Radically different
WASHINGTON — Vice President JD Vance on Wednesday announced new steps in the Trump administration’s initiative to root out fraud in federal health programs, including a $1.3 billion deferral in Medicaid reimbursements to California.
“These fraudulent health care providers are getting rich by giving people medications they don’t even need,” Vance said during an event at the White House, adding that taxpayers and program beneficiaries are victimized by such fraud.
Researchers at The University of Texas MD Anderson Cancer Center have identified immune cell and tumor-specific features in triple-negative breast cancer (TNBC) that may help predict which patients are most likely to respond to chemotherapy before treatment begins, according to a study published in Nature. Using single-cell and spatial transcriptomic analyses of pretreatment tumor samples, the team identified specific macrophage subtypes and cancer-cell gene expression programs associated with response to neoadjuvant chemotherapy (NAC). The team also developed a 13-gene panel and a machine learning model that could help classify tumors according to their likelihood of responding to chemotherapy.
“This study provides novel insights into the gene-expression programs and the different cell states of the tumor microenvironment in patients with triple-negative breast cancer,” said Nicholas Navin, PhD, chair of systems biology at MD Anderson. “Importantly, we’ve identified certain programs and macrophage subtypes that are associated with good responses to neoadjuvant chemotherapy, which has tremendous potential to improve patient outcomes.”
TNBC accounts for between 10% and 20% of breast cancer cases. Because it lacks estrogen, progesterone, and HER2 receptors, treatment options are limited, resulting in a higher rate of recurrence compared with other form of breast cancer. Chemotherapy is the main treatment approach, particularly in early-stage disease, where neoadjuvant chemotherapy can achieve pathological complete response in 40% to 50% of patients. However, treatment outcomes vary widely from patient to patient, and researchers have been looking for ways that can better predict response before therapy begins.
For this study, the researchers analyzed pretreatment core biopsy samples from treatment-naive patients with early-stage TNBC. They performed single-cell RNA sequencing on 427,857 cells collected from 101 patients and spatial transcriptomic profiling on tumors from 44 patients. The findings also were compared with normal breast tissue data from the Human Breast Cell Atlas.
Based on their testing the researchers classified TNBC tumors into four patient-level “archetypes” based on cancer-cell gene expression patterns. They also identified 13 metaprograms that reflected heterogeneity within tumors at the single-cell level.
The tumor microenvironment consisted of 49 immune and stromal cell states organized into eight cellular communities, or ecotypes, defined by the co-occurrence of cancer cells and surrounding immune cell populations. Researchers found these cellular neighborhoods were associated both with tumor archetypes and chemotherapy response.
The study homed in on macrophages, a type of immune cell that has received less attention in TNBC research than T cells. The investigators said that seven of eight macrophage cell states were significantly associated with treatment response, while none of the 14 T-cell and natural killer-cell states showed significant associations with NAC response.
Macrophage subtypes linked to interferon signaling and complement activity, identified as Mac-IFN and Mac-lip-C1Q, were more abundant in patients who achieved pathological complete response. By comparison, two macrophages associated with angiogenesis and extracellular matrix remodeling, called Mac-angio and Mac-ECM, were enriched in patients with residual disease after chemotherapy.
The team also found that tumors linked to good response to NAC showed increased interferon signaling and elevated expression of human leukocyte antigen class II genes. Researchers said these findings indicate that cancer cells themselves may actively participate in modulating immune signaling related to chemotherapy response.
As part of their work, the researchers developed a 13-gene transcriptional signature panel developed from the single-cell analyses that can be used as a predictive model for chemotherapy response. Researchers said the model’s predictions correlated with chemotherapy response and overall survival across multiple public TNBC cohorts.
These new findings have the potential to influence how patients with TNBC are treated in the future by helping clinicians identify which patients are more likely to benefit from standard chemotherapy and which patients may need alternative therapeutic strategies earlier.
In addition, “these findings suggest that targeting specific macrophage subtypes could potentially provide new therapeutic opportunities in TNBC,” the researchers wrote.
The MD Anderson team noted that the study is one of the first large-scale single-cell genomic studies of TNBC integrating cancer cells, immune cells and treatment-response data. Earlier research exploring tumor heterogeneity has often lacked therapy response information, focused only on cancer cells or immune cells separately, or included relatively small patient cohorts.
Whether single-cell RNA seq could eventually become a basis for predictive diagnostics remains an open question. Today, the method is still expensive and technically challenging, two hindrances to it wider adoption. The researchers noted, however, that advances in sample multiplexing and other methods compatible with formalin-fixed paraffin-embedded tissue could make it feasible in the future.
Clinton Yam, MD, an associate professor of breast medical oncology at MD Anderson, said the findings could support more individualized approaches to TNBC care.
