Q-omics provides the consensus-scored RYBP profile across patient tissues and cancer cell-line models. RYBP expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RYBP is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, RYBP RNA expression shows 20,558 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight KIRC, KICH, and KIRP as cancer lineages where RYBP 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 RYBP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RYBP survival associations across molecular data types. RYBP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RYBP RNA expression–survival associations across cancer types. High RYBP expression shows unfavorable associations in ACC, LGG and KICH, but favorable associations in KIRC, BRCA 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 RYBP RNA expression.
This table summarizes RYBP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in LUSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for RYBP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RYBP shows lower tumor expression in KICH, LUSC, LUAD and KIRC and higher tumor expression in HNSC and BRCA. The KICH box plot shows higher RYBP RNA expression in normal versus tumor tissue (log2 FC = −0.957, t-test p < 0.001).
This table shows molecular features associated with RYBP in patient tissues and cancer cell lines. In patient samples, RYBP shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, RYBP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and OVARY.
