solute carrier family 6 member 5Genealiases: GLYT-2 · GLYT2 · HKPX3 · NET1
Q-omics provides the consensus-scored SLC6A5 profile across patient tissues and cancer cell-line models. SLC6A5 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SLC6A5 is differentially expressed in 7, with the highest sampling consensus in HNSC. Additionally, SLC6A5 RNA expression shows 9,979 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, HNSC, and TGCT as cancer lineages where SLC6A5 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 SLC6A5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC6A5 survival associations across molecular data types. SLC6A5 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLC6A5 RNA expression–survival associations across cancer types. High SLC6A5 expression shows unfavorable associations in KIRC, KIRP, CHOL, LIHC, KICH and READ. The KIRC 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 KIRC as the clearest survival context for SLC6A5 RNA expression.
This table summarizes SLC6A5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SLC6A5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC6A5 shows lower tumor expression in COAD, KIRP, READ and THCA and higher tumor expression in HNSC and LUSC. The HNSC box plot shows higher SLC6A5 RNA expression in tumor versus normal tissue (log2 FC = +0.026, t-test p = .001).
This table shows molecular features associated with SLC6A5 in patient tissues and cancer cell lines. In patient samples, SLC6A5 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, SLC6A5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and LUNG_SCLC.
