Characterizing the ecological and evolutionary dynamics of cancer

The role of single-cell sequencing in studying tumour evolution

Tumour evolution is a complex interplay between the acquisition of somatic (epi)genomic changes in tumour cells and the phenotypic consequences they cause, all in the context of a changing microenvironment. Single-cell sequencing offers a window into this dynamic process at the ultimate resolution of individual cells. In this review, we discuss the transformative insight offered by single-cell sequencing technologies for understanding tumour evolution.

Back to the future: Reintegrating biology to understand how past eco-evolutionary change can predict future outcomes

During the last few decades, biologists have made remarkable progress in understanding the fundamental processes that shape life. But despite the unprecedented level of knowledge now available, large gaps still remain in our understanding of the complex interplay of eco-evolutionary mechanisms across scales of life. Rapidly changing environments on Earth provide a pressing need to understand the potential implications of eco-evolutionary dynamics, which can be achieved by improving existing eco-evolutionary models and fostering convergence among the sub-fields of biology. We propose a new, data-driven approach that harnesses our knowledge of the functioning of biological systems to expand current conceptual frameworks and develop corresponding models that can more accurately represent and predict future eco-evolutionary outcomes. We suggest a roadmap toward achieving this goal. This long-term vision will move biology in a direction that can wield these predictive models for scientific applications that benefit humanity and increase the resilience of natural biological systems. We identify short, medium, and long-term key objectives to connect our current state of knowledge to this long-term vision, iteratively progressing across three stages: 1) utilizing knowledge of biological systems to better inform eco-evolutionary models, 2) generating models with more accurate predictions, and 3) applying predictive models to benefit the biosphere. Within each stage, we outline avenues of investigation and scientific applications related to the timescales over which evolution occurs, the parameter space of eco-evolutionary processes, and the dynamic interactions between these mechanisms. The ability to accurately model, monitor, and anticipate eco-evolutionary changes would be transformational to humanity's interaction with the global environment, providing novel tools to benefit human health, protect the natural world, and manage our planet's biosphere.

Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes

Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin, and drivers of ITH across cancer types are poorly understood. To address this, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types and identify cancer type-specific subclonal patterns of driver gene mutations, fusions, structural variants, and copy number alterations as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution and provide a pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.

Superlinear growth reveals the Allee effect in tumors

Integrating experimental data into ecological models plays a central role in understanding biological mechanisms that drive tumor progression where such knowledge can be used to develop new therapeutic strategies. While the current studies emphasize the role of competition among tumor cells, they fail to explain recently observed superlinear growth dynamics across human tumors. Here we study tumor growth dynamics by developing a model that incorporates evolutionary dynamics inside tumors with tumor-microenvironment interactions. Our results reveal that tumor cells' ability to manipulate the environment and induce angiogenesis drives superlinear growth-a process compatible with the Allee effect. In light of this understanding, our model suggests that, for high-risk tumors that have a higher growth rate, suppressing angiogenesis can be the appropriate therapeutic intervention.

Emerging nanotaxanes for cancer therapy

The clinical application of taxane (including paclitaxel, docetaxel, and cabazitaxel)-based formulations is significantly impeded by their off-target distribution, unsatisfactory release, and acquired resistance/metastasis. Recent decades have witnessed a dramatic progress in the development of high-efficiency, low-toxicity nanotaxanes via the use of novel biomaterials and nanoparticulate drug delivery systems (nano-DDSs). Thus, in this review, the achievements of nanotaxanes-targeted delivery and stimuli-responsive nano-DDSs-in preclinical or clinical trials have been outlined. Then, emerging nanotherapeutics against tumor resistance and metastasis have been overviewed, with a particular emphasis on synergistic therapy strategies (e.g., combination with surgery, chemotherapy, radiotherapy, biotherapy, immunotherapy, gas therapy, phototherapy, and multitherapy). Finally, the latest oral nanotaxanes have been briefly discussed.

The Clinical and Pathological Profile of BRCA1 Gene Methylated Breast Cancer Women: A Meta-Analysis

BACKGROUND

DNA aberrant hypermethylation is the major cause of transcriptional silencing of the breast cancer gene 1 (BRCA1) gene in sporadic breast cancer patients. The aim of the present meta-analysis was to analyze all available studies reporting clinical characteristics of BRCA1 gene hypermethylated breast cancer in women, and to pool the results to provide a unique clinical profile of this cancer population.

METHODS

On September 2020, a systematic literature search was performed. Data were retrieved from PubMed, MEDLINE, and Scopus by searching the terms: "BRCA*" AND "methyl*" AND "breast". All studies evaluating the association between BRCA1 methylation status and breast cancer patients' clinicopathological features were considered for inclusion.

RESULTS

465 studies were retrieved. Thirty (6.4%) studies including 3985 patients met all selection criteria. The pooled analysis data revealed a significant correlation between BRCA1 gene hypermethylation and advanced breast cancer disease stage (OR = 0.75: 95% CI: 0.58-0.97; p = 0.03, fixed effects model), lymph nodes involvement (OR = 1.22: 95% CI: 1.01-1.48; p = 0.04, fixed effects model), and pre-menopausal status (OR = 1.34: 95% CI: 1.08-1.66; p = 0.008, fixed effects model). No association could be found between BRCA1 hypermethylation and tumor histology (OR = 0.78: 95% CI: 0.59-1.03; p = 0.08, fixed effects model), tumor grading (OR = 0.78: 95% CI :0.46-1.32; p = 0.36, fixed effects model), and breast cancer molecular classification (OR = 1.59: 95% CI: 0.68-3.72; p = 0.29, random effects model).

