Q-omics provides the consensus-scored MYT1L profile across patient tissues and cancer cell-line models. MYT1L expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, MYT1L is differentially expressed in 8, with the highest sampling consensus in THCA. Additionally, MYT1L RNA expression shows 13,796 significant gene co-expression associations, with the highest sampling consensus in PCPG. Together, these results highlight KICH, THCA, and PCPG as cancer lineages where MYT1L 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 MYT1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MYT1L survival associations across molecular data types. MYT1L RNA expression shows survival associations in the most cancer types (23), followed by mutation status (9) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MYT1L RNA expression–survival associations across cancer types. High MYT1L expression shows unfavorable associations in KICH, THCA, MESO, LIHC and KIRC, but favorable associations in LGG. The KICH 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 KICH as the clearest survival context for MYT1L RNA expression.
This table summarizes MYT1L 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 2. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MYT1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MYT1L shows lower tumor expression in THCA, COAD, KICH, READ, STAD and BLCA. The THCA box plot shows higher MYT1L RNA expression in normal versus tumor tissue (log2 FC = −0.086, t-test p < 0.001).
This table shows molecular features associated with MYT1L in patient tissues and cancer cell lines. In patient samples, MYT1L shows the broadest associations at the RNA and protein expression levels, with PCPG recurring as the lineage with the largest associated feature set. In cancer cell lines, MYT1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
