Q-omics provides the consensus-scored R3HDML profile across patient tissues and cancer cell-line models. R3HDML expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, R3HDML is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, R3HDML RNA expression shows 11,036 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRC, and ESCA as cancer lineages where R3HDML 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 R3HDML — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes R3HDML survival associations across molecular data types. R3HDML RNA expression shows survival associations in the most cancer types (18), followed by mutation status (6) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible R3HDML RNA expression–survival associations across cancer types. High R3HDML expression shows unfavorable associations in KIRC, LUSC, ACC, CESC and BRCA, but favorable associations in UCS. The KIRC 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 KIRC as the clearest survival context for R3HDML RNA expression.
This table summarizes R3HDML tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for R3HDML. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. R3HDML shows lower tumor expression in KIRC, KIRP and KICH and higher tumor expression in COAD, STAD and BRCA. The KIRC box plot shows higher R3HDML RNA expression in normal versus tumor tissue (log2 FC = −0.142, t-test p < 0.001).
This table shows molecular features associated with R3HDML in patient tissues and cancer cell lines. In patient samples, R3HDML shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, R3HDML RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SKIN.
