Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing

Resolving genetic heterogeneity in cancer

To a large extent, cancer conforms to evolutionary rules defined by the rates at which clones mutate, adapt and grow. Next-generation sequencing has provided a snapshot of the genetic landscape of most cancer types, and cancer genomics approaches are driving new insights into cancer evolutionary patterns in time and space. In contrast to species evolution, cancer is a particular case owing to the vast size of tumour cell populations, chromosomal instability and its potential for phenotypic plasticity. Nevertheless, an evolutionary framework is a powerful aid to understand cancer progression and therapy failure. Indeed, such a framework could be applied to predict individual tumour behaviour and support treatment strategies.

Is cell migration a selectable trait in the natural evolution of cancer development?

Selective evolutionary pressure shapes the processes and genes that enable cancer survival and expansion in a tumour-suppressive environment. A distinguishing lethal feature of malignant cancer is its dissemination and seeding of metastatic foci. A key requirement for this process is the acquisition of a migratory/invasive ability. However, how the migratory phenotype is selected for during the natural evolution of cancer and what advantage, if any, it might provide to the growing malignant cells remain open issues. In this opinion piece, we discuss three possible answers to these issues. We will examine lines of evidence from mathematical modelling of cancer evolution that indicate that migration is an intrinsic selectable property of malignant cells that directly impacts on growth dynamics and cancer geometry. Second, we will argue that migratory phenotypes can emerge as an adaptive response to unfavourable growth conditions and endow cells not only with the ability to move/invade, but also with specific metastatic traits, including drug resistance, self-renewal and survival. Finally, we will discuss the possibility that migratory phenotypes are coincidental events that emerge by happenstance in the natural evolution of cancer. This article is part of a discussion meeting issue 'Forces in cancer: interdisciplinary approaches in tumour mechanobiology'.

The single-cell sequencing: new developments and medical applications

Single-cell sequencing technologies can be used to detect the genome, transcriptome and other multi-omics of single cells. They can show the differences and evolutionary relationships of various cells. This review introduces the latest advances in single-cell sequencing technologies and their applications in oncology, microbiology, neurology, reproduction, immunology, digestive and urinary systems, highlighting the important role that single-cell sequencing techniques play in these areas.

The Spatial and Genomic Hierarchy of Tumor Ecosystems Revealed by Single-Cell Technologies

Many malignancies display heterogeneous features that support cancer progression. Emerging high-resolution methods provide a view of heterogeneity that recognizes the influence of diverse cell types and cell states of the tumor microenvironment. Here we outline a hierarchical organization of tumor heterogeneity from a genomic perspective, summarize the origins of spatially patterned metabolic features, and review recent developments in single-cell and spatially resolved techniques for genome-wide study of multicellular tissues. We also discuss how integrating these approaches can yield new insights into human cancer and emerging immune therapies. Applying these technologies for the analysis of primary tumors, patient-derived xenografts, and in vitro systems holds great promise for understanding the hierarchical structure and environmental influences that underlie tumor ecosystems.

[Clinical challenges and implications of intratumor heterogeneity]

Tumors display a high, albeit variable, grade of intratumor heterogeneity, both from a clinical and a morphological viewpoint. Furthermore, recent methods of large-scale molecular analysis demonstrate to what extent tumors can also be heterogeneous from a molecular perspective. This is of paramount importance for patients as it has a great impact on the success of so-called precision therapies and explains the reason for a significant number of therapeutic failures in modern oncology. We present an up-to-date review of the latest findings in a group of tumors with a high social impact, commonly seen in the daily routine of the pathology laboratory.

Quantifying local malignant adaptation in tissue-specific evolutionary trajectories by harnessing cancer's repeatability at the genetic level

Cancer is a potentially lethal disease, in which patients with nearly identical genetic backgrounds can develop a similar pathology through distinct combinations of genetic alterations. We aimed to reconstruct the evolutionary process underlying tumour initiation, using the combination of convergence and discrepancies observed across 2,742 cancer genomes from nine tumour types. We developed a framework using the repeatability of cancer development to score the local malignant adaptation (LMA) of genetic clones, as their potential to malignantly progress and invade their environment of origin. Using this framework, we found that premalignant skin and colorectal lesions appeared specifically adapted to their local environment, yet insufficiently for full cancerous transformation. We found that metastatic clones were more adapted to the site of origin than to the invaded tissue, suggesting that genetics may be more important for local progression than for the invasion of distant organs. In addition, we used network analyses to investigate evolutionary properties at the system-level, highlighting that different dynamics of malignant progression can be modelled by such a framework in tumour-type-specific fashion. We find that occurrence-based methods can be used to specifically recapitulate the process of cancer initiation and progression, as well as to evaluate the adaptation of genetic clones to given environments. The repeatability observed in the evolution of most tumour types could therefore be harnessed to better predict the trajectories likely to be taken by tumours and preneoplastic lesions in the future.

