Q-omics provides the consensus-scored SIGLEC12 profile across patient tissues and cancer cell-line models. SIGLEC12 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SIGLEC12 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, SIGLEC12 RNA expression shows 9,291 significant gene co-expression associations, with the highest sampling consensus in BLCA. Together, these results highlight UVM, KIRC, and BLCA as cancer lineages where SIGLEC12 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 SIGLEC12 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SIGLEC12 survival associations across molecular data types. SIGLEC12 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SIGLEC12 RNA expression–survival associations across cancer types. High SIGLEC12 expression shows unfavorable associations in UVM, DLBC, KIRP, KIRC and LAML, but favorable associations in HNSC. The UVM 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 UVM as the clearest survival context for SIGLEC12 RNA expression.
This table summarizes SIGLEC12 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SIGLEC12. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SIGLEC12 shows lower tumor expression in LUSC and higher tumor expression in KIRC, HNSC, THCA, STAD and ESCA. The KIRC box plot shows higher SIGLEC12 RNA expression in tumor versus normal tissue (log2 FC = +0.497, t-test p < 0.001).
This table shows molecular features associated with SIGLEC12 in patient tissues and cancer cell lines. In patient samples, SIGLEC12 shows the broadest associations at the RNA and protein expression levels, with BLCA recurring as the lineage with the largest associated feature set. In cancer cell lines, SIGLEC12 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
