ribosomal protein S4X pseudogene 16Genealiases: RPS4P16 · RPS4X_8_1313
Q-omics provides the consensus-scored RPS4XP16 profile across patient tissues and cancer cell-line models. RPS4XP16 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RPS4XP16 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, RPS4XP16 RNA expression shows 18,564 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, HNSC, and UVM as cancer lineages where RPS4XP16 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 RPS4XP16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPS4XP16 survival associations across molecular data types. RPS4XP16 RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPS4XP16 RNA expression–survival associations across cancer types. High RPS4XP16 expression shows unfavorable associations in ACC, UVM, LIHC and OV, but favorable associations in GBM and UCS. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify ACC as the clearest survival context for RPS4XP16 RNA expression.
This table summarizes RPS4XP16 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for RPS4XP16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPS4XP16 shows lower tumor expression in KICH and higher tumor expression in HNSC, COAD, KIRC, LUSC and LUAD. The HNSC box plot shows higher RPS4XP16 RNA expression in tumor versus normal tissue (log2 FC = +0.555, t-test p < 0.001).
This table shows molecular features associated with RPS4XP16 in patient tissues and cancer cell lines. In patient samples, RPS4XP16 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set.
