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Cloudflare Expands AI Capabilities with Launch of Thirteen New MCP Servers

26 June 2025 at 20:00

Cloudflare has unveiled thirteen new Model Context Protocol (MCP) servers, enhancing the integration of AI agents with its platform. These servers allow AI clients to interact with Cloudflare's services through natural language, streamlining tasks such as debugging, data analysis, and security monitoring.

By Craig Risi

Gene Expression Analysis and Validation of a Novel Biomarker Signature for Early-Stage Lung Adenocarcinoma

Biomolecules. 2025 May 31;15(6):803. doi: 10.3390/biom15060803.

ABSTRACT

Lung cancer is responsible for 2.21 million annual cancer cases and is the leading worldwide cause of cancer-related deaths. Specifically, lung adenocarcinoma (LUAD) is the most prevalent lung cancer subtype resulting from genetic causes; LUAD has a 15% patient survival rate due to it commonly being detected in its advanced stages. This study aimed to identify a novel biomarker signature of early-stage LUAD utilizing gene expression analysis of human lung tissue samples. Using 22 pairs of LUAD and matched normal lung microarrays, 229 differentially expressed genes were identified. These genes were networked for their protein-protein interactions, and 44 hub genes were determined from protein essentiality. Survival analysis of 478 LUAD patient samples identified four statistically significant candidates. These candidate genes' expression profiles were validated from GTEx and TCGA (347 normal, 483 LUAD samples); immunohistochemistry validated the subsequent protein presence. Through intensive bioinformatic identification and multiple validations of the four-biomarker gene signature, AGER, MGP, and PECAM1 were identified as downregulated in LUAD; SLC2A1 was identified as upregulated in LUAD. These four biologically significant genes are involved in tumorigenesis and poor LUAD prognosis, meriting their use as a clinical biomarker signature and therapeutic targets for early-stage LUAD.

PMID:40563443 | PMC:PMC12191159 | DOI:10.3390/biom15060803

Spatial Proteomics and Transcriptomics Reveal Early Immune Cell Organization in Pancreatic Intraepithelial Neoplasia

JCI Insight. 2025 Jun 26:e191595. doi: 10.1172/jci.insight.191595. Online ahead of print.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) has a poor survival rate due to late detection. PDAC arises from precursor microscopic lesions, termed pancreatic intraepithelial neoplasia (PanIN), that develop at least a decade before overt disease--this provides an opportunity to intercept PanIN-to-PDAC progression. However, immune interception strategies require full understanding of PanIN and PDAC cellular architecture. Surgical specimens containing PanIN and PDAC lesions from a unique cohort of five treatment-naïve patients with PDAC were surveyed using spatial-omics (proteomic and transcriptomic). Findings were corroborated by spatial proteomics of PanIN and PDAC from tamoxifen-inducible KPC (tiKPC) mice. We uncovered the organization of lymphoid cells into tertiary lymphoid structures (TLSs) adjacent to PanIN lesions. These TLSs lacked CD21+CD23+ B cells compared to more mature TLSs near the PDAC border. PanINs harbored mostly CD4+ T cells with fewer Tregs and exhausted T cells than PDAC. Peri-tumoral space was enriched with naïve CD4+ and central memory T cells. These observations highlight the opportunity to modulate the immune microenvironment in PanINs before immune exclusion and immunosuppression emerge during progression into PDAC.

PMID:40569674 | DOI:10.1172/jci.insight.191595

Extrachromosomal DNA replication and maintenance couple with DNA damage pathway in tumors

This study demonstrates that extrachromosomal DNA (ecDNA) replication induces DNA double-strand breaks and activates the DNA damage response (DDR). The DDR pathways, such as alt-NHEJ, are critical for ecDNA maintenance in tumor cells. Mechanistic insights into ecDNA replication and maintenance unveil a therapeutic approach for treating tumors harboring ecDNA.
  • ✇MIT Technology Review
  • The Download: Google DeepMind’s DNA AI, and heatwaves’ impact on the grid Rhiannon Williams
    This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Google’s new AI will help researchers understand how our genes work When scientists first sequenced the human genome in 2003, they revealed the full set of DNA instructions that make a person. But we still didn’t know what all those 3 billion genetic letters actually do.Now Google’s DeepMind division says it’s made a leap in trying to understand the code
     

The Download: Google DeepMind’s DNA AI, and heatwaves’ impact on the grid

26 June 2025 at 20:10

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Google’s new AI will help researchers understand how our genes work

When scientists first sequenced the human genome in 2003, they revealed the full set of DNA instructions that make a person. But we still didn’t know what all those 3 billion genetic letters actually do.

