Q-omics provides the consensus-scored ERBB3 profile across patient tissues and cancer cell-line models. ERBB3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ERBB3 is differentially expressed in 16, with the highest sampling consensus in THCA. Additionally, ERBB3 RNA expression shows 20,696 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, THCA, and GBM as cancer lineages where ERBB3 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 ERBB3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERBB3 survival associations across molecular data types. ERBB3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (9) 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 ERBB3 RNA expression–survival associations across cancer types. High ERBB3 expression shows unfavorable associations in LIHC and ACC, but favorable associations in UVM, KIRC, UCS and KIRP. The UVM 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 UVM as the clearest survival context for ERBB3 RNA expression.
This table summarizes ERBB3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 4. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ERBB3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERBB3 shows lower tumor expression in HNSC and KICH and higher tumor expression in THCA, LIHC, KIRC and BLCA. The THCA box plot shows higher ERBB3 RNA expression in tumor versus normal tissue (log2 FC = +2.347, t-test p < 0.001).
This table shows molecular features associated with ERBB3 in patient tissues and cancer cell lines. In patient samples, ERBB3 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, ERBB3 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 BREAST and LARGE_INTESTINE.
