This is a PDF file of a peer-reviewed paper that has been accepted for publication. Although unedited, the content has been subjected to preliminary formatting. Nature is providing this early version of the typeset paper as a service to our authors and readers. The text and figures will undergo copyediting and a proof review before the paper is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

Various studies have presented clinical or in vitro evidence linking bacteria to colorectal cancer, but these bacteria have not previously been concurrently quantified by qPCR in a single cohort. We quantify these bacteria (Fusobacterium spp., Streptococcus gallolyticus, Enterococcus faecalis, Enterotoxigenic Bacteroides fragilis (ETBF), Enteropathogenic Escherichia coli (EPEC), and afaC- or pks-positive E. coli) in paired tumour and normal tissue samples from 55 colorectal cancer patients. We further investigate the relationship between a) the presence and b) the level of colonisation of each bacterial species with site and stage of disease, age, gender, ethnicity and MSI-status. With the exception of S. gallolyticus, we detected all bacteria profiled here in both tumour and normal samples at varying frequencies. ETBF (FDR = 0.001 and 0.002 for normal and tumour samples) and afaC-positive E. coli (FDR = 0.03, normal samples) were significantly enriched in the colon compared to the rectum. ETBF (FDR = 0.04 and 0.002 for normal and tumour samples, respectively) and Fusobacterium spp. (FDR = 0.03 tumour samples) levels were significantly higher in late stage (III/IV) colorectal cancers. Fusobacterium was by far the most common bacteria detected, occurring in 82% and 81% of paired tumour and normal samples. Fusobacterium was also the only bacterium that was significantly higher in tumour compared to normal samples (p = 6e-5). We also identified significant associations between high-level colonisation by Fusobacterium and MSI-H (FDR = 0.05), age (FDR = 0.03) or pks-positive E. coli (FDR = 0.01). Furthermore, we exclusively identified atypical EPEC in our cohort, which has not been previously reported in association with colorectal cancer. By quantifying colorectal cancer-associated bacteria across a single cohort, we uncovered inter- and intra-individual patterns of colonization not previously recognized, as well as important associations with clinicopathological features, especially in the case of Fusobacterium and ETBF.

This is a PDF file of a peer-reviewed paper that has been accepted for publication. Although unedited, the content has been subjected to preliminary formatting. Nature is providing this early version of the typeset paper as a service to our authors and readers. The text and figures will undergo copyediting and a proof review before the paper is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

Background: The functional interplay between tumor cells and their adjacent stroma has been suggested to play crucial roles in the initiation and progression of tumors and the effectiveness of chemotherapy. The extracellular matrix (ECM), a complex network of extracellular proteins, provides both physical and chemicals cues necessary for cell proliferation, survival, and migration. Understanding how ECM composition and biomechanical properties affect cancer progression and response to chemotherapeutic drugs is vital to the development of targeted treatments. Methods: 3D cell-derived-ECMs and esophageal cancer cell lines were used as a model to investigate the effect of ECM proteins on esophageal cancer cell lines response to chemotherapeutics. Immunohistochemical and qRT-PCR evaluation of ECM proteins and integrin gene expression was done on clinical esophageal squamous cell carcinoma biopsies. Esophageal cancer cell lines (WHCO1, WHCO5, WHCO6, KYSE180, KYSE 450 and KYSE 520) were cultured on decellularised ECMs (fibroblasts-derived ECM; cancer cell-derived ECM; combinatorial-ECM) and treated with 0.1% Dimethyl sulfoxide (DMSO), 4.2 µM cisplatin, 3.5 µM 5-fluorouracil and 2.5 µM epirubicin for 24 h. Cell proliferation, cell cycle progression, colony formation, apoptosis, migration and activation of signaling pathways were used as our study endpoints. Results: The expression of collagens, fibronectin and laminins was significantly increased in esophageal squamous cell carcinomas (ESCC) tumor samples compared to the corresponding normal tissue. Decellularised ECMs abrogated the effect of drugs on cancer cell cycling, proliferation and reduced drug induced apoptosis by 20–60% that of those plated on plastic. The mitogen-activated protein kinase-extracellular signal-regulated kinase (MEK-ERK) and phosphoinositide 3-kinase-protein kinase B (PI3K/Akt) signaling pathways were upregulated in the presence of the ECMs. Furthermore, our data show that concomitant addition of chemotherapeutic drugs and the use of collagen- and fibronectin-deficient ECMs through siRNA inhibition synergistically increased cancer cell sensitivity to drugs by 30–50%, and reduced colony formation and cancer cell migration. Conclusion: Our study shows that ECM proteins play a key role in the response of cancer cells to chemotherapy and suggest that targeting ECM proteins can be an effective therapeutic strategy against chemoresistant tumors.

Directed evolution of proteins depends on the production of molecular diversity by random mutagenesis. While a number of methods have been developed for introducing this diversity, the best ways to sample it are not always clear. Here we used simple statistics to analyse completeness and diversity in randomized libraries generated by oligonucleotide-directed mutagenesis, error-prone polymerase chain reaction (epPCR) and in vitro recombination of highly homologous sequences. For oligonucleotide-directed mutagenesis, we derive equations to estimate how complete a given library is expected to be and also to predict the size of library required to give a fixed probability of being 100% complete. We describe the statistical bases for computer programs which estimate the number of distinct variants represented in epPCR and shuffled libraries, dubbed PEDEL and DRIVeR, respectively. These programs allow the user to calculate (rather than guess) the diversity represented in a given library and also provide empirical guidelines for maximizing this diversity. PEDEL and DRIVeR are available at www.bio.cam.ac.uk/ approximately blackburn/stats.html.