Q-omics provides the consensus-scored PFAS profile across patient tissues and cancer cell-line models. PFAS expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, PFAS is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, PFAS RNA expression shows 19,752 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SCLC, COAD, and ACC as cancer lineages where PFAS 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 PFAS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PFAS survival associations across molecular data types. PFAS RNA expression shows survival associations in the most cancer types (29), followed by mutation status (6) 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 PFAS RNA expression–survival associations across cancer types. High PFAS expression shows unfavorable associations in ACC and LIHC, but favorable associations in SCLC, KIRC, UCS and READ. The SCLC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SCLC as the clearest survival context for PFAS RNA expression.
This table summarizes PFAS 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 5. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PFAS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PFAS shows higher tumor expression in COAD, HNSC, STAD, KIRP, LIHC and LUAD. The COAD box plot shows higher PFAS RNA expression in tumor versus normal tissue (log2 FC = +1.187, t-test p < 0.001).
This table shows molecular features associated with PFAS in patient tissues and cancer cell lines. In patient samples, PFAS 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, PFAS 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 BLOOD_Lymphoma and BLOOD_Leukemia.
