Q-omics provides the consensus-scored RSF1 profile across patient tissues and cancer cell-line models. RSF1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RSF1 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, RSF1 protein abundance shows 30,062 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where RSF1 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 RSF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RSF1 survival associations across molecular data types. RSF1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (9) and mass-spec protein abundance (13). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RSF1 RNA expression–survival associations across cancer types. High RSF1 expression shows unfavorable associations in ACC and PAAD, but favorable associations in KIRC, UCS, SCLC and BRCA. 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 RSF1 RNA expression.
This table summarizes RSF1 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 6. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RSF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RSF1 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, STAD, LUSC and BRCA. The HNSC box plot shows higher RSF1 RNA expression in tumor versus normal tissue (log2 FC = +0.841, t-test p < 0.001).
This table shows molecular features associated with RSF1 in patient tissues and cancer cell lines. In patient samples, RSF1 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, RSF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
