Q-omics provides the consensus-scored RGS18 profile across patient tissues and cancer cell-line models. RGS18 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, RGS18 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, RGS18 RNA expression shows 18,854 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SKCM, KIRC, and LSCC as cancer lineages where RGS18 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 RGS18 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGS18 survival associations across molecular data types. RGS18 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RGS18 RNA expression–survival associations across cancer types. High RGS18 expression shows unfavorable associations in LGG and UVM, but favorable associations in SKCM, HNSC, CESC and KIRC. 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 RGS18 RNA expression.
This table summarizes RGS18 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 KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RGS18. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGS18 shows lower tumor expression in LUSC, LUAD and COAD and higher tumor expression in KIRC, STAD and HNSC. The KIRC box plot shows higher RGS18 RNA expression in tumor versus normal tissue (log2 FC = +1.713, t-test p < 0.001).
This table shows molecular features associated with RGS18 in patient tissues and cancer cell lines. In patient samples, RGS18 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, RGS18 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and URINARY_TRACT.
