Q-omics provides the consensus-scored ARHGEF5 profile across patient tissues and cancer cell-line models. ARHGEF5 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ARHGEF5 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, ARHGEF5 protein abundance shows 29,809 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, THCA, and LSCC as cancer lineages where ARHGEF5 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 ARHGEF5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF5 survival associations across molecular data types. ARHGEF5 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARHGEF5 RNA expression–survival associations across cancer types. High ARHGEF5 expression shows unfavorable associations in LAML and LGG, but favorable associations in KIRC, MESO, UVM and ACC. The KIRC 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 KIRC as the clearest survival context for ARHGEF5 RNA expression.
This table summarizes ARHGEF5 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 9. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ARHGEF5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF5 shows lower tumor expression in THCA and KIRC and higher tumor expression in HNSC, BLCA, LUSC and CHOL. The THCA box plot shows higher ARHGEF5 RNA expression in normal versus tumor tissue (log2 FC = −0.760, t-test p < 0.001).
This table shows molecular features associated with ARHGEF5 in patient tissues and cancer cell lines. In patient samples, ARHGEF5 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, ARHGEF5 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 SKIN and OVARY.
