reticulophagy regulator family member 2Genealiases: C2orf17 · FAM134A · MAG-2
Q-omics provides the consensus-scored RETREG2 profile across patient tissues and cancer cell-line models. RETREG2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RETREG2 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, RETREG2 RNA expression shows 19,921 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where RETREG2 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 RETREG2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RETREG2 survival associations across molecular data types. RETREG2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) 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 RETREG2 RNA expression–survival associations across cancer types. High RETREG2 expression shows unfavorable associations in ACC, LIHC and COAD, but favorable associations in KIRC, BRCA and LGG. 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 RETREG2 RNA expression.
This table summarizes RETREG2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for RETREG2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RETREG2 shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRC, LIHC, LUAD and STAD. The HNSC box plot shows higher RETREG2 RNA expression in tumor versus normal tissue (log2 FC = +0.594, t-test p < 0.001).
This table shows molecular features associated with RETREG2 in patient tissues and cancer cell lines. In patient samples, RETREG2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, RETREG2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
