Q-omics provides the consensus-scored RPS17 profile across patient tissues and cancer cell-line models. RPS17 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RPS17 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, RPS17 RNA expression shows 18,831 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where RPS17 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 RPS17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPS17 survival associations across molecular data types. RPS17 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPS17 RNA expression–survival associations across cancer types. High RPS17 expression shows unfavorable associations in ACC, KIRP, LUAD, COAD, HNSC and PAAD. 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 RPS17 RNA expression.
This table summarizes RPS17 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for RPS17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPS17 shows lower tumor expression in BRCA and higher tumor expression in KIRC, LIHC, KIRP, CHOL and COAD. The KIRC box plot shows higher RPS17 RNA expression in tumor versus normal tissue (log2 FC = +0.644, t-test p < 0.001).
This table shows molecular features associated with RPS17 in patient tissues and cancer cell lines. In patient samples, RPS17 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, RPS17 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
