Q-omics provides the consensus-scored SMG7 profile across patient tissues and cancer cell-line models. SMG7 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, SMG7 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, SMG7 protein abundance shows 29,294 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight BLCA, HNSC, and LSCC as cancer lineages where SMG7 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 SMG7 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SMG7 survival associations across molecular data types. SMG7 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SMG7 RNA expression–survival associations across cancer types. High SMG7 expression shows unfavorable associations in BLCA, KIRP, ACC, KICH and UCEC, but favorable associations in KIRC. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify BLCA as the clearest survival context for SMG7 RNA expression.
This table summarizes SMG7 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 9. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SMG7. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SMG7 shows higher tumor expression in HNSC, BLCA, LIHC, STAD, LUSC and LUAD. The HNSC box plot shows higher SMG7 RNA expression in tumor versus normal tissue (log2 FC = +1.330, t-test p < 0.001).
This table shows molecular features associated with SMG7 in patient tissues and cancer cell lines. In patient samples, SMG7 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, SMG7 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
