Q-omics provides the consensus-scored PEG10 profile across patient tissues and cancer cell-line models. PEG10 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PEG10 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, PEG10 RNA expression shows 18,223 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, KICH, and TGCT as cancer lineages where PEG10 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 PEG10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PEG10 survival associations across molecular data types. PEG10 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 PEG10 RNA expression–survival associations across cancer types. High PEG10 expression shows unfavorable associations in KIRP, KICH, ACC, BLCA and UCEC, but favorable associations in KIRC. The KIRP 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 KIRP as the clearest survival context for PEG10 RNA expression.
This table summarizes PEG10 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 4. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PEG10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PEG10 shows lower tumor expression in KICH, LUSC, COAD and LUAD and higher tumor expression in LIHC and KIRP. The KICH box plot shows higher PEG10 RNA expression in normal versus tumor tissue (log2 FC = −3.405, t-test p < 0.001).
This table shows molecular features associated with PEG10 in patient tissues and cancer cell lines. In patient samples, PEG10 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PEG10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.
