Q-omics provides the consensus-scored ARHGEF37 profile across patient tissues and cancer cell-line models. ARHGEF37 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ARHGEF37 is differentially expressed in 15, with the highest sampling consensus in THCA. Additionally, ARHGEF37 protein abundance shows 25,143 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, THCA, and LUAD as cancer lineages where ARHGEF37 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 ARHGEF37 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF37 survival associations across molecular data types. ARHGEF37 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARHGEF37 RNA expression–survival associations across cancer types. High ARHGEF37 expression shows unfavorable associations in LIHC and THCA, but favorable associations in KIRC, UVM, SARC and KIRP. 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 ARHGEF37 RNA expression.
This table summarizes ARHGEF37 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ARHGEF37. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF37 shows lower tumor expression in THCA, STAD, BLCA, COAD, LUAD and KIRP. The THCA box plot shows higher ARHGEF37 RNA expression in normal versus tumor tissue (log2 FC = −1.632, t-test p < 0.001).
This table shows molecular features associated with ARHGEF37 in patient tissues and cancer cell lines. In patient samples, ARHGEF37 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, ARHGEF37 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and OVARY.
