Q-omics provides the consensus-scored MARK3 profile across patient tissues and cancer cell-line models. MARK3 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, MARK3 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, MARK3 RNA expression shows 21,303 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where MARK3 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 MARK3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MARK3 survival associations across molecular data types. MARK3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MARK3 RNA expression–survival associations across cancer types. High MARK3 expression shows unfavorable associations in ACC, UVM, LIHC and HNSC, but favorable associations in BRCA and OV. 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 MARK3 RNA expression.
This table summarizes MARK3 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 8. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MARK3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MARK3 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, BLCA, STAD and COAD. The HNSC box plot shows higher MARK3 RNA expression in tumor versus normal tissue (log2 FC = +1.263, t-test p < 0.001).
This table shows molecular features associated with MARK3 in patient tissues and cancer cell lines. In patient samples, MARK3 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, MARK3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
