Q-omics provides the consensus-scored RGS8 profile across patient tissues and cancer cell-line models. RGS8 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, RGS8 is differentially expressed in 6, with the highest sampling consensus in THCA. Additionally, RGS8 RNA expression shows 12,537 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight SKCM, THCA, and THYM as cancer lineages where RGS8 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 RGS8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGS8 survival associations across molecular data types. RGS8 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RGS8 RNA expression–survival associations across cancer types. High RGS8 expression shows unfavorable associations in KIRC and UVM, but favorable associations in SKCM, UCS, ESCA and ACC. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify SKCM as the clearest survival context for RGS8 RNA expression.
This table summarizes RGS8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 1. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RGS8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGS8 shows lower tumor expression in THCA, KIRC, KIRP and COAD and higher tumor expression in KICH and BRCA. The THCA box plot shows higher RGS8 RNA expression in normal versus tumor tissue (log2 FC = −3.571, t-test p < 0.001).
This table shows molecular features associated with RGS8 in patient tissues and cancer cell lines. In patient samples, RGS8 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, RGS8 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 STOMACH and LUNG_SCLC.
