Q-omics provides the consensus-scored MORN1 profile across patient tissues and cancer cell-line models. MORN1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, MORN1 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, MORN1 protein abundance shows 24,415 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KICH, and GBM as cancer lineages where MORN1 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 MORN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MORN1 survival associations across molecular data types. MORN1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MORN1 RNA expression–survival associations across cancer types. High MORN1 expression shows unfavorable associations in ACC, KICH and LGG, but favorable associations in BRCA, UCS and UVM. The ACC 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 ACC as the clearest survival context for MORN1 RNA expression.
This table summarizes MORN1 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 6. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for MORN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MORN1 shows lower tumor expression in KICH and THCA and higher tumor expression in COAD, STAD, BRCA and LIHC. The KICH box plot shows higher MORN1 RNA expression in normal versus tumor tissue (log2 FC = −1.371, t-test p < 0.001).
This table shows molecular features associated with MORN1 in patient tissues and cancer cell lines. In patient samples, MORN1 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, MORN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
