by altering some of the differences in brain structure that we’ve documented, or whether they had those effects by other means.”

The research was funded by the Bill and Melinda Gates Foundation and the National Institutes of Health.

By Anne Trafton | MIT News Office