Q-omics provides the consensus-scored ARHGEF35 profile across patient tissues and cancer cell-line models. ARHGEF35 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, ARHGEF35 is differentially expressed in 11, with the highest sampling consensus in BLCA. Additionally, ARHGEF35 RNA expression shows 16,893 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight MESO, BLCA, and KIRP as cancer lineages where ARHGEF35 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 ARHGEF35 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARHGEF35 survival associations across molecular data types. ARHGEF35 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARHGEF35 RNA expression–survival associations across cancer types. High ARHGEF35 expression shows unfavorable associations in LAML and KIRP, but favorable associations in MESO, UVM, ACC and SARC. The MESO 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 MESO as the clearest survival context for ARHGEF35 RNA expression.
This table summarizes ARHGEF35 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 2. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ARHGEF35. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARHGEF35 shows lower tumor expression in THCA and KICH and higher tumor expression in BLCA, LUSC, CHOL and HNSC. The BLCA box plot shows higher ARHGEF35 RNA expression in tumor versus normal tissue (log2 FC = +1.934, t-test p = .003).
This table shows molecular features associated with ARHGEF35 in patient tissues and cancer cell lines. In patient samples, ARHGEF35 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, ARHGEF35 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 BLOOD_Leukemia and OVARY.
