Q-omics provides the consensus-scored LMO2 profile across patient tissues and cancer cell-line models. LMO2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, LMO2 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, LMO2 RNA expression shows 20,461 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, KICH, and LSCC as cancer lineages where LMO2 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 LMO2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LMO2 survival associations across molecular data types. LMO2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) 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 LMO2 RNA expression–survival associations across cancer types. High LMO2 expression shows unfavorable associations in LGG and UVM, but favorable associations in KIRC, UCEC, SKCM and HNSC. The KIRC 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 KIRC as the clearest survival context for LMO2 RNA expression.
This table summarizes LMO2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for LMO2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LMO2 shows lower tumor expression in KICH, LUAD, COAD, KIRP, LUSC and HNSC. The KICH box plot shows higher LMO2 RNA expression in normal versus tumor tissue (log2 FC = −2.752, t-test p < 0.001).
This table shows molecular features associated with LMO2 in patient tissues and cancer cell lines. In patient samples, LMO2 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, LMO2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BONE and LUNG_SCLC.
