Q-omics provides the consensus-scored UFM1 profile across patient tissues and cancer cell-line models. UFM1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, UFM1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, UFM1 protein abundance shows 35,072 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight HNSC, and PDAC as cancer lineages where UFM1 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 UFM1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UFM1 survival associations across molecular data types. UFM1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UFM1 RNA expression–survival associations across cancer types. High UFM1 expression shows unfavorable associations in HNSC, CESC, ACC and UVM, but favorable associations in KIRC and SKCM. The HNSC 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 HNSC as the clearest survival context for UFM1 RNA expression.
This table summarizes UFM1 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 11. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for UFM1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UFM1 shows lower tumor expression in THCA and LUSC and higher tumor expression in HNSC, KIRC, STAD and COAD. The HNSC box plot shows higher UFM1 RNA expression in tumor versus normal tissue (log2 FC = +0.848, t-test p < 0.001).
This table shows molecular features associated with UFM1 in patient tissues and cancer cell lines. In patient samples, UFM1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, UFM1 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 BONE and BLOOD_Lymphoma.
