Q-omics provides the consensus-scored SDHAF1 profile across patient tissues and cancer cell-line models. SDHAF1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SDHAF1 is differentially expressed in 14, with the highest sampling consensus in LIHC. Additionally, SDHAF1 RNA expression shows 18,432 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where SDHAF1 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 SDHAF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SDHAF1 survival associations across molecular data types. SDHAF1 RNA expression shows survival associations in the most cancer types (26), followed by mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SDHAF1 RNA expression–survival associations across cancer types. High SDHAF1 expression shows unfavorable associations in ACC, LGG and CESC, but favorable associations in UVM, KIRC and CHOL. 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 SDHAF1 RNA expression.
This table summarizes SDHAF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for SDHAF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SDHAF1 shows lower tumor expression in KICH and higher tumor expression in LIHC, BLCA, HNSC, COAD and LUSC. The LIHC box plot shows higher SDHAF1 RNA expression in tumor versus normal tissue (log2 FC = +1.022, t-test p < 0.001).
This table shows molecular features associated with SDHAF1 in patient tissues and cancer cell lines. In patient samples, SDHAF1 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, SDHAF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Lymphoma.
