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Molecular mapping reveals hidden cellular programs in heart transplant rejection

Researchers at Vanderbilt University Medical Center used spatial transcriptomics to characterize acute rejection and response to immunomodulatory therapies following heart transplantation. The study linked cell-specific gene expression patterns to the development of cardiac allograft vasculopathy, a form of chronic rejection that limit...

SourceVanderbilt University Medical Center·JournalNature Cardiovascular Research·TypeImaging analysis·DateAug 10, 2026

Emerging roles of hepatocellular carcinoma gene signatures in prognosis and immunotherapy: challenges and opportunities

Hepatocellular carcinoma (HCC) gene signatures can predict prognosis and respond to immune checkpoint inhibitors. However, validating these signatures across different platforms and overcoming ethical concerns hinder their widespread adoption. Integrating multi-omics approaches with liquid biopsy holds promise for personalized therapy,...

SourceXia & He Publishing Inc.·JournalGene Expression·DateJul 14, 2026

New AI tool developed by Stowers Institute and Helmholtz Munich scientists predicts how cells choose their future — helping uncover hidden drivers of development

Researchers developed RegVelo, an AI framework that models cellular dynamics and gene regulation to predict cellular fate decisions. The model traces developmental trajectories and simulates regulatory interactions, providing insights into hidden drivers of development and potential therapeutic targets.

Mapping 3D-super-enhancers with machine learning to pinpoint regulators of cell identity

Scientists at St. Jude Children's Research Hospital developed BOUQUET to analyze 3D-enhancer architecture in machine learning-based graph theory framework, identifying protein condensates and predicting gene expression. The findings provide new insight into how cells regulate genes controlling specialized identities.

SourceSt. Jude Children's Research Hospital·JournalNucleic Acids Research·DateMar 9, 2026

Unlocking key insights into gene expression using a novel mouse model

Researchers developed a novel mouse model to visualize RNA Polymerase II during elongation, shedding light on gene expression dynamics. The study revealed dynamic patterns of gene transcription activity in various tissues and developmental states, with implications for understanding development, differentiation, and disease mechanisms.

SourceInstitute of Science Tokyo·JournalJournal of Molecular Biology·TypeExperimental study·DateNov 11, 2025

Combining the VIGex gene expression signature with liquid biopsy may improve response prediction to immunotherapy

Researchers have found that combining the VIGex gene expression signature with liquid biopsy analysis improves response prediction to immunotherapy in patients with advanced solid tumors. The study analyzed tumor samples and circulating tumor DNA (ctDNA) by liquid biopsy, showing that the VIGex-Hot subgroup was associated with higher o...

SourceVall d'Hebron Institute of Oncology·JournalJCO Precision Oncology·DateNov 7, 2024

Unlocking the ‘chain of worms’

A team of scientists has created a single-cell atlas for the highly regenerative worm Pristina leidyi, revealing new insights into its regenerative abilities. The study characterizes all major annelid cell types and provides molecular signatures that could inform stem cell technologies and regenerative medicine.

SourceWashington University in St. Louis·JournalNature Communications·TypeExperimental study·DateApr 15, 2024

CD4+ T cell patterns linked to autoimmune disorders

A study published in Cell Genomics reveals that specific changes in CD4+ T cell categories and gene programs are associated with autoimmune diseases, including distinct patterns related to aging and sex. The findings provide a comprehensive catalog of CD4+ T cell changes linked to 20 different autoimmune diseases.

SourceOsaka University·JournalCell Genomics·TypeObservational study·DateJan 11, 2024

New insights into the prognostic power of gene expression signatures in breast cancer

The study analyzed 10,000 gene expression signatures to assess their prognostic ability, finding that they lead to accurate patient prognosis in no more than 80% of cases. The researchers emphasize the need for a comprehensive approach incorporating molecular, clinical, histological, and other factors to ensure an accurate prognosis.

SourceUniversität Leipzig·JournalScientific Reports·TypeData/statistical analysis·DateOct 5, 2023

ER-positive breast cancer presents differing metabolic signatures in African American, white women

Researchers found that African American women with ER-positive breast cancer have decreased levels of amino acids and increased levels of fatty acids compared to non-Hispanic white women. This study may help explain the higher mortality rates in African American women with the disease, suggesting potential new screening strategies.

