TRACERx MRD Results Showcase ppmSeq’s Ultra-Sensitive ctDNA Detection at AACR

Minimal residual disease (MRD) continues to be a central focus at the AACR meeting. The small numbers of cancer cells that remain in the body after treatment helps gauge the effectiveness of a treatment and relapse risk. The ability to detect those cells, even in tiny amounts, is an ongoing goal of the cancer community.

At this year’s AACR, the sequencing company Ultima Genomics is announcing new findings in this area using its ppmSeq technology. The data will be presented across six abstracts, including a plenary session.

Highlighting the program will be initial TRACERx (TRAcking Cancer Evolution through therapy (Rx)) MRD data showcasing performance of ppmSeq relative to ultrasensitive bespoke panels.

TRACERx is a long-term study—one of the largest tumor evolution studies—funded by Cancer Research UK. The program analyzes how cancer evolves, spreads to other parts of the body, and develops resistance to treatments. Instead of taking just one biopsy, researchers sample different parts of the same tumor and metastases; the program involves sequencing multi-region and multi-time-point genetic data from over 3,200 tumor samples from over 800 lung cancer patients.

The data will be presented at a plenary session by Charles Swanton, FRCP, BSc, PhD,  professor at The Francis Crick Institute in the U.K. He will present an early validation pilot of ppmSeq across 50 plasma samples—using tumor-specific variants identified from prior whole genome sequencing—achieved high analytical sensitivity for ctDNA detection at low single-digit parts-per-million.

“TRACERx has always followed the science of cancer evolution wherever it leads,” said Swanton. “Improving the sensitivity of ctDNA detection is central to the wider ambition for MRD monitoring, and expanding studies across a broader patient population will give us the statistical power and clinical context to determine how whole genome MRD monitoring can be deployed at NHS scale and beyond.”

Data from collaborators will also be presented at the conference. Labcorp will present data from an independent analytical study of an assay developed in coordination with ppmSeq technology, including the performance across multiple solid tumor types in pre-surgical, treatment-naive plasma samples. This analysis of 120 non-cancerous donor samples showed specificity exceeding 99.9%, underscoring the ability of ppmSeq whole genome sequencing to accurately differentiate between cancerous and non-cancerous samples, minimizing false positives. Additional analysis across three commercially available cancer cell lines spanning 13 concentration levels from 0.5 to 500 parts per million showed a 95% limit of detection below 3 ppm, demonstrating the assay’s capacity to detect ultra-low levels of circulating tumor DNA (ctDNA).

“For a long time, the question has been whether you can get truly ultra-sensitive MRD detection from a whole genome approach without all the complexity of bespoke assays,” notes Gilad Almogy, PhD, CEO of Ultima Genomics. “What these AACR data show is that the answer is yes. We’re seeing ppmSeq deliver the level of sensitivity needed to make whole genome MRD practical, scalable, and much easier to deploy globally.”

The post TRACERx MRD Results Showcase ppmSeq’s Ultra-Sensitive ctDNA Detection at AACR appeared first on GEN – Genetic Engineering and Biotechnology News.

<![CDATA[Artemis astronauts spotlight psychiatric medication, mental health support, and trust—revealing why psychiatry’s village mindset strengthens care, leadership, and ethics.]]>

The Download: bad news for inner Neanderthals, and AI warfare’s human illusion

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.

The problem with thinking you’re part Neanderthal

There’s a theory that many of us have an “inner Neanderthal.” The idea is that Homo sapiens and a cousin species once bred, leaving some people today with a trace of Neanderthal DNA. 

This DNA is arguably the 21st century’s most celebrated discovery in human evolution. But in 2024, a pair of French geneticists called into question the theory’s very foundations. 

They proposed that what scientists interpret as interbreeding could instead be explained by population structure—the way genes concentrate in smaller, isolated groups.

Find out what it all means for human evolution.

