Spatial biology of cancer evolution.

The natural history of cancers can be understood through the lens of evolution given that the driving forces of cancer development are mutation and selection of fitter clones. Cancer growth and progression are spatial processes that involve the breakdown of normal tissue organization, invasion and metastasis. For these reasons, spatial patterns are an integral part of histological tumour grading and staging as they measure the progression from normal to malignant disease. Furthermore, tumour cells are part of an ecosystem of tumour cells and their surrounding tumour microenvironment. A range of new spatial genomic, transcriptomic and proteomic technologies offers new avenues for the study of cancer evolution with great molecular and spatial detail. These methods enable precise characterizations of the tumour microenvironment, cellular interactions therein and micro-anatomical structures. In conjunction with spatial genomics, it emerges that tumours and microenvironments co-evolve, which helps explain observable patterns of heterogeneity and offers new routes for therapeutic interventions.

Spatial genomics maps the structure, nature and evolution of cancer clones.

Genome sequencing of cancers often reveals mosaics of different subclones present in the same tumour1-3. Although these are believed to arise according to the principles of somatic evolution, the exact spatial growth patterns and underlying mechanisms remain elusive4,5. Here, to address this need, we developed a workflow that generates detailed quantitative maps of genetic subclone composition across whole-tumour sections. These provide the basis for studying clonal growth patterns, and the histological characteristics, microanatomy and microenvironmental composition of each clone. The approach rests on whole-genome sequencing, followed by highly multiplexed base-specific in situ sequencing, single-cell resolved transcriptomics and dedicated algorithms to link these layers. Applying the base-specific in situ sequencing workflow to eight tissue sections from two multifocal primary breast cancers revealed intricate subclonal growth patterns that were validated by microdissection. In a case of ductal carcinoma in situ, polyclonal neoplastic expansions occurred at the macroscopic scale but segregated within microanatomical structures. Across the stages of ductal carcinoma in situ, invasive cancer and lymph node metastasis, subclone territories are shown to exhibit distinct transcriptional and histological features and cellular microenvironments. These results provide examples of the benefits afforded by spatial genomics for deciphering the mechanisms underlying cancer evolution and microenvironmental ecology.

Spatial transcriptomics.

Spatial transcriptomics, with other spatial technologies, has enabled scientists to dissect the organization and interaction of different cell types within the tumor microenvironment. We asked experts to discuss some aspects of this technology from revealing the tumor microenvironment and heterogeneity, to tracking tumor evolution, to guiding tumor therapy, to current technical challenges.

Mechanisms of breast cancer metastasis.

Invasive breast cancer tends to metastasize to lymph nodes and systemic sites. The management of metastasis has evolved by focusing on controlling the growth of the disease in the breast/chest wall, and at metastatic sites, initially by surgery alone, then by a combination of surgery with radiation, and later by adding systemic treatments in the form of chemotherapy, hormone manipulation, targeted therapy, immunotherapy and other treatments aimed at inhibiting the proliferation of cancer cells. It would be valuable for us to know how breast cancer metastasizes; such knowledge would likely encourage the development of therapies that focus on mechanisms of metastasis and might even allow us to avoid toxic therapies that are currently used for this disease. For example, if we had a drug that targeted a gene that is critical for metastasis, we might even be able to cure a vast majority of patients with breast cancer. By bringing together scientists with expertise in molecular aspects of breast cancer metastasis, and those with expertise in the mechanical aspects of metastasis, this paper probes interesting aspects of the metastasis cascade, further enlightening us in our efforts to improve the outcome from breast cancer treatments.

Pervasive chromosomal instability and karyotype order in tumour evolution.

