Q-omics provides the consensus-scored SLC25A43 profile across patient tissues and cancer cell-line models. SLC25A43 expression is associated with patient survival in 31 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, SLC25A43 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SLC25A43 RNA expression shows 19,516 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCEC, KIRC, and UVM as cancer lineages where SLC25A43 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 SLC25A43 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC25A43 survival associations across molecular data types. SLC25A43 RNA expression shows survival associations in the most cancer types (31), followed by mutation status (1) and 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 SLC25A43 RNA expression–survival associations across cancer types. High SLC25A43 expression shows unfavorable associations in UCEC, ACC, LGG, LUAD and HNSC, but favorable associations in KIRC. The UCEC 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 UCEC as the clearest survival context for SLC25A43 RNA expression.
This table summarizes SLC25A43 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 2. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SLC25A43. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC25A43 shows higher tumor expression in KIRC, LIHC, HNSC, BLCA, STAD and BRCA. The KIRC box plot shows higher SLC25A43 RNA expression in tumor versus normal tissue (log2 FC = +1.254, t-test p < 0.001).
This table shows molecular features associated with SLC25A43 in patient tissues and cancer cell lines. In patient samples, SLC25A43 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, SLC25A43 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