—Ben Crair

This story is from the next issue of our print magazine, which is all about nature. Subscribe now to read it when it lands on Wednesday, April 22.

Why having “humans in the loop” in an AI war is an illusion

—Uri Maoz

AI is starting to shape real wars. It’s at the center of a legal battle between Anthropic and the Pentagon, playing a growing role in the conflict with Iran, and raising questions about how much humans should remain “in the loop.”

Under Pentagon guidelines, human oversight is meant to provide accountability, context, and security. But the idea of “humans in the loop” is a comforting distraction.

The real danger isn’t that machines will act without oversight; it’s that human overseers have no idea what the machines are actually “thinking.” Thankfully, science may offer a way forward.

Read the full op-ed on the urgent need for new safeguards around AI warfare.

The must-reads

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

1 Despite blacklisting Anthropic, the White House wants its new model
Trump officials are negotiating access to Mythos. (Axios)
+ Anthropic said it was too dangerous for a public release. (Bloomberg $)
+ Finance ministers are alarmed about the security risks. (BBC)
+ Anthropic just rolled out a model that’s less risky than Mythos. (CNBC)
+ The Pentagon has pursued a culture war against the company. (MIT Technology Review)

2 Sam Altman’s side hustles have raised conflict-of-interest concerns
His opaque investments could influence decisions at OpenAI. (WSJ $)
+ A jury will soon decide if OpenAI abandoned its founding mission. (Wired $)
+ The company is making a big play for science. (MIT Technology Review)

3 A Starlink outage during drone tests exposed the Pentagon’s SpaceX reliance
It was one of several Navy test disruptions linked to Starlink. (Reuters $)
+ The DoD is also tapping Ford and GM for military innovations.(NYT $)

4 Data center delays threaten to choke AI expansion
40% of this year’s projects are at risk of falling behind schedule. (FT $)
+ Partly because no one wants a data center in their backyard. (MIT Technology Review)

5 Alibaba just released its own version of a world model
Happy Oyster is the latest attempt to extend AI’s ability to comprehend physical reality. (SCMP)
+ But they still need to understand cause and effect. (FT $)

6 Google’s Gemini is now generating AI images tailored to personal data
By analyzing users’ Google services and data. (Quartz)
+ Google says it will cut the need for detailed prompts. (TechCrunch)

7 OpenAI is beefing up its agentic coding and development system
Its Codex update is a direct shot at Claude Code. (The Verge)
+ But not everyone is convinced about AI coding. (MIT Technology Review)

8 Europe’s online age verification app is here
It’s available for free to any company that wants it. (Wired $) 

9 Smartglasses are giving Korean theaters hope of a K-Pop moment
Their AI-powered translations are taking the shows to the world. (NYT $)

10 Global voice actors are fighting Hollywood’s AI push
Their voices are training the models that are replacing them. (Rest of World)

Quote of the day

“There’s this dark period between now and some time in the future where the advantage is very much offensive AI.” 

—Rob Joyce, former director of cybersecurity at the National Security Agency, tells Bloomberg how AI is creating new hacking threats.

One More Thing

COURTESY OF NOVEON MAGNETICS


The race to produce rare earth elements

Access to rare earth elements will determine which countries meet their goals for lowering emissions or generating energy from non-fossil-fuel sources. But some nations, including the US, are worried about the supply of these elements. 

China dominates the market, while extraction in the US is limited. As a result, scientists and companies are exploring unconventional sources. Read the full story on their search for critical minerals.


—Mureji Fatunde

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.)

+ This ska cover of Rage Against the Machine is an upbeat way to start a revolution.
+ We finally know how far Stretch Armstrong can really stretch.
+ Customize these ambient sounds to wash away disruptive thoughts.
+ Here’s proof childhood dreams can come true: a girl guiding a seal to perform tricks. 

