Q-omics provides the consensus-scored PIGX profile across patient tissues and cancer cell-line models. PIGX expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, PIGX is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PIGX RNA expression shows 19,130 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, HNSC, and ACC as cancer lineages where PIGX 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 PIGX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PIGX survival associations across molecular data types. PIGX RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1) 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 PIGX RNA expression–survival associations across cancer types. High PIGX expression shows unfavorable associations in KICH, LIHC, SCLC, PAAD and MESO, but favorable associations in KIRC. The KICH 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 KICH as the clearest survival context for PIGX RNA expression.
This table summarizes PIGX 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 1. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PIGX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PIGX shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, LUSC, LUAD and BRCA. The HNSC box plot shows higher PIGX RNA expression in tumor versus normal tissue (log2 FC = +1.285, t-test p < 0.001).
This table shows molecular features associated with PIGX in patient tissues and cancer cell lines. In patient samples, PIGX 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, PIGX RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
