Q-omics provides the consensus-scored SLC35F3 profile across patient tissues and cancer cell-line models. SLC35F3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SLC35F3 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, SLC35F3 RNA expression shows 17,932 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where SLC35F3 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 SLC35F3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC35F3 survival associations across molecular data types. SLC35F3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLC35F3 RNA expression–survival associations across cancer types. High SLC35F3 expression shows unfavorable associations in MESO, LUAD, KIRP and LIHC, but favorable associations in KICH and ACC. The MESO 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 MESO as the clearest survival context for SLC35F3 RNA expression.
This table summarizes SLC35F3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SLC35F3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC35F3 shows lower tumor expression in BRCA and higher tumor expression in HNSC, KIRC, KICH, LUAD and LUSC. The HNSC box plot shows higher SLC35F3 RNA expression in tumor versus normal tissue (log2 FC = +0.874, t-test p < 0.001).
This table shows molecular features associated with SLC35F3 in patient tissues and cancer cell lines. In patient samples, SLC35F3 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, SLC35F3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BONE.
