Q-omics provides the consensus-scored KRBA1 profile across patient tissues and cancer cell-line models. KRBA1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, KRBA1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, KRBA1 RNA expression shows 19,324 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, KIRC, and ACC as cancer lineages where KRBA1 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 KRBA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KRBA1 survival associations across molecular data types. KRBA1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KRBA1 RNA expression–survival associations across cancer types. High KRBA1 expression shows unfavorable associations in LIHC and LGG, but favorable associations in UVM, KIRC, ESCA and PAAD. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .003). Together, the overview and detailed table identify UVM as the clearest survival context for KRBA1 RNA expression.
This table summarizes KRBA1 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 2. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for KRBA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KRBA1 shows lower tumor expression in COAD and higher tumor expression in KIRC, HNSC, LIHC, CHOL and LUSC. The KIRC box plot shows higher KRBA1 RNA expression in tumor versus normal tissue (log2 FC = +2.553, t-test p < 0.001).
This table shows molecular features associated with KRBA1 in patient tissues and cancer cell lines. In patient samples, KRBA1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, KRBA1 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 BONE and LARGE_INTESTINE.
