Q-omics provides the consensus-scored RPS4X profile across patient tissues and cancer cell-line models. RPS4X expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, RPS4X is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, RPS4X protein abundance shows 29,564 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, KIRC, and GBM as cancer lineages where RPS4X 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 RPS4X — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPS4X survival associations across molecular data types. RPS4X RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) 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 RPS4X RNA expression–survival associations across cancer types. High RPS4X expression shows unfavorable associations in KIRP, ACC and HNSC, but favorable associations in BRCA, UVM and LGG. 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 RPS4X RNA expression.
This table summarizes RPS4X 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 7. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RPS4X. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPS4X shows lower tumor expression in UCEC and higher tumor expression in KIRC, COAD, THCA, LIHC and CHOL. The KIRC box plot shows higher RPS4X RNA expression in tumor versus normal tissue (log2 FC = +0.713, t-test p < 0.001).
This table shows molecular features associated with RPS4X in patient tissues and cancer cell lines. In patient samples, RPS4X 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, RPS4X RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and UPPER_AERODIGESTIVE_TRACT.
