Q-omics provides the consensus-scored LYG1 profile across patient tissues and cancer cell-line models. LYG1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, LYG1 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, LYG1 RNA expression shows 18,335 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, KICH, and UVM as cancer lineages where LYG1 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 LYG1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LYG1 survival associations across molecular data types. LYG1 RNA expression shows survival associations in the most cancer types (26), 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 LYG1 RNA expression–survival associations across cancer types. High LYG1 expression shows unfavorable associations in ACC and KICH, but favorable associations in KIRP, HNSC, KIRC and BLCA. The KIRP 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 KIRP as the clearest survival context for LYG1 RNA expression.
This table summarizes LYG1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for LYG1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LYG1 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, COAD, UCEC and LUAD. The KICH box plot shows higher LYG1 RNA expression in normal versus tumor tissue (log2 FC = −4.285, t-test p < 0.001).
This table shows molecular features associated with LYG1 in patient tissues and cancer cell lines. In patient samples, LYG1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, LYG1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
