Q-omics provides the consensus-scored RHOXF2B profile across patient tissues and cancer cell-line models. RHOXF2B expression is associated with patient survival in 8 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, RHOXF2B is differentially expressed in 2, with the highest sampling consensus in KICH. Additionally, RHOXF2B RNA expression shows 3,460 significant pathway-activity associations, with the highest sampling consensus in LIHC. Together, these results highlight HNSC, KICH, and LIHC as cancer lineages where RHOXF2B 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 RHOXF2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RHOXF2B survival associations across molecular data types. RHOXF2B RNA expression shows survival associations in the most cancer types (8), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RHOXF2B RNA expression–survival associations across cancer types. High RHOXF2B expression shows unfavorable associations in HNSC, LIHC, UCS, UCEC, KICH and KIRP. The HNSC 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 HNSC as the clearest survival context for RHOXF2B RNA expression.
This table summarizes RHOXF2B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for RHOXF2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RHOXF2B shows higher tumor expression in KICH and LIHC. The KICH box plot shows higher RHOXF2B RNA expression in tumor versus normal tissue (log2 FC = +0.187, t-test p = .026).
This table shows molecular features associated with RHOXF2B in patient tissues and cancer cell lines. In patient samples, RHOXF2B shows the broadest associations at the RNA and protein expression levels, with LIHC recurring as the lineage with the largest associated feature set. In cancer cell lines, RHOXF2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
