Q-omics provides the consensus-scored ARHGEF33 profile across patient tissues and cancer cell-line models. ARHGEF33 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ARHGEF33 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, ARHGEF33 RNA expression shows 19,841 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, THCA, and THYM as cancer lineages where ARHGEF33 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 ARHGEF33 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF33 survival associations across molecular data types. ARHGEF33 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARHGEF33 RNA expression–survival associations across cancer types. High ARHGEF33 expression shows favorable associations in HNSC, MESO, CESC, KIRP, UCS and SKCM. The HNSC 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 HNSC as the clearest survival context for ARHGEF33 RNA expression.
This table summarizes ARHGEF33 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for ARHGEF33. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF33 shows lower tumor expression in THCA, KICH, UCEC, BRCA and KIRP and higher tumor expression in CHOL. The THCA box plot shows higher ARHGEF33 RNA expression in normal versus tumor tissue (log2 FC = −0.687, t-test p < 0.001).
This table shows molecular features associated with ARHGEF33 in patient tissues and cancer cell lines. In patient samples, ARHGEF33 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, ARHGEF33 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
