Q-omics provides the consensus-scored SLC43A2 profile across patient tissues and cancer cell-line models. SLC43A2 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, SLC43A2 is differentially expressed in 10, with the highest sampling consensus in KIRP. Additionally, SLC43A2 protein abundance shows 25,790 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUSC, KIRP, and GBM as cancer lineages where SLC43A2 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 SLC43A2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC43A2 survival associations across molecular data types. SLC43A2 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (7) 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 SLC43A2 RNA expression–survival associations across cancer types. High SLC43A2 expression shows unfavorable associations in LUSC and LGG, but favorable associations in KIRC, PAAD, MESO and HNSC. The LUSC 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 LUSC as the clearest survival context for SLC43A2 RNA expression.
This table summarizes SLC43A2 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SLC43A2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC43A2 shows lower tumor expression in KIRP, KIRC, THCA and LUAD and higher tumor expression in HNSC and LIHC. The KIRP box plot shows higher SLC43A2 RNA expression in normal versus tumor tissue (log2 FC = −2.010, t-test p < 0.001).
This table shows molecular features associated with SLC43A2 in patient tissues and cancer cell lines. In patient samples, SLC43A2 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, SLC43A2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