Cancer overdiagnosis: a biological challenge and clinical dilemma

For cancer screening to be successful, it should primarily detect cancers with lethal potential or their precursors early, leading to therapy that reduces mortality and morbidity. Screening programmes have been successful for colon and cervical cancers, where subsequent surgical removal of precursor lesions has resulted in a reduction in cancer incidence and mortality. However, many types of cancer exhibit a range of heterogeneous behaviours and variable likelihoods of progression and death. Consequently, screening for some cancers may have minimal impact on mortality and may do more harm than good. Since the implementation of screening tests for certain cancers (for example, breast and prostate cancers), a spike in incidence of in situ and early-stage cancers has been observed, but a link to reduction in cancer-specific mortality has not been as clear. It is difficult to determine how many of these mortality reductions are due to screening and how many are due to improved treatments of tumours. In cancers with lower incidence but high mortality (for example, pancreatic cancer), screening has focused on high-risk populations, but challenges similar to those for general population screening remain, particularly with regard to finding lesions with difficult-to-characterize malignant potential (for example, intraductal papillary mucinous neoplasms). More sensitive screening methods are detecting smaller and smaller lesions, but this has not been accompanied by a comparable reduction in the incidence of invasive cancers. In this Opinion article, we focus on the contribution of screening in general and high-risk populations to overdiagnosis, the effects of overdiagnosis on patients and emerging strategies to reduce overdiagnosis of indolent cancers through an understanding of tumour heterogeneity, the biology of how cancers evolve and progress, the molecular and cellular features of early neoplasia and the dynamics of the interactions of early lesions with their surrounding tissue microenvironment.

Atypical function of a centrosomal module in WNT signalling drives contextual cancer cell motility

Centrosomes control cell motility, polarity and migration that is thought to be mediated by their microtubule-organizing capacity. Here we demonstrate that WNT signalling drives a distinct form of non-directional cell motility that requires a key centrosome module, but not microtubules or centrosomes. Upon exosome mobilization of PCP-proteins, we show that DVL2 orchestrates recruitment of a CEP192-PLK4/AURKB complex to the cell cortex where PLK4/AURKB act redundantly to drive protrusive activity and cell motility. This is mediated by coordination of formin-dependent actin remodelling through displacement of cortically localized DAAM1 for DAAM2. Furthermore, abnormal expression of PLK4, AURKB and DAAM1 is associated with poor outcomes in breast and bladder cancers. Thus, a centrosomal module plays an atypical function in WNT signalling and actin nucleation that is critical for cancer cell motility and is associated with more aggressive cancers. These studies have broad implications in how contextual signalling controls distinct modes of cell migration.

Centrosomes function in cell migration by organizing microtubules. Here, Luo et al. surprisingly show that centrosome proteins also control migration after recruitment by Wnt-PCP proteins to the cell cortex, leading to actin remodelling and protrusive activity relevant to aggressive cancer motility.

Targeting the Interplay between Epithelial-to-Mesenchymal-Transition and the Immune System for Effective Immunotherapy

