Whole transcriptome sequencing
BostonGene’s whole transcriptome sequencing (WTS / RNA-seq) of nearly 20,000 genes enables the precise identification of gene fusions, expression levels and gene expression signatures in a CLIA/CAP environment.
Our comprehensive bioinformatic analysis offers in-depth insights into the tumor and its microenvironment (TME), driving complex biomarker discovery.
Our comprehensive bioinformatic analysis offers in-depth insights into the tumor and its microenvironment (TME), driving complex biomarker discovery.
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The most comprehensive analysis utilizing RNA-seq data
Performance metricsGene fusion analysis
- Well-known fusions
Precise identification of established fusion partners - Novel fusions
An unbiased approach enables the identification of new breakpoints and previously unknown fusions
Gene expression analysis
- Single gene expression
Robust assessment of expression levels for over 20,000 genes. - Gene expression signatures
Multi-gene expression signatures accurately reflect the underlying biology of a specific cancer type
Additional RNA-seq capabilities
- TME analysis
- TCR/BCR repertoire
- HLA haplotyping
- Vaccines analysis
Transcriptomic analysis:
Incidence rate
Identifying diagnoses with the highest target expression or prevalence of a specific fusion for indication selection.
Potential adverse event assessment
Predicting on-target, off-tumor effects by evaluating target expression levels in normal tissues.
Discrimination between tumor and TME cell expression
Expression signals in a bulk RNA-seq sample can come from tumor, microenvironment (TME), or a mixture of both. An ML-based tool, Helenus, separates those signals for accurate expression assessment.
Identifying diagnoses with the highest target expression or prevalence of a specific fusion for indication selection.
Potential adverse event assessment
Predicting on-target, off-tumor effects by evaluating target expression levels in normal tissues.
Discrimination between tumor and TME cell expression
Expression signals in a bulk RNA-seq sample can come from tumor, microenvironment (TME), or a mixture of both. An ML-based tool, Helenus, separates those signals for accurate expression assessment.
AI-based models for clinical outcome prediction
BostonGene specializes in advanced gene expression and signature analysis, empowering the development of predictive AI models.
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Optimized RNA-seq protocols for FFPE samples
- Refined RNA extraction and sequencing protocols provide uniform gene body coverage, equivalent to that obtained with FF PolyA RNA-seq.
- Multi-step quality control ensures the integrity of each sample from RNA extraction to the analyzed data.
- Gene expression levels are orthogonally validated by qPCR.
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Explore BostonGene’s publications that demonstrate WTS analysis
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Cancer Cell • May 1, 2021
Conserved pan-cancer microenvironment subtypes predict response to immunotherapy
Article
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Journal for ImmunoTherapy of cancer • November 3, 2023
Correlating RNA-seq detection and IHC staining of potential antibody-drug conjugate (ADC) targets: HER3, HER2, TROP2, Nectin4, and aFLR
Article
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Nature • March 30, 2024
Procrustes is a machine-learning approach that removes cross-platform batch effects from clinical RNA sequencing data
Article
