Physical pressure on the brain triggers neurons’ self-destruction programming

Anna Wenninger and Maksym Zarodniuk demonstrate a research project in the Patzke Lab.
Photo Credit: Michael Caterina/University of Notre Dame

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Chronic physical compression on the brain, such as that exerted by a growing tumor, triggers specific molecular pathways that program neurons to self-destruct, independent of direct tissue invasion.
• Methodology: Researchers created a model neural network using induced pluripotent stem cells (iPSCs) to mimic the brain's environment, applied mechanical pressure to simulate glioblastoma growth, and analyzed the resulting cellular responses via mRNA sequencing and preclinical live models.
• Key Data: The sequencing revealed a marked increase in HIF-1 molecules and AP-1 gene expression in compressed cells, specific biomarkers indicating stress adaptation and neuroinflammation that precipitate neuronal death and synaptic dysfunction.
• Significance: This study isolates mechanical force as a critical, independent factor in neurodegeneration, explaining why patients with brain tumors often suffer from cognitive decline, motor deficits, and seizures even in non-cancerous brain regions.
• Future Application: Identifying these specific death-signaling pathways provides novel targets for drugs designed to block mechanically induced neuron loss, with potential relevance for treating traumatic brain injury (TBI) alongside brain cancer.
• Branch of Science: Neuroscience, Bioengineering, and Oncology.

Scientists now know why ovarian cancer spreads so rapidly in the abdomen

Cancer cells (red) stick to mesothelial cells (green) and form hybrid spheres that cut into surrounding abdominal tissue.
Image Credit: Uno et al., 2026

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Ovarian cancer cells accelerate their spread by recruiting protective mesothelial cells from the abdominal lining to form hybrid spheres, rather than traveling alone.
• Methodology: Researchers analyzed abdominal fluid from patients using advanced live microscopy, single-cell genetic analysis, and mouse models to observe the interaction between cancer and mesothelial cells.
• Key Data: Approximately 60% of cancer spheres contain these recruited mesothelial cells, which are transformed by the cancer-secreted protein TGF-β1 to develop invasive properties.
• Significance: This mechanism explains why ovarian cancer metastasizes rapidly and resists chemotherapy, as the cancer cells effectively outsource the physical work of tissue invasion to the mesothelial cells.
• Future Application: New therapies could target the TGF-β1 signaling pathway or disrupt the formation of these hybrid clusters to prevent metastasis and improve treatment efficacy.
• Branch of Science: Oncology and Cell Biology
• Additional Detail: The cancer cells themselves undergo minimal genetic changes during this process, relying instead on the spike-like invadopodia of the recruited cells to drill into organs.

UrFU Chemists Have Synthesized New Compound to Fight Cancer

If successful in trials, such drugs could reach the Russian market in 7-10 years.
Photo Credit: Vladimir Petrov

Scientific Frontline: Extended "At a Glance" Summary

The Core Concept: Researchers at Ural Federal University (UrFU) have synthesized a new family of chemical compounds that selectively target and suppress the growth of specific tumor cells by halting their division rather than immediately destroying them.

Key Distinction/Mechanism: Unlike traditional chemotherapy drugs that are often cytotoxic (cell-killing) and harmful to healthy tissues, these new compounds utilize a cytostatic mechanism. They effectively "freeze" the tumor by blocking Cyclin-dependent kinase 2 (CDK2), a protein critical for cell division, thereby preventing tumor proliferation with reduced toxicity to healthy cells.

Origin/History:

• Discovery Context: Developed by the UrFU Scientific, Educational and Innovative Center of Chemical and Pharmaceutical Technologies.
• Publication: Findings and descriptions of the compounds were published in the international journal ChemMedChem.
• Timeline: Announced in February 2026, with potential market availability estimated in 7-10 years pending successful trials.

