Decoding Resistance to Targeted Therapy via New Cancer Models

ATCC and the Broad Institute report the development of engineered isogenic cancer models designed to replicate resistance to targeted therapies, beginning with osimertinib, the latest-generation epidermal growth factor receptor (EGFR) inhibitor used to treat non-small cell lung cancer (NSCLC) with EGFR mutations.

According to the researchers, the work addresses a critical challenge in oncology—treatment resistance that emerges over time. EGFR-mutant lung cancer was among the first subsets of a major epithelial cancer where directly targeting an oncogene was associated with marked clinical benefit. While targeted therapies have significantly improved overall survival, resistance inevitably develops.

cancer drug resistance
Understanding resistance mechanisms is essential for identifying combination therapies capable of producing durable responses and potentially disease-free remissions. [Planet Flem/Getty Images]

Developing resistant models directly from patient tumors can take years due to the scarcity of samples. In contrast, engineering resistance mechanisms in controlled laboratory models allows researchers to systematically study multiple escape pathways much faster.

To accelerate discovery, scientists from ATCC and the Broad Institute collaborated to engineer a panel of drug-resistant NSCLC models using CRISPR gene editing and gene overexpression techniques. These models systematically model the resistance mechanisms that arise in patients treated with osimertinib, note the researchers.

“With this powerful new set of tools, drug-sensitive and drug-resistant cancer cells can be studied side by side to understand therapeutic resistance and the underlying drivers,” says Roth Cheng, PhD, CEO of ATCC. “By creating and providing these cancer models along with a rich data-set to the global research community, our hope is to reveal hidden targets and combination strategies that turn today’s treatment failures into tomorrow’s breakthrough. We look forward to extending this approach to additional cancer types.”

Engineering drug-resistant lung cancer models

Led by William R. Sellers, MD, director of the cancer program at the Broad Institute, Fang Tian, PhD, director of biological content at ATCC, and Francisca Vazquez, PhD, director of the Cancer Dependency Map (DepMap) at the Broad Institute, the team identified representative classes of resistance mechanisms to osimertinib. They then selected three disease-representative, osimertinib sensitive NSCLC cell lines as the foundation for developing the new isogenic drug-resistant cell models.

ATCC engineered the selected authenticated cell lines with resistance mechanisms using CRISPR-based methods. The six resistance mechanisms included: PIK3CA E545K mutation, KRAS G12D mutation, BRAF V600E mutation, EGFR C797S mutation, CCDC6-RET fusion, and TPM3–NTRK1 fusion.

In addition, scientists at the Broad Institute are generating additional resistant cell lines driven by gene amplification mechanisms using overexpression methods.

These engineered isogenic model systems allow researchers to compare genetically matched cancer cells that differ only by a specific resistance alteration—providing a powerful framework to study how tumors evolve under targeted therapy.

The models will be integrated into the DepMap, a global effort to identify genetic vulnerabilities across hundreds of cancer cell models. The collaboration also contributes to the development of a Response and Resistance Map (ResMap), an emerging framework designed to systematically characterize how cancers respond to therapy and how resistance evolves.

cancer researchers
Engineered isogenic model systems allow researchers to compare genetically matched cancer cells that differ only by a specific resistance alteration—providing a powerful framework to study how tumors evolve under targeted therapy. [Sanjeri/Getty Images]

“Drug resistance remains one of the most significant barriers to durable cancer treatment,” said Kirsty Wienand, PhD, senior research scientist in DepMap at the Broad. “Systematically engineering resistance mechanisms in well-characterized cell models allows us to study how tumors adapt to targeted therapy. Integrating these models into DepMap will help researchers worldwide identify new vulnerabilities and potential therapeutic combinations.”

The collaboration ensures that both the biological models and the associated data will be widely accessible to the scientific community, says the research team. Data will be integrated into the DepMap portal, with links to the corresponding ATCC cell line identifiers. In addition, the engineered cell lines will be distributed globally through ATCC following authentication and quality control.

Systematically engineering clinically relevant resistance mechanisms in lung cancer models, the collaboration establishes a scalable framework for studying how tumors escape targeted therapies, explain the scientists, adding that the resulting models and datasets will help researchers identify new vulnerabilities and therapeutic strategies to overcome drug resistance and improve outcomes for patients with cancer.

By combining advanced cell engineering, functional genomics, and computational biology, the collaboration should provide an important resource for studying drug resistance, cancer vulnerabilities, and precision oncology strategies.

