The mRNA-cancer connection, creepy crimefighting critters, and more

💉 Power Duo: Cancer and mRNA Vaccines

Recent research indicates that the mRNA COVID-19 vaccine may make some cancer treatments more effective. As Science News’s Meghan Rosen reports, even when these vaccines aren’t designed for cancer, they could make tumors more sensitive to concurrent therapies.

👩🏼‍🏫 Teaching your immune system

Messenger RNA, or mRNA, is a molecular instruction set inside your cells. In the case of the COVID-19 vaccine, the mRNA holds information on assembling a segment of the coronavirus spike protein. That teaches your body to recognize the protein and fight it. Cancer mRNA vaccines work similarly, but encode bits of tumor proteins instead of viral ones.

A finding published this past July in the journal Nature Biomedical Engineering showed that an experimental mRNA vaccine given to tumorous mice improved the activity of immunotherapy drugs, empowering the immune system to better harness the drugs and tackle cancer. But, the vaccine didn’t include tumor mRNA. The authors discovered that the mRNA itself, rather than what it encoded, galvanized the immune system against cancer.

The authors then analyzed records of about 1,000 people with a form of lung cancer, who also received an immunotherapy drug. Nearly 200 of the patients also received a COVID mRNA vaccine within 100 days of drug treatment. The researchers reported in October in the journal Nature that three years after diagnosis, 56 percent of vaccinated patients were still alive compared to 31 percent of unvaccinated patients. This played out similarly in patients with another cancer.

💪 A novel approach to cancer treatment

It’s still too early to say whether combining a general mRNA vaccine with immunotherapy is beneficial for cancer patients. While there’s promising evidence, we still need a clinical trial — which the study authors are working on. As cancer is a group of diseases rather than one, the treatment approach is many-pronged. If mRNA vaccines edify the human immune system to be more receptive to treatment, it could be another tool in our growing toolkit to treat cancer. And as mRNA vaccines have been having a moment since 2020 — while meeting resistance, too — all the better to continue putting them to use beyond viral indications.

🤝 mRNA vaccines x cancer immunotherapy

A number of companies have gotten on the mRNA train, using this method to treat cancer, autoimmune diseases and more.

• RNAimmune: This Maryland-based Series A startup, founded in 2020, uses mRNA as the basis for its therapeutics and vaccines to treat an array of indications, including cancer. Over three funding rounds they’ve raised $39.4 million, most recently $27 million in March 2022.
  
• Abogen Biosciences: Founded in 2019, this Series C company based in Suzhou, China pursues mRNA drug discovery for a suite of indications, including oncology and autoimmune diseases. They’ve raised a total of $1.4 billion over six funding rounds.

The wonders of mRNA vaccines continue to pay off.

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♀ Benign, but Not Harmless: Understanding Uterine Fibroids

For biomedical engineer Erika Moore, her research is personal. Having lived with uterine fibroids — noncancerous tumors that grow in the uterus — she knows that while these poorly understood growths are classified as benign, they’re far from harmless. SN’s Tina Hesman Saey reports on how Moore is investigating the mechanism that makes them grow.

🧫 Modeling mechanisms in hydrogel

Uterine fibroids can cause anemia, pain, heavy or irregular menstrual bleeding and reproductive challenges. In the U.S., an estimated 70 percent of white women and 80 percent of Black women will develop them by age 50. And treatment options are paltry, with professionals able to recommend either monitoring or surgery.

We don’t fully understand why or how fibroids grow. Nor are there great in vitro or animal models to aid in research, in particular because they don’t replicate the uterus’s complex 3-D tissue mechanics.

Moore and her team use gelatinous materials called hydrogels to simulate the uterine environment, where they examine how fibroid cells behave, a strategy they published in September in the journal ACS Biomaterials Science & Engineering. Growing these cells in the hydrogel can reveal how they migrate, interact with other cells and change depending on their environment. The team can also explore how certain drugs affect the fibroid cells. Their hope is that they will one day understand how to stop them from forming entirely.

🧪 Historically neglected medicine

Medicine has undervalued and ignored women’s health concerns for centuries. As more researchers and investors realize this area’s critical importance, startups are looking to fill the massive gaps in women’s reproductive medicine. And while all women suffer this discrimination, women of color do so in disproportionate amounts.

In addition to uterine fibroids, conditions like endometriosis, polycystic ovary syndrome and menstrual disorders are still not entirely understood. In 2024, the so-called femtech industry was worth nearly $60 billion.

👩🏿‍🔬 It’s about time

From diagnostic tools to potential treatments, biotech companies are eager to bolster medical knowledge surrounding women’s reproductive health.

• Womed: Stemming from research at a biopolymer lab at France’s University of Montpelier, this company was founded in 2006 to find solutions for intrauterine growths. For uterine fibroids, they’re developing technology to reduce abnormal bleeding associated with the condition. In December 2023, they raised over $6.9 million.
  
• Afynia Laboratories: Founded in 2021, this Hamilton, Canada-based company developed a screening blood test for endometriosis. Endometriosis can be difficult to diagnose without surgery. Instead, the test compares blood levels of bits of genetic material key to endometriosis with those from surgically confirmed endometriosis cases. This seed-stage company most recently raised $5 million this past February, bringing their total to $6.6 million over four funding rounds.
  
• Evestra: This biopharma company targets women’s healthcare, including uterine fibroids and endometriosis. Founded in 2007 and based in San Antonio, Texas, this company is developing treatments in the form of a pill and vaginal ring. In 2009, it raised $1.8 million, and in 2020 received a $15.9 million grant from the Bill & Melinda Gates Foundation to develop contraceptives for people in underserved regions.

