Q-omics provides the consensus-scored SIAE profile across patient tissues and cancer cell-line models. SIAE expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SIAE is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, SIAE protein abundance shows 22,698 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, COAD, and GBM as cancer lineages where SIAE 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 SIAE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SIAE survival associations across molecular data types. SIAE RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 SIAE RNA expression–survival associations across cancer types. High SIAE expression shows unfavorable associations in BLCA, UVM, CESC and LUSC, but favorable associations in KIRC and KIRP. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for SIAE RNA expression.
This table summarizes SIAE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SIAE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SIAE shows lower tumor expression in COAD, HNSC, KIRC, LUSC and THCA and higher tumor expression in STAD. The COAD box plot shows higher SIAE RNA expression in normal versus tumor tissue (log2 FC = −1.917, t-test p < 0.001).
This table shows molecular features associated with SIAE in patient tissues and cancer cell lines. In patient samples, SIAE 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, SIAE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
