Q-omics provides the consensus-scored PGAP1 profile across patient tissues and cancer cell-line models. PGAP1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PGAP1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PGAP1 RNA expression shows 20,858 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, and THYM as cancer lineages where PGAP1 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 PGAP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PGAP1 survival associations across molecular data types. PGAP1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and 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 PGAP1 RNA expression–survival associations across cancer types. High PGAP1 expression shows unfavorable associations in UVM, ACC and LIHC, but favorable associations in HNSC, KIRC and LUAD. The HNSC 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 HNSC as the clearest survival context for PGAP1 RNA expression.
This table summarizes PGAP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PGAP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PGAP1 shows lower tumor expression in KIRC, KICH, LUAD and BRCA and higher tumor expression in HNSC and LUSC. The HNSC box plot shows higher PGAP1 RNA expression in tumor versus normal tissue (log2 FC = +0.567, t-test p = .001).
This table shows molecular features associated with PGAP1 in patient tissues and cancer cell lines. In patient samples, PGAP1 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, PGAP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and UPPER_AERODIGESTIVE_TRACT.
