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Solid Tumors Pan Cancer Transcriptome: Tissue/Cancer specific expression groups at the Isoform-Level
Pallavi Surana1, Matthew Obusan1, Ramana V Davuluri1
1Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794, USA.
Abstract:
Most of the human genome is transcribed into diverse isoforms whose tissue specificity is profoundly disrupted in cancer, yet isoform-level dysregulation remains poorly characterized across solid tumors. Here, we introduce STPCaT (Solid Tumors Pan-Cancer Transcriptome), an isoform-centric analysis extending TransTEx to systematically classify transcript expression across TCGA solid tumors and GTEx normal tissues. STPCaT reveals a striking collapse of normal tissue-specific programs in cancer, accompanied by the emergence of two dominant expression groups: cancer-high (CanHigh) and normal-high (NorHigh) isoforms. We uncover a large repertoire of previously unannotated Cancer-Testis Antigens (CTAs), majority of which are absent from existing CTA databases, with broad relevance across multiple cancers, including gliomas. In pan-gliomas, consensus clustering and random-forest feature selection identify compact, highly discriminative isoform signatures that robustly stratify low-grade and glioblastomas with up to 97-98% accuracy using as few as five transcripts. These signatures recapitulate canonical glioma biology and highlight pathways linked to migration, development, and vesicle trafficking. Independent validation in the GLASS consortium cohort demonstrates cohort-specific trends that partially recapitulate primary findings, reflecting known biological heterogeneity across patient populations. Together, STPCaT provides a scalable, isoform-resolved resource for tumor stratification, CTAs discovery, and precision oncology applications across solid tumors.
Insights
The Solid Tumors Pan-Cancer Transcriptome (STPCaT) reveals a collapse of normal tissue-specific gene expression in cancer, identifying new cancer-testis antigens and isoform signatures for precise tumor stratification.
Area of Science:
- Genomics and Transcriptomics
- Cancer Biology
- Bioinformatics
Background:
- The human genome transcribes into diverse isoforms, with tissue-specific expression often disrupted in cancer.
- Isoform-level dysregulation in solid tumors remains poorly understood, limiting diagnostic and therapeutic applications.
- Existing cancer-testis antigen (CTA) databases are incomplete, missing many potential tumor biomarkers.
Purpose of the Study:
- To systematically classify transcript expression across solid tumors and normal tissues using an isoform-centric approach.
- To identify novel diagnostic biomarkers and unannotated CTAs through pan-cancer transcriptome analysis.
- To develop accurate isoform signatures for stratifying glioma subtypes and enabling precision oncology.
Main Methods:
- Development and application of STPCaT (Solid Tumors Pan-Cancer Transcriptome) analysis, extending TransTEx.
- Classification of transcript expression across TCGA solid tumors and GTEx normal tissues.
- Consensus clustering and random-forest feature selection for identifying discriminative isoform signatures in pan-gliomas.
Main Results:
- STPCaT revealed a collapse of normal tissue-specific expression programs in cancer, with two dominant isoform groups: cancer-high and normal-high.
- A significant repertoire of previously unannotated CTAs was discovered, many relevant across multiple cancers, including gliomas.
- Highly accurate (97-98%) isoform signatures for stratifying low-grade gliomas and glioblastomas were identified using as few as five transcripts.
Conclusions:
- STPCaT provides a scalable, isoform-resolved resource for advancing tumor stratification and biomarker discovery in solid tumors.
- The identified isoform signatures offer potential for precision oncology applications, particularly in glioma subtyping.
- The study highlights the critical role of isoform-level analysis in understanding cancer biology and uncovering novel therapeutic targets.
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