Q-omics provides the consensus-scored SMG1P5 profile across patient tissues and cancer cell-line models. SMG1P5 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SMG1P5 is differentially expressed in 8, with the highest sampling consensus in THCA. Additionally, SMG1P5 RNA expression shows 20,215 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, THCA, and UVM as cancer lineages where SMG1P5 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 SMG1P5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SMG1P5 survival associations across molecular data types. SMG1P5 RNA expression shows survival associations in the most cancer types (24). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SMG1P5 RNA expression–survival associations across cancer types. High SMG1P5 expression shows unfavorable associations in LGG and KIRP, but favorable associations in KIRC, HNSC, UCS and SKCM. 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 SMG1P5 RNA expression.
This table summarizes SMG1P5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for SMG1P5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SMG1P5 shows lower tumor expression in THCA, KICH and PRAD and higher tumor expression in KIRC, HNSC and LIHC. The THCA box plot shows higher SMG1P5 RNA expression in normal versus tumor tissue (log2 FC = −0.306, t-test p < 0.001).
This table shows molecular features associated with SMG1P5 in patient tissues and cancer cell lines. In patient samples, SMG1P5 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, SMG1P5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS.