Now Google’s DeepMind division says it’s made a leap in trying to understand the code with AlphaGenome, an AI model that predicts what effects small changes in DNA will have on an array of molecular processes, such as whether a gene’s activity will go up or down.

It’s just the sort of question biologists regularly assess in lab experiments, and is an attempt to further smooth biologists’ work by answering basic questions about how changing DNA letters alters gene activity and, eventually, how genetic mutations affect our health. Read the full story.

—Antonio Regalado

It’s officially summer, and the grid is stressed

It’s crunch time for the grid this week. Large swaths of the US have reached or exceeded record-breaking temperatures. Spain recently went through a dramatic heat wave too, as did the UK, which is bracing for another one soon.

We rely on electricity to keep ourselves comfortable, and more to the point, safe. These are the moments we design the grid for: when need is at its very highest. The key to keeping everything running smoothly during these times might be just a little bit of flexibility. But demand for electricity from major grids is already peaking, and that’s a good reason to be a little nervous. Read the full story.

—Casey Crownhart

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

MIT Technology Review Narrated: How did China come to dominate the world of electric cars?

From generous government subsidies to support for lithium batteries, here are the keys to understanding how China managed to build a world-leading industry in electric vehicles.

This is our latest story to be turned into a MIT Technology Review Narrated podcast, which we’re publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.

Inside OpenAI’s empire with Karen Hao

Journalist Karen Hao’s newly released book, Empire of AI: Dreams and Nightmares in Sam Altman’s OpenAI, tells the story of OpenAI’s rise to power and its far-reaching impact all over the world.

Hao, a former MIT Technology Review senior editor, will join our executive editor Niall Firth in an intimate subscriber-exclusive Roundtable conversation exploring the AI arms race, what it means for all of us, and where it’s headed. Register here to join us at 9am ET on Monday June 30th June.

Special giveaway: Attendees will have the chance to receive a free copy of Hao’s book. See registration form for details.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Meta has won an AI copyright case against authors
The judge said the authors hadn’t presented enough evidence to back up their case. (TechCrunch)
+ It’s not an entirely decisive victory for Meta, though. (Wired $)
+ It’s the second lawsuit in favor of AI giants this week. (Insider $)

2 The US will stop contributing towards a global vaccine alliance
RFK Jr made unsubstantiated claims about Gavi’s safety record. (WP $)
+ Kennedy’s newly-assembled vaccine panel is reviewing its guidelines for children. (Vox)
+ Experts are worried the once-influential panel will cause irreparable harm. (Ars Technica)
+ How measuring vaccine hesitancy could help health professionals tackle it. (MIT Technology Review)

3 Jeff Bezos is cozying up to Donald Trump
If the Trump administration happens to need a new space company, he’s ready and willing to supply it. (WSJ $)
+ Meanwhile, a private astronaut mission is on its way to the ISS. (CNN)

4 Taiwan is working on suicide drones to defend itself from China
The country is taking a leaf out of Ukraine’s defense book. (FT $)
+ This giant microwave may change the future of war. (MIT Technology Review)

5 Biohackers are feeling emboldened by the Trump administration
They welcome lower barriers to entry for their unorthodox treatments. (Wired $)
+ The first US hub for experimental medical treatments is coming. (MIT Technology Review)

6 A UK cyberattack on a health firm contributed to a patient’s death
The ransomware attack disrupted blood services at London hospitals. (BBC)
+ A Russian hacking gang is to blame for the incident. (Bloomberg $)

7 Take a look inside Amazon’s colossal new data center
Four construction teams are working around the clock to finish it. (NYT $)
+ Generating video is the most energy-intensive AI prompt. (WSJ $)
+ We did the math on AI’s energy footprint. Here’s the story you haven’t heard. (MIT Technology Review)

8 The debate around dark energy is intensifying
New research suggests it evolves over time. But not everyone agrees. (Undark)

9 Trump Mobile is no longer claiming to be ‘made in the USA’
It’s now “designed with American values in mind” instead. (Ars Technica)

10 It’s official: The Social Network is getting a sequel
Zuck goes MAGA? (Deadline $)

Quote of the day

“By training generative AI models with copyrighted works, companies are creating something that often will dramatically undermine the market for those works, and thus dramatically undermine the incentive for human beings to create things the old-fashioned way.”

