Q-omics provides the consensus-scored LGALS3 profile across patient tissues and cancer cell-line models. LGALS3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, LGALS3 is differentially expressed in 15, with the highest sampling consensus in THCA. Additionally, LGALS3 protein abundance shows 20,058 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight UVM, THCA, and UCEC as cancer lineages where LGALS3 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 LGALS3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LGALS3 survival associations across molecular data types. LGALS3 RNA expression shows survival associations in the most cancer types (23), followed by mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LGALS3 RNA expression–survival associations across cancer types. High LGALS3 expression shows unfavorable associations in UVM, LGG, PAAD, ESCA and LIHC, but favorable associations in COAD. 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 LGALS3 RNA expression.
This table summarizes LGALS3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for LGALS3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LGALS3 shows lower tumor expression in COAD and LUAD and higher tumor expression in THCA, LIHC, KICH and KIRC. The THCA box plot shows higher LGALS3 RNA expression in tumor versus normal tissue (log2 FC = +3.025, t-test p < 0.001).
This table shows molecular features associated with LGALS3 in patient tissues and cancer cell lines. In patient samples, LGALS3 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, LGALS3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BONE.
