Q-omics provides the consensus-scored LGALS16 profile across patient tissues and cancer cell-line models. LGALS16 expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in COAD. Additionally, LGALS16 RNA expression shows 6,579 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight COAD, and TGCT as cancer lineages where LGALS16 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 LGALS16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LGALS16 survival associations across molecular data types. LGALS16 RNA expression shows survival associations in the most cancer types (14), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LGALS16 RNA expression–survival associations across cancer types. High LGALS16 expression shows unfavorable associations in COAD, LIHC, KIRC, CESC, THYM and ACC. The COAD 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 COAD as the clearest survival context for LGALS16 RNA expression.
This table shows molecular features associated with LGALS16 in patient tissues and cancer cell lines. In patient samples, LGALS16 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, LGALS16 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
