secretoglobin family 1D member 1Genealiases: LIPA · LPHA · LPNA
Q-omics provides the consensus-scored SCGB1D1 profile across patient tissues and cancer cell-line models. SCGB1D1 expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in DLBC. Among the 18 cancer types available for tumor–normal comparison, SCGB1D1 is differentially expressed in 3, with the highest sampling consensus in UCEC. Additionally, SCGB1D1 RNA expression shows 6,789 significant gene co-expression associations, with the highest sampling consensus in CESC. Together, these results highlight DLBC, UCEC, and CESC as cancer lineages where SCGB1D1 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 SCGB1D1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCGB1D1 survival associations across molecular data types. SCGB1D1 RNA expression shows survival associations in the most cancer types (15), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCGB1D1 RNA expression–survival associations across cancer types. High SCGB1D1 expression shows unfavorable associations in DLBC, COAD, READ, ESCA and THCA, but favorable associations in UCEC. The DLBC 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 DLBC as the clearest survival context for SCGB1D1 RNA expression.
This table summarizes SCGB1D1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in UCEC for RNA.
This table ranks reproducible tumor–normal expression differences for SCGB1D1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCGB1D1 shows lower tumor expression in HNSC and BRCA and higher tumor expression in UCEC. The UCEC box plot shows higher SCGB1D1 RNA expression in tumor versus normal tissue (log2 FC = +1.613, t-test p = .002).
This table shows molecular features associated with SCGB1D1 in patient tissues and cancer cell lines. In patient samples, SCGB1D1 shows the broadest associations at the RNA and protein expression levels, with CESC recurring as the lineage with the largest associated feature set. In cancer cell lines, SCGB1D1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BREAST.
