Q-omics provides the consensus-scored CLDND2 profile across patient tissues and cancer cell-line models. CLDND2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, CLDND2 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, CLDND2 RNA expression shows 13,168 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight CESC, KICH, and THYM as cancer lineages where CLDND2 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 CLDND2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLDND2 survival associations across molecular data types. CLDND2 RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CLDND2 RNA expression–survival associations across cancer types. High CLDND2 expression shows unfavorable associations in KIRC, COAD, LGG, KIRP and ACC, but favorable associations in CESC. The CESC 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 CESC as the clearest survival context for CLDND2 RNA expression.
This table summarizes CLDND2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for CLDND2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLDND2 shows lower tumor expression in KICH, BRCA, LUAD and UCEC and higher tumor expression in LIHC and KIRC. The KICH box plot shows higher CLDND2 RNA expression in normal versus tumor tissue (log2 FC = −1.079, t-test p < 0.001).
This table shows molecular features associated with CLDND2 in patient tissues and cancer cell lines. In patient samples, CLDND2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, CLDND2 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 LUNG_NSCLC_LUSC and BLOOD_Lymphoma.
