Q-omics provides the consensus-scored RPLP0 profile across patient tissues and cancer cell-line models. RPLP0 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RPLP0 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, RPLP0 protein abundance shows 33,672 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where RPLP0 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 RPLP0 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPLP0 survival associations across molecular data types. RPLP0 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) 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 RPLP0 RNA expression–survival associations across cancer types. High RPLP0 expression shows unfavorable associations in ACC, KIRP, LIHC, KICH and LUAD, but favorable associations in BRCA. The ACC 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 ACC as the clearest survival context for RPLP0 RNA expression.
This table summarizes RPLP0 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 9. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RPLP0. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPLP0 shows higher tumor expression in KIRC, KIRP, COAD, LIHC, LUSC and CHOL. The KIRC box plot shows higher RPLP0 RNA expression in tumor versus normal tissue (log2 FC = +1.232, t-test p < 0.001).
This table shows molecular features associated with RPLP0 in patient tissues and cancer cell lines. In patient samples, RPLP0 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, RPLP0 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
