CUGBP Elav-like family member 2Genealiases: BRUNOL3 · CELF-2 · CUG-BP2 · CUGBP2 · DEE97 · ETR-3
Q-omics provides the consensus-scored CELF2 profile across patient tissues and cancer cell-line models. CELF2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, CELF2 is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, CELF2 protein abundance shows 24,265 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, BLCA, and LSCC as cancer lineages where CELF2 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 CELF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CELF2 survival associations across molecular data types. CELF2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CELF2 RNA expression–survival associations across cancer types. High CELF2 expression shows unfavorable associations in UVM, but favorable associations in HNSC, CESC, COAD, CHOL and UCS. The UVM 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 UVM as the clearest survival context for CELF2 RNA expression.
This table summarizes CELF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 4. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CELF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CELF2 shows lower tumor expression in BLCA, LUAD, LUSC, UCEC and BRCA and higher tumor expression in KIRC. The BLCA box plot shows higher CELF2 RNA expression in normal versus tumor tissue (log2 FC = −2.914, t-test p < 0.001).
This table shows molecular features associated with CELF2 in patient tissues and cancer cell lines. In patient samples, CELF2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, CELF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