—US district judge Vince Chhabria, who presided over a copyright lawsuit brought against Meta by a group of authors, warns of the implications of the company’s actions, the Guardian reports.

One more thing

Beyond gene-edited babies: the possible paths for tinkering with human evolution

Editing human embryos is restricted in much of the world—and making an edited baby is fully illegal in most countries surveyed by legal scholars. But advancing technology could render the embryo issue moot.

New ways of adding CRISPR, the revolutionary gene editing tool, to the bodies of people already born could let them easily receive changes as well. It’s possible that in 125 years, many people will be the beneficiaries of multiple rare, but useful, gene mutations currently found in only small segments of the population. 

These could protect us against common diseases and infections, but eventually they could also yield improvements in other traits, such as height, metabolism, or even cognition. But humanity won’t necessarily do things the right way. Read the full story.

—Antonio Regalado

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ Amazing things are happening in New York’s Central Park.
+ A newly-discovered species of dinosaur has gone on display in London, and it’s small but perfectly formed.
+ Cool—Bob Dylan is releasing a new art book, this time of his drawings.
+ Iron Maiden bassist Steve Harris has a secret second career—as a footballer ⚽

  • ✇MIT Technology Review
  • Google’s new AI will help researchers understand how our genes work Antonio Regalado
    When scientists first sequenced the human genome in 2003, they revealed the full set of DNA instructions that make a person. But we still didn’t know what all those 3 billion genetic letters actually do.  Now Google’s DeepMind division says it’s made a leap in trying to understand the code with AlphaGenome, an AI model that predicts what effects small changes in DNA will have on an array of molecular processes, such as whether a gene’s activity will go up or down. It’s just the sort of questi
     

Google’s new AI will help researchers understand how our genes work

25 June 2025 at 22:00

When scientists first sequenced the human genome in 2003, they revealed the full set of DNA instructions that make a person. But we still didn’t know what all those 3 billion genetic letters actually do. 

Now Google’s DeepMind division says it’s made a leap in trying to understand the code with AlphaGenome, an AI model that predicts what effects small changes in DNA will have on an array of molecular processes, such as whether a gene’s activity will go up or down. It’s just the sort of question biologists regularly assess in lab experiments.

“We have, for the first time, created a single model that unifies many different challenges that come with understanding the genome,” says Pushmeet Kohli, a vice president for research at DeepMind.

Five years ago, the Google AI division released AlphaFold, a technology for predicting the 3D shape of proteins. That work was honored with a Nobel Prize last year and spawned a drug-discovery spinout, Isomorphic Labs, and a boom of companies that hope AI will be able to propose new drugs.

AlphaGenome is an attempt to further smooth biologists’ work by answering basic questions about how changing DNA letters alters gene activity and, eventually, how genetic mutations affect our health. 

“We have these 3 billion letters of DNA that make up a human genome, but every person is slightly different, and we don’t fully understand what those differences do,” says Caleb Lareau, a computational biologist at Memorial Sloan Kettering Cancer Center who has had early access to AlphaGenome. “This is the most powerful tool to date to model that.”

Google says AlphaGenome will be free for noncommercial users and plans to release full details of the model in the future. According to Kohli, the company is exploring ways to “enable use of this model by commercial entities” such as biotech companies. 

Lareau says AlphaGenome will allow certain types of experiments now done in the lab to be carried out virtually, on a computer. For instance, studies of people who’ve donated their DNA for research often turn up thousands of genetic differences, each slightly raising or lowering the chance a person gets a disease such as Alzheimer’s.

