Q-omics provides the consensus-scored MCOLN2 profile across patient tissues and cancer cell-line models. MCOLN2 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, MCOLN2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, MCOLN2 RNA expression shows 16,771 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LUAD, HNSC, and UVM as cancer lineages where MCOLN2 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 MCOLN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MCOLN2 survival associations across molecular data types. MCOLN2 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MCOLN2 RNA expression–survival associations across cancer types. High MCOLN2 expression shows unfavorable associations in UVM and LGG, but favorable associations in LUAD, SKCM, CESC and ACC. The LUAD Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify LUAD as the clearest survival context for MCOLN2 RNA expression.
This table summarizes MCOLN2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for MCOLN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MCOLN2 shows lower tumor expression in LUSC and COAD and higher tumor expression in HNSC, STAD, BRCA and KIRC. The HNSC box plot shows higher MCOLN2 RNA expression in tumor versus normal tissue (log2 FC = +0.785, t-test p < 0.001).
This table shows molecular features associated with MCOLN2 in patient tissues and cancer cell lines. In patient samples, MCOLN2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, MCOLN2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and SKIN.