CONCLUSIONS

hypermethylation of the BRCA1 gene significantly correlates with advanced breast cancer disease, lymph nodes involvement, and pre-menopausal cancer onset.

How Chaotic Is Genome Chaos?

Simple Summary

Cancer genomes can undergo major restructurings involving many chromosomal locations at key stages in tumor development. This restructuring process has been designated “genome chaos” by some authors. In order to examine how chaotic cancer genome restructuring may be, the cell and molecular processes for DNA restructuring are reviewed. Examination of the action of these processes in various cancers reveals a degree of specificity that indicates genome restructuring may be sufficiently reproducible to enable possible therapies that interrupt tumor progression to more lethal forms.

Abstract

Cancer genomes evolve in a punctuated manner during tumor evolution. Abrupt genome restructuring at key steps in this evolution has been called “genome chaos.” To answer whether widespread genome change is truly chaotic, this review (i) summarizes the limited number of cell and molecular systems that execute genome restructuring, (ii) describes the characteristic signatures of DNA changes that result from activity of those systems, and (iii) examines two cases where genome restructuring is determined to a significant degree by cell type or viral infection. The conclusion is that many restructured cancer genomes display sufficiently unchaotic signatures to identify the cellular systems responsible for major oncogenic transitions, thereby identifying possible targets for therapies to inhibit tumor progression to greater aggressiveness.

Reviving the Autopsy for Modern Cancer Evolution Research

Outstanding questions plaguing oncologists, centred around tumour evolution and heterogeneity, include the development of treatment resistance, immune evasion, and optimal drug targeting strategies. Such questions are difficult to study in limited cancer tissues collected during a patient's routine clinical care, and may be better investigated in the breadth of cancer tissues that may be permissible to collect during autopsies. We are starting to better understand key tumour evolution challenges based on advances facilitated by autopsy studies completed to date. This review article explores the great progress in understanding that cancer tissues collected at autopsy have already enabled, including the shared origin of metastatic cells, the importance of early whole-genome doubling events for amplifying genes needed for tumour survival, and the creation of a wealth of tissue resources powered to answer future questions, including patient-derived xenografts, cell lines, and a wide range of banked tissues. We also highlight the future role of these programmes in advancing our understanding of cancer evolution. The research autopsy provides a special opportunity for cancer patients to give the ultimate gift-to selflessly donate their tissues towards better cancer care.

Directed Evolution. The Legacy of a Nobel Prize

This article is part of an anniversary issue of Journal of Molecular Evolution, commenting on a paper published on 1999 by the Nobel laureate Frances Arnold and her colleague Kentaro Miyazaki. The paper by Miyazaki and Arnold presented saturation mutagenesis as an alternative method to random mutagenesis for obtaining enzymes with increasing stability. Both techniques were conceived to accomplish directed evolution, an approach honoured by the Nobel Prize of Chemistry 2018. Here, I am commenting on the pros and cons of random and saturation mutagenesis, while also discussing important results from directed evolution. I conclude that molecular evolution is finding new applications in science and it is definitely an integral part of the genomic era's revolution.

Restoring the epigenetically silenced PCK2 suppresses renal cell carcinoma progression and increases sensitivity to sunitinib by promoting endoplasmic reticulum stress

Rationale: Tumors have significant abnormalities in various biological properties. In renal cell carcinoma (RCC), metabolic abnormalities are characteristic biological dysfunction that cannot be ignored. Despite this, many aspects of this dysfunction have not been fully explained. The purpose of this study was to reveal a new mechanism of metabolic and energy-related biological abnormalities in RCC.

Methods: Molecular screening and bioinformatics analysis were performed in RCC based on data from The Cancer Genome Atlas (TCGA) database. Regulated pathways were investigated by qRT-PCR, immunoblot analysis and immunohistochemistry. A series of functional analyses was performed in cell lines and xenograft models.

Results: By screening the biological abnormality core dataset-mitochondria-related dataset and the metabolic abnormality core dataset-energy metabolism-related dataset in public RCC databases, PCK2 was found to be differentially expressed in RCC compared with normal tissue. Further analysis by the TCGA database showed that PCK2 was significantly downregulated in RCC and predicted a poor prognosis. Through additional studies, it was found that a low expression of PCK2 in RCC was caused by methylation of its promoter region. Restoration of PCK2 expression in RCC cells repressed tumor progression and increased their sensitivity to sunitinib. Finally, mechanistic investigations indicated that PCK2 mediated the above processes by promoting endoplasmic reticulum stress.

Conclusions: Collectively, our results identify a specific mechanism by which PCK2 suppresses the progression of renal cell carcinoma (RCC) and increases sensitivity to sunitinib by promoting endoplasmic reticulum stress. This finding provides a new biomarker for RCC as well as novel targets and strategies for the treatment of RCC.