Q-omics provides the consensus-scored ERMP1 profile across patient tissues and cancer cell-line models. ERMP1 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, ERMP1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, ERMP1 protein abundance shows 25,607 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where ERMP1 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 ERMP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERMP1 survival associations across molecular data types. ERMP1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) 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 ERMP1 RNA expression–survival associations across cancer types. High ERMP1 expression shows unfavorable associations in ACC, LIHC, DLBC and MESO, but favorable associations in KIRC and GBM. 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 ERMP1 RNA expression.
This table summarizes ERMP1 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 11. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ERMP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERMP1 shows lower tumor expression in KIRC and KIRP and higher tumor expression in LIHC, BLCA, BRCA and STAD. The KIRC box plot shows higher ERMP1 RNA expression in normal versus tumor tissue (log2 FC = −2.347, t-test p < 0.001).
This table shows molecular features associated with ERMP1 in patient tissues and cancer cell lines. In patient samples, ERMP1 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, ERMP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
