Q-omics provides the consensus-scored RPS6 profile across patient tissues and cancer cell-line models. RPS6 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, RPS6 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, RPS6 protein abundance shows 28,066 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, KIRC, and PDAC as cancer lineages where RPS6 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 RPS6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPS6 survival associations across molecular data types. RPS6 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPS6 RNA expression–survival associations across cancer types. High RPS6 expression shows unfavorable associations in ACC, LIHC, KICH and HNSC, but favorable associations in LGG and SKCM. 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 RPS6 RNA expression.
This table summarizes RPS6 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 KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RPS6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPS6 shows lower tumor expression in BRCA and higher tumor expression in KIRC, COAD, LIHC, KIRP and CHOL. The KIRC box plot shows higher RPS6 RNA expression in tumor versus normal tissue (log2 FC = +0.604, t-test p < 0.001).
This table shows molecular features associated with RPS6 in patient tissues and cancer cell lines. In patient samples, RPS6 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, RPS6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
