Q-omics provides the consensus-scored OASL profile across patient tissues and cancer cell-line models. OASL 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, OASL is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, OASL protein abundance shows 15,287 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, HNSC, and LSCC as cancer lineages where OASL 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 OASL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OASL survival associations across molecular data types. OASL RNA expression shows survival associations in the most cancer types (26), 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 OASL RNA expression–survival associations across cancer types. High OASL expression shows unfavorable associations in UVM, ACC, KIRC, PAAD and LGG, but favorable associations in 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 OASL RNA expression.
This table summarizes OASL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for OASL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OASL shows lower tumor expression in LUAD and LUSC and higher tumor expression in HNSC, KIRC, KIRP and BRCA. The HNSC box plot shows higher OASL RNA expression in tumor versus normal tissue (log2 FC = +3.186, t-test p < 0.001).
This table shows molecular features associated with OASL in patient tissues and cancer cell lines. In patient samples, OASL 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, OASL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
