Q-omics provides the consensus-scored EEFSEC profile across patient tissues and cancer cell-line models. EEFSEC expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, EEFSEC is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, EEFSEC RNA expression shows 19,088 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, COAD, and ACC as cancer lineages where EEFSEC 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 EEFSEC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EEFSEC survival associations across molecular data types. EEFSEC RNA expression shows survival associations in the most cancer types (25), 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 EEFSEC RNA expression–survival associations across cancer types. High EEFSEC expression shows unfavorable associations in ACC, KICH and LIHC, but favorable associations in UVM, KIRC and SCLC. 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 EEFSEC RNA expression.
This table summarizes EEFSEC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 8. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EEFSEC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EEFSEC shows lower tumor expression in THCA and KICH and higher tumor expression in COAD, HNSC, LIHC and LUSC. The COAD box plot shows higher EEFSEC RNA expression in tumor versus normal tissue (log2 FC = +0.984, t-test p < 0.001).
This table shows molecular features associated with EEFSEC in patient tissues and cancer cell lines. In patient samples, EEFSEC 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, EEFSEC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
