Q-omics provides the consensus-scored SIRT3 profile across patient tissues and cancer cell-line models. SIRT3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SIRT3 is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, SIRT3 RNA expression shows 20,211 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, KICH, and ACC as cancer lineages where SIRT3 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 SIRT3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SIRT3 survival associations across molecular data types. SIRT3 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 SIRT3 RNA expression–survival associations across cancer types. High SIRT3 expression shows unfavorable associations in KICH and ACC, but favorable associations in UVM, KIRP, KIRC and BRCA. The UVM 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 UVM as the clearest survival context for SIRT3 RNA expression.
This table summarizes SIRT3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SIRT3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SIRT3 shows lower tumor expression in KICH, BRCA, BLCA and UCEC and higher tumor expression in STAD and CHOL. The KICH box plot shows higher SIRT3 RNA expression in normal versus tumor tissue (log2 FC = −0.948, t-test p < 0.001).
This table shows molecular features associated with SIRT3 in patient tissues and cancer cell lines. In patient samples, SIRT3 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, SIRT3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and UPPER_AERODIGESTIVE_TRACT.
