Q-omics provides the consensus-scored SLC26A11 profile across patient tissues and cancer cell-line models. SLC26A11 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, SLC26A11 is differentially expressed in 6, with the highest sampling consensus in KICH. Additionally, SLC26A11 RNA expression shows 20,583 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, KICH, and UVM as cancer lineages where SLC26A11 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 SLC26A11 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC26A11 survival associations across molecular data types. SLC26A11 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) 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 SLC26A11 RNA expression–survival associations across cancer types. High SLC26A11 expression shows unfavorable associations in LIHC, ACC and UVM, but favorable associations in PAAD, BRCA and HNSC. The LIHC 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 LIHC as the clearest survival context for SLC26A11 RNA expression.
This table summarizes SLC26A11 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 2. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SLC26A11. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC26A11 shows lower tumor expression in KICH and LUSC and higher tumor expression in LIHC, BRCA, CHOL and STAD. The KICH box plot shows higher SLC26A11 RNA expression in normal versus tumor tissue (log2 FC = −1.561, t-test p < 0.001).
This table shows molecular features associated with SLC26A11 in patient tissues and cancer cell lines. In patient samples, SLC26A11 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, SLC26A11 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 BREAST and SOFT_TISSUE.
