Q-omics provides the consensus-scored RIC8B profile across patient tissues and cancer cell-line models. RIC8B expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, RIC8B is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, RIC8B RNA expression shows 21,590 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SCLC, HNSC, and ACC as cancer lineages where RIC8B 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 RIC8B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RIC8B survival associations across molecular data types. RIC8B RNA expression shows survival associations in the most cancer types (26), followed by mutation status (7) 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 RIC8B RNA expression–survival associations across cancer types. High RIC8B expression shows unfavorable associations in ACC, LGG and LUSC, but favorable associations in SCLC, KIRC and PAAD. The SCLC 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 SCLC as the clearest survival context for RIC8B RNA expression.
This table summarizes RIC8B 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 RIC8B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RIC8B shows lower tumor expression in THCA, KICH and UCEC and higher tumor expression in HNSC, LIHC and COAD. The HNSC box plot shows higher RIC8B RNA expression in tumor versus normal tissue (log2 FC = +0.758, t-test p < 0.001).
This table shows molecular features associated with RIC8B in patient tissues and cancer cell lines. In patient samples, RIC8B shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, RIC8B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BLOOD_Leukemia.
