Q-omics provides the consensus-scored OBSCN profile across patient tissues and cancer cell-line models. OBSCN expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, OBSCN is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, OBSCN RNA expression shows 18,791 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LIHC, HNSC, and TGCT as cancer lineages where OBSCN 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 OBSCN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OBSCN survival associations across molecular data types. OBSCN RNA expression shows survival associations in the most cancer types (23), followed by mutation status (11) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OBSCN RNA expression–survival associations across cancer types. High OBSCN expression shows unfavorable associations in LIHC, UCEC, KIRP, SKCM and LGG, but favorable associations in READ. The LIHC 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 LIHC as the clearest survival context for OBSCN RNA expression.
This table summarizes OBSCN 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 3. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for OBSCN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OBSCN shows lower tumor expression in HNSC and BRCA and higher tumor expression in COAD, KIRC, LIHC and CHOL. The HNSC box plot shows higher OBSCN RNA expression in normal versus tumor tissue (log2 FC = −1.245, t-test p = .008).
This table shows molecular features associated with OBSCN in patient tissues and cancer cell lines. In patient samples, OBSCN 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, OBSCN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
