Q-omics provides the consensus-scored SCML2 profile across patient tissues and cancer cell-line models. SCML2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SCML2 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, SCML2 protein abundance shows 28,130 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight MESO, THCA, and LSCC as cancer lineages where SCML2 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 SCML2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCML2 survival associations across molecular data types. SCML2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCML2 RNA expression–survival associations across cancer types. High SCML2 expression shows unfavorable associations in MESO, KICH, LIHC, KIRP and BLCA, but favorable associations in PAAD. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify MESO as the clearest survival context for SCML2 RNA expression.
This table summarizes SCML2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SCML2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCML2 shows lower tumor expression in THCA and KIRC and higher tumor expression in COAD, LIHC, LUSC and HNSC. The THCA box plot shows higher SCML2 RNA expression in normal versus tumor tissue (log2 FC = −1.264, t-test p < 0.001).
This table shows molecular features associated with SCML2 in patient tissues and cancer cell lines. In patient samples, SCML2 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, SCML2 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 BONE and LARGE_INTESTINE.
