Background: Identification of expression alternations between early and late stage cancers is helpful for\r\nunderstanding cancer development and progression. Much research has been done focusing on stage-dependent\r\ngene expression profiles. In contrast, relatively fewer studies on isoform expression profiles have been performed\r\ndue to the difficulty of quantification and noisy splicing. Here we conducted both gene- and isoform-level analysis\r\non RNA-seq data of 234 stage I and 81 stage IV kidney renal clear cell carcinoma patients, aiming to uncover the\r\nstage-dependent expression signatures and investigate the advantage of isoform expression profiling for\r\nidentifying advanced stage cancers and predicting clinical outcome.\r\nResults: Both gene and isoform expression signatures are useful for distinguishing cancer stages. They provide\r\ncommon and unique information associated with cancer progression and metastasis. Combining gene and isoform\r\nsignatures even improves the classification performance and reveals additional important biological processes, such\r\nas angiogenesis and TGF-beta signaling pathway. Moreover, expression abundance of a number of genes and\r\nisoforms is predictive of the risk of cancer death in an independent dataset, such as gene and isoform expression\r\nof ITPKA, the expression of a functional important isoform of UPS19.\r\nConclusion: Isoform expression profiling provides unique and important information which cannot be detected by\r\ngene expression profiles. Combining gene and isoform expression signatures helps to identify advanced stage\r\ncancers, predict clinical outcome, and present a comprehensive view of cancer development and progression.
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