SourceUniversity of Illinois at Urbana-Champaign, News Bureau·JournalScientific Reports·TypeRandomized controlled/clinical trial·DateSep 11, 2023

Time is right to develop a consensus Human Skin Cell Atlas, according to leading dermatology experts

A global team of experts outlines a roadmap for creating a comprehensive and inclusive reference work on human skin cell composition. The proposed Human Skin Cell Atlas will provide a standardized framework for semi-automated mapping of patient-specific changes in skin diseases, supporting personalized medicine.

SourceElsevier·JournalJournal of Investigative Dermatology·TypeSystematic review·DateAug 21, 2023

People who preserve ‘immune resilience’ live longer, resist infections

A multinational study identified immune resilience as a critical factor influencing life span, HIV/AIDS, flu, sepsis mortality, recurrent skin cancer, and COVID-19 mortality. Individuals with optimal levels of immune resilience were more likely to resist infections and recover from inflammatory stressors.

SourceUniversity of Texas Health Science Center at San Antonio·JournalNature Communications·TypeMeta-analysis·DateJun 13, 2023

Researchers at the GIST develop deep learning model to predict adverse drug-drug interactions

Researchers developed a deep learning-based model to predict drug-drug interactions using gene expression data. The DeSIDE-DDI model can identify potentially dangerous pairs and act as a drug safety monitoring system, helping establish the correct usage of drugs in the development phase.

SourceGIST (Gwangju Institute of Science and Technology)·JournalJournal of Cheminformatics·TypeComputational simulation/modeling·DateMay 4, 2022

Early, persistent activation of specific immune cells may be a predictor of severe COVID-19

Researchers found early and persistent activation of neutrophils in patients who developed severe COVID-19. The study suggests that identifying specific gene signatures could lead to effective treatments targeting high-risk patients. This discovery may also inform the development of simple blood tests to prioritize treatment.

SourceUniversity of Illinois Chicago·JournalJCI Insight·TypeComputational simulation/modeling·DateMar 14, 2022

How alike are the cancer cells from a single patient?

A new study by USC researchers uses a genetic technology to analyze gene expression signatures of individual cancer cells from patients with leukemia. The findings show that cancer cells with distinct gene expression profiles tend to grow in different organs, while those with specific genes are more resistant to chemotherapy.

SourceKeck School of Medicine of USC·JournalNature Communications·TypeExperimental study·DateNov 11, 2021

Genomic signature explains FDG-avidity of PSMA-suppressed prostate tumors

A genomic signature associates with differential expression of glucose transporters and hexokinase proteins in prostate cancers with low PSMA expression. This allows for improved uptake of 18F-FDG compared to PSMA-targeted radioligands, making it an attractive imaging tool for neuroendocrine prostate cancer patients.

SourceSociety of Nuclear Medicine and Molecular Imaging·JournalJournal of Nuclear Medicine·DateJul 22, 2020

New test identifies high-risk liver patients

A new test has identified a gene signature related to the immune response in liver tissue of patients with high-risk Primary Biliary Cholangitis (PBC), a rare autoimmune condition. The test allows for early intervention with alternative treatments, increasing chances of success and potentially staving off the need for a liver transplant.

SourceNewcastle University·JournalEBioMedicine·DateDec 2, 2016

Targeted antibody, immune checkpoint blocker rein in follicular lymphoma

A phase II clinical trial at the University of Texas M. D. Anderson Cancer Center showed that a combination of rituximab and pidilizumab sparked complete responses in 19 out of 29 patients with relapsed follicular lymphoma, with a response rate of 66%. The treatment had a mild side effect profile, with no grade 3 or 4 adverse events.

SourceUniversity of Texas M. D. Anderson Cancer Center·JournalThe Lancet Oncology·DateDec 11, 2013

Gene expression findings a step toward better classification and treatment of juvenile arthritis

Scientists have identified gene expression patterns in children with juvenile idiopathic arthritis (JIA) that can help predict their disease outcome and guide treatment. These findings could lead to more precise classification of JIA subtypes and the development of individually tailored treatments.

Nurture over nature

Researchers found that up to one-third of genes are differentially expressed due to environment, with respiratory genes upregulated in urban populations. The study suggests that environmental factors play a large role in modulating gene expression, and that the same gene can be expressed differently depending on the environment.

SourceNorth Carolina State University·JournalPLOS Genetics·DateApr 22, 2008