Discussions of cancer often stress the genetic mutations that drive disease by altering the normal function of cellular proteins. KRAS, for example, normally acts as an on/off switch for cellular proliferation, but mutations to the gene — common in lung cancer, colorectal cancer, and pancreatic cancer — cause that switch to stay on. 

Yet mutations are only half of the story.

Interactions between these genetic mutations and external factors, such as tissue injury that leads to inflammation, reshape both cells’ identities and their local environment in ways that foster cancer’s emergence and runaway growth.

In pancreatic cancer, these changes start to happen fast — within 24 to 48 hours after tissue damage. They happen predictably. And they greatly expand some cells’ ability to communicate and interact with nearby cells.

Those were the findings from a new study published May 11 in Science by an international research team led by investigators at Sloan Kettering Institute at Memorial Sloan Kettering Cancer Center (MSK) and IRB Barcelona. The research combined sophisticated genetically engineered mouse models and advanced computational methods to map the earliest cell states leading to pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer.

While the five-year survival rate for pancreatic cancer has been inching upward in recent years, it remains quite low — just 12%, according to the Pancreatic Cancer Action Network. The disease is usually not caught until the cancer is in advanced stages and, thanks in part to advances in treating other types of cancer, pancreatic cancer is the third-leading cause of cancer-related death.

The research aimed not only to shed light on the difficult-to-study early cellular events that give rise to pancreatic cancer but also to find potential opportunities for medical intervention at earlier stages of the disease.

How Plasticity Drives Cancer

The ability for cells to shed their original identity and adapt is called plasticity. And this plasticity is enhanced by inflammation, the researchers found.

“These precancerous cells gain the ability to send and receive far more signals than a normal cell,” says computational biologist Dana Pe’er, Ph.D., one of the paper’s two senior authors. “And we saw that this isn’t random — it’s structured. You see the same patterns emerge over and over when you run the experiments in different mice.”

The study was led by co-first authors Cassandra Burdziak, a doctoral student in the Pe’er Lab, and Direna Alonso-Curbelo, PhD., a former member of the lab of co-senior author Scott Lowe, Ph.D., who now leads her lab at IRB Barcelona.

To study the origins and impacts of plasticity on cells expressing a mutated version of KRAS, the scientists performed single-cell analyses on normal, inflamed, premalignant, and malignant tissues using a genetically engineered mouse model designed to accurately recreate many aspects of pancreatic cancer in humans — from its earliest beginnings to metastasis.

“These models allowed us to capture the earliest changes in pancreatic epithelial cells as they progressed from a healthy state toward a malignant state,” says Dr. Lowe, a Howard Hughes Medical Institute Investigator and Chair of the Cancer Biology and Genetics Program at the Sloan Kettering Institute. The single-cell analyses allowed researchers to tease apart the characteristics of sub-populations of individual cells within the pancreas at each stage of progression and how their interactions further drive the progression.

“This project required a significant amount of computational innovation, most of it led by Cassandra,” notes Pe’er, who is also a Howard Hughes Medical Institute Investigator and who heads the Computational and Systems Biology Program at the Sloan Kettering Institute. “We had to invent several new methods to answer questions that aren’t typically asked about plasticity, cell-to-cell communication, and tumor progression.”

For example, the team invented a new classification score to measure the plasticity of a cell.

The team also found that increased plasticity led to the enhancement of genes related to cell-to-cell communication: like those that encode ligands and receptors.

“Basically, these are genes that enable cells to send and receive signals from its environment and with other cells,” Pe’er says. “This gives the cell the ability to respond to signals that a normal cell wouldn’t be able to. They also have an enhanced ability to communicate with immune cells, and, as a result, the immune system around these cells starts to change.”

Additionally, the researchers were able to determine that a few sub-populations of cells, some of them quite rare, transform into major hubs of communication, driving a feedback loop that leads to the development and progression of pancreatic cancer.

The study represents the culmination of research initiated by Dr. Alonso-Curbelo, who has a long-standing interest in detailing the molecular mechanism by which inflammation promotes cancer initiation.

“This work was a true partnership between experimental science and computational science,” Dr. Alonso-Curbelo says. 

