maestro heat like repeat family member 2BGenealiases: HEATR7B2 · SPIF
Q-omics provides the consensus-scored MROH2B profile across patient tissues and cancer cell-line models. MROH2B expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, MROH2B is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, MROH2B RNA expression shows 12,104 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, BLCA, and LSCC as cancer lineages where MROH2B 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 MROH2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MROH2B survival associations across molecular data types. MROH2B RNA expression shows survival associations in the most cancer types (18), followed by mutation status (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MROH2B RNA expression–survival associations across cancer types. High MROH2B expression shows unfavorable associations in STAD, LUAD, LGG and CESC, but favorable associations in ACC and ESCA. The ACC 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 ACC as the clearest survival context for MROH2B RNA expression.
This table summarizes MROH2B 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 1. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MROH2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MROH2B shows lower tumor expression in BLCA, KIRC, KIRP, LUSC, UCEC and BRCA. The BLCA box plot shows higher MROH2B RNA expression in normal versus tumor tissue (log2 FC = −0.051, t-test p = .001).
This table shows molecular features associated with MROH2B in patient tissues and cancer cell lines. In patient samples, MROH2B shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, MROH2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LARGE_INTESTINE.
