Q-omics provides the consensus-scored SDE2 profile across patient tissues and cancer cell-line models. SDE2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SDE2 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, SDE2 protein abundance shows 22,103 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where SDE2 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 SDE2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SDE2 survival associations across molecular data types. SDE2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) 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 SDE2 RNA expression–survival associations across cancer types. High SDE2 expression shows unfavorable associations in ACC, KIRP, UVM, BLCA and PAAD, but favorable associations in KIRC. 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 SDE2 RNA expression.
This table summarizes SDE2 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 6. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SDE2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SDE2 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, BRCA and COAD. The HNSC box plot shows higher SDE2 RNA expression in tumor versus normal tissue (log2 FC = +0.927, t-test p < 0.001).
This table shows molecular features associated with SDE2 in patient tissues and cancer cell lines. In patient samples, SDE2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SDE2 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 LARGE_INTESTINE.
