Q-omics provides the consensus-scored MARK2 profile across patient tissues and cancer cell-line models. MARK2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, MARK2 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, MARK2 protein abundance shows 25,239 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KICH, BLCA, and GBM as cancer lineages where MARK2 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 MARK2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MARK2 survival associations across molecular data types. MARK2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 MARK2 RNA expression–survival associations across cancer types. High MARK2 expression shows unfavorable associations in KICH, LIHC, ACC, PAAD and LUAD, but favorable associations in ESCA. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KICH as the clearest survival context for MARK2 RNA expression.
This table summarizes MARK2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in BLCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for MARK2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MARK2 shows higher tumor expression in BLCA, LIHC, LUAD, STAD, LUSC and BRCA. The BLCA box plot shows higher MARK2 RNA expression in tumor versus normal tissue (log2 FC = +0.985, t-test p < 0.001).
This table shows molecular features associated with MARK2 in patient tissues and cancer cell lines. In patient samples, MARK2 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, MARK2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
