sushi, nidogen and EGF like domains 1Genealiases: IRE-BP1 · SST3 · Snep
Q-omics provides the consensus-scored SNED1 profile across patient tissues and cancer cell-line models. SNED1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SNED1 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, SNED1 RNA expression shows 23,194 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, THCA, and LSCC as cancer lineages where SNED1 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 SNED1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNED1 survival associations across molecular data types. SNED1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) 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 SNED1 RNA expression–survival associations across cancer types. High SNED1 expression shows unfavorable associations in BLCA, UCS and ACC, but favorable associations in KIRC, SKCM and HNSC. 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 SNED1 RNA expression.
This table summarizes SNED1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for SNED1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNED1 shows lower tumor expression in THCA, KIRP, UCEC, BLCA, LUSC and KICH. The THCA box plot shows higher SNED1 RNA expression in normal versus tumor tissue (log2 FC = −1.900, t-test p < 0.001).
This table shows molecular features associated with SNED1 in patient tissues and cancer cell lines. In patient samples, SNED1 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, SNED1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
