ras homolog family member QGenealiases: ARHQ · HEL-S-42 · RASL7A · TC10 · TC10A
Q-omics provides the consensus-scored RHOQ profile across patient tissues and cancer cell-line models. RHOQ expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, RHOQ is differentially expressed in 14, with the highest sampling consensus in LIHC. Additionally, RHOQ RNA expression shows 19,924 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and LIHC as cancer lineages where RHOQ 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 RHOQ — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RHOQ survival associations across molecular data types. RHOQ RNA expression shows survival associations in the most cancer types (27), followed by mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RHOQ RNA expression–survival associations across cancer types. High RHOQ expression shows unfavorable associations in UVM, LGG, LIHC, STAD and KICH, but favorable associations in LUAD. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for RHOQ RNA expression.
This table summarizes RHOQ tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 3. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RHOQ. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RHOQ shows lower tumor expression in LUAD, BLCA, BRCA and UCEC and higher tumor expression in LIHC and HNSC. The LIHC box plot shows higher RHOQ RNA expression in tumor versus normal tissue (log2 FC = +1.204, t-test p < 0.001).
This table shows molecular features associated with RHOQ in patient tissues and cancer cell lines. In patient samples, RHOQ shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, RHOQ 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 SOFT_TISSUE and BONE.
