Q-omics provides the consensus-scored RPS6KA3 profile across patient tissues and cancer cell-line models. RPS6KA3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RPS6KA3 is differentially expressed in 10, with the highest sampling consensus in UCEC. Additionally, RPS6KA3 protein abundance shows 25,521 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, UCEC, and PDAC as cancer lineages where RPS6KA3 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 RPS6KA3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPS6KA3 survival associations across molecular data types. RPS6KA3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPS6KA3 RNA expression–survival associations across cancer types. High RPS6KA3 expression shows unfavorable associations in LGG, ACC and LIHC, but favorable associations in KIRC, SKCM and READ. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for RPS6KA3 RNA expression.
This table summarizes RPS6KA3 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 LUSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for RPS6KA3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPS6KA3 shows lower tumor expression in UCEC, BRCA and LUSC and higher tumor expression in LIHC, STAD and ESCA. The UCEC box plot shows higher RPS6KA3 RNA expression in normal versus tumor tissue (log2 FC = −1.293, t-test p < 0.001).
This table shows molecular features associated with RPS6KA3 in patient tissues and cancer cell lines. In patient samples, RPS6KA3 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, RPS6KA3 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 UPPER_AERODIGESTIVE_TRACT and BONE.
