Q-omics provides the consensus-scored ARHGEF28 profile across patient tissues and cancer cell-line models. ARHGEF28 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, ARHGEF28 is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, ARHGEF28 RNA expression shows 18,297 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight KIRC, THCA, and KIRP as cancer lineages where ARHGEF28 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 ARHGEF28 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF28 survival associations across molecular data types. ARHGEF28 RNA expression shows survival associations in the most cancer types (23), 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 ARHGEF28 RNA expression–survival associations across cancer types. High ARHGEF28 expression shows unfavorable associations in UVM, KIRP, THCA and LGG, but favorable associations in KIRC and READ. 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 ARHGEF28 RNA expression.
This table summarizes ARHGEF28 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ARHGEF28. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF28 shows lower tumor expression in THCA, UCEC and BRCA and higher tumor expression in COAD, LIHC and CHOL. The THCA box plot shows higher ARHGEF28 RNA expression in normal versus tumor tissue (log2 FC = −2.230, t-test p < 0.001).
This table shows molecular features associated with ARHGEF28 in patient tissues and cancer cell lines. In patient samples, ARHGEF28 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, ARHGEF28 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
