Q-omics provides the consensus-scored ARHGEF9 profile across patient tissues and cancer cell-line models. ARHGEF9 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ARHGEF9 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, ARHGEF9 RNA expression shows 20,959 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, COAD, and UVM as cancer lineages where ARHGEF9 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 ARHGEF9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF9 survival associations across molecular data types. ARHGEF9 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARHGEF9 RNA expression–survival associations across cancer types. High ARHGEF9 expression shows unfavorable associations in KICH, UVM and LUSC, but favorable associations in KIRC, SKCM and PAAD. 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 ARHGEF9 RNA expression.
This table summarizes ARHGEF9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for ARHGEF9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF9 shows lower tumor expression in COAD, BLCA, THCA, UCEC and KICH and higher tumor expression in LIHC. The COAD box plot shows higher ARHGEF9 RNA expression in normal versus tumor tissue (log2 FC = −0.665, t-test p < 0.001).
This table shows molecular features associated with ARHGEF9 in patient tissues and cancer cell lines. In patient samples, ARHGEF9 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, ARHGEF9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