Over the last decade, both early diagnosis and targeted therapy have improved the survival rates of many cancer patients. Most recently, immunotherapy has revolutionized the treatment options for cancers such as melanoma. Unfortunately, a significant portion of cancers (including lung and breast cancers) do not respond to immunotherapy, and many of them develop resistance to chemotherapy. Molecular characterization of non-responsive cancers suggest that an embryonic program known as epithelial-mesenchymal transition (EMT), which is mostly latent in adults, can be activated under selective pressures, rendering these cancers resistant to chemo- and immunotherapies. EMT can also drive tumor metastases, which in turn also suppress the cancer-fighting activity of cytotoxic T cells that traffic into the tumor, causing immunotherapy to fail. In this review, we compare and contrast immunotherapy treatment options of non-small cell lung cancer (NSCLC) and triple negative breast cancer (TNBC). We discuss why, despite breakthrough progress in immunotherapy, attaining predictable outcomes in the clinic is mostly an unsolved problem for these tumors. Although these two cancer types appear different based upon their tissues of origin and molecular classification, gene expression indicate that they possess many similarities. Patient tumors exhibit activation of EMT, and resulting stem cell properties in both these cancer types associate with metastasis and resistance to existing cancer therapies. In addition, the EMT transition in both these cancers plays a crucial role in immunosuppression, which exacerbates treatment resistance. To improve cancer-related survival we need to understand and circumvent, the mechanisms through which these tumors become therapy resistant. In this review, we discuss new information and complementary perspectives to inform combination treatment strategies to expand and improve the anti-tumor responses of currently available clinical immune checkpoint inhibitors.

Control of Invasion by Epithelial-to-Mesenchymal Transition Programs during Metastasis

Epithelial-to-mesenchymal transition (EMT) programs contribute to the acquisition of invasive properties that are essential for metastasis. It is well established that EMT programs alter cell state and promote invasive behavior. This review discusses how rather than following one specific program, EMT states are diverse in their regulation and invasive properties. Analysis across a spectrum of models using a combination of approaches has revealed how unique features of distinct EMT programs dictate whether tumor cells invade as single cells or collectively as cohesive groups of cells. It has also been shown that the mode of collective invasion is determined by the nature of the EMT, with cells in a trailblazer-type EMT state being capable of initiating collective invasion, whereas cells that have undergone an opportunist-type EMT are dependent on extrinsic factors to invade. In addition to altering cell intrinsic properties, EMT programs can influence invasion through non-cell autonomous mechanisms. Analysis of tumor subpopulations has demonstrated how EMT-induced cells can drive the invasion of sibling epithelial populations through paracrine signaling and remodeling of the microenvironment. Importantly, the variation in invasive properties controlled by EMT programs influences the kinetics and location of metastasis.

A breast one-patient panel of heterogeneous genomes reveals genetic alterations driving DCIS into invasive lesions

Aim: Utilize breast cancer samples in the same patient to indicate breast cancer development. Patients & methods: We performed whole-exome analysis of spatially independent ductal carcinoma in situ (DCIS) and invasive ductal carcinoma samples from the same breast. Results: In VEGF pathway, we observed two genes disrupted in DCIS, while another four (including ACTN2) mutated in invasive ductal carcinoma. When looked up TCGA database, we identified seven breast cancer patients with ACTN2 somatic mutations and observed a dramatic decrease in the overall survival time in ACTN2 mutant patients (p = 0.0182). A further finding in the TCGA database shows that breast cancer patients with ≥2 mutated genes in VEGF pathways showed worse prognosis (p = 0.0013). Conclusion: TCGA database and special case could inform each other to reveal DCIS developmental rules.

Intratumoral Heterogeneity: More Than Just Mutations

Most human tumors are composed of genetically and phenotypically heterogeneous cancer cell populations, which poses a major challenge for the clinical management of cancer patients. Advances of single-cell technologies have allowed the profiling of tumors at unprecedented depth, which, in combination with newly developed computational tools, enable the dissection of tumor evolution with increasing precision. However, our understanding of mechanisms that regulate intratumoral heterogeneity and our ability to modulate it has been lagging behind. Recent data demonstrate that epigenetic regulators, including histone demethylases, may control the cell-to-cell variability of transcriptomes and chromatin profiles and they may modulate therapeutic responses via this function. Thus, the therapeutic targeting of epigenetic enzymes may be used to decrease intratumoral cellular heterogeneity and treatment resistance, when used in combination with other types of agents.

