Q-omics provides the consensus-scored XPOT profile across patient tissues and cancer cell-line models. XPOT expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, XPOT is differentially expressed in 18, with the highest sampling consensus in HNSC. Additionally, XPOT protein abundance shows 23,420 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight BLCA, HNSC, and LSCC as cancer lineages where XPOT 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 XPOT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes XPOT survival associations across molecular data types. XPOT RNA expression shows survival associations in the most cancer types (28), followed by mutation status (8) 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 XPOT RNA expression–survival associations across cancer types. High XPOT expression shows unfavorable associations in BLCA, MESO, KIRP, UVM, KICH and LIHC. The BLCA 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 BLCA as the clearest survival context for XPOT RNA expression.
This table summarizes XPOT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 18, 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 XPOT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. XPOT shows higher tumor expression in HNSC, COAD, BLCA, KIRC, KIRP and LIHC. The HNSC box plot shows higher XPOT RNA expression in tumor versus normal tissue (log2 FC = +1.217, t-test p < 0.001).
This table shows molecular features associated with XPOT in patient tissues and cancer cell lines. In patient samples, XPOT 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, XPOT 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 LUNG_SCLC and SOFT_TISSUE.
