Q-omics provides the consensus-scored ARHGEF25 profile across patient tissues and cancer cell-line models. ARHGEF25 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ARHGEF25 is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, ARHGEF25 RNA expression shows 19,300 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, BLCA, and UVM as cancer lineages where ARHGEF25 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 ARHGEF25 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF25 survival associations across molecular data types. ARHGEF25 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARHGEF25 RNA expression–survival associations across cancer types. High ARHGEF25 expression shows unfavorable associations in ACC, UVM, KIRC, BLCA, COAD and THCA. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for ARHGEF25 RNA expression.
This table summarizes ARHGEF25 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 4. The strongest signals are observed in BLCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ARHGEF25. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF25 shows lower tumor expression in BLCA, KICH, COAD, UCEC and BRCA and higher tumor expression in HNSC. The BLCA box plot shows higher ARHGEF25 RNA expression in normal versus tumor tissue (log2 FC = −2.041, t-test p < 0.001).
This table shows molecular features associated with ARHGEF25 in patient tissues and cancer cell lines. In patient samples, ARHGEF25 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, ARHGEF25 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BONE and OVARY.
