Q-omics provides the consensus-scored SLC35E1 profile across patient tissues and cancer cell-line models. SLC35E1 expression is associated with patient survival in 31 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, SLC35E1 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SLC35E1 protein abundance shows 22,284 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BLCA, KIRC, and GBM as cancer lineages where SLC35E1 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 SLC35E1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC35E1 survival associations across molecular data types. SLC35E1 RNA expression shows survival associations in the most cancer types (31), followed by mutation status (3) 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 SLC35E1 RNA expression–survival associations across cancer types. High SLC35E1 expression shows unfavorable associations in BLCA, ACC, KICH and UVM, but favorable associations in KIRC and UCS. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify BLCA as the clearest survival context for SLC35E1 RNA expression.
This table summarizes SLC35E1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SLC35E1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC35E1 shows higher tumor expression in KIRC, HNSC, LIHC, KIRP, BLCA and BRCA. The KIRC box plot shows higher SLC35E1 RNA expression in tumor versus normal tissue (log2 FC = +0.736, t-test p < 0.001).
This table shows molecular features associated with SLC35E1 in patient tissues and cancer cell lines. In patient samples, SLC35E1 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, SLC35E1 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 LARGE_INTESTINE.
