sushi, von Willebrand factor type A, EGF and pentraxin domain containing 1Genealiases: C9orf13 · CCP22 · POLYDOM · SEL-OB · SELOB
Q-omics provides the consensus-scored SVEP1 profile across patient tissues and cancer cell-line models. SVEP1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, SVEP1 is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, SVEP1 protein abundance shows 23,223 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UCEC, BLCA, and LSCC as cancer lineages where SVEP1 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 SVEP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SVEP1 survival associations across molecular data types. SVEP1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (13) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SVEP1 RNA expression–survival associations across cancer types. High SVEP1 expression shows unfavorable associations in BLCA, KIRP and STAD, but favorable associations in UCEC, LUAD and ESCA. The UCEC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify UCEC as the clearest survival context for SVEP1 RNA expression.
This table summarizes SVEP1 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 THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SVEP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SVEP1 shows lower tumor expression in BLCA, THCA, KIRC, LUAD, KIRP and COAD. The BLCA box plot shows higher SVEP1 RNA expression in normal versus tumor tissue (log2 FC = −2.675, t-test p < 0.001).
This table shows molecular features associated with SVEP1 in patient tissues and cancer cell lines. In patient samples, SVEP1 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, SVEP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and UPPER_AERODIGESTIVE_TRACT.
