Q-omics provides the consensus-scored MORC1 profile across patient tissues and cancer cell-line models. MORC1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, MORC1 is differentially expressed in 5, with the highest sampling consensus in COAD. Additionally, MORC1 protein abundance shows 12,155 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, COAD, and HNSC as cancer lineages where MORC1 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 MORC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MORC1 survival associations across molecular data types. MORC1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) 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 MORC1 RNA expression–survival associations across cancer types. High MORC1 expression shows unfavorable associations in ACC, LAML, THCA, CHOL and LUAD, but favorable associations in MESO. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify ACC as the clearest survival context for MORC1 RNA expression.
This table summarizes MORC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 4. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for MORC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MORC1 shows lower tumor expression in COAD, KICH, BLCA, PRAD and READ. The COAD box plot shows higher MORC1 RNA expression in normal versus tumor tissue (log2 FC = −0.058, t-test p < 0.001).
This table shows molecular features associated with MORC1 in patient tissues and cancer cell lines. In patient samples, MORC1 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, MORC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in CNS and LARGE_INTESTINE.
