solute carrier family 16 member 10Genealiases: MCT10 · PRO0813 · TAT1
Q-omics provides the consensus-scored SLC16A10 profile across patient tissues and cancer cell-line models. SLC16A10 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SLC16A10 is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, SLC16A10 RNA expression shows 17,542 significant gene co-expression associations, with the highest sampling consensus in KICH. Together, these results highlight ACC, KIRP, and KICH as cancer lineages where SLC16A10 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 SLC16A10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC16A10 survival associations across molecular data types. SLC16A10 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLC16A10 RNA expression–survival associations across cancer types. High SLC16A10 expression shows unfavorable associations in UCEC, COAD and SARC, but favorable associations in ACC, UVM and THYM. The ACC 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 ACC as the clearest survival context for SLC16A10 RNA expression.
This table summarizes SLC16A10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SLC16A10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC16A10 shows lower tumor expression in KIRP, KIRC, LUAD and LUSC and higher tumor expression in BLCA and UCEC. The KIRP box plot shows higher SLC16A10 RNA expression in normal versus tumor tissue (log2 FC = −1.237, t-test p < 0.001).
This table shows molecular features associated with SLC16A10 in patient tissues and cancer cell lines. In patient samples, SLC16A10 shows the broadest associations at the RNA and protein expression levels, with KICH recurring as the lineage with the largest associated feature set. In cancer cell lines, SLC16A10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
