Characterizing the mutational burden, DNA methylation landscape, and proteome of germ cell tumor-related somatic-type malignancies to identify the tissue-of-origin, mechanisms of therapy resistance, and druggable targets.
Felix BremmerPailin PongratanakulMargaretha SkowronYue CheAnnika RichterStefan KüfferKirsten Reuter-JessenHanibal BohnenbergerStella PaulsCatena KresbachUlrich SchüllerKai StühlerPhilipp StröbelPeter AlbersDaniel NettersheimPublished in: British journal of cancer (2023)
For the first time, we show that based on DNA methylation and proteome data carcinoma-related STM more closely resemble yolk-sac tumors, while sarcoma-related STM resemble teratoma. STM harbor mutations in FGF signaling factors (FGF6/23, FGFR1/4) highlighting the corresponding pathway as a therapeutic target. Furthermore, STM utilize signaling pathways, like AKT, FGF, MAPK, and WNT to mediate molecular functions coping with oxidative stress, toxin transport, DNA helicase activity, apoptosis and the cell cycle. Collectively, these data might explain the high therapy resistance of STM. Finally, we identified putative novel biomarkers secreted by STM, like EFEMP1, MIF, and DNA methylation at specific CpG dinucleotides.
Keyphrases
- dna methylation
- oxidative stress
- cell cycle
- signaling pathway
- cell proliferation
- genome wide
- gene expression
- electronic health record
- germ cell
- escherichia coli
- stem cells
- pi k akt
- copy number
- big data
- single molecule
- depressive symptoms
- dna damage
- endoplasmic reticulum stress
- machine learning
- ischemia reperfusion injury
- risk factors
- bone marrow
- deep learning
- single cell
- diabetic rats