Q-omics provides the consensus-scored RFX2 profile across patient tissues and cancer cell-line models. RFX2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, RFX2 is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, RFX2 protein abundance shows 21,560 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight CESC, KICH, and UCEC as cancer lineages where RFX2 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 RFX2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RFX2 survival associations across molecular data types. RFX2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RFX2 RNA expression–survival associations across cancer types. High RFX2 expression shows unfavorable associations in MESO and LIHC, but favorable associations in CESC, ACC, KIRC and PAAD. The CESC 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 CESC as the clearest survival context for RFX2 RNA expression.
This table summarizes RFX2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 9. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RFX2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RFX2 shows lower tumor expression in KICH, LUAD and UCEC and higher tumor expression in KIRC, KIRP and HNSC. The KICH box plot shows higher RFX2 RNA expression in normal versus tumor tissue (log2 FC = −1.430, t-test p < 0.001).
This table shows molecular features associated with RFX2 in patient tissues and cancer cell lines. In patient samples, RFX2 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, RFX2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Lymphoma.