AKT1low quiescent cancer cells in ductal carcinoma in situ of the breast

Ductal carcinoma in situ (DCIS) of the breast precedes the development of invasive breast cancer and reflects the genomic changes and protein expression profile of invasive disease. AKT1^low cancer cells (QCC) are a rare, drug-tolerant, epigenetically plastic, and quiescent cancer cell subset that we previously identified at a frequency of 0.5–1% in primary breast tumors using the marker profile: AKT^low/H3K9me2^low/HES1^high. Here we used quantitative immunofluorescence microscopy with computational image analysis to show that AKT1^low QCCs are present in DCIS from patients with and without co-existing invasive breast cancer. These data suggest that a drug-resistant, quiescent cancer cell state is present in premalignant breast lesions prior to the development of invasive disease. These findings warrant further study of whether AKT1^low QCCs contribute to invasive tumor development and recurrence, similar to their role in more advanced malignancy.

The interplay of circulating tumor DNA and chromatin modification, therapeutic resistance, and metastasis

Peripheral circulating free DNA (cfDNA) is DNA that is detected in plasma or serum fluid with a cell-free status. For cancer patients, cfDNA not only originates from apoptotic cells but also from necrotic tumor cells and disseminated tumor cells that have escaped into the blood during epithelial-mesenchymal transition. Additionally, cfDNA derived from tumors, also known as circulating tumor DNA (ctDNA), carries tumor-associated genetic and epigenetic changes in cancer patients, which makes ctDNA a potential biomarker for the early diagnosis of tumors, monitory and therapeutic evaluations, and prognostic assessments, among others, for various kinds of cancer. Moreover, analyses of cfDNA chromatin modifications can reflect the heterogeneity of tumors and have potential for predicting tumor drug resistance.

Error-Prone Replication through UV Lesions by DNA Polymerase θ Protects against Skin Cancers

Cancers from sun-exposed skin accumulate "driver" mutations, causally implicated in oncogenesis. Because errors incorporated during translesion synthesis (TLS) opposite UV lesions would generate these mutations, TLS mechanisms are presumed to underlie cancer development. To address the role of TLS in skin cancer formation, we determined which DNA polymerase is responsible for generating UV mutations, analyzed the relative contributions of error-free TLS by Polη and error-prone TLS by Polθ to the replication of UV-damaged DNA and to genome stability, and examined the incidence of UV-induced skin cancers in Polθ-/-, Polη-/-, and Polθ-/- Polη-/- mice. Our findings that the incidence of skin cancers rises in Polθ-/- mice and is further exacerbated in Polθ-/- Polη-/- mice compared with Polη-/- mice support the conclusion that error-prone TLS by Polθ provides a safeguard against tumorigenesis and suggest that cancer formation can ensue in the absence of somatic point mutations.

Deciphering Human Tumor Biology by Single-Cell Expression Profiling

Human tumors are complex ecosystems where diverse cancer and noncancer cells interact to determine tumor biology and response to therapies. Genomic and transcriptomic methods have traditionally profiled these intricate ecosystems as bulk samples, thereby masking individual cellular programs and the variability among them. Recent advances in single-cell profiling have paved the way for studying tumors at the resolution of individual cells, providing a compelling strategy to bridge gaps in our understanding of human tumors. Here, we review methodologies for single-cell expression profiling of tumors and the initial studies deploying them in clinical contexts. We highlight how these studies uncover new biology and provide insights into drug resistance, stem cell programs, metastasis, and tumor classifications. We also discuss areas of technology development in single-cell genomics that provide new tools to address key questions in cancer biology. These emerging studies and technologies have the potential to revolutionize our understanding and management of human malignancies.

Lineage Tracing: Computational Reconstruction Goes Beyond the Limit of Imaging

Tracking the fate of individual cells and their progeny through lineage tracing has been widely used to investigate various biological processes including embryonic development, homeostatic tissue turnover, and stem cell function in regeneration and disease. Conventional lineage tracing involves the marking of cells either with dyes or nucleoside analogues or genetic marking with fluorescent and/or colorimetric protein reporters. Both are imaging-based approaches that have played a crucial role in the field of developmental biology as well as adult stem cell biology. However, imaging-based lineage tracing approaches are limited by their scalability and the lack of molecular information underlying fate transitions. Recently, computational biology approaches have been combined with diverse tracing methods to overcome these limitations and so provide high-order scalability and a wealth of molecular information. In this review, we will introduce such novel computational methods, starting from single-cell RNA sequencing-based lineage analysis to DNA barcoding or genetic scar analysis. These novel approaches are complementary to conventional imaging-based approaches and enable us to study the lineage relationships of numerous cell types during vertebrate, and in particular human, development and disease.

