Q-omics provides the consensus-scored IMPA1 profile across patient tissues and cancer cell-line models. IMPA1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, IMPA1 is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, IMPA1 protein abundance shows 34,751 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, LIHC, and GBM as cancer lineages where IMPA1 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 IMPA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IMPA1 survival associations across molecular data types. IMPA1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IMPA1 RNA expression–survival associations across cancer types. High IMPA1 expression shows unfavorable associations in UVM, CESC, LGG, UCEC, OV and KIRP. 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 IMPA1 RNA expression.
This table summarizes IMPA1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 10. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for IMPA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IMPA1 shows lower tumor expression in THCA and COAD and higher tumor expression in LIHC, STAD, HNSC and KIRC. The LIHC box plot shows higher IMPA1 RNA expression in tumor versus normal tissue (log2 FC = +1.134, t-test p < 0.001).
This table shows molecular features associated with IMPA1 in patient tissues and cancer cell lines. In patient samples, IMPA1 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, IMPA1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in CNS and UPPER_AERODIGESTIVE_TRACT.
