Q-omics provides the consensus-scored PPARGC1B profile across patient tissues and cancer cell-line models. PPARGC1B expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PPARGC1B is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, PPARGC1B RNA expression shows 19,165 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, COAD, and UVM as cancer lineages where PPARGC1B 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 PPARGC1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPARGC1B survival associations across molecular data types. PPARGC1B RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPARGC1B RNA expression–survival associations across cancer types. High PPARGC1B expression shows unfavorable associations in LIHC, UCEC and SCLC, but favorable associations in HNSC, READ and LUSC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for PPARGC1B RNA expression.
This table summarizes PPARGC1B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PPARGC1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPARGC1B shows lower tumor expression in COAD, LUAD, BLCA and READ and higher tumor expression in KIRC and LIHC. The COAD box plot shows higher PPARGC1B RNA expression in normal versus tumor tissue (log2 FC = −1.052, t-test p < 0.001).
This table shows molecular features associated with PPARGC1B in patient tissues and cancer cell lines. In patient samples, PPARGC1B shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, PPARGC1B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Lymphoma.