 

ATCC and the Broad Institute will present the research findings at the American Association for Cancer Research® (AACR) Annual Meeting 2026, April 17–22 in San Diego:

Title: Engineering isogenic models harboring resistance mechanisms to the latest-generation EGFR inhibitor in non-small cell lung cancer

Session Category: Experimental and Molecular Therapeutics; Session Title: Drug Resistance 2: Tyrosine Kinase Inhibitors

Date: April 22, 2026, 9:00 AM–12:00 PM, Poster Section 11, Poster Board: 8, Poster Number: 7029

The post Decoding Resistance to Targeted Therapy via New Cancer Models appeared first on GEN – Genetic Engineering and Biotechnology News.

The Download: murderous ‘mirror’ bacteria, and Chinese workers fighting AI doubles

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.

No one’s sure if synthetic mirror life will kill us all

In February 2019, a group of scientists proposed a high-risk, cutting-edge, irresistibly exciting idea that the National Science Foundation should fund: making “mirror” bacteria.

These lab-created microbes would be organized like ordinary bacteria, but their proteins and sugars would be mirror images of those found in nature. Researchers believed they could reveal new insights into building cells, designing drugs, and even the origins of life.

But now, many of them have reversed course. They’ve become convinced that mirror organisms could trigger a catastrophic event threatening every form of life on Earth. Find out why they’re ringing alarm bells.

—Stephen Ornes

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

Chinese tech workers are starting to train their AI doubles—and pushing back

Earlier this month, a GitHub project called Colleague Skill struck a nerve by claiming to “distill” a worker’s skills and personality—and replicate them with an AI agent. Though the project was a spoof, it prompted a wave of soul-searching among otherwise enthusiastic early adopters.

A number of tech workers told MIT Technology Review that their bosses are already encouraging them to document their workflows for automation via tools like OpenClaw. Many now fear that they are being flattened into code and losing their professional identity.

In response, some are fighting back with tools designed to sabotage the automation process.

Read the full story.

—Caiwei Chen

The must-reads

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

1 The White House and Anthropic are working toward a compromise
The Trump administration says they had a “productive meeting.” (Reuters $)
+ Trump had ordered US agencies to phase out Anthropic’s tech. (Guardian)
+ Despite the blacklist, the NSA is using Anthropic’s new Mythos model. (Axios)

2 Palantir has unveiled a manifesto calling for universal national service
While denouncing inclusivity and “regressive” cultures. (TechCrunch)
+ It’s a summary of CEO Alex Karp’s book “The Technological Republic.” (Engadget)
+ One critic called the book “a piece of corporate sales material.“ (Bloomberg $)

3 Germany’s chancellor and largest company want looser AI rules
Chancellor Merz said industrial AI needs ‌more regulatory freedom. (Reuters $)
+ Siemens says it plans to shift investments to the US if EU rules don’t change. (Bloomberg $)
+ Fractures over AI regulation are also emerging in the US. (MIT Technology Review)  

4 Nvidia’s once-tight bond with gamers is cracking over AI  
Consumer graphics cards are no longer the priority. (CNBC)
+ But generative AI could reinvent what it means to play. (MIT Technology Review)

5 Insurers are trying to exclude AI-related harms from their coverage
And escape legal liability for AI’s mistakes. (FT $)
+ AI images are being used in insurance scams. (BBC)

6 AI is about to make the global e-waste crisis much worse
And most of the trash will end up in non-Western countries. (Rest of World)
+ Here’s what we can do about it. (MIT Technology Review)

7 Tinder and Zoom have partnered with Sam Altman’s eye-scanning firm
To offer a “proof of humanity” badge to users. (BBC)

8 Islamist insurgents in West Africa are driving surging demand for drones
A Nigerian UAV startup is opening its first factory abroad in Ghana. (Bloomberg $)

9 Hundreds of fake pro-Trump AI influencers are flooding social media
In an apparent bid to hook conservative voters. (NYT)

10 A Chinese humanoid has smashed the human half-marathon record
Despite crashing into a railing near the end of the race. (NBC News)
+ Chinese tech firm Honor swept the podium spots. (Engadget)
+ Last year, humans won the race by a mile. (CNN)

Quote of the day

“This is the only issue where you’ve got Steve Bannon and Ralph Nader, Glenn Beck and Bernie Sanders fighting for the same thing.”

—Ben Cumming, head of communications at the AI safety nonprofit Future of Life Institute, tells the Washington Post that diverse public figures are endorsing a declaration of AI policy priorities.

