Q-omics provides the consensus-scored ARHGEF40 profile across patient tissues and cancer cell-line models. ARHGEF40 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, ARHGEF40 is differentially expressed in 13, with the highest sampling consensus in LUAD. Additionally, ARHGEF40 protein abundance shows 20,054 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight LUSC, and LUAD as cancer lineages where ARHGEF40 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 ARHGEF40 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF40 survival associations across molecular data types. ARHGEF40 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (12) 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 ARHGEF40 RNA expression–survival associations across cancer types. High ARHGEF40 expression shows unfavorable associations in LUSC, ACC, UVM, HNSC and LIHC, but favorable associations in KIRC. The LUSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify LUSC as the clearest survival context for ARHGEF40 RNA expression.
This table summarizes ARHGEF40 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 4. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ARHGEF40. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF40 shows lower tumor expression in LUAD, THCA, KICH and LUSC and higher tumor expression in HNSC and LIHC. The LUAD box plot shows higher ARHGEF40 RNA expression in normal versus tumor tissue (log2 FC = −0.605, t-test p < 0.001).
This table shows molecular features associated with ARHGEF40 in patient tissues and cancer cell lines. In patient samples, ARHGEF40 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, ARHGEF40 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 STOMACH and BLOOD_Leukemia.