Computational models were validated with follow-up experiments. “For example, imaging showed us that the populations of cells that computational methods said were talking to each other were significantly closer to each other in the tissue,” Burdziak says.

Through further experiments, the team was able to demonstrate that these conversations drive cancer development.

“We developed new mouse models to specifically block cell-to-cell signaling associated with neoplastic plasticity,” Dr. Alonso-Curbelo says. “These analyses showed that these expansive communication networks direct pancreatic tumor formation in the mice.“

Toward Clinical Applications

As a whole, the research provides a new, detailed understanding of how cells carrying a mutated copy of the KRAS gene gain plasticity and drive the progression of cancer when subjected to inflammation.

“This provides a roadmap that can help develop strategies to detect or possibly even prevent pancreatic tumors before they reach an incurable stage,” Dr. Lowe says. “And understanding how cell-to-cell communication networks drive the initiation of pancreatic cancer holds promise for the development of therapeutics to block or slow early cancer progression, and even potentially more advanced disease.”

As our computers and other electronic devices become faster and more powerful, they are coming closer to an undeniable physical limitation: heat generated by the electrons that carry information as they move through semiconductors.

“Making heat is a fundamental limit that will prevent the further development of electronic devices. So, we are basically hitting a bottleneck because our computers are way faster than they used to be two decades ago,” said Ran Cheng, an assistant professor of electrical and computer engineering with UCR’s Bourns College of Engineering. 

Workarounds – such as the energy- and water-consuming cooling systems at the warehouse-sized data centers operated by Google and other big tech companies -- can go only so far as artificial intelligence, machine learning, video streaming, and other applications demand faster and faster computer processing and memory retrievals. 

Yet, Cheng envisions a much cooler future. 

In a recent paper, entitled “Coherent Antiferromagnetic Spintronics”, Cheng and his collaborators at Tohoku University in Sendai, Japan, and the Massachusetts Institute of Technology, detail a decade of research advancements in the emerging field of antiferromagnetic spintronics that holds the promise of moving beyond today’s world of electrons moving through semiconductors. 

In this future, information will instead travel without generating significant heat in the form of magnons, which are fundamental quantum units of spinning magnetic moments. Since magnetic moments can spin in different directions along anchored axes, their quantum excitations – magnons – could be used to encode and transfer information in the binary language that sets up the basis of today’s computing. But that’s just a start.

“For binary operation, we just encode zeroes and ones in the counterclockwise and clockwise rotations of the magnetic moments,” Cheng said. “But the exciting thing is that with using the antiferromagnetic insulators, we can also possibly move and process quantum information, which goes beyond simply zeroes and ones.”

Besides energy saving and quantum operation, antiferromagnetic spintronics also offers a great speed advantage over semiconductor electronics. The technology could allow computer processing or memory saving and retrievals to be done at speeds a hundred times faster than electrons moving through semiconductors. If electrons achieve the same level of performance by traveling extremely fast through semiconductors, the enormous amount of heat generated would make your cellphone, laptop, or desktop computer would simply melt, Cheng said.

Cheng’s paper describes a series of crucial findings in coherent antiferromagnetic spintronics, including spin generation and transport, electrically driven spin rotation, and related ultrafast spintronic effects. The paper further outlines areas in immediate attention for the technology to have practical applications. This includes finding ways to interface the fast transfer of information to other components of devices, the visualization of magnetic switching processes, and the exploration of novel quantum effects of magnons.

“When we try to integrate the magnons with other integrated circuits, we are going to have to make the interface perfect,” Cheng said.  “So, I think that there's still a lot of practical problems that we need to solve in the near future.”

Certain types and applications pose an “existential threat to humanity,” healthcare professionals warn

An international group of doctors and public health experts have joined the clamor for a moratorium on AI research until the development and use of the technology are properly regulated. 

Despite its transformative potential for society, including in medicine and public health, certain types and applications of AI, including self-improving general purpose AI (AGI), pose an “existential threat to humanity,” they warn in the open-access journal BMJ Global Health.

They highlight 3 sets of threats associated with the misuse of AI and the ongoing failure to anticipate, adapt to, and regulate the transformational impacts of the technology on society.

