Q-omics provides the consensus-scored PF4 profile across patient tissues and cancer cell-line models. PF4 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PF4 is differentially expressed in 8, with the highest sampling consensus in THCA. Additionally, PF4 protein abundance shows 13,844 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, THCA, and GBM as cancer lineages where PF4 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 PF4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PF4 survival associations across molecular data types. PF4 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PF4 RNA expression–survival associations across cancer types. High PF4 expression shows unfavorable associations in SKCM, ACC, UVM, LUAD and CESC, but favorable associations in COAD. The SKCM 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 SKCM as the clearest survival context for PF4 RNA expression.
This table summarizes PF4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PF4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PF4 shows lower tumor expression in THCA, LUAD, LUSC and BRCA and higher tumor expression in KIRC and COAD. The THCA box plot shows higher PF4 RNA expression in normal versus tumor tissue (log2 FC = −0.493, t-test p < 0.001).
This table shows molecular features associated with PF4 in patient tissues and cancer cell lines. In patient samples, PF4 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, PF4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
