Q-omics provides the consensus-scored MFSD6 profile across patient tissues and cancer cell-line models. MFSD6 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MFSD6 is differentially expressed in 7, with the highest sampling consensus in LIHC. Additionally, MFSD6 protein abundance shows 21,706 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LIHC, and GBM as cancer lineages where MFSD6 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 MFSD6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MFSD6 survival associations across molecular data types. MFSD6 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (7) 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 MFSD6 RNA expression–survival associations across cancer types. High MFSD6 expression shows unfavorable associations in UCS, but favorable associations in KIRC, ACC, HNSC, COAD and SARC. The KIRC 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 KIRC as the clearest survival context for MFSD6 RNA expression.
This table summarizes MFSD6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 2. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for MFSD6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MFSD6 shows lower tumor expression in KIRC, KICH and STAD and higher tumor expression in LIHC, CHOL and PAAD. The LIHC box plot shows higher MFSD6 RNA expression in tumor versus normal tissue (log2 FC = +1.676, t-test p < 0.001).
This table shows molecular features associated with MFSD6 in patient tissues and cancer cell lines. In patient samples, MFSD6 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, MFSD6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
