TEF transcription factor, PAR bZIP family memberGenealiases: []
Q-omics provides the consensus-scored TEF profile across patient tissues and cancer cell-line models. TEF expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TEF is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, TEF RNA expression shows 22,495 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, COAD, and GBM as cancer lineages where TEF 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 TEF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TEF survival associations across molecular data types. TEF RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TEF RNA expression–survival associations across cancer types. High TEF expression shows favorable associations in KIRC, KIRP, HNSC, LGG, SKCM and MESO. 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 TEF RNA expression.
This table summarizes TEF 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 COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TEF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TEF shows lower tumor expression in COAD, KIRP, LUAD, BLCA and KIRC and higher tumor expression in LIHC. The COAD box plot shows higher TEF RNA expression in normal versus tumor tissue (log2 FC = −1.687, t-test p < 0.001).
This table shows molecular features associated with TEF in patient tissues and cancer cell lines. In patient samples, TEF 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, TEF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.