Lareau says DeepMind’s software could be used to quickly make predictions about how each of those variants works at a molecular level, something that would otherwise require time-consuming lab experiments. “You’ll get this list of gene variants, but then I want to understand which of those are actually doing something, and where can I intervene,” he says. “This system pushes us closer to a good first guess about what any variant will be doing when we observe it in a human.”

Don’t expect AlphaGenome to predict very much about individual people, however. It offers clues to nitty-gritty molecular details of gene activity, not 23andMe-type revelations of a person’s traits or ancestry. 

“We haven’t designed or validated AlphaGenome for personal genome prediction, a known challenge for AI models,” Google said in a statement.

Underlying the AI system is the so-called transformer architecture invented at Google that also powers large language models like GPT-4. This one was trained on troves of experimental data produced by public scientific projects.

Lareau says the system will not broadly change how his lab works day to day but could permit new types of research. For instance, sometimes doctors encounter patients with ultra-rare cancers, bristling with unfamiliar mutations. AlphaGenome could suggest which of those mutations are really causing the root problem, possibly pointing to a treatment.

“A hallmark of cancer is that specific mutations in DNA make the wrong genes express in the wrong context,” says Julien Gagneur, a professor of computational medicine at the Technical University of Munich. “This type of tool is instrumental in narrowing down which ones mess up proper gene expression.” 

The same approach could apply to patients with rare genetic disease, many of whom never learn the source of their condition, even if their DNA has been decoded. “We can obtain their genomes, but we are clueless as to which genetic alterations cause the disease,” says Gagneur. He thinks AlphaGenome could give medical scientists a new way to diagnose such cases. 

Eventually, some researchers aspire to use AI to design entire genomes from the ground up and create new life forms. Others think the models will be used to create a fully virtual laboratory for drug studies. “My dream would be to simulate a virtual cell,” Demis Hassabis, CEO of Google DeepMind, said this year. 

Kohli calls AlphaGenome a “milestone” on the road to that kind of system. “AlphaGenome may not model the whole cell in its entirety … but it’s starting to sort of shed light on the broader semantics of DNA,” he says.

Rescuing dendritic cell interstitial motility sustains antitumour immunity

Nature, Published online: 25 June 2025; doi:10.1038/s41586-025-09202-9

Disruption of dendritic cell (DC) interstitial motility in the tumour microenvironment promotes immune evasion, and enhancement of DC interstitial motility offers a route for DC-centric immunotherapy.
  • ✇MRD
  • Clinical Utility of ctDNA Analysis in Lung Cancer-A Review Kamil Makar · Agata Wróbel · Adam Antczak · Damian Tworek
    Adv Respir Med. 2025 Jun 12;93(3):17. doi: 10.3390/arm93030017.ABSTRACTCirculating free DNA (cfDNA) is genetic material released from various cells into bodily fluids. Among its fractions, circulating tumor DNA (ctDNA) originates from tumor cells and reflects their genetic material, including mutations and epigenetic changes. Methods commonly employed for detecting ctDNA in blood include next-generation sequencing (NGS) and various types of PCR. The presence of ctDNA can be utilized in liquid bi
     

Clinical Utility of ctDNA Analysis in Lung Cancer-A Review

25 June 2025 at 18:00

Adv Respir Med. 2025 Jun 12;93(3):17. doi: 10.3390/arm93030017.

ABSTRACT

Circulating free DNA (cfDNA) is genetic material released from various cells into bodily fluids. Among its fractions, circulating tumor DNA (ctDNA) originates from tumor cells and reflects their genetic material, including mutations and epigenetic changes. Methods commonly employed for detecting ctDNA in blood include next-generation sequencing (NGS) and various types of PCR. The presence of ctDNA can be utilized in liquid biopsies for many diagnostic purposes related to various cancers. It is a minimally invasive method of sampling molecular compounds from tumor cells. In this paper, we focus on current knowledge regarding the liquid biopsy of blood ctDNA in the context of lung cancer, one of the leading causes of cancer-related mortality. Currently, as a clinically approved method, liquid biopsy serves as a complementary technique in NSCLC diagnostic and genetic profiling. Other applications of liquid biopsy that are still being investigated include the detection of minimal residual disease (MRD) after curative treatment and response monitoring to systemic treatment. This review discusses current and future potential directions for the development and implementation of ctDNA for patients with NSCLC.

