Q-omics provides the consensus-scored MCF2L profile across patient tissues and cancer cell-line models. MCF2L expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, MCF2L is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, MCF2L RNA expression shows 24,404 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where MCF2L 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 MCF2L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MCF2L survival associations across molecular data types. MCF2L RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MCF2L RNA expression–survival associations across cancer types. High MCF2L expression shows unfavorable associations in ACC and MESO, but favorable associations in UCEC, HNSC, BLCA and KIRC. 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 MCF2L RNA expression.
This table summarizes MCF2L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for MCF2L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MCF2L shows lower tumor expression in KICH and THCA and higher tumor expression in KIRC, COAD, STAD and LIHC. The KIRC box plot shows higher MCF2L RNA expression in tumor versus normal tissue (log2 FC = +1.089, t-test p < 0.001).
This table shows molecular features associated with MCF2L in patient tissues and cancer cell lines. In patient samples, MCF2L 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, MCF2L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
