Q-omics provides the consensus-scored RPSAP17 profile across patient tissues and cancer cell-line models. RPSAP17 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, RPSAP17 is differentially expressed in 7, with the highest sampling consensus in LIHC. Additionally, RPSAP17 RNA expression shows 14,416 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight COAD, LIHC, and ACC as cancer lineages where RPSAP17 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 RPSAP17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPSAP17 survival associations across molecular data types. RPSAP17 RNA expression shows survival associations in the most cancer types (25). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPSAP17 RNA expression–survival associations across cancer types. High RPSAP17 expression shows unfavorable associations in ACC and KICH, but favorable associations in COAD, SKCM, READ and UVM. The COAD 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 COAD as the clearest survival context for RPSAP17 RNA expression.
This table summarizes RPSAP17 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for RPSAP17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPSAP17 shows lower tumor expression in HNSC and higher tumor expression in LIHC, COAD, KIRC, THCA and KIRP. The LIHC box plot shows higher RPSAP17 RNA expression in tumor versus normal tissue (log2 FC = +0.172, t-test p < 0.001).
This table shows molecular features associated with RPSAP17 in patient tissues and cancer cell lines. In patient samples, RPSAP17 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set.
