Q-omics provides the consensus-scored MLLT6 profile across patient tissues and cancer cell-line models. MLLT6 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, MLLT6 is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, MLLT6 RNA expression shows 21,066 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KICH as cancer lineages where MLLT6 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 MLLT6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MLLT6 survival associations across molecular data types. MLLT6 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) 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 MLLT6 RNA expression–survival associations across cancer types. High MLLT6 expression shows unfavorable associations in ACC, LIHC and OV, but favorable associations in HNSC, UCS and LGG. The ACC 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 ACC as the clearest survival context for MLLT6 RNA expression.
This table summarizes MLLT6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 3. The strongest signals are observed in KICH for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MLLT6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MLLT6 shows lower tumor expression in KICH, KIRC and BLCA and higher tumor expression in COAD, LIHC and CHOL. The KICH box plot shows higher MLLT6 RNA expression in normal versus tumor tissue (log2 FC = −1.187, t-test p < 0.001).
This table shows molecular features associated with MLLT6 in patient tissues and cancer cell lines. In patient samples, MLLT6 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, MLLT6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
