Q-omics provides the consensus-scored RMI2 profile across patient tissues and cancer cell-line models. RMI2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RMI2 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, RMI2 RNA expression shows 18,813 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where RMI2 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 RMI2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RMI2 survival associations across molecular data types. RMI2 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RMI2 RNA expression–survival associations across cancer types. High RMI2 expression shows unfavorable associations in ACC, KIRP, MESO, LIHC and LGG, but favorable associations in CESC. 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 RMI2 RNA expression.
This table summarizes RMI2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for RMI2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RMI2 shows higher tumor expression in HNSC, BLCA, THCA, KIRP, COAD and LUSC. The HNSC box plot shows higher RMI2 RNA expression in tumor versus normal tissue (log2 FC = +1.864, t-test p < 0.001).
This table shows molecular features associated with RMI2 in patient tissues and cancer cell lines. In patient samples, RMI2 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, RMI2 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 OESOPHAGUS and UPPER_AERODIGESTIVE_TRACT.
