Q-omics provides the consensus-scored PIGH profile across patient tissues and cancer cell-line models. PIGH expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PIGH is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, PIGH protein abundance shows 19,701 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where PIGH 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 PIGH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PIGH survival associations across molecular data types. PIGH RNA expression shows survival associations in the most cancer types (18), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PIGH RNA expression–survival associations across cancer types. High PIGH expression shows unfavorable associations in UVM, ACC and LIHC, but favorable associations in BRCA, KIRC and MESO. 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 PIGH RNA expression.
This table summarizes PIGH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PIGH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PIGH shows lower tumor expression in KIRC, THCA, KICH and KIRP and higher tumor expression in LIHC and COAD. The KIRC box plot shows higher PIGH RNA expression in normal versus tumor tissue (log2 FC = −0.976, t-test p < 0.001).
This table shows molecular features associated with PIGH in patient tissues and cancer cell lines. In patient samples, PIGH 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, PIGH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
