Q-omics provides the consensus-scored RPL36 profile across patient tissues and cancer cell-line models. RPL36 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RPL36 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, RPL36 protein abundance shows 21,725 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, KIRC, and PDAC as cancer lineages where RPL36 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 RPL36 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPL36 survival associations across molecular data types. RPL36 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPL36 RNA expression–survival associations across cancer types. High RPL36 expression shows unfavorable associations in ACC, KIRP, KICH, LIHC, SKCM and UCS. 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 RPL36 RNA expression.
This table summarizes RPL36 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RPL36. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPL36 shows higher tumor expression in KIRC, COAD, KIRP, LIHC, THCA and CHOL. The KIRC box plot shows higher RPL36 RNA expression in tumor versus normal tissue (log2 FC = +1.155, t-test p < 0.001).
This table shows molecular features associated with RPL36 in patient tissues and cancer cell lines. In patient samples, RPL36 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, RPL36 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
