Uncategorized
HELIX AI Model Accurately Predicts RNA Splicing, Unlocks Precision Medicine
HELIX AI Model Accurately Predicts RNA Splicing, Unlocks Precision Medicine
RNA splicing, in which different coding RNA, or exons, are joined together after noncoding regions, or introns, are removed, allows for a large array of RNA transcript isoforms with distinct sequences, and functions in tissue- and cell-type-specific patterns. Conversely, transcript isoform alterations can sensitively reflect dynamic changes in cellular states. Aberrant splicing is closely associated with major diseases, such as cancer.
In a new study published in Nature Computational Science titled, “HELIX: a scalable model for predicting context-dependent regulation of RNA splicing and isoform usage,” researchers from the Chinese Academy of Sciences have developed an AI-driven framework that enables highly accurate prediction of RNA splicing and isoform usage by integrating genomic sequence features with tissue-specific RNA binding protein (RBP) expression profiles. The work offers valuable insights for splicing regulatory patterns, pathogenic variant interpretation, and precision medicine research.
Isoform usage is jointly regulated by multiple layers of control, including regulatory elements, such as splicing enhancers and silencers on exons and introns, and tissue microenvironments. Scientists have been challenged to accurately characterize and predict RNA splicing and isoform usage across tissues, cell types, and disease states.
The study’s AI framework, Hierarchical Explainable LSTM for Isoform eXpression (HELIX), overcomes the limitations of conventional approaches via a two-layer deep-learning architecture.
First, the framework integrates DNA sequence information with the expression profiles of 1,499 RBPs. Long short-term memory (LSTM) networks are then employed to effectively capture the complex dependencies and competitive relationships among multiple splice sites.
This design enables precise, reliable prediction of RNA splicing and transcript isoform usage. The model was trained and optimized on large-scale short- and long-read RNA-seq datasets covering 30 distinct human tissues, allowing accurate quantification of complex transcript structures and isoform usage. Results show that HELIX substantially outperforms existing mainstream methods in both splicing strength prediction and overall isoform usage prediction.
In disease-related studies, HELIX deciphered aberrant RNA splicing and transcript isoform alterations. Notably, the researchers identified widespread splicing dysregulation and abnormal isoform usage in tumor cells using large colorectal cancer cohorts.
The results reveal strong correlations among such alterations and genomic mutations, RBP dysregulation, and patient clinical profiles. Results support that splicing abnormalities can serve as key molecular signatures for tumor progression and guiding patient stratification.
The team also developed scHELIX, a single-cell RNA sequencing extension of HELIX. scHELIX supports high-resolution profiling of transcript isoform usage across different cell types and tumor subpopulations, which offer a refined view of intratumoral heterogeneity.
The findings reveal distinct RNA splicing and isoform usage patterns among tumor subclones, providing new clues for tumor evolution research and potential therapeutic target discovery.
The post HELIX AI Model Accurately Predicts RNA Splicing, Unlocks Precision Medicine appeared first on GEN – Genetic Engineering and Biotechnology News.
Uncategorized
New webinar: Tackling drug discovery challenges in cancer research

Hosted by Drug Discovery World and supported by Sartorius and BioIVT, this webinar will explore the opportunities and challenges that exist within cancer research drug discovery and development.
You will hear from Dr Sudha Rao, Chief Scientific Officer of Kazia Therapeutics, Karol Budzik, PhD, Business Development Associate at Vyriad Therapeutics and Lars van der Veen, Chief Scientific Officer at iOnctura.
Presentations will cover how cancer treatments have shifted towards reprogramming the biology driving tumour growth, immune escape and treatment resistance, the trajectory that in vivo CAR-T treatments are taking, and how challenging tumours burdened by stroma and immune-mediated resistance can be tackled.
Q&A with the speakers follows the presentations.
The post New webinar: Tackling drug discovery challenges in cancer research appeared first on Drug Discovery World (DDW).
Uncategorized
Psilocybin proves promising in neuropathic pain mouse study
Amid the rise of psychedelics in the mental health space, researchers have begun to explore psilocybin as a treatment for chemotherapy-induced peripheral neuropathy.
Uncategorized
New Spectrometry Technique Could Aid Formulation Development
New Spectrometry Technique Could Aid Formulation Development
A new technique combining two forms of spectrometry could help biopharmaceutical companies improve their choice of formulation buffer for antibody manufacturing by revealing how molecular forms and three-dimensional shapes of complex biologics respond to their environment. That’s the view of Christian Bleiholder, PhD, a professor at Florida State University who helped develop the technique.
According to Bleiholder, what happens structurally when a complex biological molecule, such as an antibody or viral spike protein, binds to its target is currently poorly understood.
“This is where [this approach] can help with the bioprocessing and formulation,” he says, as structural changes “can affect the lifespan [of the product] and lead to issues, such as aggregation.”
Because antibodies are complex, existing techniques tend to be powerful at different levels of complexity, he explains. Mass spectrometry is particularly powerful for distinguishing molecular composition, while structural approaches such as X-ray crystallography and cryo-electron microscopy can provide high-resolution structural information.
The challenge is understanding the link between these things within a heterogeneous sample, he says.
To overcome this, Bleiholder and his team worked with Bruker Daltonics to develop Tandem-Trapped Ion Mobility Spectrometry (Tandem-TIMS). This combines tandem ion mobility spectrometry with tandem mass spectrometry to disentangle three overlapping layers of molecular complexity: molecular form, three-dimensional shape, and binding or assembly state, he says.
He explains that, if the proteins have different structures, they can be characterized with tandem ion mobility spectrometry, and then mass spectrometry can be used to look at their molecular forms and binding states.
Going forward, Bleiholder hopes the technique can be used for formulation development but also earlier, during drug discovery of new products, such as multi-specific antibodies, to determine which molecular states are important and how those change when a biologic engages its target. He also plans to look at automating the technique.
Bleiholder spoke about using Tandem-TIMS at the Bioprocessing Summit in Boston earlier this year.
The post New Spectrometry Technique Could Aid Formulation Development appeared first on GEN – Genetic Engineering and Biotechnology News.
-
Uncategorized8 months agoNovartis buys Synnovation’s PI3Kα inhibitors for $3 billion
-
Endpoints News8 months ago
Novartis to pay $2B upfront to take next-gen PI3Kα inhibitor from Synnovation
-
Uncategorized6 months agoOptical Pooled CRISPR Screen Reveals Regulators of NF-κB Dynamics in Human Cells
-
Uncategorized6 months ago
Relay’s PI3Kα inhibitor clears efficacy bar in Phase 2 vascular anomalies study
-
Uncategorized5 months ago
Hybrid solid−liquid optics enable scalable, high-resolution light-sheet microscopy across diverse immersion media
-
Fierce Biotech7 months ago
Scientists turn pig semen extract into eye drops that kill cancer in mice
-
Nature Biotechnology8 months ago
Sustained nitric oxide production by engineered E. coli remodels the tumor microenvironment and potentiates immunotherapy
-
Nature Biotechnology7 months ago
Mapping cis-regulatory mutations at scale in sorghum enables modulation of gene expression
Scan to Read