Tag: Medication

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Aberrant Splicing Patterns Could Predict Therapy Response in mRCC

Transcriptomic analysis of more than 100 metastatic renal cell carcinomas (mRCC) has revealed key differences in aberrant alternative gene splicing events between treatment responders and nonresponders that could aid prognostication in future.

“In the near term, these findings could help guide treatment selection by identifying patients more likely to respond to targeted therapies or standard immuno-oncology regimens,” said Patrick Pirrotte, PhD, director of the Integrated Mass Spectrometry Shared Resource at TGen and City of Hope, associate professor in TGen’s Early Detection and Prevention Division, and senior author of the paper.

“Longer term, splicing-derived antigens could provide a foundation for more personalized adoptive immunotherapy strategies tailored to the molecular features of an individual patient’s tumor,” he told Inside Precision Medicine.

Pirrotte explained that “alternative splicing [AS] is a fundamental transcriptional mechanism that expands proteomic diversity in normal cells, but aberrant splicing is increasingly recognized as a feature of cancer that can contribute to tumorigenesis, progression, and metastasis.”

His group, and collaborators, have previously demonstrated that aberrant splicing could act as a broadly relevant biomarker across different malignancies, including ovarian cancer and sarcomatoid renal cell carcinoma, but its diagnostic and predictive potential in mRCC remained largely unexplored.

To address this, Pirrotte and team conducted a retrospective analysis on tumor samples from 101 patients with mRCC who received immune checkpoint inhibitor (n=91) and/or targeted (n=77) therapies. Response rates to each of the therapies were 63% and 77%, respectively.

The researchers report in the Journal for ImmunoTherapy of Cancer that they identified 10 AS events that were specific to mRCC. Six of these were intron retention events and four were exon skipping events.

Differential AS analysis identified 461 slicing events that differed between responders and non-responders to immune checkpoint inhibitors and 253 events that differed between targeted therapy responders and non-responders. In both cases, more than 70% of novel AS events among responders involved intron retention.

“Intron retention was the predominant alternative splicing event observed in patients who responded well to therapy,” observed Pirrotte.

“Mechanistically, intron retention occurs when intronic sequences that are normally removed during RNA processing are retained in the mature transcript. This can generate novel amino acid sequences and, in some cases, tumor-associated antigens derived from aberrant splicing,” he explained. “A high intron-retention burden was associated with an immunogenic tumor microenvironment, marked by adaptive immune activation and enriched antigen processing. In simple terms, these cancer-specific splicing errors may help ‘flag’ tumor cells, making them more visible to the immune system.”

The team then investigated whether differentially spliced sequences shared between the immunotherapy and targeted therapy responder cohorts could potentially act as neoantigenic targets.

This revealed that novel peptide-generating AS events in the genes IFFO1 and ZNF692 were highly expressed among the responders. Both genes are known to play a role in tumorigenesis and metastasis in RCC and colorectal cancer. The researchers note that although the specific impact of AS events within these genes is unclear, the resulting neoantigens could play a role in future treatment approaches.

“It is becoming increasingly feasible to identify splicing-derived neoantigens that could be used in personalized immunotherapy approaches, including adoptive cell therapies such as CAR T-cell or tumor-infiltrating lymphocyte therapies,” said Pirrotte. “These strategies are designed to train or redirect a patient’s immune system to recognize tumor-specific antigen signatures. In this case, the targets would be antigens generated by aberrant splicing events, allowing immune cells to selectively recognize and kill cancer cells.”

Finally, the investigators showed that tumors with higher levels of aberrant splicing were more common among therapy responders than nonresponders. This could potentially be used as a biomarker for treatment response.

“Current biomarkers such as PD-L1 expression and microsatellite instability have shown limited and inconsistent predictive value in mRCC,” said Pirrotte. “In contrast, our study identified a significant association between tumor ‘splicing burden’ (the extent of aberrant splicing) and clinical response to therapy. These findings suggest that the tumor transcriptome, particularly splicing dysregulation, may provide a more informative framework for predicting treatment response and personalizing therapy.”

