Theodor-Boveri-Institut für Biowissenschaften
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The gastrointestinal tract is abundantly colonized by microbes, yet the translocation of oral species to the intestine is considered a rare aberrant event, and a hallmark of disease. By studying salivary and fecal microbial strain populations of 310 species in 470 individuals from five countries, we found that transmission to, and subsequent colonization of, the large intestine by oral microbes is common and extensive among healthy individuals. We found evidence for a vast majority of oral species to be transferable, with increased levels of transmission in colorectal cancer and rheumatoid arthritis patients and, more generally, for species described as opportunistic pathogens. This establishes the oral cavity as an endogenous reservoir for gut microbial strains, and oral-fecal transmission as an important process that shapes the gastrointestinal microbiome in health and disease.
Eine veränderte Expression des Transkriptionsfaktors MYC wird als entscheidender Faktor für Tumorentstehung und -progress im kolorektalen Karzinom gesehen. Somit ist die Hemmung dessen Expression und Funktion ein zentraler Ansatz bei der zielgerichteten Tumortherapie.
Als geeignete Strategie, sowohl die Halbwertszeit als auch die Translation von MYC zu verringern, erschien eine duale PI3K-/mTOR-Hemmung durch den small molecule-Inhibitor BEZ235. Gegenteilig ist jedoch unter Behandlung mit BEZ235 eine verstärkte MYC-Expression in verschiedenen Kolonkarzinom-Zelllinien zu beobachten. Neben verstärkter Transkription, konnte eine verstärkte IRES-abhängige Translation von MYC nach Hemmung der mTOR-/5´Cap-abhängigen Translation durch BEZ235, als Ursache der MYC-Induktion nachgewiesen werden.
Es konnte gezeigt werden, dass die Induktion von MYC nach PI3K-/mTOR-Hemmung durch eine kompensatorische Aktivierung des MAPK-Signalwegs in Folge einer FOXO-abhängigen Induktion von Rezeptortyrosinkinasen, stattfindet.
Eine mögliche Strategie, diese Feedback-Mechanismen zu umgehen, ist die direkte Hemmung der Translationsinitiation. Hierfür wurden Rocaglamid und dessen Derivat Silvestrol als small molecule-Inhibitoren der eIF4A-Helikase verwendet. Im Gegensatz zur PI3K/mTOR-Hemmung, ist durch eIF4A-Inhibition eine Reduktion der MYC-Proteinexpression in verschiedenen Kolonkarzinom-Zelllinien zu erreichen – ohne einhergehende MAPK-Aktivierung.
Anhand der Ergebnisse kann postuliert werden, dass Silvestrol das Potential besitzt, sowohl die Cap-/eIF4F-abhängie als auch die somit eIF4A-abhängige IRES-vermittelte Translation von MYC zu hemmen.
Weiterhin kann eine proliferationshemmende Wirkung durch Silvestrol auf Kolonkarzinom-Zellen in vitro, via Zellzyklusarrest und Induktion von Apoptose, gezeigt werden. Dies stellt die Voraussetzung für eine potentielle Eignung als tumorhemmender Wirkstoff in der Therapie des kolorektalen Karzinoms dar.
To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.
Colorectal Cancer and the Human Gut Microbiome: Reproducibility with Whole-Genome Shotgun Sequencing
(2016)
Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient power to detect associations that are reproducible and significant after correction for multiple testing.