Q-omics provides the consensus-scored SCML4 profile across patient tissues and cancer cell-line models. SCML4 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SCML4 is differentially expressed in 9, with the highest sampling consensus in LUSC. Additionally, SCML4 RNA expression shows 18,259 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, LUSC, and LSCC as cancer lineages where SCML4 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 SCML4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCML4 survival associations across molecular data types. SCML4 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCML4 RNA expression–survival associations across cancer types. High SCML4 expression shows unfavorable associations in UVM and LGG, but favorable associations in HNSC, BRCA, OV and LUAD. The HNSC 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 HNSC as the clearest survival context for SCML4 RNA expression.
This table summarizes SCML4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 1. The strongest signals are observed in LUSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SCML4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCML4 shows lower tumor expression in LUSC, THCA, KICH and BLCA and higher tumor expression in KIRC and ESCA. The LUSC box plot shows higher SCML4 RNA expression in normal versus tumor tissue (log2 FC = −1.137, t-test p < 0.001).
This table shows molecular features associated with SCML4 in patient tissues and cancer cell lines. In patient samples, SCML4 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, SCML4 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 OVARY and BLOOD_Leukemia.
