Q-omics provides the consensus-scored SLC35G5 profile across patient tissues and cancer cell-line models. SLC35G5 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SLC35G5 is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, SLC35G5 RNA expression shows 13,536 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where SLC35G5 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 SLC35G5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC35G5 survival associations across molecular data types. SLC35G5 RNA expression shows survival associations in the most cancer types (23), 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 SLC35G5 RNA expression–survival associations across cancer types. High SLC35G5 expression shows unfavorable associations in KIRC, ACC, MESO and LAML, but favorable associations in HNSC and BLCA. 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 SLC35G5 RNA expression.
This table summarizes SLC35G5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SLC35G5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC35G5 shows lower tumor expression in COAD and higher tumor expression in HNSC, STAD, CHOL and LIHC. The HNSC box plot shows higher SLC35G5 RNA expression in tumor versus normal tissue (log2 FC = +0.295, t-test p = .004).
This table shows molecular features associated with SLC35G5 in patient tissues and cancer cell lines. In patient samples, SLC35G5 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SLC35G5 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 STOMACH and SKIN.
