regulator of G protein signaling 9Genealiases: PERRS · PERRS1 · RGS9L
Q-omics provides the consensus-scored RGS9 profile across patient tissues and cancer cell-line models. RGS9 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, RGS9 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, RGS9 RNA expression shows 18,854 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SKCM, KICH, and LSCC as cancer lineages where RGS9 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 RGS9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGS9 survival associations across molecular data types. RGS9 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) 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 RGS9 RNA expression–survival associations across cancer types. High RGS9 expression shows unfavorable associations in UCEC, but favorable associations in SKCM, PAAD, BRCA, KIRC and LGG. The SKCM 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 SKCM as the clearest survival context for RGS9 RNA expression.
This table summarizes RGS9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for RGS9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGS9 shows lower tumor expression in KICH, LUAD, COAD, BLCA, LUSC and UCEC. The KICH box plot shows higher RGS9 RNA expression in normal versus tumor tissue (log2 FC = −2.085, t-test p < 0.001).
This table shows molecular features associated with RGS9 in patient tissues and cancer cell lines. In patient samples, RGS9 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, RGS9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
