Q-omics provides the consensus-scored QPCT profile across patient tissues and cancer cell-line models. QPCT expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, QPCT is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, QPCT protein abundance shows 18,010 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, THCA, and GBM as cancer lineages where QPCT 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 QPCT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes QPCT survival associations across molecular data types. QPCT RNA expression shows survival associations in the most cancer types (27), 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 QPCT RNA expression–survival associations across cancer types. High QPCT expression shows unfavorable associations in ACC, UVM, MESO, LGG and LIHC, but favorable associations in COAD. 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 QPCT RNA expression.
This table summarizes QPCT 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 4. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for QPCT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. QPCT shows higher tumor expression in THCA, LUAD, LIHC, BRCA, COAD and ESCA. The THCA box plot shows higher QPCT RNA expression in tumor versus normal tissue (log2 FC = +3.883, t-test p < 0.001).
This table shows molecular features associated with QPCT in patient tissues and cancer cell lines. In patient samples, QPCT 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, QPCT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in SKIN and CNS.
