Publications

Background: Cancer genomes are peppered with somatic mutations imprinted by different mutational processes. The mutational pattern of a cancer genome can be used to identify and understand the etiology of the underlying mutational processes. A plethora of prior research has focused on examining mutational signatures and mutational patterns from single base substitutions and their immediate sequencing context. We recently demonstrated that further classification of small mutational events (including substitutions, insertions, deletions, and doublet substitutions) can be used to provide a deeper understanding of the mutational processes that have molded a cancer genome. However, there has been no standard tool that allows fast, accurate, and comprehensive classification for all types of small mutational events.

Results: Here, we present SigProfilerMatrixGenerator, a computational tool designed for optimized exploration and visualization of mutational patterns for all types of small mutational events. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment. SigProfilerMatrixGenerator produces fourteen distinct matrices by considering transcriptional strand bias of individual events and by incorporating distinct classifications for single base substitutions, doublet base substitutions, and small insertions and deletions. While the tool provides a comprehensive classification of mutations, SigProfilerMatrixGenerator is also faster and more memory efficient than existing tools that generate only a single matrix.

Conclusions: SigProfilerMatrixGenerator provides a standardized method for classifying small mutational events that is both efficient and scalable to large datasets. In addition to extending the classification of single base substitutions, the tool is the first to provide support for classifying doublet base substitutions and small insertions and deletions.

Immunotherapy with checkpoint inhibitors, such as the programmed death-1 (PD-1) antibodies pembrolizumab and nivolumab, are effective in a variety of tumors, yet not all patients respond. Tumor microsatellite instability-high (MSI-H) has emerged as a biomarker of response to checkpoint blockade, leading to the tissue agnostic approval of pembrolizumab in MSI-H cancers. Here we describe a patient with MSI-H colorectal cancer that was treated with this immune checkpoint inhibitor and exhibited progression of disease. We examined this intrinsic resistance through genomic, transcriptional, and pathologic characterization of the patient's tumor and the associated immune microenvironment. The tumor had typical MSI-H molecular features, including a high neoantigen load. We also identified biallelic loss of the gene for β2-microglobulin (B2M), whose product is critical for antigen presentation. Immune infiltration deconvolution analysis of bulk transcriptome data from this anti-PD-1–resistant tumor and hundreds of other colorectal cancer specimens revealed a high natural killer cell and M2 macrophage infiltration in the patient's cancer. This was confirmed by single-cell transcriptome analysis and multiplex immunofluorescence. Our study provides insight into resistance in MSI-H tumors and suggests immunotherapeutic strategies in additional genomic contexts of colorectal cancer.

There is ample evidence that inflammatory processes and signaling play a critical role in the progression of most cancers (1), especially as potent initiators at sites of chronic injury (2). In these chronic inflammation–associated cancers (CIACs), tissue injury is caused by sustained or recurrent infection, irritation, or trauma. This distinct class of malignancies, which includes acid reflux–associated esophageal adenocarcinoma (EAC), smoking-associated lung squamous cell carcinoma, Helicobacter pylori infection–associated gastric adenocarcinoma, and inflammatory bowel disease–associated colon adenocarcinoma, is responsible for 20 to 25% of all cancer deaths worldwide, killing more than 2 million people annually. Compared with other tumor types, CIACs tend to have a poorer prognosis, attributable to a high propensity for metastasis and drug resistance. The underlying mechanisms by which chronic inflammation promotes the development of such lethal cancers are still poorly understood.

Ductal carcinoma in situ (DCIS) now represents 20–25% of all ‘breast cancers’ consequent upon detection by population-based breast cancer screening programmes. Currently, all DCIS lesions are treated, and treatment comprises either mastectomy or breast-conserving surgery supplemented with radiotherapy. However, most DCIS lesions remain indolent. Difficulty in discerning harmless lesions from potentially invasive ones can lead to overtreatment of this condition in many patients. To counter overtreatment and to transform clinical practice, a global, comprehensive and multidisciplinary collaboration is required. Here we review the incidence of DCIS, the perception of risk for developing invasive breast cancer, the current treatment options and the known molecular aspects of progression. Further research is needed to gain new insights for improved diagnosis and management of DCIS, and this is integrated in the PRECISION (PREvent ductal Carcinoma In Situ Invasive Overtreatment Now) initiative. This international effort will seek to determine which DCISs require treatment and prevent the consequences of overtreatment on the lives of many women affected by DCIS.

The human microbiota is the collection of microorganisms—bacteria, archaea, viruses, fungi, protozoa, and helminths—that populate the human body. They are emerging as an important feature of human health and disease. Currently, access to the genomic data of human cells and of microbiota (microbiomes) is more affordable and accessible than ever before. A major challenge is to unravel how we integrate microbiome data into precision medicine approaches for the prevention, diagnosis, and treatment of diseases such as cancer. The gastrointestinal (GI) tract is densely populated with microorganisms. Colorectal cancer (CRC) is the third most prevalent cancer worldwide. It is increasing in individuals less than 50 years old and is associated with specific dietary factors and eating patterns that affect the gut microbiota. Therefore, CRC seems ripe for microbiome-based prevention, diagnostics, and therapeutics.