Q-omics provides the consensus-scored ERP29 profile across patient tissues and cancer cell-line models. ERP29 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ERP29 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, ERP29 protein abundance shows 23,770 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KICH, HNSC, and GBM as cancer lineages where ERP29 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 ERP29 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERP29 survival associations across molecular data types. ERP29 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ERP29 RNA expression–survival associations across cancer types. High ERP29 expression shows unfavorable associations in KICH, LIHC, KIRC, LGG and SKCM, but favorable associations in OV. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KICH as the clearest survival context for ERP29 RNA expression.
This table summarizes ERP29 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 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ERP29. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERP29 shows lower tumor expression in KICH and higher tumor expression in HNSC, STAD, KIRP, BRCA and BLCA. The HNSC box plot shows higher ERP29 RNA expression in tumor versus normal tissue (log2 FC = +0.701, t-test p < 0.001).
This table shows molecular features associated with ERP29 in patient tissues and cancer cell lines. In patient samples, ERP29 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ERP29 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 UPPER_AERODIGESTIVE_TRACT.