Blueprints for Designing T Cells that Kill

This image shows killer T cells surrounding and attacking a cancer cell. A new atlas developed by researchers at UC San Diego could make it possible to design custom T cells for immunotherapy to maximize patient benefit while minimizing potential negative effects.
Image Credit: National Institutes of Health/NIAID

Scientific Frontline: "At a Glance" Summary

• Main Discovery: A comprehensive genetic atlas of CD8+ T cell states was developed, identifying specific transcription factors that determine whether these immune cells persist as effective defenders or succumb to dysfunctional exhaustion.
• Methodology: Researchers utilized advanced computational modeling, gene editing, and in vivo mouse studies to map nine distinct T cell states and experimentally manipulated genetic switches to decouple the pathways regulating immune memory from those driving exhaustion.
• Key Data: The study identified nine distinct CD8+ T cell states and discovered two previously unknown transcription factors, ZSCAN20 and JDP2, which, when inhibited, restored tumor-killing capacity without sacrificing long-term immune memory.
• Significance: This research fundamentally challenges the long-standing scientific belief that T cell exhaustion is an inevitable byproduct of chronic immune activation, proving instead that exhaustion and protective memory are distinct, separable genetic programs.
• Future Application: These findings provide a blueprint for engineering "custom" T cells in adoptive cell transfer and CAR T-cell therapies that are programmed to resist burnout while maintaining long-term potency against cancer and chronic infections.
• Branch of Science: Immunology, Oncology, and Computational Biology.

‘Personal lives’ of lung cancer cells help predict response to treatment

A cancer cell featuring metabolic uptake (in yellow) and vessels (in blue).
Photo credit: The University of Queensland

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Cell metabolism within specific "neighbourhoods" of non-small cell lung carcinoma (NSCLC) acts as a critical determinant for patient response and resistance to immunotherapy.
• Methodology: Researchers employed machine learning algorithms and computational spatial biology to map cell interactions at cellular resolution, specifically profiling how individual cancer cells and tumor regions metabolize glucose.
• Key Data: While immunotherapy costs governments approximately $400,000 per patient annually, it is effective in only 20% to 30% of cases; higher glucose uptake was directly correlated with poorer patient outcomes.
• Significance: This profiling capability allows clinicians to identify non-responders early, preventing the use of ineffective, expensive treatments and facilitating the selection of patients who require combination or alternative therapies.
• Future Application: The findings will guide the development of metabolic inhibitors to enhance immunotherapy efficacy and are planned for expansion into clinical trials for head, neck, and aggressive skin cancers.
• Branch of Science: Oncology and Computational Biology
• Additional Detail: The research, published in Nature Communications, utilized technologies to visualize glucose processing heterogeneity within tumors to advance precision medicine.

Immunotherapy before surgery helps shrink tumors in patients with desmoplastic melanoma

Dr. Antoni Ribas (far right) with members of his research team at UCLA, who helped lead the clinical trial showing that immunotherapy before surgery can shrink or eliminate tumors in patients with desmoplastic melanoma.
Photo Credit: Courtesy of UCLA/Health

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Neoadjuvant treatment with the immunotherapy drug pembrolizumab significantly shrinks or eliminates tumors in patients with desmoplastic melanoma, a rare and aggressive form of skin cancer.
• Methodology: In the SWOG S1512 clinical trial (Cohort A), researchers administered three infusions of pembrolizumab over a nine-week period to 28 patients with surgically resectable desmoplastic melanoma prior to their scheduled surgery.
• Key Data: Pathologic analysis revealed that 71% of patients had no detectable live tumor cells at the time of surgery, and at the three-year follow-up, 95% of patients survived with a 74% disease-free recurrence rate.
• Significance: This therapeutic approach can spare patients from extensive, potentially disfiguring surgeries and postoperative radiation, drastically improving quality of life without compromising survival outcomes.
• Future Application: The findings support a paradigm shift toward using PD-1 blockade immunotherapy as the standard neoadjuvant care for resectable desmoplastic melanoma, replacing immediate invasive excision.
• Branch of Science: Oncology, Immunology, and Dermatology.
• Additional Detail: Desmoplastic melanoma, typically resistant to chemotherapy and radiation, was found to be highly responsive to PD-1 blockade due to its high mutational burden caused by UV damage.

New cancer-killing material developed by Oregon State University nanomedicine researchers

Graphic depicting how new CDT nanoagent works.
Illustration Credit: Parinaz Ghanbari.

