Q-omics provides the consensus-scored RBP5 profile across patient tissues and cancer cell-line models. RBP5 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, RBP5 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, RBP5 protein abundance shows 24,243 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, KICH, and LSCC as cancer lineages where RBP5 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 RBP5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RBP5 survival associations across molecular data types. RBP5 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RBP5 RNA expression–survival associations across cancer types. High RBP5 expression shows unfavorable associations in LGG, but favorable associations in HNSC, KIRP, LUAD, KIRC and BLCA. The HNSC 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 HNSC as the clearest survival context for RBP5 RNA expression.
This table summarizes RBP5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 8. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RBP5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RBP5 shows lower tumor expression in KICH, KIRP, COAD, LIHC and THCA and higher tumor expression in KIRC. The KICH box plot shows higher RBP5 RNA expression in normal versus tumor tissue (log2 FC = −5.183, t-test p < 0.001).
This table shows molecular features associated with RBP5 in patient tissues and cancer cell lines. In patient samples, RBP5 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, RBP5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LUNG_SCLC.
