secretoglobin family 3A member 2Genealiases: LU103 · PNSP1 · UGRP1 · pnSP-1
Q-omics provides the consensus-scored SCGB3A2 profile across patient tissues and cancer cell-line models. SCGB3A2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, SCGB3A2 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, SCGB3A2 RNA expression shows 17,154 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UCEC, KIRC, and LSCC as cancer lineages where SCGB3A2 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 SCGB3A2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCGB3A2 survival associations across molecular data types. SCGB3A2 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCGB3A2 RNA expression–survival associations across cancer types. High SCGB3A2 expression shows unfavorable associations in UCEC, KIRC, LUSC, ACC and STAD, but favorable associations in UCS. The UCEC 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 UCEC as the clearest survival context for SCGB3A2 RNA expression.
This table summarizes SCGB3A2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SCGB3A2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCGB3A2 shows lower tumor expression in LUAD, LUSC, HNSC and THCA and higher tumor expression in KIRC and BLCA. The KIRC box plot shows higher SCGB3A2 RNA expression in tumor versus normal tissue (log2 FC = +1.399, t-test p < 0.001).
This table shows molecular features associated with SCGB3A2 in patient tissues and cancer cell lines. In patient samples, SCGB3A2 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, SCGB3A2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
