Q-omics provides the consensus-scored TMEM100 profile across patient tissues and cancer cell-line models. TMEM100 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, TMEM100 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, TMEM100 RNA expression shows 15,540 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRP, COAD, and PDAC as cancer lineages where TMEM100 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 TMEM100 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TMEM100 survival associations across molecular data types. TMEM100 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (1) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TMEM100 RNA expression–survival associations across cancer types. High TMEM100 expression shows unfavorable associations in KIRP and BLCA, but favorable associations in LGG, ACC, CHOL and LIHC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRP as the clearest survival context for TMEM100 RNA expression.
This table summarizes TMEM100 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 3. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for TMEM100. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TMEM100 shows lower tumor expression in COAD, LUAD, HNSC, LUSC, BLCA and STAD. The COAD box plot shows higher TMEM100 RNA expression in normal versus tumor tissue (log2 FC = −2.694, t-test p < 0.001).
This table shows molecular features associated with TMEM100 in patient tissues and cancer cell lines. In patient samples, TMEM100 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, TMEM100 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and SKIN.