Scientific Frontline: "At a Glance" Summary

• Main Discovery: A novel iron-based metal-organic framework (MOF) nanoagent has been developed to trigger dual chemical reactions within cancer cells, generating oxidative stress via hydroxyl radicals and singlet oxygen to eradicate malignant cells while sparing healthy tissue.
• Methodology: The researchers designed a chemodynamic therapy (CDT) agent that leverages the acidic and high-hydrogen peroxide microenvironment of tumors to catalyze the simultaneous production of hydroxyl radicals and singlet oxygen.
• Key Data: In preclinical studies involving mice with human breast cancer, systemic administration of the nanoagent resulted in complete tumor eradication and long-term prevention of recurrence with no observed systemic toxicity or adverse effects on healthy cells.
• Significance: This advancement overcomes limitations of existing CDT agents that typically generate only one type of reactive oxygen species or lack sufficient catalytic activity, offering a more potent and durable therapeutic benefit for cancer treatment.
• Future Application: The team plans to evaluate the therapeutic efficacy of this nanoagent in various other cancer types, including aggressive pancreatic cancer, to establish its broad applicability prior to human clinical trials.
• Branch of Science: Nanomedicine, Oncology, and Pharmaceutical Sciences

Purdue team announces new therapeutic target for breast cancer

Graduate student Addison Young (left) and Kyle Cottrell, assistant professor, both in Purdue’s department of biochemistry. Young and Cottrell have reported discovering a new therapeutic target for triple-negative breast cancer in the journal RNA.
Photo Credit: Courtesy of Purdue University

Scientific Frontline: "At a Glance" Summary

• Main Discovery: A specific double-stranded RNA (dsRNA)-binding protein called PACT has been identified as a novel therapeutic target for triple-negative breast cancer (TNBC), a deadly form of the disease that currently lacks targeted therapies.
• Methodology: Researchers utilized the gene-editing tool CRISPR-Cas9 to deplete PACT in various cell lines, allowing them to observe which cellular pathways became activated and to confirm PACT's role as a suppressor of the RNA-activated protein kinase (PKR).
• Key Data: The study established that PACT functions as a dimer—requiring the fusion of two monomers to operate—and that TNBC cells are particularly sensitive to its depletion, which triggers a "viral mimicry" state that can lead to cancer cell death.
• Significance: This research resolves a scientific controversy by confirming PACT acts as a suppressor rather than an activator of PKR; blocking PACT allows PKR to sense dsRNA and initiate stress responses that kill cancer cells, offering a strategy to treat TNBC without broad chemotherapy.
• Future Application: Scientists aim to develop molecules that specifically inhibit PACT dimerization, creating precise drugs for TNBC and potentially other cancer types that depend on this protein for survival.
• Branch of Science: Biochemistry and Oncology.
• Additional Detail: Unlike many therapeutic targets which are enzymes, PACT is a structural protein; therefore, treatment strategies must focus on physically preventing the binding of its two monomers rather than blocking enzymatic activity.

AI-powered model advances treatment planning for patients with spinal metastasis

Image Credit: Scientific Frontline / AI generated (Gemini)

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Researchers developed a machine learning-based prognostic scoring system for spinal metastasis that accurately predicts one-year survival using modern clinical data.
• Methodology: The team employed Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression to analyze prospective data from 401 patients undergoing surgery at 35 medical institutions.
• Key Data: The model demonstrated high accuracy with an AUROC of 0.762, distinguishing one-year survival rates between low-risk (82.2%), intermediate-risk (67.2%), and high-risk (34.2%) groups.
• Significance: This tool resolves the limitations of traditional scoring systems based on obsolete 1990s data by integrating outcomes from contemporary treatments like molecularly targeted therapies and immunotherapies.
• Future Application: Clinical deployment to guide surgical versus palliative care decisions, with ongoing plans to validate the model's efficacy using international datasets.
• Branch of Science: Orthopedics, Oncology, and Data Science
• Additional Detail: Prognostic stratification relies on five non-invasive variables: vitality index, age, performance status, bone metastasis presence, and preoperative opioid usage.

Optimized Solvent Design Improves Lymphatic Drug Delivery to Metastatic Lymph Nodes

Overview of Lymphatic Drug Delivery Systems (LDDS) and the Optimal Ranges of Solvent Osmolarity and Viscosity Depending on Therapeutic Strategies.
Illustration Credit: ©Taiki Shimano et al.

