Publications

As ongoing trials study the safety of an active surveillance strategy for low-risk ductal carcinoma in situ (DCIS), there is a need to explain why particular choices regarding treatment strategies are made by eligible women as well as their oncologists, what factors enter the decision process, and how much each factor affects their choice. To measure preferences for treatment and surveillance strategies, women with newly-diagnosed, primary low-risk DCIS enrolled in the Dutch CONTROL DCIS Registration and LORD trial, and oncologists participating in the Dutch Health Professionals Study were invited to complete a discrete choice experiment (DCE). The relative importance of treatment strategy-related attributes (locoregional intervention, 10-year risk of ipsilateral invasive breast cancer (iIBC), and follow-up interval) were discerned using conditional logit models. A total of n = 172 patients and n = 30 oncologists completed the DCE. Patient respondents had very strong preferences for an active surveillance strategy with no surgery, irrespective of the 10-year risk of iIBC. Extensiveness of the locoregional treatment was consistently shown to be an important factor for patients and oncologists in deciding upon treatment strategies. Risk of iIBC was least important to patients and most important to oncologists. There was a stronger inclination toward a twice-yearly follow-up for both groups compared to annual follow-up. 

Next generation sequencing technologies (NGS) have been critical in characterizing the genomic landscape and untangling the genetic heterogeneity of human cancer. Since its advent, NGS has played a pivotal role in identifying the patterns of somatic mutations imprinted on cancer genomes and in deciphering the signatures of the mutational processes that have generated these patterns. Mutational signatures serve as phenotypic molecular footprints of exposures to environmental factors as well as deficiency and infidelity of DNA replication and repair pathways. Since the first roadmap of mutational signatures in human cancer was generated from whole-genome and whole-exome sequencing data, there has been a growing interest to extract mutational signatures from other NGS technologies such as targeted panel sequencing, RNA sequencing, single-cell sequencing, duplex sequencing, reduced representation sequencing, and long-read sequencing. Many of these technologies have their inherent sequencing biases and produce technical artifacts that can confound the extraction of reliable and interpretable mutational signatures. In this review, we highlight the relevance, limitations, and prospects of using different NGS technologies for examining mutational patterns and for deciphering mutational signatures.

Advances in multiplexed imaging technologies have drastically improved our ability to characterize healthy and diseased tissues at the single-cell level. Co-detection by indexing (CODEX) relies on DNA-conjugated antibodies and the cyclic addition and removal of complementary fluorescently labeled DNA probes and has been used so far to simultaneously visualize up to 60 markers in situ. CODEX enables a deep view into the single-cell spatial relationships in tissues and is intended to spur discovery in developmental biology, disease and therapeutic design. Herein, we provide optimized protocols for conjugating purified antibodies to DNA oligonucleotides, validating the conjugation by CODEX staining and executing the CODEX multicycle imaging procedure for both formalin-fixed, paraffin-embedded (FFPE) and fresh-frozen tissues. In addition, we describe basic image processing and data analysis procedures. We apply this approach to an FFPE human tonsil multicycle experiment. The hands-on experimental time for antibody conjugation is ~4.5 h, validation of DNA-conjugated antibodies with CODEX staining takes ~6.5 h and preparation for a CODEX multicycle experiment takes ~8 h. The multicycle imaging and data analysis time depends on the tissue size, number of markers in the panel and computational complexity.

Colorectal cancer is multifaceted, with subtypes defined by genetic, histologic, and immunologic features that are potentially influenced by inflammation, mutagens, and/or microbiota. Colorectal cancers with activating mutations in BRAF are associated with distinct clinical characteristics, although the pathogenesis is not well understood. The Wnt-driven multiple intestinal neoplasia (Min^ApcΔ716/+) enterotoxigenic Bacteroides fragilis (ETBF) murine model is characterized by IL17-dependent, distal colon adenomas. Herein, we report that the addition of the BRAF^V600E mutation to this model results in the emergence of a distinct locus of midcolon tumors. In ETBF-colonized BRAF^V600ELgr5^CreMin (BLM) mice, tumors have similarities to human BRAF^V600E tumors, including histology, CpG island DNA hypermethylation, and immune signatures. In comparison to Min ETBF tumors, BLM ETBF tumors are infiltrated by CD8⁺ T cells, express IFNγ signatures, and are sensitive to anti–PD-L1 treatment. These results provide direct evidence for critical roles of host genetic and microbiota interactions in colorectal cancer pathogenesis and sensitivity to immunotherapy.

Significance: Colorectal cancers with BRAF mutations have distinct characteristics. We present evidence of specific colorectal cancer gene–microbial interactions in which colonization with toxigenic bacteria drives tumorigenesis in BRAF^V600ELgr5^CreMin mice, wherein tumors phenocopy aspects of human BRAF-mutated tumors and have a distinct IFNγ-dominant immune microenvironment uniquely responsive to immune checkpoint blockade.

Shotgun metatranscriptomics (MTX) is an increasingly practical way to survey microbial community gene function and regulation at scale. This review begins by summarizing the motivations for community transcriptomics and the history of the field. We then explore the principles, best practices, and challenges of contemporary MTX workflows: beginning with laboratory methods for isolation and sequencing of community RNA, followed by informatics methods for quantifying RNA features, and finally statistical methods for detecting differential expression in a community context. In thesecond half of the review, we survey important biological findings from the MTX literature, drawing examples from the human microbiome, other (nonhuman) host-associated microbiomes, and the environment. Across these examples, MTX methods prove invaluable for probing microbe–microbe and host–microbe interactions, the dynamics of energy harvest and chemical cycling, and responses to environmental stresses. We conclude with a review of open challenges in the MTX field, including making assays and analyses more robust, accessible, and adaptable to new technologies; deciphering roles for millions of uncharacterized microbial transcripts; and solving applied problems such as biomarker discovery and development of microbial therapeutics.