Q-omics provides the consensus-scored LYST profile across patient tissues and cancer cell-line models. LYST expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, LYST is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, LYST protein abundance shows 25,331 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KICH, HNSC, and LSCC as cancer lineages where LYST 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 LYST — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LYST survival associations across molecular data types. LYST RNA expression shows survival associations in the most cancer types (24), followed by mutation status (11) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LYST RNA expression–survival associations across cancer types. High LYST expression shows unfavorable associations in KICH, LGG and KIRP, but favorable associations in BRCA, KIRC and LAML. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KICH as the clearest survival context for LYST RNA expression.
This table summarizes LYST 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 7. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for LYST. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LYST shows lower tumor expression in COAD, LUSC and UCEC and higher tumor expression in HNSC, KIRC and LIHC. The HNSC box plot shows higher LYST RNA expression in tumor versus normal tissue (log2 FC = +0.695, t-test p < 0.001).
This table shows molecular features associated with LYST in patient tissues and cancer cell lines. In patient samples, LYST shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, LYST RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BONE and SKIN.
