Q-omics provides the consensus-scored SAE1 profile across patient tissues and cancer cell-line models. SAE1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SAE1 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, SAE1 protein abundance shows 23,854 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where SAE1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for SAE1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SAE1 survival associations across molecular data types. SAE1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SAE1 RNA expression–survival associations across cancer types. High SAE1 expression shows unfavorable associations in MESO, UVM, ACC, LIHC, SKCM and KIRP. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify MESO as the clearest survival context for SAE1 RNA expression.
This table summarizes SAE1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SAE1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SAE1 shows lower tumor expression in THCA and higher tumor expression in HNSC, COAD, KIRC, LIHC and KIRP. The HNSC box plot shows higher SAE1 RNA expression in tumor versus normal tissue (log2 FC = +1.058, t-test p < 0.001).
This table shows molecular features associated with SAE1 in patient tissues and cancer cell lines. In patient samples, SAE1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SAE1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
