Predicting the future with better data visualization

January 10, 2019

Imagine you operate an amusement park and you want to ensure your park is optimized for both guest satisfaction and operational efficiency. One way to do it is to track how visitors move throughout the park. Monitoring that data will allow you to improve the park layout, manage ride wait times and generally improve operations.

That type of data is no longer limited to video games such as "Roller Coaster Tycoon." It is part of the research that Ross Maciejewski, an associate professor of computer science in the Ira A. Fulton Schools of Engineering at Arizona State University, is conducting as he focuses his work on how to enable the exploration and communication of data. Ross Maciejewski is exploring spatiotemporal data to find patterns and identify anomalies that help forecast what might occur in the future. Photo by Jessica Hochreiter/ASU Download Full Image

Specifically, he looks at data — such as crime statistics, census data and climate data — that encompass a specific geographic location and time.

“What we’re trying to do is develop new solutions for exploring this large spatiotemporal data to find patterns and identify anomalies,” Maciejewski said. “Our goal is to help analysts build models that can forecast what might occur in the future. This allows for better planning and management.”

Maciejewski, the director of the Center for Accelerating Operational Efficiency, is also expanding this work as some of his research has looked at how people might walk through a city and how to organize landscaping to provide better shade.

In his lab, Maciejewski is looking at ways to help designers better convey their messages in maps, known as choropleth maps, like those seen during election coverage.

“We’re looking at choropleth maps that put data into discrete buckets; however, the choice of how those buckets are decided can be done in numerous ways,” explained Maciejewski. “We’ve been developing tools to try and help designers understand how well their design is actually conveying the real data.”

Yifan Zhang, a former doctoral student and member of Maciejewski’s lab, worked to explore how various map classification schemes could be manipulated to create different messaging.

For example, imagine an election map of the United States split into two colors, red and blue. Election results for each state will give each color a value between 0 and 100 with the color of each state determined by their given value.

That methodology may give you an answer, but it won’t give you the full story of the data. If you split red and blue at above and below 50, then states with a value of 49 get placed in blue even though this value is very close to being in the red.

“We want to see how much these sorts of issues impact the map messaging and provide map designers with an awareness that this is occurring,” said Maciejewski.

The beginning of a research journey

This work is all related to the National Science Foundation’s CAREER Award Maciejewski was awarded in 2014.

“The main goals of our research when we first set out was, how can we effectively explore such space-time data in order to enhance knowledge discovery and dissemination,” said Maciejewski.

The team produced a solid body of literature demonstrating challenges and potential solutions in this area and identifying areas where more work is needed. This includes 10 journal publications with five of those appearing in IEEE Transactions on Visualization and Computer Graphics, one in the Annals of the American Association of Geographers and seven conference publications.

“We had envisioned particular domains that we were going to explore such as crime, climate and health,” said Maciejewski. “However, given the abundance of these types of data, we were able to really hit new areas, including movement data, like taxi data and amusement park visitors as well as global trade data. This allowed us to see how well things might generalize and really strengthened our findings.”

Looking back to move forward

For Maciejewski, the NSF CAREER Award represented his first significant research recognition.

“It served as a really important mechanism for me to pursue some of my interdisciplinary collaborations,” said Maciejewski. “For visualization, we need data and domain problems.”

Working with climate scientists, urban planners, criminologists and other experts allowed him to think about different problems and domains he could pursue.

“It helped me develop other research ideas that could spin out from this work,” said Maciejewski. “I’m very grateful for this award and the support that I had at ASU for doing interdisciplinary research.” 

Developing future researchers

The NSF CAREER Award requires an education component to the recipient’s project. For Maciejewski, this involved developing an entire college course.

“I developed the class known as Introduction to Undergraduate Research,” said Maciejewski. “This course is open to any student in the Fulton Schools and is primarily targeted to freshmen and sophomores who want to learn about the research that goes on at ASU and how to get involved.”

At least 50 percent of the students engaged in the class went on to conduct undergraduate research in one form or another, according to surveys done by Maciejewski. Several students from the course even joined his lab, with Scott Freitas, Rolando Garcia and Alexandra Porter each receiving NSF Graduate Research Fellowships to continue their studies in graduate school.

“It’s been great to see students I’ve worked with as undergrads at ASU go on to Berkeley (Garcia), Stanford (Porter) and Georgia Tech (Freitas), to name a few,” said Maciejewski. “I’m excited to see their PhD research.”

Erik Wirtanen

Web content comm administrator, Ira A. Fulton Schools of Engineering


ASU researchers address a primary cause of treatment failure for pancreatic cancer

January 10, 2019

As the second leading cause of death worldwide, cancer is a focal point in both clinical research and health care fields, but not all cancers are created equal. While some cancers are now much less deadly due to recent medical advances, other aggressive cancers remain highly resistant to currently available therapies.

