Q-omics provides the consensus-scored PIGT profile across patient tissues and cancer cell-line models. PIGT expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PIGT is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PIGT protein abundance shows 19,240 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, HNSC, and GBM as cancer lineages where PIGT 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 PIGT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PIGT survival associations across molecular data types. PIGT RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PIGT RNA expression–survival associations across cancer types. High PIGT expression shows unfavorable associations in UVM, MESO, LGG, LIHC and BLCA, but favorable associations in 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 PIGT RNA expression.
This table summarizes PIGT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PIGT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PIGT shows higher tumor expression in HNSC, LUAD, COAD, LIHC, KIRP and STAD. The HNSC box plot shows higher PIGT RNA expression in tumor versus normal tissue (log2 FC = +1.139, t-test p < 0.001).
This table shows molecular features associated with PIGT in patient tissues and cancer cell lines. In patient samples, PIGT shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, PIGT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
