Q-omics provides the consensus-scored IQGAP3 profile across patient tissues and cancer cell-line models. IQGAP3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, IQGAP3 is differentially expressed in 17, with the highest sampling consensus in BLCA. Additionally, IQGAP3 RNA expression shows 24,147 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, BLCA, and LSCC as cancer lineages where IQGAP3 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 IQGAP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IQGAP3 survival associations across molecular data types. IQGAP3 RNA expression shows survival associations in the most cancer types (28), 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 IQGAP3 RNA expression–survival associations across cancer types. High IQGAP3 expression shows unfavorable associations in ACC, KIRC, KIRP, MESO, LIHC and KICH. The ACC 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 ACC as the clearest survival context for IQGAP3 RNA expression.
This table summarizes IQGAP3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for IQGAP3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IQGAP3 shows higher tumor expression in BLCA, COAD, HNSC, KIRC, LUAD and KIRP. The BLCA box plot shows higher IQGAP3 RNA expression in tumor versus normal tissue (log2 FC = +3.041, t-test p < 0.001).
This table shows molecular features associated with IQGAP3 in patient tissues and cancer cell lines. In patient samples, IQGAP3 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, IQGAP3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SOFT_TISSUE.
