Q-omics provides the consensus-scored RPS18 profile across patient tissues and cancer cell-line models. RPS18 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, RPS18 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, RPS18 protein abundance shows 27,212 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, KIRC, and GBM as cancer lineages where RPS18 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 RPS18 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPS18 survival associations across molecular data types. RPS18 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPS18 RNA expression–survival associations across cancer types. High RPS18 expression shows unfavorable associations in KIRP, ACC, LIHC and SARC, but favorable associations in THYM and UVM. The KIRP 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 KIRP as the clearest survival context for RPS18 RNA expression.
This table summarizes RPS18 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RPS18. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPS18 shows lower tumor expression in KICH and higher tumor expression in KIRC, KIRP, LIHC, COAD and CHOL. The KIRC box plot shows higher RPS18 RNA expression in tumor versus normal tissue (log2 FC = +1.018, t-test p < 0.001).
This table shows molecular features associated with RPS18 in patient tissues and cancer cell lines. In patient samples, RPS18 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, RPS18 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
