TransLnc

TransLnc catalogs translatable long non-coding RNAs (lncRNAs), their encoded peptides, tissue expression, homology relationships, supporting evidence, and predicted neoantigens to enable studies of lncRNA translation and cancer immunopeptidomes.

Key Features:

• Extensive Peptide Catalog: Documents approximately 583,840 peptides encoded by 33,094 lncRNAs, supported by computational predictions and experimental evidence.
• Evidence Integration: Integrates six types of direct and indirect evidence to support coding potential, with 65.28% of peptide entries backed by at least one evidence type.
• Tissue-Specific Expression: Provides peptide data across 34 tissues to reflect tissue-specific lncRNA expression patterns.
• Homology and Unique Characteristics: Predicts and reports homology relationships and unique characteristics of lncRNA-encoded peptides for comparative studies.
• Cancer Immunotherapy Insights: Computationally predicts tumor neoantigens from lncRNA-encoded peptides, including 220,791 candidates binding MHC class I and 237,915 binding MHC class II molecules.
• Flexible Analytical Tools: Includes analytical functionalities for examining lncRNA tissue expression patterns and assessing clinical relevance across various cancer types.

Scientific Applications:

• Translational Research: Investigation of the translational capacity of lncRNAs and identification of translated peptides.
• Immunopeptidome and Neoantigen Discovery: Extending understanding of the cancer immunopeptidome by providing candidate lncRNA-derived neoantigens.
• Clinical and Therapeutic Research: Supporting biomarker discovery, personalized medicine, and targeted cancer immunotherapy research via neoantigen datasets and clinical relevance assessments.

Methodology:

Combines computational peptide prediction with experimental evidence, integrates six types of direct and indirect evidence, predicts homology relationships, and computationally predicts MHC class I and II binding neoantigens.