“These insights provide an important foundation for improving our understanding of why different TNBC tumors respond differently to chemotherapy, and the findings have strong potential to inform future strategies aimed at better predicting treatment response and guiding more individualized care for patients with triple-negative breast cancer.”
Future research will focus on validating the predictive models in prospective patient cohorts and evaluating TNBC treated with chemo-immunotherapy, which has become the standard of care when TNBC is detected early. The researchers also plan to study longitudinal tumor samples collected before, during, and after treatment to better understand how cancer cells and the tumor microenvironment evolve over time and how those changes relate to chemotherapy response and survival.
The post TNBC Ecotypes Reveal Molecular Signatures Tied to Chemotherapy Response appeared first on Inside Precision Medicine.
Arriving in the isolation ward of a biocontainment hospital is an unsettling, scary experience. In 2014, I spent 19 days in one while being treated for Ebola, watching the news cycle churn around me as my world receded to a small window, a phone, and the handful of providers in protective suits who came into my room every day.
More than a dozen Americans are living some version of that right now in a Nebraska quarantine facility — passengers from the MV Hondius, the cruise ship that is at the center of a small but instructive outbreak of Andes hantavirus.
Scientists have developed a sensor platform that can monitor cerebrospinal fluid (CSF) in intensive care unit patients, overcoming major delays in diagnosis associated with current testing methods. A study published today in Science Translational Medicine reports that the NeuroSense platform can provide near real-time readings of four key biomarkers every 27 minutes, with results accurately reflecting standard clinical measurements.
In neurological intensive care units, external ventricular drainage (EVD) systems are routinely used to temporarily assist patients with drainage of excess CSF, manage postoperative complications and monitor intracranial pressure. However, the use of these devices carries a high infection risk, with rates reaching up to 20% of patients.
Delayed diagnosis of these infections can lead to severe meningitis, neural damage, cognitive impairment, permanent disability, or even death. However, current testing methods are labor-intensive and require sending samples to external laboratories for biomarker analysis and manual inspection. This limits testing to every one to two days, significantly delaying clinical decisions that can be critical for preventing severe complications.
“To address these limitations, we developed NeuroSense, a multiplexed sensing platform that integrates with standard external ventricular drainage systems to enable near real-time monitoring of key CSF biomarkers, including glucose, lactate, pH, and flow rate, that are essential for detecting infection and drain dysfunction,” write the study authors.
The NeuroSense platform employs aptamer-based biosensors to detect glucose and lactate levels in CSF, which are key markers of bacterial infections. These types of biosensors are more stable and have a longer shelf life than conventional enzymatic biosensors, ensuring the platform can consistently and accurately track these markers for the entire time EVD systems remain in place, typically between five to 10 days.
Furthermore, an impedance-based sensor measures CSF flow rate to monitor for potential catheter obstructions or incorrect EVD settings, while a polydopamine sensor keeps track of pH changes, which can indicate acidosis, hemorrhage, infection, or a disrupted blood-brain barrier.
The platform’s performance was evaluated in a small-scale study that recruited six patients with EVDs hospitalized in the intensive care unit. Every four hours, readings from the NeuroSense platform were compared with those from standard testing methods, revealing a strong correlation between the sensor platform and clinical reference measurements.
A survey of the healthcare providers and clinicians involved in the study further showed that most participants found the platform easy to use, as it integrates with standard EVD systems routinely used in the intensive care setting.
Going forward, the researchers plan on further improving the performance of the pH sensor and continue developing the platform to comply with regulatory requirements for running large-scale clinical studies and eventually making the platform available to healthcare providers.
“Beyond infection detection and EVD assessment, NeuroSense enables higher temporal-resolution tracking of CSF biomarkers and flow dynamics, supporting earlier recognition of evolving trends that may be missed with intermittent sampling,” write the researchers. “Although the current system measures glucose, lactate, pH, and flow, the platform is modular and can accommodate additional sensors in future iterations. By providing near-bedside, actionable insights into patients’ neurological health, NeuroSense has strong potential to enhance clinical decision-making and improve patient care.”
The post CSF Platform Enables Near Real-Time Monitoring of Multiple Biomarkers appeared first on Inside Precision Medicine.
Antibiotic resistance is on the rise around the world, creating an urgent need for faster and more dependable approaches to design antimicrobial candidates. While AI-driven methods have accelerated antimicrobial discovery, most have focused on screening fixed libraries or generating broad candidate sets.
Now, researchers at the University of Pennsylvania have developed ApexGO—a novel, AI-powered method that starts with a small number of candidates and improves them, using a predictive algorithm to evaluate each modification and guide the next.
“Antibiotic discovery is fundamentally a search problem across an enormous molecular space. ApexGO gives us a way to navigate that space with far more direction,” says César de la Fuente, PhD, presidential associate professor in the School of Engineering and Applied Science at UPenn.
