Q-omics provides the consensus-scored RFC1 profile across patient tissues and cancer cell-line models. RFC1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RFC1 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, RFC1 protein abundance shows 32,713 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where RFC1 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 RFC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RFC1 survival associations across molecular data types. RFC1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RFC1 RNA expression–survival associations across cancer types. High RFC1 expression shows unfavorable associations in LIHC, KICH and ACC, but favorable associations in KIRC, UCS 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 RFC1 RNA expression.
This table summarizes RFC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 10. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for RFC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RFC1 shows lower tumor expression in THCA and UCEC and higher tumor expression in HNSC, LIHC, CHOL and STAD. The HNSC box plot shows higher RFC1 RNA expression in tumor versus normal tissue (log2 FC = +0.729, t-test p < 0.001).
This table shows molecular features associated with RFC1 in patient tissues and cancer cell lines. In patient samples, RFC1 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, RFC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