Chromosomal instability in cancer consists of dynamic changes to the number and structure of chromosomes1,2. The resulting diversity in somatic copy number alterations (SCNAs) may provide the variation necessary for tumour evolution1,3,4. Here we use multi-sample phasing and SCNA analysis of 1,421 samples from 394 tumours across 22 tumour types to show that continuous chromosomal instability results in pervasive SCNA heterogeneity. Parallel evolutionary events, which cause disruption in the same genes (such as BCL9, MCL1, ARNT (also known as HIF1B), TERT and MYC) within separate subclones, were present in 37% of tumours. Most recurrent losses probably occurred before whole-genome doubling, that was found as a clonal event in 49% of tumours. However, loss of heterozygosity at the human leukocyte antigen (HLA) locus and loss of chromosome 8p to a single haploid copy recurred at substantial subclonal frequencies, even in tumours with whole-genome doubling, indicating ongoing karyotype remodelling. Focal amplifications that affected chromosomes 1q21 (which encompasses BCL9, MCL1 and ARNT), 5p15.33 (TERT), 11q13.3 (CCND1), 19q12 (CCNE1) and 8q24.1 (MYC) were frequently subclonal yet appeared to be clonal within single samples. Analysis of an independent series of 1,024 metastatic samples revealed that 13 focal SCNAs were enriched in metastatic samples, including gains in chromosome 8q24.1 (encompassing MYC) in clear cell renal cell carcinoma and chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. Chromosomal instability may enable the continuous selection of SCNAs, which are established as ordered events that often occur in parallel, throughout tumour evolution.

Interacting with Members of the Public to Discuss the Impact of Food Choices on Climate Change-Experiences from Two UK Public Engagement Events.

Food systems contribute to up to 37% of global greenhouse gas emissions, and emissions are increasing. Since the emissions vary greatly between different foods, citizens' choices can make a big difference to climate change. Public engagement events are opportunities to communicate these complex issues: to raise awareness about the impact of citizens' own food choices on climate change and to generate support for changes in all food system activities, the food environment and food policy. This article summarises findings from our 'Take a Bite Out of Climate Change' stand at two UK outreach activities during July 2019. We collected engagement information in three main ways: (1) individuals were invited to complete a qualitative evaluation questionnaire comprising of four questions that gauged the person's interests, perceptions of food choices and attitudes towards climate change; (2) an online multiple-choice questionnaire asking about eating habits and awareness/concerns; and (3) a token drop voting activity where visitors answered the question: 'Do you consider greenhouse gases when choosing food?' Our results indicate whether or not people learnt about the environmental impacts of food (effectiveness), how likely they are to move towards a more climate-friendly diet (behavioural change), and how to gather information more effectively at this type of event.

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis.

We use deep transfer learning to quantify histopathological patterns across 17,355 hematoxylin and eosin-stained histopathology slide images from 28 cancer types and correlate these with matched genomic, transcriptomic and survival data. This approach accurately classifies cancer types and provides spatially resolved tumor and normal tissue distinction. Automatically learned computational histopathological features correlate with a large range of recurrent genetic aberrations across cancer types. This includes whole-genome duplications, which display universal features across cancer types, individual chromosomal aneuploidies, focal amplifications and deletions, as well as driver gene mutations. There are widespread associations between bulk gene expression levels and histopathology, which reflect tumor composition and enable the localization of transcriptomically defined tumor-infiltrating lymphocytes. Computational histopathology augments prognosis based on histopathological subtyping and grading, and highlights prognostically relevant areas such as necrosis or lymphocytic aggregates. These findings show the remarkable potential of computer vision in characterizing the molecular basis of tumor histopathology.

Timing the Landmark Events in the Evolution of Clear Cell Renal Cell Cancer: TRACERx Renal.

Clear cell renal cell carcinoma (ccRCC) is characterized by near-universal loss of the short arm of chromosome 3, deleting several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cell carcinoma. We find hotspots of point mutations in the 5' UTR of TERT, targeting a MYC-MAX-MAD1 repressor associated with telomere lengthening. The most common structural abnormality generates simultaneous 3p loss and 5q gain (36% patients), typically through chromothripsis. This event occurs in childhood or adolescence, generally as the initiating event that precedes emergence of the tumor's most recent common ancestor by years to decades. Similar genomic changes drive inherited ccRCC. Modeling differences in age incidence between inherited and sporadic cancers suggests that the number of cells with 3p loss capable of initiating sporadic tumors is no more than a few hundred. Early development of ccRCC follows well-defined evolutionary trajectories, offering opportunity for early intervention.

