Q-omics provides the consensus-scored LYG2 profile across patient tissues and cancer cell-line models. LYG2 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, LYG2 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, LYG2 RNA expression shows 17,816 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, and UVM as cancer lineages where LYG2 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 LYG2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LYG2 survival associations across molecular data types. LYG2 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LYG2 RNA expression–survival associations across cancer types. High LYG2 expression shows unfavorable associations in KIRC, COAD, ACC, KICH and UCEC, but favorable associations in PAAD. The KIRC 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 KIRC as the clearest survival context for LYG2 RNA expression.
This table summarizes LYG2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for LYG2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LYG2 shows higher tumor expression in KIRC, LIHC, BLCA, HNSC, UCEC and READ. The KIRC box plot shows higher LYG2 RNA expression in tumor versus normal tissue (log2 FC = +0.171, t-test p < 0.001).
This table shows molecular features associated with LYG2 in patient tissues and cancer cell lines. In patient samples, LYG2 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, LYG2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Lymphoma.
