Q-omics provides the consensus-scored KEL profile across patient tissues and cancer cell-line models. KEL expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, KEL is differentially expressed in 6, with the highest sampling consensus in THCA. Additionally, KEL RNA expression shows 15,147 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, THCA, and UVM as cancer lineages where KEL 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 KEL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KEL survival associations across molecular data types. KEL RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KEL RNA expression–survival associations across cancer types. High KEL expression shows unfavorable associations in ACC, THCA and UCEC, but favorable associations in BLCA, CESC and SCLC. The ACC 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 ACC as the clearest survival context for KEL RNA expression.
This table summarizes KEL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 3. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for KEL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KEL shows lower tumor expression in THCA, KICH, HNSC, PAAD and PRAD and higher tumor expression in LUAD. The THCA box plot shows higher KEL RNA expression in normal versus tumor tissue (log2 FC = −0.458, t-test p < 0.001).
This table shows molecular features associated with KEL in patient tissues and cancer cell lines. In patient samples, KEL shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, KEL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
