Q-omics provides the consensus-scored MBL2 profile across patient tissues and cancer cell-line models. MBL2 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MBL2 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, MBL2 protein abundance shows 11,675 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LIHC, and GBM as cancer lineages where MBL2 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 MBL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MBL2 survival associations across molecular data types. MBL2 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MBL2 RNA expression–survival associations across cancer types. High MBL2 expression shows unfavorable associations in KIRC, STAD, HNSC, MESO and BRCA, but favorable associations in ACC. The KIRC 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 KIRC as the clearest survival context for MBL2 RNA expression.
This table summarizes MBL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 4. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for MBL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MBL2 shows lower tumor expression in LIHC, CHOL and BRCA and higher tumor expression in KIRC, LUSC and HNSC. The LIHC box plot shows higher MBL2 RNA expression in normal versus tumor tissue (log2 FC = −2.388, t-test p < 0.001).
This table shows molecular features associated with MBL2 in patient tissues and cancer cell lines. In patient samples, MBL2 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, MBL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in CNS and LARGE_INTESTINE.
