Q-omics provides the consensus-scored PID1 profile across patient tissues and cancer cell-line models. PID1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, PID1 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, PID1 protein abundance shows 22,438 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight BLCA, COAD, and LSCC as cancer lineages where PID1 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 PID1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PID1 survival associations across molecular data types. PID1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (9) 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 PID1 RNA expression–survival associations across cancer types. High PID1 expression shows unfavorable associations in BLCA and KIRP, but favorable associations in KIRC, ESCA, LGG and COAD. The BLCA 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 BLCA as the clearest survival context for PID1 RNA expression.
This table summarizes PID1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PID1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PID1 shows lower tumor expression in COAD, THCA, BLCA, KICH, LUAD and KIRP. The COAD box plot shows higher PID1 RNA expression in normal versus tumor tissue (log2 FC = −1.952, t-test p < 0.001).
This table shows molecular features associated with PID1 in patient tissues and cancer cell lines. In patient samples, PID1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, PID1 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 BLOOD_Myeloma and SOFT_TISSUE.
