solute carrier family 35 member G4Genealiases: AMAC1L1 · SLC35G4P
Q-omics provides the consensus-scored SLC35G4 profile across patient tissues and cancer cell-line models. SLC35G4 expression is associated with patient survival in 11 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SLC35G4 is differentially expressed in 2, with the highest sampling consensus in THCA. Additionally, SLC35G4 RNA expression shows 6,454 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight KIRC, THCA, and STAD as cancer lineages where SLC35G4 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 SLC35G4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC35G4 survival associations across molecular data types. SLC35G4 RNA expression shows survival associations in the most cancer types (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLC35G4 RNA expression–survival associations across cancer types. High SLC35G4 expression shows unfavorable associations in KIRC, CESC, KICH, PAAD, SKCM and LIHC. 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 SLC35G4 RNA expression.
This table summarizes SLC35G4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for SLC35G4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC35G4 shows lower tumor expression in THCA and BRCA. The THCA box plot shows higher SLC35G4 RNA expression in normal versus tumor tissue (log2 FC = −0.047, t-test p < 0.001).
This table shows molecular features associated with SLC35G4 in patient tissues and cancer cell lines. In patient samples, SLC35G4 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, SLC35G4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD.
