Q-omics provides the consensus-scored RPL8 profile across patient tissues and cancer cell-line models. RPL8 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, RPL8 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, RPL8 protein abundance shows 25,729 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, COAD, and HNSC as cancer lineages where RPL8 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 RPL8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPL8 survival associations across molecular data types. RPL8 RNA expression shows survival associations in the most cancer types (27), 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 RPL8 RNA expression–survival associations across cancer types. High RPL8 expression shows unfavorable associations in ACC, LIHC, KIRP, CESC and THCA, but favorable associations in LGG. 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 RPL8 RNA expression.
This table summarizes RPL8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, 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 RPL8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPL8 shows higher tumor expression in COAD, KIRC, KIRP, LIHC, LUSC and HNSC. The COAD box plot shows higher RPL8 RNA expression in tumor versus normal tissue (log2 FC = +1.565, t-test p < 0.001).
This table shows molecular features associated with RPL8 in patient tissues and cancer cell lines. In patient samples, RPL8 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, RPL8 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 BONE.
