Q-omics provides the consensus-scored PGAP3 profile across patient tissues and cancer cell-line models. PGAP3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PGAP3 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, PGAP3 RNA expression shows 19,407 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, KICH, and ACC as cancer lineages where PGAP3 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 PGAP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PGAP3 survival associations across molecular data types. PGAP3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) 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 PGAP3 RNA expression–survival associations across cancer types. High PGAP3 expression shows unfavorable associations in OV, KIRP and COAD, but favorable associations in KIRC, LUAD and UCEC. 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 PGAP3 RNA expression.
This table summarizes PGAP3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for PGAP3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PGAP3 shows lower tumor expression in KICH, LUSC, KIRC and COAD and higher tumor expression in STAD and BRCA. The KICH box plot shows higher PGAP3 RNA expression in normal versus tumor tissue (log2 FC = −1.589, t-test p < 0.001).
This table shows molecular features associated with PGAP3 in patient tissues and cancer cell lines. In patient samples, PGAP3 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PGAP3 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 UPPER_AERODIGESTIVE_TRACT and BREAST.
