Q-omics provides the consensus-scored TEDC2 profile across patient tissues and cancer cell-line models. TEDC2 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, TEDC2 is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, TEDC2 RNA expression shows 22,700 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, COAD, and LSCC as cancer lineages where TEDC2 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 TEDC2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TEDC2 survival associations across molecular data types. TEDC2 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TEDC2 RNA expression–survival associations across cancer types. High TEDC2 expression shows unfavorable associations in ACC, KIRC, MESO, KICH, LIHC and LUAD. The ACC 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 ACC as the clearest survival context for TEDC2 RNA expression.
This table summarizes TEDC2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for TEDC2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TEDC2 shows higher tumor expression in COAD, HNSC, BLCA, KIRP, LUAD and STAD. The COAD box plot shows higher TEDC2 RNA expression in tumor versus normal tissue (log2 FC = +2.018, t-test p < 0.001).
This table shows molecular features associated with TEDC2 in patient tissues and cancer cell lines. In patient samples, TEDC2 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, TEDC2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