One More Thing

International Space Station photographed from space with Earth in the distance

NASA


The great commercial takeover of low Earth orbit

The International Space Station will be decommissioned as soon as 2030, but the story of America in low Earth orbit (LEO) will continue. 

Using lessons from the ISS, NASA has partnered with private companies to develop new commercial space stations for research, manufacturing, and tourism. If they are successful, these businesses will bring about a new era of space exploration: private rockets flying to private destinations.

They will also demonstrate a new model in which NASA builds infrastructure and the private sector takes it from there—freeing the agency to explore deeper and deeper into space. Read the full story.


—David W. Brown

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.)

+ Bask in thisadorable test of a dog’s devotion.
+ This vocal pitch trainer improves your singing straight from your browser.
+ Master international etiquette with this interactive guide to the world’s cultures.
+ Explore the networks of public figures with this intriguing interactive graph

Short-term intrinsic connectivity changes induced by cognitive exertion in healthy participants

IntroductionChanges in brain intrinsic connectivity on the timescale of minutes, as provoked by a cognitive task, have not been well documented.MethodsA total of two 7.5-min 7 Tesla functional MRI (fMRI) scans (Run 1 and Run 2), separated by 90 s, were acquired for 23 healthy participants during cognitive exertion induced by the Stroop color–word interference task. Independent component analysis (ICA) of the paired Run 1 and Run 2 fMRI acquisitions identified components with distinct spatial and temporal signatures.ResultsThe spatial extent of the ICA components coincided with hubs of the brain’s intrinsic networks. In addition, these components correlated with brain regions from other networks, thereby defining inter-network connectivity. Run 1 and Run 2 showed significantly different patterns of connections (p-FWE < 0.01) across 10 ICA-identified intrinsic networks and 20 inter-networks. Connectivity in Run 2 was higher in 12 nodes and lower in eight nodes, indicating dynamic changes during the task response. Overall, the right angular gyrus/supramarginal gyrus and the right frontal pole regions of the ventral attention network showed greater activity in Run 1, but activity shifted to the fusiform gyrus, supplementary motor area (SMA), and precentral and postcentral gyrus nodes in Run 2. Response times (RTs) and Stroop test accuracy did not change between runs in these healthy participants.ConclusionInter-network connectivity indicated that surveillance and task oversight nodes were required early in learning how to complete the Stroop task (Run 1), but these were replaced by object recognition and more automatic responses in Run 2. These findings define inter-networks that are sensitive to cognitive exertion and provide a framework for understanding cognitive dysfunction.

Altered static and dynamic regional homogeneity in basal ganglia–thalamocortical circuits and their association with neuropsychiatric manifestations in Wilson’s disease

PurposeWilson’s disease (WD) is an autosomal recessive disorder caused by ATP7B mutations, resulting in impaired copper metabolism and progressive neuropsychiatric manifestations. This study investigated spatiotemporal alterations in regional brain activity using static and dynamic resting-state fMRI with regional homogeneity (ReHo), and their relationships with clinical features.MethodsResting-state fMRI data were acquired from WD patients and healthy controls (HCs). Static and dynamic ReHo analyses were performed to characterize local synchronization strength and temporal variability of spontaneous neural activity. Group differences were assessed across the basal ganglia, thalamus, cerebellum, and cortical regions. Associations between altered ReHo metrics and clinical measures were evaluated with FDR correction for multiple comparisons.ResultsCompared with HCs, WD patients exhibited widespread ReHo abnormalities involving the basal ganglia (putamen and globus pallidus), thalamus, cerebellum, and cortical regions. Static ReHo in the left putamen and globus pallidus was positively associated with anxiety severity, while right putaminal ReHo was negatively associated with neurological severity and positively associated with disease duration. Dynamic ReHo in the left middle frontal gyrus showed negative associations with depression severity and disease duration. All brain–behavior correlations survived FDR correction, indicating robust effects.ConclusionWD is characterized by disrupted spatiotemporal organization of local functional synchronization within cerebellar and basal ganglia–thalamo–cortical circuits. These findings support a network-level dysfunction model involving subcortical synchronization deficits and cortical temporal instability, which together underpin neuropsychiatric manifestations and disease progression.