This work is published Nature Machine Intelligence in the paper, “A generative artificial intelligence approach for peptide antibiotic optimization.”
“What is striking is that ApexGO’s predictions held up in the real world,” says Jacob R. Gardner, PhD, assistant professor in computer and information science (CIS) at UPenn. “ApexGO was optimizing against another computer model, so one concern was that it might find molecules that looked good to the model but failed in the lab. Instead, the majority of the molecules it designed actually worked.”
indeed, 85% of the AI-generated molecules halted bacterial growth, while 72% outperformed the peptides from which they were derived. In mice, two antimicrobial peptides created by ApexGO reduced bacterial counts at levels comparable to the antibiotic polymyxin B.
“This result points toward a future in which we can optimize molecules for a desired function in a fraction of the time,” adds de la Fuente, “using machines to guide discovery through chemical spaces too vast for humans to explore by trial and error.”
For years, the de la Fuente lab has looked for antibiotic candidates in unlikely places, from frog secretions to ancient microbes. Two years ago, the group released APEX, an AI model that predicts whether or not a given peptide is likely to have antimicrobial properties.
“APEX helped us find promising antibiotic candidates in enormous biological datasets,” says Marcelo Torres, PhD, research assistant professor of psychiatry in the Perelman School of Medicine. “ApexGO takes the next step: once we have a promising molecule, it helps us ask how to make it better.”
One part of ApexGO (short for APEX Generative Optimization) suggests molecular tweaks, while the previously published APEX model predicts whether those changes are likely to increase antimicrobial activity. ApexGO then uses those predictions to guide the next round of proposed edits.
While some of the molecules proposed by ApexGO showed promising antibiotic activity, the researchers emphasize that even the best-performing peptides are still early-stage candidates. Before any could be used to treat infections in humans, they would need to be further optimized for safety, stability, and how long they remain active in the body.
Still, the study suggests that AI can help researchers decide which molecules are worth making and testing in the first place. For de la Fuente, the approach could eventually extend beyond antibiotics. “In this case, we wanted to optimize peptides for antimicrobial activity,” he says. “But you could imagine applying the same idea to peptides with other biological functions, like modulating the immune system or targeting tumors.”
“ApexGO shows that AI can do more than predict which molecules might work: it can help us improve them,” adds de la Fuente. “At a time when antibiotic resistance is rising worldwide, we need technologies that help us move faster from an idea to a real therapeutic candidate. ApexGO is an important step toward that future.”
The post ApexGO: AI-Driven Approach to Faster Antibiotic Discovery appeared first on GEN – Genetic Engineering and Biotechnology News.
What you’re describing sounds really overwhelming. I’m glad you reached out. The fears you mention — being scared of doing something against your will, worrying you might not have control, and feeling intensely concerned about being judged — are patterns I often see in people with anxiety and, sometimes, people with obsessive-compulsive disorder (OCD). A hallmark of OCD is a deep doubt about control: the fear that you might act in a way that goes against your values, even though you don’t want to. These kinds of fears are called intrusive thoughts. While intrusive thoughts can feel very real and frightening, they are not things you actually intend to do or predictions of things that you will do — they’re unwanted experiences that don’t define you.
Avoiding sports and other things for fear of being judged is also a symptom of anxiety. I can understand how hard it is to tell your family what you’re going through, especially if you have felt ignored in the past. At the same time, your pain deserves to be heard and taken seriously. I encourage you to try talking to your parents again, but if you truly feel like you can’t, consider telling one safe person — whether that’s another family member, a school counselor, or even a teacher you trust. You can write how you’re feeling in a note if speaking feels too hard.
The physical symptoms you mentioned — neck and shoulder pain, fidgeting — are also common in anxiety because our bodies can hold tension when our brains are on high alert. What this likely means is that your brain is caught in a fear loop, constantly scanning for danger around control and judgment.
The good news is that this is very treatable. A mental health professional may recommend a type of cognitive behavioral therapy called exposure and response prevention (ERP). ERP helps you gradually face the situations or thoughts you fear instead of looking for reassurance from someone else or avoiding those situations or thoughts altogether. Over time, ERP teaches your brain that thoughts are just thoughts, not actions, and that you can tolerate uncertainty without something bad happening.
For now, you might try gently labeling upsetting thoughts as anxiety, not facts, and practicing not accepting them as true when they show up. Taking small steps toward what you’ve been avoiding can help you rebuild your confidence, even if it feels uncomfortable at first.
While you can practice managing anxiety or intrusive thoughts on your own, it’s better to have help. Once you talk to someone you know and trust, have them help you reach out to a mental health professional who can provide a more thorough assessment and the appropriate treatment for you. You don’t have to go through this alone, and with the right support, this can get much better.
The post I’m scared of everything — what does it mean and how do I get over it? appeared first on Child Mind Institute.