Genomic Evolution of Breast Cancer Metastasis and Relapse.

Patterns of genomic evolution between primary and metastatic breast cancer have not been studied in large numbers, despite patients with metastatic breast cancer having dismal survival. We sequenced whole genomes or a panel of 365 genes on 299 samples from 170 patients with locally relapsed or metastatic breast cancer. Several lines of analysis indicate that clones seeding metastasis or relapse disseminate late from primary tumors, but continue to acquire mutations, mostly accessing the same mutational processes active in the primary tumor. Most distant metastases acquired driver mutations not seen in the primary tumor, drawing from a wider repertoire of cancer genes than early drivers. These include a number of clinically actionable alterations and mutations inactivating SWI-SNF and JAK2-STAT3 pathways.

Intratumoral heterogeneity and subclonal diversification of early breast cancer.

Heterogeneity has long been recognized as a feature of some primary breast cancers manifesting as mixed histopathological subtypes or variable expression of the therapeutic targets ER, PgR and HER2. The recent emergence of next generation sequencing (NGS) technologies has revolutionized our understanding of the extent and nature of subclonal diversification. Careful examination of primary breast cancers often reveals multiple genomically distinct subclones that may contain driver alterations that follow spatial patterns of segregation. Subclonality is of clinical relevance as it forms the substrate of selection and can give rise to aggressive clinical features such as invasiveness, metastasis and treatment resistance. However, spatial and temporal intra-tumoral heterogeneity pose fundamental challenges to representative sampling and consequently the feasibility of a personalized medicine approach. Fundamental clinical and biological questions are starting to be addressed by applying NGS to the study of intra-tumoral heterogeneity and the insights that it provides should be used to better inform the prospective design of clinico-genomics trials.

Translational Genomics: Practical Applications of the Genomic Revolution in Breast Cancer.

The genomic revolution has fundamentally changed our perception of breast cancer. It is now apparent from DNA-based massively parallel sequencing data that at the genomic level, every breast cancer is unique and shaped by the mutational processes to which it was exposed during its lifetime. More than 90 breast cancer driver genes have been identified as recurrently mutated, and many occur at low frequency across the breast cancer population. Certain cancer genes are associated with traditionally defined histologic subtypes, but genomic intertumoral heterogeneity exists even between cancers that appear the same under the microscope. Most breast cancers contain subclonal populations, many of which harbor driver alterations, and subclonal structure is typically remodeled over time, across metastasis and as a consequence of treatment interventions. Genomics is deepening our understanding of breast cancer biology, contributing to an accelerated phase of targeted drug development and providing insights into resistance mechanisms. Genomics is also providing tools necessary to deliver personalized cancer medicine, but a number of challenges must still be addressed. Clin Cancer Res; 23(11); 2630-9. ©2017 AACRSee all articles in this CCR Focus section, "Breast Cancer Research: From Base Pairs to Populations."

HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures.

Approximately 1-5% of breast cancers are attributed to inherited mutations in BRCA1 or BRCA2 and are selectively sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. In other cancer types, germline and/or somatic mutations in BRCA1 and/or BRCA2 (BRCA1/BRCA2) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with BRCA1/BRCA2 dysfunction. Herein we used a lasso logistic regression model to identify six distinguishing mutational signatures predictive of BRCA1/BRCA2 deficiency. A weighted model called HRDetect was developed to accurately detect BRCA1/BRCA2-deficient samples. HRDetect identifies BRCA1/BRCA2-deficient tumors with 98.7% sensitivity (area under the curve (AUC) = 0.98). Application of this model in a cohort of 560 individuals with breast cancer, of whom 22 were known to carry a germline BRCA1 or BRCA2 mutation, allowed us to identify an additional 22 tumors with somatic loss of BRCA1 or BRCA2 and 47 tumors with functional BRCA1/BRCA2 deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers and demonstrated its efficacy in alternative sequencing strategies. Integrating all of the classes of mutational signatures thus reveals a larger proportion of individuals with breast cancer harboring BRCA1/BRCA2 deficiency (up to 22%) than hitherto appreciated (∼1-5%) who could have selective therapeutic sensitivity to PARP inhibition.

