Q-omics provides the consensus-scored IPO11 profile across patient tissues and cancer cell-line models. IPO11 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, IPO11 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, IPO11 protein abundance shows 31,672 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LIHC, and GBM as cancer lineages where IPO11 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 IPO11 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IPO11 survival associations across molecular data types. IPO11 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IPO11 RNA expression–survival associations across cancer types. High IPO11 expression shows unfavorable associations in MESO, LIHC, KICH and OV, but favorable associations in KIRC and READ. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for IPO11 RNA expression.
This table summarizes IPO11 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 13. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IPO11. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IPO11 shows lower tumor expression in THCA and higher tumor expression in LIHC, COAD, KIRC, CHOL and LUAD. The LIHC box plot shows higher IPO11 RNA expression in tumor versus normal tissue (log2 FC = +0.938, t-test p < 0.001).
This table shows molecular features associated with IPO11 in patient tissues and cancer cell lines. In patient samples, IPO11 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, IPO11 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Lymphoma.
