Q-omics provides the consensus-scored RPS6KB1 profile across patient tissues and cancer cell-line models. RPS6KB1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, RPS6KB1 is differentially expressed in 16, with the highest sampling consensus in KIRP. Additionally, RPS6KB1 protein abundance shows 27,247 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, and GBM as cancer lineages where RPS6KB1 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 RPS6KB1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPS6KB1 survival associations across molecular data types. RPS6KB1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPS6KB1 RNA expression–survival associations across cancer types. High RPS6KB1 expression shows unfavorable associations in KIRP, LIHC, UVM, KICH, ACC and CESC. 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 RPS6KB1 RNA expression.
This table summarizes RPS6KB1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 10. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RPS6KB1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPS6KB1 shows lower tumor expression in THCA and KICH and higher tumor expression in KIRP, KIRC, LUAD and LIHC. The KIRP box plot shows higher RPS6KB1 RNA expression in tumor versus normal tissue (log2 FC = +0.607, t-test p < 0.001).
This table shows molecular features associated with RPS6KB1 in patient tissues and cancer cell lines. In patient samples, RPS6KB1 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, RPS6KB1 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 LUNG_NSCLC_LUAD and UPPER_AERODIGESTIVE_TRACT.
