solute carrier family 15 member 1Genealiases: HPECT1 · HPEPT1 · PEPT1
Q-omics provides the consensus-scored SLC15A1 profile across patient tissues and cancer cell-line models. SLC15A1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, SLC15A1 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, SLC15A1 protein abundance shows 16,120 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, KICH, and GBM as cancer lineages where SLC15A1 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 SLC15A1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC15A1 survival associations across molecular data types. SLC15A1 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLC15A1 RNA expression–survival associations across cancer types. High SLC15A1 expression shows unfavorable associations in SKCM, ACC, LUAD and LGG, but favorable associations in KIRP and HNSC. The SKCM 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 SKCM as the clearest survival context for SLC15A1 RNA expression.
This table summarizes SLC15A1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 3. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SLC15A1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC15A1 shows lower tumor expression in KICH and COAD and higher tumor expression in LUAD, LUSC, UCEC and BLCA. The KICH box plot shows higher SLC15A1 RNA expression in normal versus tumor tissue (log2 FC = −2.697, t-test p < 0.001).
This table shows molecular features associated with SLC15A1 in patient tissues and cancer cell lines. In patient samples, SLC15A1 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, SLC15A1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in CNS and LARGE_INTESTINE.