Before assessment of AS can be implemented in routine clinical practice, the core technologies will need further refinement, including clinically validated RNA sequencing workflows, robust computational pipelines for splicing analysis, and clear regulatory and technical frameworks for using the results to guide treatment decisions or develop biologic therapies.

Pirrotte and team are now assembling validation cohorts to confirm their findings in larger patient populations. They are also expanding their work to other cancer types to determine whether aberrant splicing and splicing-derived antigens represent broadly applicable biomarkers and therapeutic targets.

The post Aberrant Splicing Patterns Could Predict Therapy Response in mRCC appeared first on Inside Precision Medicine.

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Opinion: Hospitals are silencing doctors online, and it’s fueling the health misinformation crisis

I started creating health content online in medical school. I realized I could reach thousands of people in seconds and share medically accurate information with students around the world. For example, I made a video showing how deep an injection goes for vaccination. The public is both fascinated and afraid of injections, but dispelling the rumors that a massive needle could go as deep as your bone goes a long way in vaccine adoption.

During my emergency medicine residency, though, things changed. What had been seen during my interview process as a strength and skill set became “high risk” overnight. I was told that continuing to post on social media could jeopardize my career.

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Rate of New Late-Stage Breast Cancers Increases

The incidence of stage IV breast cancer increased significantly overall, across ages, and for both sexes from 2010 through 2021, according to research from a Dana Farber-led team. The percentage of patients with stage IV breast cancers, versus those with stages I to III diagnoses also increased. 

Notably, this increase was seen for all tumor subtypes in both sexes.

The researchers write, “These findings suggest that efforts are needed to determine factors contributing to these increases and to identify breast cancer before patients present with de novo stage IV disease.”

The study appears this week (May 12 issue) in JAMA Network Open. The senior author is José P. Leone, MD, department of medical oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston.

In their analysis of data from over 700,000 U.S. patients, the incidence of stage IV breast cancer increased significantly by 1.2% per year, and the percentage of people with stage IV also increased significantly. Stage IV incidence increased widely across all ages, races, sexes, and tumor subtypes. Still, survival improved significantly from 2010 through 2021.

Stage IV incidence increased across all tumor subtypes in both sexes. In women, those subtypes include hormone receptor (HR)–positive/ERBB2-negative, HR-positive/ERBB2-positive, HR-negative/ERBB2-positive, and triple-negative disease. 

Trends in the incidence of de novo stage IV breast cancer “remain underreported,” these authors write. A previous study evaluating incidence of distant disease in the U.S. before 2010 showed a statistically significant increase in incidence for younger patients and a statistically significant decrease in older patients. But, this current study’s authors said, a meta-analysis reported a decreasing percentage of stage IV presentation over time.

Breast cancer is the second most common cancer in women, behind skin cancer. It is the most common cancer diagnosed in females worldwide and an estimated 30% of patients develop metastases. The American Cancer Society estimates 42,140 U.S. women will die from breast cancer in 2026.

The incidence of breast cancer in younger women, in particular, has been rising. In August 2025, the CDC reported that: “Most breast cancers occur in older women, but rates have been increasing slowly among women younger than 45 years in all racial and ethnic groups.” The agency added that survival from breast cancer is improving “among women in most racial and ethnic groups.” 

Breast cancer in men remains rare, but  the rate is increasing also. 

This population-based cohort study used data from the Surveillance, Epidemiology, and End Results (SEER) program to identify patients diagnosed with de novo invasive breast cancer between January 1, 2010, and December 31, 2021. Data analyses were conducted from January 2024 to June 2025.

Of 761,471 breast cancer diagnoses, 43,934 (5.8%) were stage IV. Stage IV incidence increased from 9.5 cases per 100,000 females in 2010 to 11.2 cases per 100,000 females in 2021. The incidence of stages I to III disease also increased, from 163 cases per 100,000 females in 2010 to 177.4 cases per 100,000 females in 2021. 

Among males, there was also a statistically significant increase in stage IV incidence.

The researchers noted that, “Although overall survival improved, research is warranted to determine factors contributing to increased incidence, including potential changes in natural history of breast cancer, disease screening, and incidence and mortality of other conditions.”

