Q-omics provides the consensus-scored CDH9 profile across patient tissues and cancer cell-line models. CDH9 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CDH9 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, CDH9 RNA expression shows 12,193 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, KIRC, and GBM as cancer lineages where CDH9 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 CDH9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CDH9 survival associations across molecular data types. CDH9 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (11) 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 CDH9 RNA expression–survival associations across cancer types. High CDH9 expression shows unfavorable associations in COAD, BLCA, SKCM and UVM, but favorable associations in KIRP and LGG. The KIRP 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 KIRP as the clearest survival context for CDH9 RNA expression.
This table summarizes CDH9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CDH9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CDH9 shows lower tumor expression in KIRC, KICH, KIRP, READ and ESCA and higher tumor expression in THCA. The KIRC box plot shows higher CDH9 RNA expression in normal versus tumor tissue (log2 FC = −0.991, t-test p < 0.001).
This table shows molecular features associated with CDH9 in patient tissues and cancer cell lines. In patient samples, CDH9 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, CDH9 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 BLOOD_Leukemia and LARGE_INTESTINE.
