Publications

Objective: The majority of ‘low-risk’ (grade I/II) Ductal Carcinoma In Situ (DCIS) may not progress to invasive breast cancer during a women’s lifetime. Therefore, the safety of active surveillance versus standard surgical treatment for DCIS is prospectively being evaluated in clinical trials. If proven safe and selectively implemented in clinical practice, a significant group of women with low-risk DCIS may forego surgery and radiotherapy in the future. Identification of modifiable and non-modifiable risk factors associated with prognosis after a primary DCIS would also enhance our care of women with low-risk DCIS.

Methods: To identify modifiable and non-modifiable risk factors for subsequent breast events after DCIS, we performed a systematic literature search in PUBMED, EMBASE and Scopus.

Results: Six out of the 3870 articles retrieved were included for final data extraction. These six studies included a total of 4950 patients with primary DCIS and 640 recorded subsequent breast events. There was moderate evidence for an association of a family history of breast cancer, premenopausal status, high BMI, and high breast density with a subsequent breast cancer or further DCIS.

Conclusion: There is a limited number of recent studies published on the impact of modifiable and non-modifiable risk factors on subsequent events after DCIS. The available evidence is insufficient to identify potential targets for risk reduction strategies, reflecting the relatively small numbers and the lack of long-term follow-up in DCIS, a low-event condition.

The impact of the human microbiome on health and disease is of utmost importance and has been studied intensively in recent years. Microbes promote immune system development and are essential to the production and absorption of nutrients for the host but are also implicated in disease pathogenesis. Particularly, bacterial biofilms have long been recognized as contributors to chronic infections and diseases in humans. However, our understanding of how the host responds to the presence of biofilms, specifically the immune response to biofilms, and how this contributes to disease pathogenesis is limited. This review aims to highlight what is known about biofilm formation and in vivo models available for the biofilm study. We critique the contribution of biofilms to human diseases, focusing on the lung diseases, cystic fibrosis and chronic obstructive pulmonary disease, and the gut diseases, inflammatory bowel disease and colorectal cancer.

Various species of the intestinal microbiota have been associated with the development of colorectal cancer, but it has not been demonstrated that bacteria have a direct role in the occurrence of oncogenic mutations. Escherichia coli can carry the pathogenicity island pks, which encodes a set of enzymes that synthesize colibactin. This compound is believed to alkylate DNA on adenine residues and induces double-strand breaks in cultured cells. Here we expose human intestinal organoids to genotoxic pks+ E. coli by repeated luminal injection over five months. Whole-genome sequencing of clonal organoids before and after this exposure revealed a distinct mutational signature that was absent from organoids injected with isogenic pks-mutant bacteria. The same mutational signature was detected in a subset of 5,876 human cancer genomes from two independent cohorts, predominantly in colorectal cancer. Our study describes a distinct mutational signature in colorectal cancer and implies that the underlying mutational process results directly from past exposure to bacteria carrying the colibactin-producing pks pathogenicity island.

Genomic alterations shape cell phenotypes and the structure of tumor ecosystems in poorly defined ways. To investigate these relationships, we used imaging mass cytometry to quantify the expression of 37 proteins with subcellular spatial resolution in 483 tumors from the METABRIC cohort. Single-cell analysis revealed cell phenotypes spanning epithelial, stromal and immune types. Distinct combinations of cell phenotypes and cell–cell interactions were associated with genomic subtypes of breast cancer. Epithelial luminal cell phenotypes separated into those predominantly impacted by mutations and those affected by copy number aberrations. Several features of tumor ecosystems, including cellular neighborhoods, were linked to prognosis, illustrating their clinical relevance. In summary, systematic analysis of single-cell phenotypic and spatial correlates of genomic alterations in cancer revealed how genomes shape both the composition and architecture of breast tumor ecosystems and will enable greater understanding of the phenotypic impact of genomic alterations.

Somatic mutations accumulate in healthy tissues as we age, giving rise to cancer and potentially contributing to ageing. To study somatic mutations in non-neoplastic tissues, we developed a series of protocols to sequence the genomes of small populations of cells isolated from histological sections. Here, we describe a complete workflow that combines laser-capture microdissection (LCM) with low-input genome sequencing, while circumventing the use of whole-genome amplification (WGA). The protocol is subdivided broadly into four steps: tissue processing, LCM, low-input library generation and mutation calling and filtering. The tissue processing and LCM steps are provided as general guidelines that might require tailoring based on the specific requirements of the study at hand. Our protocol for low-input library generation uses enzymatic rather than acoustic fragmentation to generate WGA-free whole-genome libraries. Finally, the mutation calling and filtering strategy has been adapted from previously published protocols to account for artifacts introduced via library creation. To date, we have used this workflow to perform targeted and whole-genome sequencing of small populations of cells (typically 100–1,000 cells) in thousands of microbiopsies from a wide range of human tissues. The low-input DNA protocol is designed to be compatible with liquid handling platforms and make use of equipment and expertise standard to any core sequencing facility. However, obtaining low-input DNA material via LCM requires specialized equipment and expertise. The entire protocol from tissue reception through whole-genome library generation can be accomplished in as little as 1 week, although 2–3 weeks would be a more typical turnaround time.