The post Rate of New Late-Stage Breast Cancers Increases appeared first on Inside Precision Medicine.

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Machine Learning for Comparative Antidepressant Selection in Major Depressive Disorder: Systematic Review

Background: Major depressive disorder (MDD) affects approximately 1 in 6 adults during their lifetime, yet antidepressant selection relies predominantly on trial-and-error, with response rates of only 42% to 53%. While machine learning (ML) models have shown promise in predicting treatment outcomes, most focus on single treatments rather than comparative selection across therapeutic alternatives, limiting their clinical utility for the medication choice decisions that clinicians face in practice. Objective: This systematic review evaluates ML approaches that examine 2 or more pharmacological interventions for predicting treatment outcomes in MDD, with a focus on their capacity to facilitate comparative treatment selection between medications or medication classes for individual patients. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we searched PubMed, Scopus, and Web of Science for studies published from 2015 to 2025. We included studies involving adults with MDD that used ML models to predict treatment outcomes across 2 or more pharmacological treatments and reported medication-specific prediction outcomes. Risk of bias was assessed using PROBAST-AI (Prediction Model Risk of Bias Assessment Tool for Artificial Intelligence). We conducted a narrative synthesis organized by modeling strategies, data integration approaches, validation methodologies, and performance patterns. Results: From 5370 initial records, 19 studies met the inclusion criteria, with dataset sample sizes ranging from 49 to 77,226 participants. Studies employed 3 distinct modeling strategies: drug-specific supervised models trained independently for each medication, subtype- or trajectory-based approaches using clustering methods to identify differential response patterns, and a unified differential prediction framework generating calibrated cross-treatment predictions. Performance varied substantially, with area under the curve values ranging from 0.59 to 0.95 and classification accuracies between 62% and 95.4%, though high performance was concentrated in studies with small samples, high-dimensional neurobiological features, and internal-only validation. Only 7 studies conducted external validation, which generally yielded more conservative performance estimates. Feature informativeness was more consistently associated with performance variation than algorithm complexity. Most studies did not formally distinguish between prognostic features predicting general outcomes and predictive features identifying differential medication responses, and none applied formal explainability techniques. Conclusions: ML for comparative antidepressant selection remains in an early stage of development. Only 1 study implemented a unified framework directly supporting patient-level treatment ranking. Key barriers to clinical translation include insufficient distinction between prognostic and predictive markers, limited cross-trial validation, near-absent calibration reporting, and absent explainability. Future research should prioritize unified comparative frameworks with calibrated predictions, rigorous external validation on diverse cohorts, explicit modeling of heterogeneous treatment effects, and integration of explainability into model development.
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Roles of NRXN1 in neuropsychiatric disorders: from genetic lesion to molecular mechanism

Numerous neuropsychiatric disorders frequently exhibit overlapping genetic risk factors, implying the molecular basis for their comorbidity. Nevertheless, the pathogenesis of these disorders remains elusive, particularly regarding how genetic variations impair the physiological function of risk genes and contribute to disease phenotypes. Neurexin 1 protein, encoded by NRXN1 gene, belongs to the neurexin family of presynaptic adhesion molecules. And neurexin 1 is involved in synaptogenesis and the maintenance of synaptic action. Genetic variations of NRXN1 have been demonstrated to be associated with a spectrum of neuropsychiatric disorders. Herein, this review focuses on the most recent and relevant literature concerning the genetic and molecular mechanisms through which NRXN1 variants contribute to the pathogenesis of neuropsychiatric disorders, particularly schizophrenia and autism spectrum disorder. Among them, we propose the isoform-dependent excitation-inhibition imbalance hypothesis of NRXN1 in autism spectrum disorder. And this hypothesis may account for both the elevated and decreased excitation-inhibition ratios observed in diverse individuals with autism spectrum disorder. Moreover, both schizophrenia and autism spectrum disorder involve deletions and alternative splicing of NRXN1, offering molecular evidence for their comorbidity. Then, we analyzed and summarized the current research status of NRXN1 in other neuropsychiatric disorders, including attention-deficit hyperactivity disorder, insomnia, epilepsy, suicide, and depression. Additionally, available limited researches on NRXN1-targeted therapeutic strategies and associated pharmacological studies are also incorporated. Finally, we discussed existing challenges in NRXN1 research within the context of neuropsychiatric disorders and proposed potential avenues to overcome these obstacles.
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Direct modulation of human GABA-A α1β2γ2 receptors by the endocannabinoid 2-arachidonoylglycerol: implications for cannabinoid-related ligands and limitations for anxiolytic drug development

