Q-omics provides the consensus-scored OBP2A profile across patient tissues and cancer cell-line models. OBP2A expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, OBP2A is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, OBP2A protein abundance shows 20,553 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, HNSC, and LSCC as cancer lineages where OBP2A 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 OBP2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OBP2A survival associations across molecular data types. OBP2A RNA expression shows survival associations in the most cancer types (19), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OBP2A RNA expression–survival associations across cancer types. High OBP2A expression shows unfavorable associations in KIRC, UVM, LIHC, OV, KIRP and MESO. The KIRC 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 KIRC as the clearest survival context for OBP2A RNA expression.
This table summarizes OBP2A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for OBP2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OBP2A shows higher tumor expression in HNSC, BLCA, COAD, KIRC, THCA and LUSC. The HNSC box plot shows higher OBP2A RNA expression in tumor versus normal tissue (log2 FC = +0.401, t-test p < 0.001).
This table shows molecular features associated with OBP2A in patient tissues and cancer cell lines. In patient samples, OBP2A 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, OBP2A 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 BLOOD_Myeloma and SOFT_TISSUE.
