cAMP responsive element binding protein like 2Genealiases: []
Q-omics provides the consensus-scored CREBL2 profile across patient tissues and cancer cell-line models. CREBL2 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, CREBL2 is differentially expressed in 11, with the highest sampling consensus in LUSC. Additionally, CREBL2 protein abundance shows 23,615 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LUSC, and GBM as cancer lineages where CREBL2 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 CREBL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CREBL2 survival associations across molecular data types. CREBL2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CREBL2 RNA expression–survival associations across cancer types. High CREBL2 expression shows unfavorable associations in LGG, but favorable associations in KIRC, BRCA, LUAD, MESO and UCEC. 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 CREBL2 RNA expression.
This table summarizes CREBL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 8. The strongest signals are observed in LUSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CREBL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CREBL2 shows lower tumor expression in LUSC, LUAD, THCA, UCEC, BLCA and BRCA. The LUSC box plot shows higher CREBL2 RNA expression in normal versus tumor tissue (log2 FC = −0.864, t-test p < 0.001).
This table shows molecular features associated with CREBL2 in patient tissues and cancer cell lines. In patient samples, CREBL2 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, CREBL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Lymphoma.
