Mukesh Verma

Detecting circulating tumor material and digital pathology imaging during pancreatic cancer progression

Developments in the diagnosis and treatment of colorectal cancer (CRC) have been made in the last decade, but the overall survival rate of patients with CRC has not improved dramatically. Genetic and epigenetic events contribute to CRC pathogenesis. Tumor heterogeneity results in a range of prognoses and responses to CRC management and therapy. Epigenetic biomarkers have potential in CRC diagnosis and in measuring response to therapy. Combining information from genetic and epigenetic alterations provides an opportunity to predict response to therapy. Epigenetic biomarkers can be used in disease stratification, which also helps in designing therapeutic approaches for CRC. Challenges in the understanding of CRC development and gaps in knowledge are discussed.

This article reviews the significance of the microbiome in cancer epidemiology, mechanistic and technical challenges in the field, and characterization of the microbiome in different tumor types to identify biomarkers of risk, progression, and prognosis. Publications on the microbiome and cancer epidemiology were reviewed to analyze sample collection and processing, microbiome taxa characterization by 16S ribosomal RNA sequencing, and microbiome metabolite characterization (metabotyping) by nuclear magnetic resonance and mass spectrometry. The analysis identified methodology types, research design, sample types, and issues in integrating data from different platforms. Aerodigestive cancer epidemiology studies conducted by different groups demonstrated the significance of microbiome information in developing approaches to improve health. Challenges exist in sample preparation and processing (eg, standardization of methods for collection and analysis). These challenges relate to technology, data integration from “omics” studies, inherent bias in primer selection during 16S ribosomal RNA sequencing, the need for large consortia with well-characterized biospecimens, cause and effect issues, resilience of microbiota to exposure events (requires longitudinal studies), and expanding studies for fungal and viral diversity (most studies used bacterial 16S ribosomal RNA sequencing for microbiota characterization). Despite these challenges, microbiome and cancer epidemiology studies are significant and may facilitate cancer risk assessment, diagnosis, and prognosis. In the future, clinical trials likely will use microbiota modifications to improve the efficacy of existing treatments.

Completion of the human genome a decade ago laid the foundation for: using genetic information in assessing risk to identify individuals and populations that are likely to develop cancer, and designing treatments based on a person's genetic profiling (precision medicine). Genome-wide association studies (GWAS) completed during the past few years have identified risk-associated single nucleotide polymorphisms that can be used as screening tools in epidemiologic studies of a variety of tumor types. This led to the conduct of epigenome-wide association studies (EWAS). This article discusses the current status, challenges and research opportunities in GWAS and EWAS. Information gained from GWAS and EWAS has potential applications in cancer control and treatment.

Metabolomics is the study of low molecular weight molecules or metabolites produced within cells and biological systems. It involves technologies such as mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) that can measure hundreds of thousands of unique chemical entities (UCEs). The metabolome provides one of the most accurate reflections of cellular activity at the functional level and can be leveraged to discern mechanistic information during normal and disease states. The advantages of metabolomics over other “omics” include its high sensitivity and ability to enable the analysis of relatively few metabolites compared with the number of genes and messenger RNAs (mRNAs). In clinical samples, metabolites are more stable than proteins or RNA. In fact, metabolomic profiling in basic, epidemiologic, clinical, and translational studies has revealed potential new biomarkers of disease and therapeutic outcome and has led to a novel mechanistic understanding of pathogenesis. These potential biomarkers include novel metabolites associated with cancer initiation, regression, and recurrence. Unlike genomics or even proteomics, however, the degree of metabolite complexity and heterogeneity within biological systems presents unique challenges that require specialized skills and resources to overcome. This article discusses epidemiologic studies of altered metabolite profiles in several cancers as well as challenges in the field and potential approaches to overcoming them.

Both normal and diseased cells continuously shed extracellular vesicles (EVs) into extracellular space, and the EVs carry molecular signatures and effectors of both health and disease. EVs reflect dynamic changes that are occurring in cells and tissue microenvironment in health and at a different stage of a disease. EVs are capable of altering the function of the recipient cells. Trafficking and reciprocal exchange of molecular information by EVs among different organs and cell types have been shown to contribute to horizontal cellular transformation, cellular reprogramming, functional alterations, and metastasis. EV contents may include tumor suppressors, phosphoproteins, proteases, growth factors, bioactive lipids, mutant oncoproteins, oncogenic transcripts, microRNAs, and DNA sequences. Therefore, the EVs present in biofluids offer unprecedented, remote, and non-invasive access to crucial molecular information about the health status of cells, including their driver mutations, classifiers, molecular subtypes, therapeutic targets, and biomarkers of drug resistance. In addition, EVs may offer a non-invasive means to assess cancer initiation, progression, risk, survival, and treatment outcomes. The goal of this review is to highlight the current status of information on the role of EVs in cancer, and to explore the utility of EVs for cancer diagnosis, prognosis, and epidemiology.