Q-omics provides the consensus-scored LIPH profile across patient tissues and cancer cell-line models. LIPH expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, LIPH is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, LIPH RNA expression shows 17,168 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UVM, THCA, and THYM as cancer lineages where LIPH 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 LIPH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LIPH survival associations across molecular data types. LIPH RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) 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 LIPH RNA expression–survival associations across cancer types. High LIPH expression shows unfavorable associations in UCEC, KIRC, BRCA and PAAD, but favorable associations in UVM and KICH. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .006). Together, the overview and detailed table identify UVM as the clearest survival context for LIPH RNA expression.
This table summarizes LIPH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for LIPH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LIPH shows lower tumor expression in KIRC, KICH, COAD, LUSC and READ and higher tumor expression in THCA. The THCA box plot shows higher LIPH RNA expression in tumor versus normal tissue (log2 FC = +5.087, t-test p < 0.001).
This table shows molecular features associated with LIPH in patient tissues and cancer cell lines. In patient samples, LIPH shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, LIPH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and PANCREAS.
