EGF like domain multiple 7Genealiases: NEU1 · VE-STATIN · ZNEU1
Q-omics provides the consensus-scored EGFL7 profile across patient tissues and cancer cell-line models. EGFL7 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, EGFL7 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, EGFL7 RNA expression shows 16,503 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight COAD, KICH, and CCRCC as cancer lineages where EGFL7 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 EGFL7 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EGFL7 survival associations across molecular data types. EGFL7 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EGFL7 RNA expression–survival associations across cancer types. High EGFL7 expression shows unfavorable associations in COAD, KIRP, MESO, UCEC, ACC and HNSC. The COAD 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 COAD as the clearest survival context for EGFL7 RNA expression.
This table summarizes EGFL7 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 KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for EGFL7. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EGFL7 shows lower tumor expression in KICH, KIRP, LUAD, LUSC and BLCA and higher tumor expression in LIHC. The KICH box plot shows higher EGFL7 RNA expression in normal versus tumor tissue (log2 FC = −2.163, t-test p < 0.001).
This table shows molecular features associated with EGFL7 in patient tissues and cancer cell lines. In patient samples, EGFL7 shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, EGFL7 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BONE.
