Q-omics provides the consensus-scored LYZ profile across patient tissues and cancer cell-line models. LYZ expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, LYZ is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, LYZ RNA expression shows 20,134 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRC, and GBM as cancer lineages where LYZ 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 LYZ — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LYZ survival associations across molecular data types. LYZ RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LYZ RNA expression–survival associations across cancer types. High LYZ expression shows unfavorable associations in UVM and LGG, but favorable associations in HNSC, KIRC, SKCM and DLBC. The HNSC 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 HNSC as the clearest survival context for LYZ RNA expression.
This table summarizes LYZ tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for LYZ. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LYZ shows lower tumor expression in LUSC, LUAD and HNSC and higher tumor expression in KIRC, THCA and BRCA. The KIRC box plot shows higher LYZ RNA expression in tumor versus normal tissue (log2 FC = +3.048, t-test p < 0.001).
This table shows molecular features associated with LYZ in patient tissues and cancer cell lines. In patient samples, LYZ shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, LYZ RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Myeloma.
