regulator of G protein signaling 17Genealiases: RGS-17 · RGSZ2 · hRGS17
Q-omics provides the consensus-scored RGS17 profile across patient tissues and cancer cell-line models. RGS17 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RGS17 is differentially expressed in 12, with the highest sampling consensus in LUAD. Additionally, RGS17 RNA expression shows 19,815 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, LUAD, and UVM as cancer lineages where RGS17 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 RGS17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGS17 survival associations across molecular data types. RGS17 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RGS17 RNA expression–survival associations across cancer types. High RGS17 expression shows unfavorable associations in KIRC, KIRP, STAD, LIHC and BLCA, but favorable associations in READ. The KIRC 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 KIRC as the clearest survival context for RGS17 RNA expression.
This table summarizes RGS17 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 2. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RGS17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGS17 shows lower tumor expression in THCA and higher tumor expression in LUAD, KIRP, LIHC, BLCA and LUSC. The LUAD box plot shows higher RGS17 RNA expression in tumor versus normal tissue (log2 FC = +1.849, t-test p < 0.001).
This table shows molecular features associated with RGS17 in patient tissues and cancer cell lines. In patient samples, RGS17 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, RGS17 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 LARGE_INTESTINE and BLOOD_Leukemia.