EEG-based stroke severity classification using higher-order topological features and graph convolutional networks

IntroductionElectroencephalography (EEG)-based stroke analysis has mainly relied on conventional signal and network descriptors, while higher-order brain network structures remain insufficiently characterized.MethodsWe used persistent homology to extract cycle-based topological features from EEG functional networks, capturing higher-order organization with reduced sensitivity to threshold selection. These features were integrated with conventional EEG representations and embedded into a graph convolutional network for stroke severity classification.ResultsThe proposed framework achieved 86% accuracy in discriminating mild from moderate stroke. Cycle ratio analysis further revealed that the prefrontal cortex exhibited the most prominent higher-order structures, indicating its prominent involvement in post-stroke brain network organization.DiscussionOur results suggest that higher-order topological features can enhance EEG-based stroke severity classification and offer additional insight into post-stroke brain network alterations.

Cerebral blood flow and functional connectivity immediate changes following intradermal acupuncture in major depressive disorder

BackgroundAcupuncture has been increasingly applied as an adjunctive treatment for major depressive disorder (MDD), yet its central neurobiological mechanisms remain insufficiently understood. Cerebral blood flow (CBF) and functional connectivity strength (FCS) provide complementary perspectives on regional metabolic activity and large-scale functional integration, and their coupling may reflect neurovascular coordination relevant to depression.MethodsTwenty patients with MDD and twenty matched healthy controls (HC) underwent resting-state MRI. Patients received intradermal acupuncture (IA) and were scanned before and immediately after stimulation, while healthy controls were scanned once. Voxel-wise analyses of CBF, FCS, and their ratio (CBF/FCS) were performed to characterize acupuncture-related changes in neurovascular coupling. Group comparisons and pre–post acupuncture effects were assessed at the whole gray matter level.ResultsAcupuncture induced significant alterations in CBF/FCS coupling across widespread brain regions, including the bilateral precuneus, postcentral gyrus, superior temporal pole, superior frontal gyrus, occipital cortex, and cerebellum. These regions are primarily involved in sensorimotor processing, cognitive control, and emotional regulation. Overall, IA was associated with an immediate increase in CBF/FCS coupling, suggesting enhanced coordination between cerebral perfusion and functional network integration.ConclusionThis study provides evidence that intradermal acupuncture modulates neurovascular coupling in patients with MDD, offering neuroimaging-based insights into its antidepressant mechanisms. The findings support the notion that acupuncture may facilitate more efficient brain function by optimizing the balance between neural activity and metabolic supply.

Effect of low-intensity focused ultrasound on hippocampus of alcohol addicted mice: a preliminary study

Alcohol addiction is a chronic relapsing brain disorder characterized by significant neurobiological changes, particularly within the hippocampus, which mediates emotional regulation and reward-seeking behavior. Previous studies have shown that alcohol-induced neuronal injury contributes to withdrawal-associated anxiety and persistent alcohol preference. This study investigated the therapeutic effects of low-intensity focused ultrasound (LIFU) on the hippocampus in a mouse model of alcohol addiction. Twenty-six male C57BL/6 mice were allocated to an alcohol-exposed group (n = 20) and a control group (n = 6). Following a 28-day modeling period, the alcohol group was randomly subdivided into a therapy group and a sham group. The therapy group received LIFU treatment, while the sham group underwent an identical procedure with the ultrasound transducer powered off. After seven days of treatment, the therapy group exhibited less severe anxiety symptoms upon alcohol withdrawal and a reduced preference for alcohol compared to the sham group. The brain-derived neurotrophic factor (BDNF) concentration was significantly lower in the therapy group than in the sham group, but did not differ significantly from the control group. Hippocampal HE staining revealed more pronounced degeneration and apoptosis of granule cells in the dentate gyrus (DG) region in the sham group relative to the therapy group. These preliminary findings suggest that LIFU may modulate alcohol addiction by mitigating hippocampal neuronal injury.

