Fas associated via death domainGenealiases: GIG3 · IMD90 · MORT1
Q-omics provides the consensus-scored FADD profile across patient tissues and cancer cell-line models. FADD expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, FADD is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, FADD RNA expression shows 18,871 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight CESC, HNSC, and ACC as cancer lineages where FADD 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 FADD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FADD survival associations across molecular data types. FADD RNA expression shows survival associations in the most cancer types (28), followed by mutation status (3) 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 FADD RNA expression–survival associations across cancer types. High FADD expression shows unfavorable associations in CESC, HNSC, LUAD and LGG, but favorable associations in UCEC and SCLC. The CESC 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 CESC as the clearest survival context for FADD RNA expression.
This table summarizes FADD tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for FADD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FADD shows higher tumor expression in HNSC, KIRC, BLCA, KIRP, LIHC and LUAD. The HNSC box plot shows higher FADD RNA expression in tumor versus normal tissue (log2 FC = +1.600, t-test p < 0.001).
This table shows molecular features associated with FADD in patient tissues and cancer cell lines. In patient samples, FADD shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, FADD 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.
