Q-omics provides the consensus-scored CD3G profile across patient tissues and cancer cell-line models. CD3G expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, CD3G is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, CD3G RNA expression shows 17,180 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, KIRC, and UVM as cancer lineages where CD3G 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 CD3G — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CD3G survival associations across molecular data types. CD3G RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CD3G RNA expression–survival associations across cancer types. High CD3G expression shows unfavorable associations in UVM, but favorable associations in SKCM, UCEC, HNSC, BLCA and CESC. The SKCM 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 SKCM as the clearest survival context for CD3G RNA expression.
This table summarizes CD3G tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CD3G. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CD3G shows lower tumor expression in COAD, LUSC and THCA and higher tumor expression in KIRC, STAD and ESCA. The KIRC box plot shows higher CD3G RNA expression in tumor versus normal tissue (log2 FC = +1.850, t-test p < 0.001).
This table shows molecular features associated with CD3G in patient tissues and cancer cell lines. In patient samples, CD3G shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, CD3G RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