Scientific Frontline: "At a Glance" Summary

• Main Discovery: The optimization of solvent osmolarity and viscosity in Lymphatic Drug Delivery Systems (LDDS) significantly regulates drug pharmacokinetics and perinodal dynamics to improve treatment of metastatic lymph nodes.
• Methodology: Researchers injected therapeutic formulations directly into the sentinel lymph nodes of MXH10/Mo/lpr mice—a model featuring human-sized nodes—to monitor real-time changes in lymphatic and vascular flow based on varied solvent properties.
• Key Data: Increased solvent osmolarity was observed to promote blood inflow and expand lymphatic sinuses (drug pathways), while solvent viscosity acted as the dominant factor determining the duration of drug retention and the extent of delivery.
• Significance: The study provides critical guidelines for "tailor-made solvent design," directly validating the protocols for ongoing Phase I clinical trials at Iwate Medical University and Tohoku University Hospital.
• Future Application: Development of next-generation cancer therapies where drug solvent properties are customized to specific clinical goals, such as maximizing retention time or enhancing downstream distribution.
• Branch of Science: Biomedical Engineering, Oncology, and Pharmacology.
• Additional Detail: This research represents the first comprehensive demonstration of how fundamental physicochemical properties of solvents independently influence drug behavior during intranodal administration.

An AI to predict the risk of cancer metastases

Group of human colon cancer cells with invasive behavior. Cell nuclei are in yellow and cell bodies in red. The finger-like protrusions of invasive cells are on the upper right region.
Image Credit: © Ariel Ruiz i Altaba, UNIGE 

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Researchers at the University of Geneva (UNIGE) have developed an artificial intelligence algorithm capable of predicting the risk of cancer metastasis and recurrence with high reliability.
• Methodology: The team identified specific gene expression signatures in colon cancer cells that drive invasive behavior and trained a predictive model, named MangroveGS, to analyze these genomic patterns across various tumor types to assess metastatic probability.
• Key Data: After training, the AI model achieved a predictive accuracy of nearly 80% in forecasting the occurrence of metastases, transforming complex genomic data into actionable prognostic information.
• Significance: This study fundamentally challenges the concept of cancer as "anarchic" cell growth, instead framing it as a distorted form of orderly biological development where suppressed genetic programs are reactivated.
• Future Application: The algorithm will enable clinicians to stratify patients based on metastatic risk, facilitating personalized treatment strategies and identifying new therapeutic targets to block the spread of tumors.
• Branch of Science: Oncology, Genetics, and Artificial Intelligence.
• Additional Detail: The research highlights that metastatic potential is defined by the reactivation of ancient developmental programs, providing a predictable "logic" to tumor progression that can be decoded by AI.

Why do T cells attacking tumors become fatigued?

Illustration Credit: Courtesy of Kyoto University

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Accumulation of active aldehydes, driven by lipid peroxidation, induces CD8⁺ T cell (killer T cell) exhaustion in the tumor microenvironment by disrupting the balance of cellular energy metabolism.
• Methodology: Researchers employed multicolor flow cytometry to analyze mitochondrial function and metabolic activities in tumor-infiltrating T cells derived from human samples and mouse models with genetic deficiencies in fatty acid oxidation (FAO) enzymes.
• Key Data: Deficiency in FAO enzymes resulted in excessive fatty acid uptake and subsequent lipid peroxidation; the resulting active aldehydes inhibited FAO while simultaneously activating glycolysis, creating a self-perpetuating cycle of metabolic failure.
• Significance: Elucidates a critical, previously undefined mechanism where active aldehydes force T cells into terminal exhaustion by rewiring metabolism, distinct from the cell death pathway of ferroptosis.
• Future Application: Development of therapeutic strategies that target and neutralize active aldehydes to disrupt this metabolic exhaustion cycle, thereby sustaining T cell functionality during cancer immunotherapy.
• Branch of Science: Immunology, Oncology, and Metabolomics
• Additional Detail: The findings overturn the prior assumption that lipid peroxidation affects T cells primarily through ferroptotic cell death, highlighting instead a non-lethal but debilitating metabolic reprogramming.

Blood test can help identify cancer in patients with non-specific symptoms

Photo Credit: Fernando Zhiminaicela

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Researchers identified a specific plasma protein signature capable of detecting cancer in patients presenting with non-specific symptoms such as fatigue, pain, and weight loss.
• Methodology: The study utilized large-scale affinity proteomics to quantify 1,463 proteins in blood samples from nearly 700 patients, comparing cancer cases against a control group that included individuals with other serious non-malignant conditions.
• Key Data: The analysis isolated a distinct protein combination from the 1,463 candidates that distinguishes cancer from inflammatory, autoimmune, and infectious diseases with high precision.
• Significance: This method resolves a common clinical dilemma by effectively filtering patients with vague symptoms, preventing unnecessary invasive investigations for benign cases while ensuring timely diagnostics for cancer patients.
• Future Application: The blood test is intended to serve as a triage tool to identify which patients require prioritization for advanced imaging (PET-CT), with further validation planned for primary care environments.
• Branch of Science: Clinical Oncology and Proteomics.

