Q-omics provides the consensus-scored CTTNBP2NL profile across patient tissues and cancer cell-line models. CTTNBP2NL expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CTTNBP2NL is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, CTTNBP2NL RNA expression shows 20,266 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, KICH, and UVM as cancer lineages where CTTNBP2NL 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 CTTNBP2NL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CTTNBP2NL survival associations across molecular data types. CTTNBP2NL RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CTTNBP2NL RNA expression–survival associations across cancer types. High CTTNBP2NL expression shows unfavorable associations in MESO, ACC, PAAD and LGG, but favorable associations in KIRC and COAD. 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 CTTNBP2NL RNA expression.
This table summarizes CTTNBP2NL 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 5. The strongest signals are observed in KIRP for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CTTNBP2NL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CTTNBP2NL shows lower tumor expression in KICH and higher tumor expression in KIRP, LIHC, CHOL, BLCA and KIRC. The KICH box plot shows higher CTTNBP2NL RNA expression in normal versus tumor tissue (log2 FC = −2.097, t-test p < 0.001).
This table shows molecular features associated with CTTNBP2NL in patient tissues and cancer cell lines. In patient samples, CTTNBP2NL shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, CTTNBP2NL 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 BLOOD_Leukemia and BONE.
