Q-omics provides the consensus-scored CECR2 profile across patient tissues and cancer cell-line models. CECR2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, CECR2 is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, CECR2 RNA expression shows 18,235 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCS, THCA, and UVM as cancer lineages where CECR2 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 CECR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CECR2 survival associations across molecular data types. CECR2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (8) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CECR2 RNA expression–survival associations across cancer types. High CECR2 expression shows unfavorable associations in KIRC, ACC and SKCM, but favorable associations in UCS, LGG and GBM. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .005). Together, the overview and detailed table identify UCS as the clearest survival context for CECR2 RNA expression.
This table summarizes CECR2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 3. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CECR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CECR2 shows lower tumor expression in THCA, KICH, KIRC, CHOL and LUAD and higher tumor expression in HNSC. The THCA box plot shows higher CECR2 RNA expression in normal versus tumor tissue (log2 FC = −1.562, t-test p < 0.001).
This table shows molecular features associated with CECR2 in patient tissues and cancer cell lines. In patient samples, CECR2 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, CECR2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and SKIN.
