Q-omics provides the consensus-scored PARL profile across patient tissues and cancer cell-line models. PARL expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PARL is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, PARL RNA expression shows 18,780 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where PARL 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 PARL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PARL survival associations across molecular data types. PARL RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PARL RNA expression–survival associations across cancer types. High PARL expression shows unfavorable associations in ACC, KICH, LIHC, PAAD and UCEC, but favorable associations in DLBC. 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 PARL RNA expression.
This table summarizes PARL 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 4. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PARL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PARL shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRC, LIHC, LUSC and CHOL. The HNSC box plot shows higher PARL RNA expression in tumor versus normal tissue (log2 FC = +1.517, t-test p < 0.001).
This table shows molecular features associated with PARL in patient tissues and cancer cell lines. In patient samples, PARL shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PARL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Myeloma.
