Q-omics provides the consensus-scored MRS2 profile across patient tissues and cancer cell-line models. MRS2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, MRS2 is differentially expressed in 15, with the highest sampling consensus in THCA. Additionally, MRS2 protein abundance shows 19,903 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight OV, THCA, and LSCC as cancer lineages where MRS2 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 MRS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MRS2 survival associations across molecular data types. MRS2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) 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 MRS2 RNA expression–survival associations across cancer types. High MRS2 expression shows unfavorable associations in ESCA, KICH and THCA, but favorable associations in OV, READ and BLCA. The OV 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 OV as the clearest survival context for MRS2 RNA expression.
This table summarizes MRS2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for MRS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MRS2 shows lower tumor expression in THCA and higher tumor expression in LIHC, BLCA, BRCA, HNSC and UCEC. The THCA box plot shows higher MRS2 RNA expression in normal versus tumor tissue (log2 FC = −0.958, t-test p < 0.001).
This table shows molecular features associated with MRS2 in patient tissues and cancer cell lines. In patient samples, MRS2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, MRS2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BREAST and UPPER_AERODIGESTIVE_TRACT.
