Q-omics provides the consensus-scored KERA profile across patient tissues and cancer cell-line models. KERA expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, KERA is differentially expressed in 6, with the highest sampling consensus in KIRC. Additionally, KERA RNA expression shows 13,473 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRP, KIRC, and THYM as cancer lineages where KERA 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 KERA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KERA survival associations across molecular data types. KERA RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KERA RNA expression–survival associations across cancer types. High KERA expression shows unfavorable associations in KIRP, KICH, UVM and LGG, but favorable associations in UCS and BRCA. The KIRP 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 KIRP as the clearest survival context for KERA RNA expression.
This table summarizes KERA 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 4. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for KERA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KERA shows lower tumor expression in READ, PRAD and STAD and higher tumor expression in KIRC, CHOL and KIRP. The KIRC box plot shows higher KERA RNA expression in tumor versus normal tissue (log2 FC = +0.114, t-test p < 0.001).
This table shows molecular features associated with KERA in patient tissues and cancer cell lines. In patient samples, KERA shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, KERA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and LARGE_INTESTINE.
