Q-omics provides the consensus-scored RPL13 profile across patient tissues and cancer cell-line models. RPL13 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RPL13 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, RPL13 protein abundance shows 19,727 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, KIRC, and HNSC as cancer lineages where RPL13 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 RPL13 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPL13 survival associations across molecular data types. RPL13 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (6) 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 RPL13 RNA expression–survival associations across cancer types. High RPL13 expression shows unfavorable associations in ACC, HNSC and BLCA, but favorable associations in UVM, LGG and UCEC. 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 RPL13 RNA expression.
This table summarizes RPL13 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RPL13. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPL13 shows lower tumor expression in BRCA and higher tumor expression in KIRC, KIRP, COAD, LIHC and THCA. The KIRC box plot shows higher RPL13 RNA expression in tumor versus normal tissue (log2 FC = +1.085, t-test p < 0.001).
This table shows molecular features associated with RPL13 in patient tissues and cancer cell lines. In patient samples, RPL13 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, RPL13 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
