Q-omics provides the consensus-scored CTCF profile across patient tissues and cancer cell-line models. CTCF expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CTCF is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, CTCF protein abundance shows 23,636 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where CTCF 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 CTCF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CTCF survival associations across molecular data types. CTCF RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) 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 CTCF RNA expression–survival associations across cancer types. High CTCF expression shows unfavorable associations in MESO, ACC and PAAD, but favorable associations in KIRC, SCLC and UCS. The KIRC 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 KIRC as the clearest survival context for CTCF RNA expression.
This table summarizes CTCF 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 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CTCF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CTCF shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, BLCA and STAD. The HNSC box plot shows higher CTCF RNA expression in tumor versus normal tissue (log2 FC = +0.677, t-test p < 0.001).
This table shows molecular features associated with CTCF in patient tissues and cancer cell lines. In patient samples, CTCF shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CTCF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
