Q-omics provides the consensus-scored IQCF2 profile across patient tissues and cancer cell-line models. IQCF2 expression is associated with patient survival in 12 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, IQCF2 is differentially expressed in 1, with the highest sampling consensus in HNSC. Additionally, IQCF2 RNA expression shows 6,252 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight READ, HNSC, and STAD as cancer lineages where IQCF2 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 IQCF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IQCF2 survival associations across molecular data types. IQCF2 RNA expression shows survival associations in the most cancer types (12), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IQCF2 RNA expression–survival associations across cancer types. High IQCF2 expression shows unfavorable associations in READ, ACC and THYM, but favorable associations in OV, LAML and ESCA. The READ 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 READ as the clearest survival context for IQCF2 RNA expression.
This table summarizes IQCF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for IQCF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IQCF2 shows higher tumor expression in HNSC. The HNSC box plot shows higher IQCF2 RNA expression in tumor versus normal tissue (log2 FC = +0.079, t-test p = .025).
This table shows molecular features associated with IQCF2 in patient tissues and cancer cell lines. In patient samples, IQCF2 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, IQCF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
