Q-omics provides the consensus-scored PCMT1 profile across patient tissues and cancer cell-line models. PCMT1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PCMT1 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, PCMT1 protein abundance shows 32,206 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, and GBM as cancer lineages where PCMT1 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 PCMT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCMT1 survival associations across molecular data types. PCMT1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) 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 PCMT1 RNA expression–survival associations across cancer types. High PCMT1 expression shows unfavorable associations in HNSC, BLCA, LIHC, MESO, BRCA and ACC. The HNSC 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 HNSC as the clearest survival context for PCMT1 RNA expression.
This table summarizes PCMT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PCMT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCMT1 shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, COAD, STAD and BRCA. The HNSC box plot shows higher PCMT1 RNA expression in tumor versus normal tissue (log2 FC = +0.543, t-test p < 0.001).
This table shows molecular features associated with PCMT1 in patient tissues and cancer cell lines. In patient samples, PCMT1 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, PCMT1 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 CNS and BLOOD_Leukemia.