The first of these comes from the ability of AI to rapidly clean, organize, and analyze massive data sets consisting of personal data, including images.

This can be used to manipulate behavior and subvert democracy, they explain, citing its role in the subversion of the 2013 and 2017 Kenyan elections, the 2016 US presidential election, and the 2017 French presidential election.

“When combined with the rapidly improving ability to distort or misrepresent reality with deep fakes, AI-driven information systems may further undermine democracy by causing a general breakdown in trust or by driving social division and conflict, with ensuing public health impacts,” they contend.

AI-driven surveillance may also be used by governments and other powerful actors to control and oppress people more directly, an example of which is China’s Social Credit System, they point out. 

This system combines facial recognition software and analysis of ‘big data’ repositories of people’s financial transactions, movements, police records, and social relationships.

But China isn’t the only country developing AI surveillance: at least 75 others, “ranging from liberal democracies to military regimes, have been expanding such systems,” they highlight.

The second set of threats concerns the development of Lethal Autonomous Weapon Systems (LAWS)---capable of locating, selecting, and engaging human targets without the need for human supervision.

LAWS can be attached to small mobile devices, such as drones, and could be cheaply mass-produced and easily set up to kill “at an industrial scale,” warn the authors. 

The third set of threats arises from the loss of jobs that will accompany the widespread deployment of AI technology, with estimates ranging from tens to hundreds of millions over the coming decade.

“While there would be many benefits from ending work that is repetitive, dangerous, and unpleasant, we already know that unemployment is strongly associated with adverse health outcomes and behavior,” they point out.

To date, increasing automation has tended only to shift income and wealth from labor to the owners of capital, so helping to contribute to inequitable wealth distribution across the globe, they note.

“Furthermore, we do not know how society will respond psychologically and emotionally to a world where work is unavailable or unnecessary, nor are we thinking much about the policies and strategies that would be needed to break the association between unemployment and ill health,” they highlight.

But the threat posed by self-improving AGI, which, theoretically, could learn and perform the full range of human tasks, is all-encompassing, they suggest. 

“We are now seeking to create machines that are vastly more intelligent and powerful than ourselves. The potential for such machines to apply this intelligence and power—whether deliberately or not—in ways that could harm or subjugate humans—is real and has to be considered. 

“If realized, the connection of AGI to the internet and the real world, including via vehicles, robots, weapons and all the digital systems that increasingly run our societies, could well represent the ‘biggest event in human history’,” they write.

“With exponential growth in AI research and development, the window of opportunity to avoid serious and potentially existential harms is closing. The future outcomes of the development of AI and AGI will depend on policy decisions taken now and on the effectiveness of regulatory institutions that we design to minimize risk and harm and maximize benefit,” they emphasize. 

International agreement and cooperation will be needed, as well as the avoidance of a mutually destructive AI ‘arms race’, they insist. And healthcare professionals have a key role in raising awareness and sounding the alarm on the risks and threats posed by AI.

“If AI is to ever fulfill its promise to benefit humanity and society, we must protect democracy, strengthen our public-interest institutions, and dilute power so that there are effective checks and balances. 

“This includes ensuring transparency and accountability of the parts of the military–corporate industrial complex driving AI developments and the social media companies that are enabling AI-driven, targeted misinformation to undermine our democratic institutions and rights to privacy,” they conclude.

Stanford engineers have found a metallic compound that could bring more efficient forms of computer memory closer to commercialization, reducing computing’s carbon footprint, enabling faster processing, and allowing AI training to happen on individual devices instead of remote servers.

Over the last decade, with the introduction of increasingly complex artificial intelligence (AI) technologies, the demand for computing power has risen exponentially. New, energy-efficient hardware designs could help meet this demand while reducing computing’s energy use, supporting faster processing, and allowing AI training to take place within the device itself.

“In my opinion, we have already transitioned from the internet era to the AI era,” says Shan Wang, the Leland T. Edwards Professor in the School of Engineering at Stanford University. “We want to enable AI on edge – training locally on your home computer, phone, or smartwatch – for things like heart attack detection or speech recognition. To do that, you need a very fast, non-volatile memory.”

