Q-omics provides the consensus-scored ARHGAP17 profile across patient tissues and cancer cell-line models. ARHGAP17 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, ARHGAP17 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, ARHGAP17 protein abundance shows 26,026 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight BLCA, KIRC, and LSCC as cancer lineages where ARHGAP17 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 ARHGAP17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGAP17 survival associations across molecular data types. ARHGAP17 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (7) 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 ARHGAP17 RNA expression–survival associations across cancer types. High ARHGAP17 expression shows unfavorable associations in BLCA, LGG, LAML, LIHC and KIRP, but favorable associations in KIRC. The BLCA 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 BLCA as the clearest survival context for ARHGAP17 RNA expression.
This table summarizes ARHGAP17 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ARHGAP17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGAP17 shows lower tumor expression in COAD and LUSC and higher tumor expression in KIRC, LIHC, HNSC and KIRP. The KIRC box plot shows higher ARHGAP17 RNA expression in tumor versus normal tissue (log2 FC = +0.847, t-test p < 0.001).
This table shows molecular features associated with ARHGAP17 in patient tissues and cancer cell lines. In patient samples, ARHGAP17 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ARHGAP17 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and CNS.
