Q-omics provides the consensus-scored SAC3D1 profile across patient tissues and cancer cell-line models. SAC3D1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, SAC3D1 is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, SAC3D1 RNA expression shows 19,238 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight LIHC, BLCA, and THYM as cancer lineages where SAC3D1 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 SAC3D1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SAC3D1 survival associations across molecular data types. SAC3D1 RNA expression shows survival associations in the most cancer types (25), followed by 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 SAC3D1 RNA expression–survival associations across cancer types. High SAC3D1 expression shows unfavorable associations in LIHC, ACC, MESO, KICH, KIRP and KIRC. The LIHC 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 LIHC as the clearest survival context for SAC3D1 RNA expression.
This table summarizes SAC3D1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SAC3D1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SAC3D1 shows higher tumor expression in BLCA, HNSC, KIRP, COAD, LIHC and STAD. The BLCA box plot shows higher SAC3D1 RNA expression in tumor versus normal tissue (log2 FC = +1.470, t-test p < 0.001).
This table shows molecular features associated with SAC3D1 in patient tissues and cancer cell lines. In patient samples, SAC3D1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SAC3D1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
