Q-omics provides the consensus-scored SLC37A3 profile across patient tissues and cancer cell-line models. SLC37A3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, SLC37A3 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, SLC37A3 RNA expression shows 20,442 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight CESC, HNSC, and ACC as cancer lineages where SLC37A3 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 SLC37A3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC37A3 survival associations across molecular data types. SLC37A3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLC37A3 RNA expression–survival associations across cancer types. High SLC37A3 expression shows unfavorable associations in CESC, ACC, LIHC, UVM, MESO and LGG. The CESC 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 CESC as the clearest survival context for SLC37A3 RNA expression.
This table summarizes SLC37A3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SLC37A3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC37A3 shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRP, LUAD, STAD and COAD. The HNSC box plot shows higher SLC37A3 RNA expression in tumor versus normal tissue (log2 FC = +0.861, t-test p < 0.001).
This table shows molecular features associated with SLC37A3 in patient tissues and cancer cell lines. In patient samples, SLC37A3 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SLC37A3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