Anxiety disorders are associated with impaired inhibitory neurotransmission mediated by γ-aminobutyric acid type A (GABA-A) receptors. Although benzodiazepines remain effective anxiolytics, their clinical utility is limited by sedation, cognitive impairment, tolerance, and dependence, prompting the search for mechanistically distinct GABAergic modulators. Among cannabinoid-related molecules, the strongest evidence for direct GABA-A receptor modulation concerns the endocannabinoid 2-arachidonoylglycerol (2-AG), which potentiates recombinant human α1β2γ2 receptors through residues located in the M4 helix of the β2 subunit. Here, we review the structural architecture, biophysical properties, and pharmacological profile of the human GABA-A α1β2γ2 isoform as the relevant molecular framework for evaluating this mechanism, while discussing the broader relevance of cannabinoid-related ligands and selected phytocannabinoids without assuming mechanistic equivalence. We further assess the hypothesis that 2-AG reaches the β2-M4 site through a membrane-access route and identify five conceptual barriers that currently limit translation of this mechanism into anxiolytic drug development: supraphysiological effective concentrations, unresolved synaptic-versus-extrasynaptic actions, uncertain subtype selectivity, incomplete validation of lipid-environment effects, and lack of clinical evidence linking this mechanism to anxiolysis in humans. We conclude that direct modulation through β2-M4 defines a mechanistically intriguing allosteric pathway distinct from benzodiazepine action; however, its location on a shared β2 subunit and the micromolar concentrations required for modulation represent substantial obstacles to the rational design of anxioselective agents based on this mechanism.
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Romanian male patients with the dual diagnosis of schizophrenia and alcohol use disorder: a prospective study of clinical, social, and treatment-related factors affecting quality of life

BackgroundSchizophrenia frequently co-occurs with alcohol use disorder (AUD), resulting in a complex clinical profile associated with poor functional outcomes and reduced quality of life (QoL). Although both conditions independently impair psychosocial functioning, few studies have examined the combined effects of clinical, social, and treatment-related factors on QoL in patients with this dual diagnosis.MethodsThis prospective observational study included 88 male inpatients diagnosed with schizophrenia and comorbid AUD and who were followed over a 6-month period. Quality of life was assessed using the World Health Organization Quality of Life–BREF (WHOQoL–BREF). The clinical variables included severity of psychotic symptoms (Positive and Negative Syndrome Scale), alcohol use severity (Michigan Alcohol Screening Test), and treatment characteristics. Social and personal factors, such as self-care capacity, social support, education, and legal problems, were also evaluated. Multivariable regression analyses were conducted to identify predictors of QoL at baseline and follow-up.ResultsAt baseline, higher QoL was significantly associated with greater self-care capacity, social support, and higher positive symptom scores, while the need for antipsychotic treatment was associated with lower QoL. At the 6-month follow-up, better QoL was predicted by greater self-care capacity, higher educational level, and receipt of anti-craving medication. By contrast, negative and general psychopathology, medico-legal problems, and the need for antidepressant treatment were associated with poorer QoL. Alcohol use severity, as measured by the MAST, was not independently associated with QoL at either timepoint.ConclusionsIn patients with schizophrenia and comorbid AUD, QoL is shaped by a complex interaction of clinical severity, functional capacity, and treatment-related factors. Beyond symptom control, interventions targeting self-care, social functioning, and integrated addiction treatment appear essential to improve long-term outcomes. These findings support the implementation of a multidimensional, recovery-oriented approach for the management of patients with the dual diagnosis.
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Extreme heat is worsening faster for Black Americans

Get your daily dose of health and medicine every weekday with STAT’s free newsletter Morning Rounds. Sign up here.

