Q-omics provides the consensus-scored IQCF6 profile across patient tissues and cancer cell-line models. IQCF6 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, IQCF6 is differentially expressed in 6, with the highest sampling consensus in KIRC. Additionally, IQCF6 RNA expression shows 6,694 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight LIHC, KIRC, and STAD as cancer lineages where IQCF6 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 IQCF6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IQCF6 survival associations across molecular data types. IQCF6 RNA expression shows survival associations in the most cancer types (18). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IQCF6 RNA expression–survival associations across cancer types. High IQCF6 expression shows unfavorable associations in LIHC, SCLC, THCA and UCS, but favorable associations in OV and KIRP. The LIHC 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 LIHC as the clearest survival context for IQCF6 RNA expression.
This table summarizes IQCF6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for IQCF6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IQCF6 shows lower tumor expression in KIRC, KIRP and BRCA and higher tumor expression in UCEC, LUAD and HNSC. The KIRC box plot shows higher IQCF6 RNA expression in normal versus tumor tissue (log2 FC = −0.542, t-test p < 0.001).
This table shows molecular features associated with IQCF6 in patient tissues and cancer cell lines. In patient samples, IQCF6 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, IQCF6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Lymphoma.
