Q-omics provides the consensus-scored EFEMP2 profile across patient tissues and cancer cell-line models. EFEMP2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EFEMP2 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, EFEMP2 protein abundance shows 27,562 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, KIRC, and PDAC as cancer lineages where EFEMP2 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 EFEMP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EFEMP2 survival associations across molecular data types. EFEMP2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EFEMP2 RNA expression–survival associations across cancer types. High EFEMP2 expression shows unfavorable associations in ACC, MESO, LGG, LUSC and BLCA, but favorable associations in UVM. 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 EFEMP2 RNA expression.
This table summarizes EFEMP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for EFEMP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EFEMP2 shows lower tumor expression in BLCA, KICH, LUAD, LUSC and UCEC and higher tumor expression in KIRC. The KIRC box plot shows higher EFEMP2 RNA expression in tumor versus normal tissue (log2 FC = +1.200, t-test p < 0.001).
This table shows molecular features associated with EFEMP2 in patient tissues and cancer cell lines. In patient samples, EFEMP2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, EFEMP2 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 BLOOD_Lymphoma and BLOOD_Leukemia.