Objective Cough Frequency, Airway Inflammation, and Disease Control in Asthma.

BACKGROUND: Cough is recognized as an important troublesome symptom in the diagnosis and monitoring of asthma. Asthma control is thought to be determined by the degree of airway inflammation and hyperresponsiveness but how these factors relate to cough frequency is unclear. The goal of this study was to investigate the relationships between objective cough frequency, disease control, airflow obstruction, and airway inflammation in asthma. METHODS: Participants with asthma underwent 24-h ambulatory cough monitoring and assessment of exhaled nitric oxide, spirometry, methacholine challenge, and sputum induction (cell counts and inflammatory mediator levels). Asthma control was assessed by using the Global Initiative for Asthma (GINA) classification and the Asthma Control Questionnaire (ACQ). The number of cough sounds was manually counted and expressed as coughs per hour (c/h). RESULTS: Eighty-nine subjects with asthma (mean ± SD age, 57 ± 12 years; 57% female) were recruited. According to GINA criteria, 18 (20.2%) patients were classified as controlled, 39 (43.8%) partly controlled, and 32 (36%) uncontrolled; the median ACQ score was 1 (range, 0.0-4.4). The 6-item ACQ correlated with 24-h cough frequency (r = 0.40; P < .001), and patients with uncontrolled asthma (per GINA criteria) had higher median 24-h cough frequency (4.2 c/h; range, 0.3-27.6) compared with partially controlled asthma (1.8 c/h; range, 0.2-25.3; P = .01) and controlled asthma (1.7 c/h; range, 0.3-6.7; P = .002). Measures of airway inflammation were not significantly different between GINA categories and were not correlated with ACQ. In multivariate analyses, increasing cough frequency and worsening FEV1 independently predicted measures of asthma control. CONCLUSIONS: Ambulatory cough frequency monitoring provides an objective assessment of asthma symptoms that correlates with standard measures of asthma control but not airflow obstruction or airway inflammation. Moreover, cough frequency and airflow obstruction represent independent dimensions of asthma control.

Catalog of genetic progression of human cancers: breast cancer.

With the rapid development of next-generation sequencing, deeper insights are being gained into the molecular evolution that underlies the development and clinical progression of breast cancer. It is apparent that during evolution, breast cancers acquire thousands of mutations including single base pair substitutions, insertions, deletions, copy number aberrations, and structural rearrangements. As a consequence, at the whole genome level, no two cancers are identical and few cancers even share the same complement of "driver" mutations. Indeed, two samples from the same cancer may also exhibit extensive differences due to constant remodeling of the genome over time. In this review, we summarize recent studies that extend our understanding of the genomic basis of cancer progression. Key biological insights include the following: subclonal diversification begins early in cancer evolution, being detectable even in in situ lesions; geographical stratification of subclonal structure is frequent in primary tumors and can include therapeutically targetable alterations; multiple distant metastases typically arise from a common metastatic ancestor following a "metastatic cascade" model; systemic therapy can unmask preexisting resistant subclones or influence further treatment sensitivity and disease progression. We conclude the review by describing novel approaches such as the analysis of circulating DNA and patient-derived xenografts that promise to further our understanding of the genomic changes occurring during cancer evolution and guide treatment decision making.

Subclonal diversification of primary breast cancer revealed by multiregion sequencing.

The sequencing of cancer genomes may enable tailoring of therapeutics to the underlying biological abnormalities driving a particular patient's tumor. However, sequencing-based strategies rely heavily on representative sampling of tumors. To understand the subclonal structure of primary breast cancer, we applied whole-genome and targeted sequencing to multiple samples from each of 50 patients' tumors (303 samples in total). The extent of subclonal diversification varied among cases and followed spatial patterns. No strict temporal order was evident, with point mutations and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2 and MYC, occurring early in some tumors and late in others. In 13 out of 50 cancers, potentially targetable mutations were subclonal. Landmarks of disease progression, such as resistance to chemotherapy and the acquisition of invasive or metastatic potential, arose within detectable subclones of antecedent lesions. These findings highlight the importance of including analyses of subclonal structure and tumor evolution in clinical trials of primary breast cancer.

Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells.

Mitochondrial genomes are separated from the nuclear genome for most of the cell cycle by the nuclear double membrane, intervening cytoplasm, and the mitochondrial double membrane. Despite these physical barriers, we show that somatically acquired mitochondrial-nuclear genome fusion sequences are present in cancer cells. Most occur in conjunction with intranuclear genomic rearrangements, and the features of the fusion fragments indicate that nonhomologous end joining and/or replication-dependent DNA double-strand break repair are the dominant mechanisms involved. Remarkably, mitochondrial-nuclear genome fusions occur at a similar rate per base pair of DNA as interchromosomal nuclear rearrangements, indicating the presence of a high frequency of contact between mitochondrial and nuclear DNA in some somatic cells. Transmission of mitochondrial DNA to the nuclear genome occurs in neoplastically transformed cells, but we do not exclude the possibility that some mitochondrial-nuclear DNA fusions observed in cancer occurred years earlier in normal somatic cells.

Spatial and temporal diversity in genomic instability processes defines lung cancer evolution.

Spatial and temporal dissection of the genomic changes occurring during the evolution of human non-small cell lung cancer (NSCLC) may help elucidate the basis for its dismal prognosis. We sequenced 25 spatially distinct regions from seven operable NSCLCs and found evidence of branched evolution, with driver mutations arising before and after subclonal diversification. There was pronounced intratumor heterogeneity in copy number alterations, translocations, and mutations associated with APOBEC cytidine deaminase activity. Despite maintained carcinogen exposure, tumors from smokers showed a relative decrease in smoking-related mutations over time, accompanied by an increase in APOBEC-associated mutations. In tumors from former smokers, genome-doubling occurred within a smoking-signature context before subclonal diversification, which suggested that a long period of tumor latency had preceded clinical detection. The regionally separated driver mutations, coupled with the relentless and heterogeneous nature of the genome instability processes, are likely to confound treatment success in NSCLC.

Mobile DNA in cancer. Extensive transduction of nonrepetitive DNA mediated by L1 retrotransposition in cancer genomes.

Long interspersed nuclear element-1 (L1) retrotransposons are mobile repetitive elements that are abundant in the human genome. L1 elements propagate through RNA intermediates. In the germ line, neighboring, nonrepetitive sequences are occasionally mobilized by the L1 machinery, a process called 3' transduction. Because 3' transductions are potentially mutagenic, we explored the extent to which they occur somatically during tumorigenesis. Studying cancer genomes from 244 patients, we found that tumors from 53% of the patients had somatic retrotranspositions, of which 24% were 3' transductions. Fingerprinting of donor L1s revealed that a handful of source L1 elements in a tumor can spawn from tens to hundreds of 3' transductions, which can themselves seed further retrotranspositions. The activity of individual L1 elements fluctuated during tumor evolution and correlated with L1 promoter hypomethylation. The 3' transductions disseminated genes, exons, and regulatory elements to new locations, most often to heterochromatic regions of the genome.

Processed pseudogenes acquired somatically during cancer development.

Cancer evolves by mutation, with somatic reactivation of retrotransposons being one such mutational process. Germline retrotransposition can cause processed pseudogenes, but whether this occurs somatically has not been evaluated. Here we screen sequencing data from 660 cancer samples for somatically acquired pseudogenes. We find 42 events in 17 samples, especially non-small cell lung cancer (5/27) and colorectal cancer (2/11). Genomic features mirror those of germline LINE element retrotranspositions, with frequent target-site duplications (67%), consensus TTTTAA sites at insertion points, inverted rearrangements (21%), 5' truncation (74%) and polyA tails (88%). Transcriptional consequences include expression of pseudogenes from UTRs or introns of target genes. In addition, a somatic pseudogene that integrated into the promoter and first exon of the tumour suppressor gene, MGA, abrogated expression from that allele. Thus, formation of processed pseudogenes represents a new class of mutation occurring during cancer development, with potentially diverse functional consequences depending on genomic context.