PMID:40558116 | PMC:PMC12189613 | DOI:10.3390/arm93030017

MiniMax Releases M1: a 456B Hybrid-Attention Model for Long-Context Reasoning and Software Tasks

25 June 2025 at 02:55

MiniMax has introduced MiniMax-M1, a new open-weight reasoning model built to handle extended contexts and complex problem-solving with high efficiency. Built on top of the earlier MiniMax-Text-01, M1 features a hybrid Mixture-of-Experts (MoE) architecture and a novel “lightning attention” mechanism.

By Robert Krzaczyński

Midjourney Debuts V1 AI Video Model

24 June 2025 at 18:31

Midjourney has launched its first video generation V1 model, a web-based tool that allows users to animate still images into 5-second video clips.

By Daniel Dominguez

Gastric cancer: from biomarkers to functional precision medicine

Trends Mol Med. 2025 Jun 23:S1471-4914(25)00118-2. doi: 10.1016/j.molmed.2025.05.007. Online ahead of print.

ABSTRACT

Gastric cancer (GC) remains a deadly disease because of late detection and limited treatment options at advanced stages. Treatment of patients with metastatic disease is based on chemotherapy, complemented by antibodies targeting HER2, VEGFR2, and more recently PD-1 or claudin 18.2. Further targets, such as FGFR2b, as well as novel drug classes including antibody-drug conjugates (ADCs) and bispecific antibodies, are promising developments in GC treatment. Despite the failure of several targeted agents, the landscape of GC therapy is evolving rapidly, facilitated by umbrella or platform precision medicine trials. The integration of next-generation sequencing and other omics techniques into molecular tumor boards, as well as functional drug testing on patient-derived models, might bring us closer to personalized oncology and ultimately improve patient survival.

PMID:40555635 | DOI:10.1016/j.molmed.2025.05.007

Integrative Multi-Omic and Immune Profiling of Lung Adenocarcinoma: Molecular Landscapes, Gene Expression, and Treatment Response Insights

Oncologist. 2025 Jun 24:oyaf191. doi: 10.1093/oncolo/oyaf191. Online ahead of print.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) is a major cause of cancer death. Traditional histopathological classification overlooks molecular heterogeneity, limiting personalized treatment. This study used multiomic data to define LUAD subtypes, assess prognostic significance, and analyze immune features, aiming to improve targeted therapy and clinical outcomes.

METHODS: This study used Consensus Clustering and Gap Statistics to analyze LUAD multiomic data, including mRNA, lncRNA, miRNA, DNA methylation, and mutations. Clustering was validated by silhouette plots and heatmaps. Molecular characterization involved regulon activity, immune and metabolic profiling. Functional assays (qPCR, WB, CCK-8, flow cytometry) assessed NDNF's role in LUAD.

RESULTS: Two molecular LUAD subtypes showed distinct clustering and survival outcomes. One subtype had worse prognosis and unique immune features, including checkpoint expression and microenvironment differences. Gene signatures and metabolism varied by subtype. NDNF was downregulated in tumors; its overexpression suppressed LUAD cell viability and promoted apoptosis, suggesting tumor-suppressive function.

CONCLUSION: This study identifies two LUAD subtypes with distinct molecular and immune features linked to prognosis and therapy response. NDNF downregulation and its tumor-suppressive effects highlight its therapeutic potential. These findings support improved LUAD stratification and personalized treatment strategies.

IMPLICATIONS FOR PRACTICE: This study reveals two LUAD molecular subtypes with distinct prognoses and immune features, offering a basis for more precise treatment strategies. The identification of NDNF as a potential tumor suppressor suggests its value as both a biomarker and therapeutic target. These findings support improved LUAD stratification and personalized therapy.