Purdue mRNA therapy delivery system proves to be shelf-stable, storable

The Proceedings of the National Academy of Sciences has published research about a Purdue University virus-mimicking platform technology that targets bladder cancer cells with mRNA therapies. The LENN platform scientists include, from left, Christina Ferreira, Saloni Darji, Bennett Elzey, Joydeep Rakshit, Feng Qu and David Thompson.
Photo Credit: Purdue University /Ali Harmeson

Scientific Frontline: "At a Glance" Summary

• Main Discovery: The LENN (Layer-by-layer Elastin-like Polypeptide Nucleic Acid Nanoparticle) platform successfully delivers mRNA therapies to bladder cancer cells while retaining full biological activity after being freeze-dried into a shelf-stable powder.
• Methodology: Researchers engineered a virus-mimicking dual-layer nanoparticle to condense and protect nucleic acids, then subjected the formulation to lyophilization (freeze-drying) and storage at -20°C to validate its stability and rehydration properties.
• Key Data: The lyophilized samples maintained complete structural integrity and functionality after three days of storage, successfully targeting upregulated receptors on tumor cells without triggering an immune response.
• Significance: This technology overcomes the severe cold-chain limitations of current lipid nanoparticle systems—which often require storage below -45°C—by providing a biomanufacturable, storable powder form that facilitates easier global distribution.
• Future Application: The team is upscaling the system for preclinical evaluation and initiating efficacy and safety studies in mouse models of bladder cancer.
• Branch of Science: Nanomedicine, Pharmaceutical Chemistry, and Oncology.
• Additional Detail: Multiple reaction monitoring (MRM) profiling confirmed that the system utilizes natural entry pathways and avoids immune detection, potentially solving the "redosing" clearance issues associated with traditional viral vectors.

“Recipe book” for reprogramming immune cells

Filipe Pereira, professor of molecular medicine at Lund University
Photo Credit: Courtesy of Lund University

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Researchers at Lund University established a high-throughput screening platform and a library of over 400 immune-related transcription factors to decode the specific "recipes" required to reprogram accessible somatic cells into distinct immune cell identities.
• Methodology: The study utilized unique DNA barcodes attached to each transcription factor, allowing the simultaneous tracking of thousands of combinatorial possibilities to determine which specific factor groups drive conversion to desired immune lineages.
• Key Data: This four-year project successfully identified reprogramming protocols for six different immune cell types, including Natural Killer (NK) cells, which were previously impossible to generate through direct reprogramming.
• Context: Prior to this breakthrough, the specific reprogramming factors had been mapped for only four of the human body's more than 70 distinct immune cell types, limiting the development of synthetic immunotherapies.
• Significance: The platform enables the production of rare, patient-specific immune cells from abundant sources like skin fibroblasts, potentially expanding immunotherapy applications from cancer treatment to autoimmune diseases and regenerative medicine.

A bacterial toxin can counteract colorectal cancer growth

Sun Nyunt Wai
Photo Credit: Mattias Pettersson

Scientific Frontline: "At a Glance" Summary

• Discovery of Anti-Tumor Toxin: The purified cytotoxin MakA, secreted by the cholera bacterium Vibrio cholerae, has been identified as an agent that significantly inhibits the growth of colorectal cancer tumors.
• Mechanism of Action: MakA accumulates specifically within tumor tissue, inducing cancer cell death and suppressing proliferation while simultaneously recruiting innate immune cells, such as macrophages and neutrophils, to the tumor microenvironment.
• Safety and Specificity: In murine models, systemic administration of MakA targeted tumors locally without causing harmful systemic inflammation, weight loss, or organ dysfunction, indicating a high degree of specificity for cancerous tissue.
• Immune Modulation: The toxin alters the cellular composition of the tumor environment, stimulating the production of immune mediators that promote apoptosis while preserving regulatory mechanisms to protect surrounding healthy tissue.
• Therapeutic Potential: This study highlights a novel therapeutic avenue utilizing bacterial toxins to both directly target cancer cells and enhance the host's immune response, offering a potential alternative to traditional treatments like chemotherapy and radiation.

