Q-omics provides the consensus-scored SIGLEC18P profile across patient tissues and cancer cell-line models. SIGLEC18P expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, SIGLEC18P is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, SIGLEC18P RNA expression shows 13,307 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ESCA, HNSC, and GBM as cancer lineages where SIGLEC18P 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 SIGLEC18P — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SIGLEC18P survival associations across molecular data types. SIGLEC18P RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SIGLEC18P RNA expression–survival associations across cancer types. High SIGLEC18P expression shows unfavorable associations in LGG, but favorable associations in ESCA, SKCM, STAD, MESO and LUAD. The ESCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify ESCA as the clearest survival context for SIGLEC18P RNA expression.
This table summarizes SIGLEC18P tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SIGLEC18P. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SIGLEC18P shows lower tumor expression in LUAD and LUSC and higher tumor expression in HNSC, KIRP, KIRC and THCA. The HNSC box plot shows higher SIGLEC18P RNA expression in tumor versus normal tissue (log2 FC = +0.137, t-test p < 0.001).
This table shows molecular features associated with SIGLEC18P in patient tissues and cancer cell lines. In patient samples, SIGLEC18P shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set.
