Q-omics provides the consensus-scored CDX1 profile across patient tissues and cancer cell-line models. CDX1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CDX1 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, CDX1 RNA expression shows 14,633 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, HNSC, and TGCT as cancer lineages where CDX1 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 CDX1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CDX1 survival associations across molecular data types. CDX1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CDX1 RNA expression–survival associations across cancer types. High CDX1 expression shows unfavorable associations in ACC, KIRP, BLCA and THCA, but favorable associations in READ and HNSC. 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 CDX1 RNA expression.
This table summarizes CDX1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CDX1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CDX1 shows lower tumor expression in KICH and higher tumor expression in HNSC, BLCA, LUAD, BRCA and STAD. The HNSC box plot shows higher CDX1 RNA expression in tumor versus normal tissue (log2 FC = +0.809, t-test p < 0.001).
This table shows molecular features associated with CDX1 in patient tissues and cancer cell lines. In patient samples, CDX1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, CDX1 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 LARGE_INTESTINE and LUNG_NSCLC_LUSC.
