Q-omics provides the consensus-scored SLC22A18 profile across patient tissues and cancer cell-line models. SLC22A18 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SLC22A18 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SLC22A18 protein abundance shows 21,505 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where SLC22A18 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 SLC22A18 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC22A18 survival associations across molecular data types. SLC22A18 RNA expression shows survival associations in the most cancer types (26), 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 SLC22A18 RNA expression–survival associations across cancer types. High SLC22A18 expression shows unfavorable associations in UVM, UCS, LGG and KICH, but favorable associations in MESO and KIRP. The UVM 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 UVM as the clearest survival context for SLC22A18 RNA expression.
This table summarizes SLC22A18 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 8. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for SLC22A18. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC22A18 shows higher tumor expression in KIRC, THCA, LUAD, BRCA, LUSC and LIHC. The KIRC box plot shows higher SLC22A18 RNA expression in tumor versus normal tissue (log2 FC = +0.857, t-test p < 0.001).
This table shows molecular features associated with SLC22A18 in patient tissues and cancer cell lines. In patient samples, SLC22A18 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SLC22A18 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BONE.