Intraoperative Tumor Histology May Enable More-Effective Cancer Surgeries

From left to right: Images of kidney tissue as detected with UV-PAM, as imaged by AI to mimic traditional H&E staining, and as they appear when directly treated with H&E staining.
Image Credit: Courtesy of California Institute of Technology

Scientific Frontline: "At a Glance" Summary

• Main Discovery: Researchers developed ultraviolet photoacoustic microscopy (UV-PAM) integrated with deep learning to perform rapid, label-free, subcellular-resolution histology on excised tumor tissue directly in the operating room.
• Mechanism: A low-energy laser excites the absorption peaks of DNA and RNA nucleic acids to generate ultrasonic vibrations; AI algorithms then process these signals to create virtual images that mimic traditional hematoxylin and eosin (H&E) staining without chemical processing.
• Key Data: The system achieves a spatial resolution of 200 to 300 nanometers and delivers diagnostic results in under 10 minutes (potentially under 5 minutes), effectively identifying the dense, enlarged nuclei characteristic of cancer cells.
• Context: Unlike standard pathology, which requires time-consuming freezing, fixation, and slicing that can damage fatty tissues like breast tissue, this method preserves sample integrity and eliminates preparation artifacts.
• Significance: This technology aims to drastically reduce re-operation rates—currently up to one-third for breast cancer lumpectomies—by allowing surgeons to confirm clean tumor margins intraoperatively across various tissue types (breast, bone, skin, organ).

Discovery on how aggressive breast cancer controls protein production

Three of the researchers behind the study, Kanchan Kumari Francesca Aguilo Margalida Esteva, Department of Molecular Biology.
Photo Credit: Mattias Pettersson

Scientific Frontline: "At a Glance" Summary

• Discovery: Researchers at Umeå University identified a novel mechanism in triple-negative breast cancer wherein the enzyme fibrillarin fine-tunes protein production to facilitate tumor growth and adaptation.
• Mechanism: Fibrillarin regulates the 2′-O-methylation (Nm) of ribosomal RNA and collaborates with the ribosomal protein RPS28 to construct specialized ribosomes with distinct translational capabilities.
• Specific Consequence: The depletion of fibrillarin causes a concurrent loss of RPS28, resulting in ribosomal heterogeneity—an imbalance of ribosome types that alters the proteome and drives oncogenic development.
• Context: This research shifts the understanding of cancer etiology beyond solely genetic mutations to include translational control, demonstrating how aggressive cells manipulate protein synthesis machinery.
• Implication: The findings suggest that targeting the ribosome assembly and modification machinery could serve as a new therapeutic strategy for treating aggressive cancers defined by misregulated protein production.

What Is: Organoid

Organoids: The Science and Ethics of Mini-Organs
Image Credit: Scientific Frontline / AI generated

The "At a Glance" Summary

• Defining the Architecture: Unlike traditional cell cultures, organoids are 3D structures grown from pluripotent stem cells (iPSCs) or adult stem cells. They rely on the cells' intrinsic ability to self-organize, creating complex structures that mimic the lineage and spatial arrangement of an in vivo organ.
• The "Avatar" in the Lab: Organoids allow for Personalized Medicine. By growing an organoid from a specific patient's cells, researchers can test drug responses on a "digital twin" of that patient’s tumor or tissue, eliminating the guesswork of trial-and-error prescriptions.
• Bridge to Clinical Trials: Organoids serve as a critical bridge between the Petri dish and human clinical trials, potentially reducing the failure rate of new drugs and decreasing the reliance on animal testing models which often fail to predict human reactions.
• The Ethical Frontier: As cerebral organoids (mini-brains) become more complex, exhibiting brain waves similar to preterm infants, science faces a profound question: At what point does biological complexity become sentience?

How Nutrient Availability Shapes Breast Cancer’s Spread

A microscope image of a breast cancer tumor (blue) and its surrounding microenvironment in a mouse model.
Image Credit: Joseph Szulczewski, David Inman, Kevin Eliceiri, and Patricia Keely/University of Wisconsin/National Institutes of Health

Scientists have gained new insights into how nutrient availability in different organs affects the spread, or metastasis, of breast cancer throughout the body.

In a study in mice jointly led by researchers at Harvard Medical School, Massachusetts General Hospital, and MIT, the team found that no single nutrient explains why breast cancer grows in one organ and not another. Instead, multiple nutrients and cancer cell characteristics work together to shape the spread of the disease.

The team also discovered that breast cancer cells require the nutrient purine to metastasize, regardless of their location or other nutrients available.