Q-omics provides the consensus-scored KRCC1 profile across patient tissues and cancer cell-line models. KRCC1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, KRCC1 is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, KRCC1 RNA expression shows 19,278 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight KIRC, COAD, and KIRP as cancer lineages where KRCC1 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 KRCC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KRCC1 survival associations across molecular data types. KRCC1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) 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 KRCC1 RNA expression–survival associations across cancer types. High KRCC1 expression shows unfavorable associations in ACC and LGG, but favorable associations in KIRC, LUSC, HNSC and SKCM. 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 KRCC1 RNA expression.
This table summarizes KRCC1 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 THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for KRCC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KRCC1 shows lower tumor expression in COAD, THCA, KICH, UCEC, READ and LUSC. The COAD box plot shows higher KRCC1 RNA expression in normal versus tumor tissue (log2 FC = −1.527, t-test p < 0.001).
This table shows molecular features associated with KRCC1 in patient tissues and cancer cell lines. In patient samples, KRCC1 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, KRCC1 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 SOFT_TISSUE and BLOOD_Leukemia.
