Q-omics provides the consensus-scored OXSM profile across patient tissues and cancer cell-line models. OXSM expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, OXSM is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, OXSM RNA expression shows 19,203 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, BLCA, and ACC as cancer lineages where OXSM 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 OXSM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OXSM survival associations across molecular data types. OXSM RNA expression shows survival associations in the most cancer types (18), followed by mutation status (4) 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 OXSM RNA expression–survival associations across cancer types. High OXSM expression shows unfavorable associations in KICH and LIHC, but favorable associations in UCEC, COAD, READ and KIRC. The KICH 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 KICH as the clearest survival context for OXSM RNA expression.
This table summarizes OXSM 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 5. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for OXSM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OXSM shows lower tumor expression in THCA and higher tumor expression in BLCA, STAD, UCEC, LIHC and BRCA. The BLCA box plot shows higher OXSM RNA expression in tumor versus normal tissue (log2 FC = +0.803, t-test p < 0.001).
This table shows molecular features associated with OXSM in patient tissues and cancer cell lines. In patient samples, OXSM shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, OXSM RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and UPPER_AERODIGESTIVE_TRACT.
