Trajectory mapping of renal clear cell carcinoma transcriptomes identifies stage-independent predictors of favorable prognosis

Abstract Objectives The prognosis of clear cell renal cell carcinoma (ccRCC) is typically based on clinical stage, but it can vary for some patients. Transcriptomic analysis is vital for understanding ccRCC progression, though its correlation with the clinical stage in predicting prognosis is uncertain. We aim to employ trajectory inference to study ccRCC’s molecular progression and identify potential new markers for judging disease progression and prognosis. Methods Using a trajectory inference approach, we characterize the molecular progression profile of ccRCC based on transcriptome profiling. Additional pathway activity, immune response, and miRNA profiling scoring were integrated to identify possible drivers of trajectory progression. Results Scoring based on the trajectory demonstrates a significant improvement in patient prognosis prediction and identifies 10 risk factors in patients with low-grade tumors, and nine protective factors in patients with high-grade tumors. Mechanistically, we demonstrate an association between solute light carrier transporters are associated with ccRCC progression, with SLC7A5 expression being validated through immunohistochemistry to increase in metastatic patients. Conclusions Trajectory analysis of ccRCC transcriptomes can be used to model the molecular progression of disease and may assist in ccRCC prognosis. SLC7A5 is aberrantly expressed in ccRCC and may be a risk factor for poor prognosis.