Q-omics provides the consensus-scored ASGR2 profile across patient tissues and cancer cell-line models. ASGR2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, ASGR2 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, ASGR2 RNA expression shows 17,319 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight CESC, KICH, and LSCC as cancer lineages where ASGR2 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 ASGR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ASGR2 survival associations across molecular data types. ASGR2 RNA expression shows survival associations in the most cancer types (23), 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 ASGR2 RNA expression–survival associations across cancer types. High ASGR2 expression shows unfavorable associations in STAD and SCLC, but favorable associations in CESC, SKCM, LIHC and HNSC. The CESC 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 CESC as the clearest survival context for ASGR2 RNA expression.
This table summarizes ASGR2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ASGR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ASGR2 shows lower tumor expression in KICH, KIRP, LUSC and BLCA and higher tumor expression in STAD and THCA. The KICH box plot shows higher ASGR2 RNA expression in normal versus tumor tissue (log2 FC = −1.181, t-test p < 0.001).
This table shows molecular features associated with ASGR2 in patient tissues and cancer cell lines. In patient samples, ASGR2 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, ASGR2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
