regulator of chromosome condensation 1Genealiases: CHC1 · IIAAN · RCC1-I
Q-omics provides the consensus-scored RCC1 profile across patient tissues and cancer cell-line models. RCC1 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, RCC1 is differentially expressed in 17, with the highest sampling consensus in BLCA. Additionally, RCC1 protein abundance shows 24,042 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, BLCA, and GBM as cancer lineages where RCC1 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 RCC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RCC1 survival associations across molecular data types. RCC1 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RCC1 RNA expression–survival associations across cancer types. High RCC1 expression shows unfavorable associations in KIRP, ACC, LIHC, KICH, LGG and SARC. 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 RCC1 RNA expression.
This table summarizes RCC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RCC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RCC1 shows higher tumor expression in BLCA, LUAD, KIRP, COAD, KIRC and HNSC. The BLCA box plot shows higher RCC1 RNA expression in tumor versus normal tissue (log2 FC = +2.065, t-test p < 0.001).
This table shows molecular features associated with RCC1 in patient tissues and cancer cell lines. In patient samples, RCC1 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, RCC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
