Q-omics provides the consensus-scored PIGF profile across patient tissues and cancer cell-line models. PIGF expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, PIGF is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, PIGF RNA expression shows 20,776 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight CESC, HNSC, and ACC as cancer lineages where PIGF 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 PIGF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PIGF survival associations across molecular data types. PIGF RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PIGF RNA expression–survival associations across cancer types. High PIGF expression shows unfavorable associations in CESC, LIHC, ACC, KICH and UVM, but favorable associations in KIRC. The CESC 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 CESC as the clearest survival context for PIGF RNA expression.
This table summarizes PIGF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for PIGF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PIGF shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, BLCA, STAD and BRCA. The HNSC box plot shows higher PIGF RNA expression in tumor versus normal tissue (log2 FC = +0.477, t-test p < 0.001).
This table shows molecular features associated with PIGF in patient tissues and cancer cell lines. In patient samples, PIGF 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, PIGF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in CNS and UPPER_AERODIGESTIVE_TRACT.