PMID:40554675 | DOI:10.1093/oncolo/oyaf191

Unraveling the role of GPCR signaling in metabolic reprogramming and immune microenvironment of lung adenocarcinoma: a multi-omics study with experimental validation

Front Immunol. 2025 Jun 6;16:1606125. doi: 10.3389/fimmu.2025.1606125. eCollection 2025.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) is characterized by metabolic and immune heterogeneity, driving tumor progression and therapy resistance. While G protein-coupled receptors (GPCR) signaling is known to regulate metabolism and immunity in cancers, its role in LUAD remains poorly defined. This study explores the influence of GPCR signaling on LUAD metabolism and immune landscape.

METHODS: We performed non-negative matrix factorization (NMF) clustering of GPCR signaling genes in TCGA-LUAD cohort to identify distinct molecular subgroups. A prognostic model was developed based on GPCR signaling genes using least absolute shrinkage and selection operator (LASSO) analysis and Cox regression. Differentially expressed genes were analyzed for metabolic pathway enrichment and immune infiltration. In addition, key genes within GPCR signaling were identified and validated through functional assays.

RESULTS: NMF clustering based on GPCR signaling identified three subgroups in LUAD, with cluster 3 exhibiting poorer overall survival and significant enrichment in multiple prognostic associated metabolism pathways including purine, pyrimidine, glyoxylate and dicarboxylate metabolism. Then, we developed a GPCRscore prognostic model and validated across multiple cohorts, which effectively stratified LUAD patients into distinct risk groups. High-risk LUAD patients had an immunosuppressive microenvironment and activated metabolic reprogramming. ADM was identified as a key gene in the high-risk group, correlating with tumor stage, immune suppression, and resistance to immunotherapy. Clinically, ADM was highly expressed in tumor tissues and shows elevated concentrations in the peripheral blood of patients with advanced-stage LUAD. Subsequently, we demonstrated that knock-down of ADM in LUAD cells impaired their proliferation, migration, and invasion, while also reducing the angiogenic potential of endothelial cells in vitro. Adrenomedullin promoted LUAD progression in a murine metastasis model. Further, adrenomedullin inhibited CD8+ T cells proliferation, induced exhaustion, and impaired cytotoxic function. Finally, drug sensitivity and cell viability analysis showed LUAD patients with high levels of ADM exhibited sensitivity to the treatment of Staurosporine and Dasatinib.

CONCLUSIONS: In summary, this study reveals the pivotal role of GPCR signaling particularly mediated by ADM in orchestrating metabolic reprogramming and immune modulation in LUAD. ADM emerges as a potential predictive biomarker and therapeutic target, offering valuable implications for optimizing strategies.

PMID:40547013 | PMC:PMC12179119 | DOI:10.3389/fimmu.2025.1606125

  • ✇MIT Technology Review
  • More news from the labs of MIT MIT Alumni News Staff
    Hundred-year storm tides could strike every decade in Bangladesh Tropical cyclones can generate devastating storm tides—seawater heightened by the tides that causes catastrophic floods in coastal regions. An MIT study finds that as the planet warms, the recurrence of destructive storm tides will increase tenfold for one of the world’s hardest-hit regions. New electronic “skin” could lead to lightweight night-vision glasses  MIT engineers have developed a technique to grow and peel ultra
     

More news from the labs of MIT


Hundred-year storm tides could strike every decade in Bangladesh

Tropical cyclones can generate devastating storm tides—seawater heightened by the tides that causes catastrophic floods in coastal regions. An MIT study finds that as the planet warms, the recurrence of destructive storm tides will increase tenfold for one of the world’s hardest-hit regions.

New electronic “skin” could lead to lightweight night-vision glasses 

MIT engineers have developed a technique to grow and peel ultrathin “skins” of electronic material that could be used in wearable sensors, flexible transistors and computing elements, and sensitive compact imaging devices.

Technology makes pesticides stick to plant leaves

A new pesticide application system developed by MIT researchers and their spinoff company could significantly cut use of pesticides and fertilizers, saving farmers money and reducing polluting runoff.

New printable metamaterials that are both strong and stretchy could allow fabrication of bendable ceramics, glass, and metals.

These tough yet bendy materials could be made into tear-resistant textiles, flexible semiconductors, electronic chip packaging, and durable yet compliant scaffolds on which to grow cells for tissue repair.

