Q-omics provides the consensus-scored LOXL4 profile across patient tissues and cancer cell-line models. LOXL4 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, LOXL4 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, LOXL4 RNA expression shows 17,178 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UVM, KICH, and TGCT as cancer lineages where LOXL4 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 LOXL4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LOXL4 survival associations across molecular data types. LOXL4 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LOXL4 RNA expression–survival associations across cancer types. High LOXL4 expression shows unfavorable associations in UVM, STAD, OV and LGG, but favorable associations in UCS and SKCM. The UVM 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 UVM as the clearest survival context for LOXL4 RNA expression.
This table summarizes LOXL4 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 5. The strongest signals are observed in BRCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for LOXL4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LOXL4 shows lower tumor expression in KICH, BRCA, KIRC, COAD and UCEC and higher tumor expression in LIHC. The KICH box plot shows higher LOXL4 RNA expression in normal versus tumor tissue (log2 FC = −4.278, t-test p < 0.001).
This table shows molecular features associated with LOXL4 in patient tissues and cancer cell lines. In patient samples, LOXL4 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, LOXL4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BONE.