Transcutaneous auricular vagus nerve stimulation to alleviate metformin-associated gastrointestinal adverse events and optimize glycaemic control: a randomized, sham-controlled pilot trial protocol

BackgroundGastrointestinal adverse events (GI AEs) are the main dose-limiting side effects of metformin in type 2 diabetes mellitus (T2DM), reducing adherence and compromising long-term glycaemic control. Current strategies (dose adjustment or combination therapy) seldom address both tolerability and sustained metabolic efficacy. Transcutaneous auricular vagus nerve stimulation (taVNS) is a non-invasive neuromodulation technique that may modulate gut–brain–metabolic pathways—vagal reflexes, inflammation, intestinal barrier function, and enteroendocrine signaling—and thus improve drug tolerance while preserving glycaemic control.MethodsThis single-center, randomized, sham-controlled pilot trial will enroll 60 T2DM patients with metformin-associated GI AEs, randomized 1:1 to either the taVNS group or the sham control group. The intervention lasts 2 weeks with a follow-up at week 4. Assessments at baseline and follow-up include a validated Metformin Symptom Severity Score (total score 0–50; primary outcome), Bristol Stool Form Scale, bowel urgency, glycaemic/metabolic indices [fasting blood glucose (FBG), 2-h postprandial glucose (PG2h), glycated albumin (GA), fasting C-peptide, fasting insulin, HOMA-IR, ISI], and mechanistic biomarkers (GLP-1, 5-HT, IL-6, IL-10, TNF-α, D-lactate, DAO, bile acids). Safety monitoring includes routine hematology, liver and renal function tests.DiscussionBy combining clinical outcomes with targeted biomarker analyses in a randomized design, this pilot study will assess whether taVNS alleviates metformin-associated GI intolerance without impairing glycaemic efficacy, and will provide feasibility data, effect-size estimates, and biomarker selection for future confirmatory trials.Clinical trial registrationTrial registration International Traditional Medicine Clinical Trial Registry (ITMCTR) http://itmctr.ccebtcm.org.cn/, Identifier: ITMCTR2025001086.

The patterns of relapse and abstinence: using machine learning to identify a multidimensional signature of long-term outcome after inpatient alcohol withdrawal treatment

AimsA machine learning approach to identify a multidimensional signature associated with relapse and long-term outcome in alcohol dependence treatment.DesignIn this observational naturalistic study, inpatients with alcohol dependence received qualified detoxification plus CBT (Cognitive Behavioral Therapy) and were followed up 6-months after discharge to assess abstinence and drinking behavior. Cross-validated multivariate sparse partial least squares analysis (SPLS) was used to investigate the relationship between clinical features and four long-term outcome variables.SettingGermany.Participants152 patients (on average 47.8 years old, 72% male) with alcohol dependence, who received inpatient qualified detoxification plus CBT.Measurements35 clinical features were used to cover all three phases of inpatient treatment (pre-, within-, post-treatment). Among these, sociodemographic characteristics, ICD-10 psychiatric diagnoses, previous detoxification treatments, and somatic measurements as well as inpatient treatment setting such as withdrawal medication, liver ultrasound, further information about the patients´ stay, and post-inpatient care were assessed. The four outcome dimensions included: continuous abstinence, abstinence at follow up, daily alcohol consumption, and days of abstinence after discharge.FindingsSix months after withdrawal treatment 46% of the patients achieved continuous abstinence. Socioeconomic, clinical and somatic features across the treatment timeline were analyzed and summarized into a multivariate signature associated with long-term treatment outcome. Thereby, the SPLS algorithm identified regular completion of withdrawal treatment, higher education, and employment status to be most strongly associated with a positive outcome. Alcohol-related hepatic and hematopoietic damage, number of previous withdrawal treatments and living in a shelter were most profoundly associated with a negative outcome.ConclusionConceiving treatment outcome as a multidimensional signature and moving beyond simple binary classifications of relapse versus abstinence may improve the understanding of relapse pathways and support more individualized treatment strategies.