Q-omics provides the consensus-scored PTMS profile across patient tissues and cancer cell-line models. PTMS expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PTMS is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, PTMS protein abundance shows 21,505 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where PTMS 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 PTMS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PTMS survival associations across molecular data types. PTMS RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PTMS RNA expression–survival associations across cancer types. High PTMS expression shows unfavorable associations in ACC, KIRP, MESO, UVM and KIRC, but favorable associations in STAD. The ACC 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 ACC as the clearest survival context for PTMS RNA expression.
This table summarizes PTMS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PTMS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PTMS shows lower tumor expression in LUAD and LIHC and higher tumor expression in HNSC, THCA, BRCA and LUSC. The HNSC box plot shows higher PTMS RNA expression in tumor versus normal tissue (log2 FC = +1.232, t-test p < 0.001).
This table shows molecular features associated with PTMS in patient tissues and cancer cell lines. In patient samples, PTMS 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, PTMS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BONE and SOFT_TISSUE.