Neurobiological effects of microbial treatments within psychiatry: a systematic review

ObjectiveThough microbial interventions such as probiotics and fecal microbiota transplantation have had a growing body of evidence suggesting their efficacy in alleviating the symptoms of psychiatric illnesses, their exact mechanisms of action and impacts on the brain are still not fully characterized. The aim of this review is to compile and summarize the current literature regarding neurobiological changes associated with microbial interventions targeting psychiatric symptoms in healthy and psychiatric populations.MethodsA systematic search of four databases was conducted using key terms related to neuroimaging, microbial interventions, and psychiatric illnesses and/or symptoms. All results were then evaluated based on specific eligibility criteria.Results10 studies met eligibility criteria and were included in this systematic review. Three of the five healthy control studies and all five of the studies conducted within psychiatric populations, observed significant neurobiological changes associated with probiotic intervention either in areas with psychiatric relevance, in the direction of a healthier profile, or correlated with improved psychiatric and/or affective symptoms. The interventions used in these studies consisted of probiotics with bacterial species primarily from the lactobacillus and bifidobacterium genera, at doses ranging from 1–900 billion CFU, taken for durations ranging from 4 weeks to 6 months.ConclusionsThe findings from this review suggest that probiotic intervention may be associated with neurobiological changes, and that these changes could play a role in ameliorating psychiatric symptoms. More research is needed to replicate these findings, explore other psychiatric populations and microbial interventions, and fully elucidate the mechanisms driving these promising neurobiological and clinical changes.

Electrocardiographic findings in children and adolescents treated with antipsychotics: a cohort study

Background/objectivesAntipsychotic drugs are increasingly prescribed in children and adolescents across a wide range of psychiatric conditions. Although cardiovascular adverse effects are generally considered uncommon, concerns about electrocardiographic abnormalities, particularly QTc interval prolongation, have led to ongoing debate regarding appropriate monitoring strategies. Real-world data on the frequency, persistence, and clinical relevance of ECG findings during antipsychotic treatment in youth remain limited.MethodsThis was a single-center, observational cohort study including patients younger than 18 years, treated with antipsychotics between January 2020 and December 2024. Inclusion required the availability of at least one 12-lead ECG performed during treatment and accompanied by a cardiology report. ECG parameters were extracted from all available recordings, with QTc calculated using Bazett’s formula and interpreted using sex-specific reference thresholds. ECG findings were analyzed primarily at the patient level, defining abnormalities based on their occurrence at any point during follow-up. An exploratory comparison was performed between patients with and without QTc prolongation.ResultsThe study included 430 patients (79.1% males; mean age 11.3 ± 3.35 years), of whom 429 had analyzable ECG data. At the patient level, 195 of 429 patients (45.5%) exhibited at least one numeric ECG abnormality during follow-up, most commonly heart rate abnormalities. QTc prolongation above sex-specific thresholds was observed in 24 patients (5.6%) and proved to be persistent in only 5 cases (20.8%), defined as occurrence in at least 2 ECG recordings. No patient exhibited a QTc ≥500 ms, and no clinically significant ventricular arrhythmias, high-grade conduction disturbances, or sudden cardiac events were observed. QTc prolongation was not significantly associated with sex, age, antipsychotic polypharmacy, combined first- and second-generation antipsychotic exposure, or QT-relevant comedications.ConclusionsIn this large naturalistic pediatric cohort, ECG abnormalities during antipsychotic treatment were relatively frequent but predominantly mild, transient, and clinically benign. QTc prolongation occurred in a small minority of patients and was not associated with adverse cardiac outcomes. These findings may support a selective, risk-based approach to ECG monitoring in children and adolescents treated with antipsychotics, rather than routine universal screening.

Postmarketing surveillance of elobixibat for patients with chronic constipation and concomitant schizophrenia or depression in Japan

