cell death inducing DFFA like effector cGenealiases: CIDE-3 · CIDE3 · FPLD5 · FSP27
Q-omics provides the consensus-scored CIDEC profile across patient tissues and cancer cell-line models. CIDEC expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, CIDEC is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, CIDEC RNA expression shows 11,366 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UVM, HNSC, and TGCT as cancer lineages where CIDEC 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 CIDEC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CIDEC survival associations across molecular data types. CIDEC RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CIDEC RNA expression–survival associations across cancer types. High CIDEC expression shows unfavorable associations in LUAD, STAD, KICH and THCA, but favorable associations in UVM and KIRP. The UVM 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 UVM as the clearest survival context for CIDEC RNA expression.
This table summarizes CIDEC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for CIDEC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CIDEC shows lower tumor expression in HNSC, COAD, READ, BLCA, BRCA and UCEC. The HNSC box plot shows higher CIDEC RNA expression in normal versus tumor tissue (log2 FC = −2.226, t-test p < 0.001).
This table shows molecular features associated with CIDEC in patient tissues and cancer cell lines. In patient samples, CIDEC shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, CIDEC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
