Q-omics provides the consensus-scored RMDN2 profile across patient tissues and cancer cell-line models. RMDN2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RMDN2 is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, RMDN2 protein abundance shows 34,044 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, COAD, and LSCC as cancer lineages where RMDN2 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 RMDN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RMDN2 survival associations across molecular data types. RMDN2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RMDN2 RNA expression–survival associations across cancer types. High RMDN2 expression shows unfavorable associations in LGG and ACC, but favorable associations in KIRC, SKCM, LUAD and LUSC. 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 RMDN2 RNA expression.
This table summarizes RMDN2 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 10. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RMDN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RMDN2 shows lower tumor expression in COAD, KICH, LUAD, LUSC, READ and BLCA. The COAD box plot shows higher RMDN2 RNA expression in normal versus tumor tissue (log2 FC = −1.754, t-test p < 0.001).
This table shows molecular features associated with RMDN2 in patient tissues and cancer cell lines. In patient samples, RMDN2 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, RMDN2 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 BREAST and BLOOD_Leukemia.
