Q-omics provides the consensus-scored SLTM profile across patient tissues and cancer cell-line models. SLTM 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, SLTM is differentially expressed in 8, with the highest sampling consensus in THCA. Additionally, SLTM protein abundance shows 28,267 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, THCA, and GBM as cancer lineages where SLTM 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 SLTM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLTM survival associations across molecular data types. SLTM RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 SLTM RNA expression–survival associations across cancer types. High SLTM expression shows unfavorable associations in ACC, LUSC, HNSC and KIRP, but favorable associations in KIRC and BRCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for SLTM RNA expression.
This table summarizes SLTM 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 8. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SLTM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLTM shows lower tumor expression in THCA and higher tumor expression in LIHC, HNSC, STAD, BLCA and CHOL. The THCA box plot shows higher SLTM RNA expression in normal versus tumor tissue (log2 FC = −0.929, t-test p < 0.001).
This table shows molecular features associated with SLTM in patient tissues and cancer cell lines. In patient samples, SLTM shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SLTM 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 OVARY and BLOOD_Leukemia.
