Q-omics provides the consensus-scored SDAD1 profile across patient tissues and cancer cell-line models. SDAD1 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, SDAD1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, SDAD1 protein abundance shows 22,354 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, HNSC, and LSCC as cancer lineages where SDAD1 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 SDAD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SDAD1 survival associations across molecular data types. SDAD1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SDAD1 RNA expression–survival associations across cancer types. High SDAD1 expression shows unfavorable associations in CESC, LGG, LIHC and HNSC, but favorable associations in KIRC and UCS. 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 SDAD1 RNA expression.
This table summarizes SDAD1 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 HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SDAD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SDAD1 shows lower tumor expression in THCA and higher tumor expression in HNSC, LUAD, COAD, CHOL and LUSC. The HNSC box plot shows higher SDAD1 RNA expression in tumor versus normal tissue (log2 FC = +0.718, t-test p < 0.001).
This table shows molecular features associated with SDAD1 in patient tissues and cancer cell lines. In patient samples, SDAD1 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, SDAD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LARGE_INTESTINE.