Wang and his colleagues recently found a material that could bring a new type of memory closer to commercialization. In a new paper, the researchers demonstrated that a thin layer of a metallic compound called manganese palladium three had the necessary properties to facilitate a form of working memory that stores data in electron spin directions. This method of memory storage, known as spin-orbit torque magnetoresistive random access memory or SOT-MRAM, has the potential to store data more quickly and efficiently than current methods, which store data using electric charge and require a continuous power input to maintain that data.

“We’ve provided a basic building block for future energy-efficient storage elements,” Wang says. “It’s very foundational, but it’s a breakthrough.”

Harnessing electron spin 

SOT-MRAM relies on an intrinsic property of electrons called spin. To understand spin, picture an electron as a rotating basketball balanced on the end of a professional athlete’s finger. Because electrons are charged particles, the rotation turns the electron into a tiny magnet, polarized along its axis (in this case, a line that extends from the finger balancing the ball). If the electron switches spin in directions, the north-south poles of the magnet switch. Researchers can use the up or down direction of that magnetism – known as the magnetic dipole moment – to represent the ones and zeroes that makeup bits and bytes of computer data.

In SOT-MRAM, a current flowing through one material (the SOT layer) generates specific spin directions. The movement of those electrons, coupled with their spin directions, creates a torque that can switch the spin directions and associated magnetic dipole moments of electrons in an adjacent magnetic material. With the right materials, storing magnetic data is as simple as switching the direction of an electrical current in the SOT layer.

But finding the right SOT materials isn’t easy. Because of the way the hardware is designed, data can be stored more densely when electron spin directions are oriented up or down in the z-direction. (If you imagine a sandwich on a plate, the x- and y-directions follow the edges of the bread and the z-direction is the toothpick shoved through the middle.) Unfortunately, most materials polarize electron spins in the y-direction if the current flows in the x-direction.

“Conventional materials only generate spin in the y-direction – that means we would need an external magnetic field to make switching happen in the z-direction, which takes more energy and space,” says Fen Xue, a postdoctoral researcher in Wang’s lab. “For the purpose of lowering the energy and having a higher density of memory, we want to be able to realize this switching without an external magnetic field.”

The researchers found that manganese palladium three has the properties they need. The material is able to generate spins in any orientation because its internal structure lacks the kind of crystal symmetry that would force all of the electrons into a particular orientation. Using manganese palladium three, the researchers were able to demonstrate magnetization switching in both the y- and z-directions without needing an external magnetic field. Although not demonstrated in the manuscript, x-direction magnetization can also be switched in the absence of an external magnetic field.

“We have the same input current as other conventional materials, but we have three different directions of spins now,” says Mahendra DC, who conducted the work as a postdoctoral researcher at Stanford and is the first author of the paper. “Depending on the application, we can control the magnetization in whatever direction we want.”

DC and Wang credit the multidisciplinary and multi-institutional collaboration that enabled these advances. “Evgeny Tsymbal’s lab at the University of Nebraska led the calculations to predict the unexpected spin directions and movement and Julie Borchers’s lab at the National Institute of Standards and Technology led the measurements and modeling efforts to reveal the intricate microstructures within manganese palladium three,” says Wang. “It truly takes a village.”

Manufacturing possibilities

In addition to its symmetry-breaking structure, manganese palladium three has several other properties that make it an excellent candidate for SOT-MRAM applications. It can, for example, survive and maintain its properties through the post-annealing process that electronics need to go through.

“Post-annealing requires electronics to be at 400 degrees Celsius for 30 minutes,” DC says. “That’s one of the challenges for new materials in these devices, and manganese palladium three can handle that.”

Also, the layer of manganese palladium three is created using a process called magnetron sputtering, which is a technique that is already used in other aspects of memory-storage hardware.

“There’s no new tools or new techniques needed for this kind of material,” Xue says. “We don’t need a textured substrate or special conditions to deposit it.”

The result is a material that not only has novel properties that could help meet our growing computing requirements but can fit smoothly into current manufacturing techniques. The researchers are already working on prototypes of SOT-MRAM using manganese palladium three that will integrate into real devices.

“We are hitting a wall with the current technology,” DC says. “So we have to figure out what other options we have.”