Good morning. After what sometimes felt like endless speculation, FDA Commissioner Marty Makary resigned from his role yesterday. Kyle Diamantas, the agency’s top food regulator, will step in as acting commissioner. STAT’s Lizzy Lawrence has the details. And Matt Herper has a hot take: Marty Makary was the worst FDA commissioner in 25 years.

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Gene Therapy ETX101 Improves Seizures and Neurodevelopment in Dravet Syndrome in Phase I/II

Dravet syndrome has long represented one of the most challenging pediatric epilepsies encountered in neurology and genetic medicine. Caused primarily by loss‑of‑function variants in SCN1A, the disorder emerges in infancy with prolonged febrile seizures and evolves into a lifelong condition marked by treatment‑resistant epilepsy, developmental delay, and significant morbidity. As the gene and cell therapy community gathers for the American Society of Gene and Cell Therapy (ASGCT) Annual Meeting, the field’s attention is turning toward approaches capable not only of reducing seizures but also of altering the developmental trajectory that defines the disorder. This year’s Presidential Symposium features new data on ETX101, an investigational gene regulation therapy from Encoded Therapeutics, that appears to move the needle on both fronts.

Encoded Therapeutics, a clinical‑stage biotechnology company developing precision genetic medicines for severe neurological disorders, has engineered ETX101 as a one‑time AAV9‑based therapy designed to increase expression of SCN1A. Rather than replacing or editing the gene, ETX101 aims to restore physiologic sodium channel function in inhibitory interneurons. The company’s Phase I/II POLARIS program is evaluating the therapy across multiple international sites in children ranging from six months to seven years of age.

The dataset presented at the ASGCT Presidential Symposium expands the emerging clinical profile of ETX101, incorporating additional patients, early readouts from the highest dose level, and longer‑term follow‑up. Across the cohort, treatment with a single intracerebroventricular dose produced a robust and dose‑dependent antiseizure effect that persisted through 52 weeks of observation. At dose level three, children experienced a median seizure reduction of approximately 76%, a notable finding given that this developmental window is typically associated with escalating seizure burden despite standard therapies. Early data from the top dose level suggest even stronger responses in participants who did not receive sirolimus, consistent with preclinical evidence that the drug can dampen protein expression.

Beyond seizure control, the therapy appears to influence developmental domains that are rarely improved in Dravet syndrome. Children who reached one year of follow‑up demonstrated measurable gains across communication, motor function, and other adaptive behaviors, as assessed by caregiver‑reported Vineland Adaptive Behavior Scales. Particularly striking were the trajectories of children treated before age two. In this group, cognitive assessments showed early and sustained divergence from the stagnation observed in the ENVISION natural history study, with trajectories more consistent with neurotypical development over the first year after treatment.

Families and clinicians have taken note of the dual signal emerging from the POLARIS dataset. “Parents of children with Dravet syndrome live with the fear of every seizure and the heartbreak of watching development stall,” said Mary Anne Meskis, CEO of the Dravet Syndrome Foundation. “To see the early and robust seizure reductions paired with meaningful developmental gains is profoundly encouraging. Families have been waiting for therapies that don’t just manage symptoms but give their children a chance to keep learning and growing.”

Encoded’s chief medical officer, Sal Rico, MD, PhD, underscored the significance of the findings. “Watching these young children not only achieve durable seizure reduction but also show early evidence of neurodevelopmental rescue is truly remarkable,” he said. “These data reinforce our belief that ETX101 has the potential to change the course of the disease and future outlook for the Dravet community.”

ETX101 has been well tolerated across all four dose levels, with no treatment‑related serious adverse events. Transaminase elevations, a known AAV class effect, were the most common treatment‑related finding; they were asymptomatic and resolved with standard management.

As the ASGCT community continues to explore the boundaries of genetic medicine, ETX101’s early results highlight the promise of targeted gene regulation as a therapeutic modality. For a disorder like Dravet syndrome, the possibility of addressing both seizures and developmental delay marks an important moment for the field.

The post Gene Therapy ETX101 Improves Seizures and Neurodevelopment in Dravet Syndrome in Phase I/II appeared first on GEN – Genetic Engineering and Biotechnology News.