Q-omics provides the consensus-scored PIGP profile across patient tissues and cancer cell-line models. PIGP expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PIGP is differentially expressed in 7, with the highest sampling consensus in KIRC. Additionally, PIGP RNA expression shows 19,168 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, KIRC, and ACC as cancer lineages where PIGP 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 PIGP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PIGP survival associations across molecular data types. PIGP RNA expression shows survival associations in the most cancer types (24), followed by mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PIGP RNA expression–survival associations across cancer types. High PIGP expression shows unfavorable associations in UVM, HNSC and LUAD, but favorable associations in MESO, KIRC and PAAD. The UVM 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 UVM as the clearest survival context for PIGP RNA expression.
This table summarizes PIGP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PIGP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PIGP shows lower tumor expression in THCA, KICH, LUSC and UCEC and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher PIGP RNA expression in tumor versus normal tissue (log2 FC = +0.365, t-test p < 0.001).
This table shows molecular features associated with PIGP in patient tissues and cancer cell lines. In patient samples, PIGP 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, PIGP 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 BLOOD_Lymphoma.
