Q-omics provides the consensus-scored RFX1 profile across patient tissues and cancer cell-line models. RFX1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, RFX1 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, RFX1 protein abundance shows 31,391 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, and LSCC as cancer lineages where RFX1 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 RFX1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RFX1 survival associations across molecular data types. RFX1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) 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 RFX1 RNA expression–survival associations across cancer types. High RFX1 expression shows unfavorable associations in ACC and LGG, but favorable associations in HNSC, SCLC, THYM and PAAD. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for RFX1 RNA expression.
This table summarizes RFX1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RFX1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RFX1 shows higher tumor expression in HNSC, COAD, LIHC, STAD, KIRC and KIRP. The HNSC box plot shows higher RFX1 RNA expression in tumor versus normal tissue (log2 FC = +0.663, t-test p < 0.001).
This table shows molecular features associated with RFX1 in patient tissues and cancer cell lines. In patient samples, RFX1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, RFX1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and UPPER_AERODIGESTIVE_TRACT.
