regulator of G protein signaling 3Genealiases: C2PA · RGP3
Q-omics provides the consensus-scored RGS3 profile across patient tissues and cancer cell-line models. RGS3 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, RGS3 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, RGS3 protein abundance shows 20,279 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KICH, HNSC, and LSCC as cancer lineages where RGS3 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 RGS3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGS3 survival associations across molecular data types. RGS3 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (9) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RGS3 RNA expression–survival associations across cancer types. High RGS3 expression shows unfavorable associations in KICH, LUSC, BRCA, LGG, PAAD and HNSC. The KICH 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 KICH as the clearest survival context for RGS3 RNA expression.
This table summarizes RGS3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RGS3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGS3 shows lower tumor expression in LUSC, KICH and BRCA and higher tumor expression in HNSC, THCA and STAD. The HNSC box plot shows higher RGS3 RNA expression in tumor versus normal tissue (log2 FC = +1.193, t-test p < 0.001).
This table shows molecular features associated with RGS3 in patient tissues and cancer cell lines. In patient samples, RGS3 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, RGS3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and CNS.