A personalized DNA vaccine targeting up to 40 patient-specific neoantigens generated robust immune responses and encouraging survival outcomes in patients with MGMT-unmethylated glioblastoma in a small Phase I clinical trial, according to new findings published in Nature Cancer.
The study evaluated GNOS-PV01, a personalized therapeutic cancer vaccine developed by Geneos Therapeutics in collaboration with researchers at Washington University School of Medicine in St. Louis. Investigators reported that the vaccine was safe, feasible to administer, and capable of stimulating circulating and tumor-infiltrating T-cell responses in a cancer type long considered highly resistant to immunotherapy.
Glioblastoma remains one of the deadliest cancers, with median survival typically ranging from 12 to 18 months. Patients with MGMT-unmethylated disease face especially poor outcomes because they derive limited benefit from temozolomide, a standard chemotherapy agent commonly used after surgery and radiation.
“Nothing really works in this MGMT-negative or unmethylated glioblastoma patient population,” said Niranjan Sardesai, Geneos’ CEO. “Median survival is around a year, and effective treatments are very much needed.”
The open-label, single-arm GT-20 study enrolled nine patients with newly diagnosed MGMT-unmethylated glioblastoma following surgical resection and radiation therapy. Each patient received a fully individualized vaccine constructed from neoantigens identified through sequencing of their own tumors. Vaccines encoded between 17 and 40 neoantigens per patient.
According to the paper, the vaccine caused no serious adverse events, unexpected toxicities, or dose-limiting toxicities. Eight of the nine evaluable patients developed measurable immune responses. The lone nonresponder had been treated with dexamethasone, an immunosuppressive corticosteroid frequently used in glioblastoma management.
Sardesai emphasized that the immunogenicity findings were particularly notable because glioblastoma is considered an “immune-excluded” tumor with low tumor mutational burden, characteristics that have historically limited the effectiveness of checkpoint inhibitors such as anti–PD-1 therapies.
“Checkpoint-based immunotherapy has not worked in GBM,” he said. “This is a cold tumor.”
The investigators also observed signals of clinical activity. Six-month progression-free survival and 12-month overall survival were each achieved in 66.7% of patients. Median progression-free survival was 8.5 months, while median overall survival reached 16.3 months. Survival at 24 months was 33%, including one patient who remains alive four years after surgery.
“What was very striking was that three of nine patients, or one-third of the patients, had lived more than two years,” Sardesai said. “The two-year survival rate is about 10% to 15%” with standard treatment approaches in this population.
The study also identified an association between stronger CD8-positive T-cell responses and longer survival. Investigators reported that patients generating higher levels of vaccine-induced cytotoxic T cells tended to experience improved overall survival.
One of the most compelling findings involved a long-term survivor who has remained progression-free for nearly five years. Researchers analyzed a brain biopsy obtained approximately three years after treatment initiation and identified vaccine-induced T-cell clones within the tumor tissue that matched T-cell populations detected in the patient’s blood.
“For the first time, we are able to match vaccine-driven immune responses,” Sardesai said. “We are able to see T-cell clones in the blood, and these T-cell clones have infiltrated and are found in her brain.”
The vaccine platform differs from earlier glioblastoma vaccine strategies in several ways. Rather than targeting a small number of antigens, the DNA-based approach allows investigators to incorporate a much larger neoantigen repertoire into each personalized product.
“These patients received as many as 40 different antigens that were identified from their own tumor,” Sardesai said. “Prior treatments had typically been looking at 20 or fewer in GBM.”
He argued that broader antigen targeting may be especially important in glioblastoma because of the disease’s pronounced intratumoral heterogeneity.
“When it comes to targeting cancer, more is better,” he said. “You want to take more shots on goal.”
Another distinguishing feature of the platform is its apparent ability to stimulate CD8-positive killer T cells, which are considered critical for direct tumor cell elimination. Sardesai noted that generating robust CD8 responses has historically been difficult for many cancer vaccine technologies.
Importantly, each vaccine is uniquely manufactured for a single patient.
“These are exquisitely personalized vaccines,” Sardesai said. “Every patient gets their own vaccine.”
The authors cautioned that the findings remain preliminary because of the trial’s small sample size and lack of a control arm. Still, they believe the results justify larger randomized studies.
“We are very encouraged by the data,” Sardesai said. “But this is still only nine patients. We have to replicate these findings in larger, well-controlled studies.”
The company has previously reported results using the same platform in hepatocellular carcinoma, suggesting the strategy could potentially extend across multiple tumor types characterized by immune exclusion and low tumor mutational burden.
“All cancers carry neoantigens,” Sardesai said. “These personalized cancer vaccines provide a very convenient way” to target those tumor-specific alterations across different cancers.
The post Personalized DNA Vaccine Shows Immune Activation and Survival Signals in Glioblastoma Trial appeared first on Inside Precision Medicine.
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.
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.