Q-omics provides the consensus-scored CETN3 profile across patient tissues and cancer cell-line models. CETN3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CETN3 is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, CETN3 RNA expression shows 19,356 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, LIHC, and UVM as cancer lineages where CETN3 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 CETN3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CETN3 survival associations across molecular data types. CETN3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 CETN3 RNA expression–survival associations across cancer types. High CETN3 expression shows unfavorable associations in HNSC, LIHC, KICH and UCS, but favorable associations in KIRC and MESO. 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 CETN3 RNA expression.
This table summarizes CETN3 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 3. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CETN3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CETN3 shows lower tumor expression in THCA, UCEC and KICH and higher tumor expression in LIHC, CHOL and BRCA. The LIHC box plot shows higher CETN3 RNA expression in tumor versus normal tissue (log2 FC = +0.720, t-test p < 0.001).
This table shows molecular features associated with CETN3 in patient tissues and cancer cell lines. In patient samples, CETN3 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, CETN3 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 UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
