Q-omics provides the consensus-scored LGALS2 profile across patient tissues and cancer cell-line models. LGALS2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, LGALS2 is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, LGALS2 protein abundance shows 25,041 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, COAD, and PDAC as cancer lineages where LGALS2 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 LGALS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LGALS2 survival associations across molecular data types. LGALS2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LGALS2 RNA expression–survival associations across cancer types. High LGALS2 expression shows unfavorable associations in LAML, but favorable associations in KIRC, HNSC, SKCM, CESC and SARC. The KIRC 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 KIRC as the clearest survival context for LGALS2 RNA expression.
This table summarizes LGALS2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 10. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for LGALS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LGALS2 shows lower tumor expression in COAD, KICH, UCEC, LUSC and LUAD and higher tumor expression in KIRC. The COAD box plot shows higher LGALS2 RNA expression in normal versus tumor tissue (log2 FC = −3.675, t-test p < 0.001).
This table shows molecular features associated with LGALS2 in patient tissues and cancer cell lines. In patient samples, LGALS2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, LGALS2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
