Q-omics provides the consensus-scored ARHGEF4 profile across patient tissues and cancer cell-line models. ARHGEF4 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, ARHGEF4 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, ARHGEF4 RNA expression shows 17,706 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight BLCA, HNSC, and LSCC as cancer lineages where ARHGEF4 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 ARHGEF4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF4 survival associations across molecular data types. ARHGEF4 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (11) 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 ARHGEF4 RNA expression–survival associations across cancer types. High ARHGEF4 expression shows unfavorable associations in BLCA, SKCM, ACC, LUAD and THCA, but favorable associations in READ. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify BLCA as the clearest survival context for ARHGEF4 RNA expression.
This table summarizes ARHGEF4 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 HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ARHGEF4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF4 shows lower tumor expression in THCA, UCEC, BRCA and LUAD and higher tumor expression in HNSC and LUSC. The HNSC box plot shows higher ARHGEF4 RNA expression in tumor versus normal tissue (log2 FC = +1.053, t-test p < 0.001).
This table shows molecular features associated with ARHGEF4 in patient tissues and cancer cell lines. In patient samples, ARHGEF4 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, ARHGEF4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LARGE_INTESTINE.