  • ✇MIT Technology Review
  • Cancer-targeting nanoparticles are moving closer to human trials Anne Trafton
    Over the past decade, Institute Professor Paula Hammond ’84, PhD ’93, and her students have used a technique known as layer-by-layer assembly to create a variety of polymer-coated nanoparticles that can be loaded with cancer-fighting drugs. The particles, which could prevent many side effects of chemotherapy by targeting tumors directly, have proved effective in mouse studies. Now the researchers have come up with a technique that allows them to manufacture many more particles in much less time,
     

Cancer-targeting nanoparticles are moving closer to human trials

25 June 2025 at 05:00

Over the past decade, Institute Professor Paula Hammond ’84, PhD ’93, and her students have used a technique known as layer-by-layer assembly to create a variety of polymer-coated nanoparticles that can be loaded with cancer-fighting drugs. The particles, which could prevent many side effects of chemotherapy by targeting tumors directly, have proved effective in mouse studies. Now the researchers have come up with a technique that allows them to manufacture many more particles in much less time, moving them closer to human use.

“There’s a lot of promise with the nanoparticle systems we’ve been developing, and we’ve been really excited more recently with the successes that we’ve been seeing in animal models for our treatments for ovarian cancer in particular,” says Hammond, the senior author of a paper on the new technique along with Darrell Irvine, a professor at the Scripps Research Institute.

In the original production technique, layers with different properties can be laid down by alternately exposing a particle to positively and negatively charged polymers, with extensive purification to remove excess polymer after each application. Each layer can carry therapeutics as well as molecules that help the particles find and enter cancer cells. But the process is time-consuming and would be difficult to scale up. 

In the new work, the researchers used a microfluidic mixing device that allows them to sequentially add layers as the particles flow through a microchannel. For each layer, they can calculate exactly how much polymer is needed, which eliminates the slow and costly purification step and saves significantly on material costs.

gloved hands hold the device
This microfluidic device can be used to assemble the drug delivery nanoparticles rapidly and in large quantities.
GRETCHEN ERTL

This strategy also facilitates compliance with the FDA’s GMP (good manufacturing practice) requirements, which ensure that products meet safety standards and can be manufactured consistently. “There’s much less chance of any sort of operator mistake or mishaps,” says Ivan Pires, PhD ’24, a postdoc at Brigham and Women’s Hospital and a visiting scientist at the Koch Institute, who is the paper’s lead author along with Ezra Gordon ’24. “We can create an innovation within the layer-by-layer nanoparticles and quickly produce it in a manner that we could go into clinical trials with.”

In minutes, the researchers can generate 15 milligrams of nanoparticles (enough for about 50 doses for certain cargos), which would have taken close to an hour with the original process. They say this means it would be realistic to produce more than enough for clinical trials and patient use.

To demonstrate the technique, the researchers created layered nanoparticles loaded with the immune molecule ­interleukin-­12; they have previously shown that such particles can slow growth of ovarian tumors in mice. Those manufactured using the new technique performed similarly to the originals and managed to bind to cancer tissue without entering the cancer cells. This lets them serve as markers that activate the immune system in the tumor, which can delay tumor growth and even lead to cures in mouse models of ovarian cancer. 

The researchers have filed for a patent and are working with MIT’s Deshpande Center for Technological Innovation in hopes of forming a company to commercialize the technology, which they say could also be applied to glioblastoma and other types of cancer. 

  • ✇InfoQ
  • New Crypto-Jacking Attacks Target DevOps and AI Infrastructure Matt Saunders
    Security researchers at Wiz have uncovered a sophisticated crypto-jacking attack targeting publically accessible API servers for several popular DevOps tools. Similarly, researchers at Sysdig have uncovered an attack on the popular AI tool Open WebUI using many of the same techniques and crypto-miners. By Matt Saunders
     

New Crypto-Jacking Attacks Target DevOps and AI Infrastructure

24 June 2025 at 16:00

Security researchers at Wiz have uncovered a sophisticated crypto-jacking attack targeting publically accessible API servers for several popular DevOps tools. Similarly, researchers at Sysdig have uncovered an attack on the popular AI tool Open WebUI using many of the same techniques and crypto-miners.

By Matt Saunders
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