BackgroundLittle is known about the optimal treatment for constipation in patients with schizophrenia or depression. Elobixibat is a laxative with a novel mechanism of action that inhibits the ileal bile acid transporter, acting as both an osmotic and a stimulant agent.MethodsWe conducted a prospective, multicenter, postmarketing surveillance study to assess the safety and effectiveness of elobixibat for patients with chronic constipation in Japan (jRCT1080223950). The surveillance period was between June 2018 and May 2022. Patients were observed from the date of initial administration of elobixibat to 55 days thereafter (4-week treatment groups) or to 419 days thereafter (52-week treatment groups). Safety outcomes included adverse drug reactions (ADRs). Effectiveness outcomes included defecation frequency, Bristol Stool Form Scale (BSFS) scores, and constipation-related symptoms.ResultsIn the safety analysis set, the 4-week treatment groups comprised 105 patients with schizophrenia and 129 with depression; the 52-week treatment groups included 43 patients with schizophrenia and 55 with depression. Approximately 85% to 95% of patients used antipsychotics, and 40% to 55% used anxiolytics or sedative-hypnotics. The proportions of patients who experienced ADRs were 4.76% in the 4-week treatment group and 2.33% in the 52-week treatment group of patients with schizophrenia, and 3.88% and 9.09% of patients with depression. Diarrhea was the most common ADR in each group. There were no serious ADRs. In the 4-week treatment groups, the mean defecation frequency per week at baseline was 3.3 among patients with schizophrenia and 3.0 among patients with depression, which increased to 5.3 and 4.9, respectively, at week 4. In the 52-week treatment groups, the mean defecation frequency per week at week 52 was higher than that at baseline. After treatment, the proportion of patients with an ideal BSFS score of 4 increased in all groups by week 2 and reached approximately 60% by week 52. All constipation-related symptoms also improved by week 2 in all groups.ConclusionsElobixibat improved chronic constipation with no new safety signal identified in patients with schizophrenia or depression and with available follow-up in real-world settings.Clinical trial registrationhttps://jrct.mhlw.go.jp/latest-detail/jRCT1080223950, identifier jRCT1080223950.

Twelve-month outcomes and comparative costs of internet-delivered psychodynamic therapy versus cognitive-behavioral therapy for adolescent depression: a randomized controlled trial

IntroductionAdolescent depression poses a major public health concern with substantial clinical and societal implications. Both internet-delivered cognitive behavioural therapy (ICBT) and internet-delivered psychodynamic therapy (IPDT) have shown efficacy, but questions remain regarding long-term efficacy and cost-effectiveness. The present study presents a 12-month follow-up and cost-comparison from a randomized controlled trial (RCT) comparing ICBT and IPDT for adolescent depression.MethodsParticipants were 272 adolescents aged 15–19 with a primary diagnosis of major depressive disorder. The primary outcome was depressive symptoms measured with the QIDS-A17-SR while the secondary outcome was anxiety symptoms measured with the GAD-7. Costs were assessed both by comparing costs of treatment and healthcare use 12-month post-treatment using the TIC-P.ResultsResults were stable at the 12-month follow up compared to treatment endpoint, for both depressive and anxiety symptoms. There were no significant group differences at the 12-month follow-up. There were no differences in treatment costs or in costs for healthcare use one-year post-treatment.DiscussionThis study suggests that treatment gains from IPDT and ICBT for adolescent depression remain stable during a 12-month follow-up period, with no differences between the treatments one-year post-treatment. Furthermore, it suggests comparable costs for the treatments. Interpretation of health-care use data was restricted due to the COVID-19 pandemic taking place during the follow-up period. This adds to the literature suggesting that ICBT and IPDT can be seen as viable alternatives for treating adolescent depression. More research into the long-term effects and cost-effectiveness is needed.

Machine learning for oral frailty factors in hospitalized schizophrenia patients: two-stage feature selection and SHAP analysis

BackgroundLong-term hospitalized patients with schizophrenia (SZ) often experience significant oral health problems, and oral frailty (OF) can further exacerbate the decline in their quality of life. However, the status and key influencing factors contributing to OF in this population remain insufficiently explored. Most existing studies rely on traditional regression models, which are prone to overfitting when processing high-dimensional data, making accurate risk identification difficult. This study aims to clarify the current status of OF in this population in Southwest China, identify the influencing factors, and optimize the predictive model using machine learning (ML), thereby providing a basis for clinical practice.MethodsA total of 404 long-term hospitalized patients with SZ from three psychiatric hospitals in Southwest China were enrolled in this study. The Oral Frailty Index-8 was employed to assess OF. Nine feature selection methods and five ML models were employed to optimize the model through two-stage feature selection, while Shapley Additive Explanations (SHAP) were used to analyze the model’s predictive logic.ResultsThe prevalence of OF in this population was determined to be 69.3%. The optimal model identified was the random forest, with the Area Under the Curve increasing to 0.779 following two-stage optimization. Compared to non-feature selection, performance improved by approximately 6.57%. SHAP analysis revealed that the Number of Teeth, Number of Psychiatric Hospitalizations, Self-discontinuation of Medication, Marital Status, and Age were core risk factors for OF.ConclusionThe prevalence of OF in long-term hospitalized patients with SZ is notably high. Two-stage feature selection enhances the accuracy of the predictive model, and the identified core factors can serve as a reference for developing individualized oral intervention programs in clinical practice.