pericentriolar material 1Genealiases: PTC4 · RET/PCM-1
Q-omics provides the consensus-scored PCM1 profile across patient tissues and cancer cell-line models. PCM1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PCM1 is differentially expressed in 10, with the highest sampling consensus in BLCA. Additionally, PCM1 protein abundance shows 24,146 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, BLCA, and GBM as cancer lineages where PCM1 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 PCM1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCM1 survival associations across molecular data types. PCM1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (9) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCM1 RNA expression–survival associations across cancer types. High PCM1 expression shows unfavorable associations in KICH and STAD, but favorable associations in HNSC, KIRC, BRCA and SKCM. The HNSC 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 HNSC as the clearest survival context for PCM1 RNA expression.
This table summarizes PCM1 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 8. The strongest signals are observed in BLCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PCM1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCM1 shows lower tumor expression in BLCA, LUSC, KICH and THCA and higher tumor expression in CHOL and READ. The BLCA box plot shows higher PCM1 RNA expression in normal versus tumor tissue (log2 FC = −0.753, t-test p = .008).
This table shows molecular features associated with PCM1 in patient tissues and cancer cell lines. In patient samples, PCM1 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, PCM1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BONE and SOFT_TISSUE.