This therapy resistance is a leading cause of cancer-associated death. Pancreatic cancer is an extreme example of this effect, and therapy resistance is a major reason why only 4 percent of patients with pancreatic cancer are still alive five years after their diagnosis.   Cover An image depicting the essentials of new ASU research was used as the cover of the Theranostics issue that published the study; it portrays pancreatic cancer cells with exosomes budding off as they are released to transmit drug resistance to other adjacent cancer cells. Download Full Image

“Researchers are still working on the mechanisms behind drug resistance. One potential point of interest is the heterogeneity in the tumor microenvironment,” said Jia Fan, an assistant research professor in the Biodesign Virginia G. Piper Center for Personalized Diagnostics at Arizona State University.

A tumor contains a large assortment of cells that differ slightly in their genetic makeup due to an ongoing mutation process. This genetic heterogeneity provides a tumor with a suite of cells that may respond differently to treatment, enhancing the probability that some tumor cells will be able to evade therapy and go on to multiply and wreak havoc.

Identifying mechanisms driving therapy resistance is a crucial step toward improving patient outcomes. To this end, researchers are working to develop biomarkers of this resistance — factors produced by cancer cells that can serve as early warning beacons of therapy resistance.

Biodesign researchers Fan and Bo Ning uncovered a cause of resistance to chemotherapy drugs, or “chemoresistance,” in a cover story for the peer-reviewed medical journal Theranostics.

“For pancreatic cancer, most of the patients are sensitive to the chemo drug at the beginning of treatment, but over time, they grow resistant to the therapy,” Fan said. “They acquire drug resistance.”

A major question is how nonresistant cancer cells acquire this drug resistance.

Fan and Ning, an assistant research professor in the Biodesign Center for Molecular Design and Biomimetics, concluded that chemoresistance from resistant cancer cells to nonresistant cancer cells is transmitted through bubble-like entities known as exosomes.

Exosomes are very small vesicles released by most cells, including cancer cells, that contain factors derived from the cytoplasm and both the endosomal and plasma membranes of their parent cells. These factors can alter the function of exosome recipient cells, although there was no evidence that they could directly transfer chemoresistance before this study.

Fan and Ning tested their hypothesis by first demonstrating that exosomes purified from chemoresistant pancreatic cancer cells could transfer this resistance to nonresistant cells. They then analyzed these exosomes to identify potential factors that could confer this resistance.

“The protein expressed on these types of exosomes may be a potential target for future treatment and also could be used as a method to predict whether patients will have subsequent drug resistance or will still be sensitive to the drugs,” Fan said. 

Their subsequent experiments revealed that blocking the expression of one of these factors greatly reduced chemoresistance transfer via an exosome-dependent mechanism.

Since exosome-derived factors can be detected in standard blood samples, these results suggest this chemoresistance-associated factor, or others like it, could serve as a “minimally invasive predictive biomarker for pancreatic cancer treatment response.”

This would be a major advance since standard methods used to assess cancer treatment responses are highly invasive, and their accuracy may depend heavily upon the region captured in the tissue biopsy.

Their concept of exosome transfer of chemoresistance was depicted on cover of the Theranostics issue that published their research.

Ning, who specializes in stem cell research and cancer immunotherapy, was responsible for cultivating the human cell lines used in the study, and Fan, the primary author on the study, performed the exosome studies using these cell lines to examine the cause of chemoresistance.

Studies on this matter are far from over, however. The researchers hope to continue this work and eventually translate it into future pancreatic cancer treatments, since they believe that these exosomes contain factors that can be used to pinpoint specific drug resistance and guide appropriate therapy.

“Based on this study, maybe we can find more collaborators to accelerate and translate this study into clinical settings,” Fang said.

Fan has established a collaboration with MD Anderson Cancer Center in Houston to analyze pancreatic cancer patient blood samples to determine the ability of the detected exosome biomarker to predict chemotherapy responses.

Ning attributes the success of the study to the fact that Biodesign promotes the sharing of ideas.

“Biodesign is quite an open environment where investigators, postdocs and undergrads are always encouraged to work together,” Ning said. “Competition is so high at other institutions, where individuals are discouraged from sharing their ideas and are more protective. Here, everybody is open with their ideas — they want to foster collaboration.”

Tony Hu, an associate professor at the Biodesign Virginia G. Piper Center for Personalized Diagnostics and at ASU’s School of Biological and Health Systems Engineering, mentored the researchers and aided in collaborations with the MD Anderson Cancer Center.

“This is a very unique study with great translational potential,” Hu said. “The discovery of a biomarker of therapy response would pave a new way for clinical prognosis in pancreatic cancer.”

Gabrielle Hirneise

Assistant science writer , Biodesign Institute