Q-omics provides the consensus-scored OLFM2 profile across patient tissues and cancer cell-line models. OLFM2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, OLFM2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, OLFM2 RNA expression shows 16,079 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight COAD, HNSC, and ESCA as cancer lineages where OLFM2 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 OLFM2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OLFM2 survival associations across molecular data types. OLFM2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) 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 OLFM2 RNA expression–survival associations across cancer types. High OLFM2 expression shows unfavorable associations in COAD, SKCM, KIRC and KIRP, but favorable associations in HNSC and ESCA. The COAD 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 COAD as the clearest survival context for OLFM2 RNA expression.
This table summarizes OLFM2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for OLFM2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OLFM2 shows lower tumor expression in KIRC, KICH and THCA and higher tumor expression in HNSC, COAD and KIRP. The HNSC box plot shows higher OLFM2 RNA expression in tumor versus normal tissue (log2 FC = +1.083, t-test p < 0.001).
This table shows molecular features associated with OLFM2 in patient tissues and cancer cell lines. In patient samples, OLFM2 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, OLFM2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BONE.
