Q-omics provides the consensus-scored ZMAT2 profile across patient tissues and cancer cell-line models. ZMAT2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ZMAT2 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, ZMAT2 protein abundance shows 22,649 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, LIHC, and GBM as cancer lineages where ZMAT2 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 ZMAT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZMAT2 survival associations across molecular data types. ZMAT2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (1) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZMAT2 RNA expression–survival associations across cancer types. High ZMAT2 expression shows unfavorable associations in HNSC, LUAD, PAAD and LIHC, but favorable associations in KIRC and SKCM. The HNSC 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 HNSC as the clearest survival context for ZMAT2 RNA expression.
This table summarizes ZMAT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ZMAT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZMAT2 shows lower tumor expression in KICH and higher tumor expression in LIHC, KIRC, HNSC, CHOL and BRCA. The LIHC box plot shows higher ZMAT2 RNA expression in tumor versus normal tissue (log2 FC = +1.230, t-test p < 0.001).
This table shows molecular features associated with ZMAT2 in patient tissues and cancer cell lines. In patient samples, ZMAT2 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, ZMAT2 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 BONE and UPPER_AERODIGESTIVE_TRACT.
