Q-omics provides the consensus-scored PARG profile across patient tissues and cancer cell-line models. PARG 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, PARG is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PARG RNA expression shows 20,900 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where PARG 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 PARG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PARG survival associations across molecular data types. PARG RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PARG RNA expression–survival associations across cancer types. High PARG expression shows unfavorable associations in ACC, MESO, LIHC and HNSC, but favorable associations in KIRC and LGG. 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 PARG RNA expression.
This table summarizes PARG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PARG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PARG shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, BLCA, STAD and LUSC. The HNSC box plot shows higher PARG RNA expression in tumor versus normal tissue (log2 FC = +0.543, t-test p < 0.001).
This table shows molecular features associated with PARG in patient tissues and cancer cell lines. In patient samples, PARG 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, PARG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and SKIN.
