Correction to: Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer (Cell, (2016), 166, 3, (755-765), (S0092867416306730), 10.1016/j.cell.2016.05.069)

(Cell 166, 755–765; July 28, 2016) Our paper characterized proteomics and phosphoproteomics data from high-grade serous ovarian cancer tumors. As part of this analysis, we, the authors, used machine learning to identify a set of protein signatures that were predictive of patient survival after treatment. We recently discovered that the code we used for this analysis selected incorrect signatures during the training phase, and these signatures were included as the protein weights listed in Table S6. The incorrect signatures in Table S6, if used on the complete proteomics dataset, would not produce the results shown in Figure 4. We have now corrected this issue in the updated table, and the combination of the resulting signatures produces the same results shown in Figure 4. Importantly, when we applied the corrected signatures to our prospective dataset (previously published in McDermott et al., 2020, 10.1016/j.xcrm.2020.100004), we obtained identical results, confirming the validity and predictive value of the corrected signatures. This error does not impact any of the reported results, figures, or conclusions in our manuscript. We have provided an updated Table S6 with the correct protein signatures linked below. We sincerely apologize for any confusion this error may have caused.