Better late than never.

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🕵️‍♀️ AI takes the stand

What’s the fastest, most reliable witness at a crime scene? No, it’s not a camera, it’s a fly. For decades, the tiny, timed life cycle of the blowfly (which includes, wait for it, maggots) has been a standard tool for estimating a corpse’s time of death, a precise but painfully slow process — until AI stepped in. You can read more about that in Meghan Rosen’s fascinating SN article on how scientists are using an AI technique to identify different varieties of these corpse-eating insects, to better fight crimes.

🪰 Like clockwork … with wings

The blowfly life cycle acts like a precise stopwatch, with different larval (read: maggot) stages linked directly to time. Historically, forensic scientists had to manually collect larvae and figure out which species they came from to link to that species’ exact stopwatch. Figuring that out is not only painstaking and highly sensitive to human error but also requires specialized entomological expertise. A team led by Rabi Musah, an organic chemist at Louisiana State University in Baton Rouge, is leveraging deep learning models trained on chemical fingerprints from hundreds of the cocoon-esque casings left behind after those maggots grow their wings. Investigators could analyze casings to get a precise determination of the species, which could help them determine time of death.

⚖️ The case for scale

Specialized forensics suffers from a critical lack of scalability in manual and biological protocols. Expert forensic entomologists are scarce. One traditional species identification technique, rearing any larvae found on a corpse to adulthood (because eggs and larvae from many species tend to look alike) can take days or weeks, delaying case resolution. AI bypasses this bottleneck; Musah’s technique shrinks turnaround time from days to about 90 seconds. This democratization of expertise might also reduce the costs of complex crime scene analysis, allowing valuable human experts to focus on nuanced case interpretation rather than basic data collection.

🪲 The VC swarm

While funding for specialized entomology AI is still in its infancy, here are a few other applications of tech-enhanced forensics.

• The US federal government supports a network of Regional Computer Forensics Laboratories. Many university forensics labs (like the one mentioned in the blowfly article) secure grants from agencies like the National Institute of Justice to develop AI-based classification systems. They apply deep learning to problems like fiber analysis, paint chip matching or toolmark identification (determining whether a specific tool was used to leave a mark at a crime scene). The laboratories often rely on commercial forensic software Cellebrite (NASDAQ:CLBT), which went public in 2018 via a $2.4 billion SPAC deal.
  
• Verogen is a leading commercial platform for forensic DNA analysis. The company was acquired by Netherlands-based QIAGEN in 2023 for $150 million.
  
• Magnet Forensics develops software for forensic analysis of computers, cloud services and mobile devices. Their tools use machine learning to identify known child exploitation images and automatically flag relevant data points across massive datasets. This Canadian company was acquired in 2023 by American private equity firm Thoma Bravo for $1.8 billion.

The takeaway? Maggots or not, AI is sure to be a key factor in future crime fighting.

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👩‍🚒 The last mile of fire tech: just outside the door

We can’t outrun climate change. But we can do more to protect structures and make communities more resilient. This means moving beyond the reactive (putting out fires) to more proactive, structural defense. The latest research shows how communities that prioritize property “hardening” (bolstering resistance through planning and safety measures) are sidestepping disaster, cutting a path for specialized tech. SN’s Nikk Ogasa reports on how science is helping.

🪵Wind-driven hot chips

Most houses lost in a wildfire are destroyed not by a wall of fire but by windborne embers. These embers land on the most vulnerable parts of a home, such as cracked roof tiles, unscreened vents or dry mulch near the foundation. That’s why it’s important to keep flammable hazards such as sheds or mulch piles 10 to 15 feet (3 to 4.5 meters) away from homes. Homeowners and communities that prepare for fire resistance through this hardening tend to see a return on investment for their efforts.

🚒 Scaling resilience

It’s not an easy method to scale. Hardening protocols, while effective, require specific, granular assessments of every roof, gutter and fence line — a massive, nonscalable effort for human inspectors. This is where predictive AI tools and data mapping become critical. Companies are now deploying algorithms trained on high-resolution aerial imagery and geospatial data to instantly score a property’s vulnerability based on roof material, vegetation proximity and slope. This allows insurers, mortgage lenders and municipal governments to prioritize intervention and accurately price risk. For example, AI models can automatically flag every home in a high-risk neighborhood that still uses wooden deck material within five feet of the foundation, enabling targeted, efficient capital deployment for mitigation. This data-driven approach moves resilience from a boutique service to a standardized, scalable financial tool.

🔥 Investing in prevention

Platforms that commoditize risk assessment and mitigation are hot:

• Zesty.ai uses aerial imagery and proprietary AI model to assess specific hazard risk for the property and casualty insurance industry, scoring a property’s vulnerability down to the roof level, and allowing owners to potentially lower insurance premiums by taking preventative measures. The San Francisco–based company has raised over $60 million to date and recently announced a partnership with insurer California Casualty to enhance wildfire underwriting and pricing in support of California’s Sustainable Insurance Strategy, a state-run effort to modernize insurance regulations.
  
• Kettle: Focused on the reinsurance market (a.k.a. “insurance for insurance companies,” a mechanism for primary insurers to transfer portions of their risk to another party), Kettle uses high-resolution satellite imagery and machine learning to underwrite wildfire risk in real-time. Their model allows them to dynamically adjust policy pricing and offer coverage where traditional carriers retreat. Kettle recently secured a $25 million Series A round, validating the demand for AI-driven catastrophe risk capacity.

The future of property insurance won’t be won by better hoses, but by smarter algorithms.

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