Q-omics provides the consensus-scored ARHGEF3 profile across patient tissues and cancer cell-line models. ARHGEF3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, ARHGEF3 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, ARHGEF3 RNA expression shows 18,896 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCEC, KIRC, and UVM as cancer lineages where ARHGEF3 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 ARHGEF3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF3 survival associations across molecular data types. ARHGEF3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 ARHGEF3 RNA expression–survival associations across cancer types. High ARHGEF3 expression shows unfavorable associations in LGG, but favorable associations in UCEC, SKCM, BRCA, KIRC and HNSC. The UCEC 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 UCEC as the clearest survival context for ARHGEF3 RNA expression.
This table summarizes ARHGEF3 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 3. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ARHGEF3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF3 shows lower tumor expression in KIRC, KICH, LUSC, LUAD and THCA and higher tumor expression in LIHC. The KIRC box plot shows higher ARHGEF3 RNA expression in normal versus tumor tissue (log2 FC = −0.976, t-test p < 0.001).
This table shows molecular features associated with ARHGEF3 in patient tissues and cancer cell lines. In patient samples, ARHGEF3 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, ARHGEF3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in OVARY and LUNG_NSCLC_LUAD.
