Q-omics provides the consensus-scored LGALS8 profile across patient tissues and cancer cell-line models. LGALS8 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, LGALS8 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, LGALS8 RNA expression shows 20,612 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KICH as cancer lineages where LGALS8 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 LGALS8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LGALS8 survival associations across molecular data types. LGALS8 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LGALS8 RNA expression–survival associations across cancer types. High LGALS8 expression shows unfavorable associations in ACC, KIRP, LGG, HNSC and UVM, but favorable associations in MESO. The ACC 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 ACC as the clearest survival context for LGALS8 RNA expression.
This table summarizes LGALS8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for LGALS8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LGALS8 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, KIRC, BRCA and STAD. The KICH box plot shows higher LGALS8 RNA expression in normal versus tumor tissue (log2 FC = −1.237, t-test p < 0.001).
This table shows molecular features associated with LGALS8 in patient tissues and cancer cell lines. In patient samples, LGALS8 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, LGALS8 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 SKIN and UPPER_AERODIGESTIVE_TRACT.