Single cell transcriptomics: moving towards multi-omics

Single-cell multi-omics analysis helps characterize multiple layers of molecular features at a single-cell scale to provide insights into cellular processes and functions.

Understanding tumor ecosystems by single-cell sequencing: promises and limitations

Cellular heterogeneity within and across tumors has been a major obstacle in understanding and treating cancer, and the complex heterogeneity is masked if bulk tumor tissues are used for analysis. The advent of rapidly developing single-cell sequencing technologies, which include methods related to single-cell genome, epigenome, transcriptome, and multi-omics sequencing, have been applied to cancer research and led to exciting new findings in the fields of cancer evolution, metastasis, resistance to therapy, and tumor microenvironment. In this review, we discuss recent advances and limitations of these new technologies and their potential applications in cancer studies.

Breaking through to the Other Side: Microenvironment Contributions to DCIS Initiation and Progression

Refinements in early detection, surgical and radiation therapy, and hormone receptor-targeted treatments have improved the survival rates for breast cancer patients. However, the ability to reliably identify which non-invasive lesions and localized tumors have the ability to progress and/or metastasize remains a major unmet need in the field. The current diagnostic and therapeutic strategies focus on intrinsic alterations within carcinoma cells that are closely associated with proliferation. However, substantial accumulating evidence has indicated that permissive changes in the stromal tissues surrounding the carcinoma play an integral role in breast cancer tumor initiation and progression. Numerous studies have suggested that the stromal environment surrounding ductal carcinoma in situ (DCIS) lesions actively contributes to enhancing tumor cell invasion and immune escape. This review will describe the current state of knowledge regarding the mechanisms through which the microenvironment interacts with DCIS lesions focusing on recent studies that describe the contributions of myoepithelial cells, fibroblasts and immune cells to invasion and subsequent progression. These mechanisms will be considered in the context of developing biomarkers for identifying lesions that will progress to invasive carcinoma and/or developing approaches for therapeutic intervention.

Intratumoral Heterogeneity in Ductal Carcinoma In Situ: Chaos and Consequence

Ductal carcinoma in situ (DCIS) is a non-invasive proliferative growth in the breast that serves as a non-obligate precursor to invasive ductal carcinoma. The widespread adoption of screening mammography has led to a steep increase in the detection of DCIS, which now comprises approximately 20% of new breast cancer diagnoses in the United States. Interestingly, the intratumoral heterogeneity (ITH) that has been observed in invasive breast cancers may have been established early in tumorigenesis, given the vast and varied ITH that has been detected in DCIS. This review will discuss the intratumoral heterogeneity of DCIS, focusing on the phenotypic and genomic heterogeneity of tumor cells, as well as the compositional heterogeneity of the tumor microenvironment. In addition, we will assess the spatial heterogeneity that is now being appreciated in these lesions, and summarize new approaches to evaluate heterogeneity of tumor and stromal cells in the context of their spatial organization. Importantly, we will discuss how a growing understanding of ITH has led to a more holistic appreciation of the complex biology of DCIS, specifically its evolution and natural history. Finally, we will consider ways in which our knowledge of DCIS ITH might be translated in the future to guide clinical care for DCIS patients.

Tumour heterogeneity and metastasis at single-cell resolution

Tumours comprise a heterogeneous collection of cells with distinct genetic and phenotypic properties that can differentially promote progression, metastasis and drug resistance. Emerging single-cell technologies provide a new opportunity to profile individual cells within tumours and investigate what roles they play in these processes. This Review discusses key technological considerations for single-cell studies in cancer, new findings using single-cell technologies and critical open questions for future applications.

Reliable detection of subchromosomal deletions and duplications using cell-based noninvasive prenatal testing

Objective

To gather additional data on the ability to detect subchromosomal abnormalities of various sizes in single fetal cells isolated from maternal blood, using low‐coverage shotgun next‐generation sequencing for cell‐based noninvasive prenatal testing (NIPT).

Method

Fetal trophoblasts were recovered from approximately 30 mL of maternal blood using maternal white blood cell depletion, density‐based cell separation, immunofluorescence staining, and high‐resolution scanning. These trophoblastic cells were picked as single cells and underwent whole genome amplification for subsequent genome‐wide copy number analysis and genotyping to confirm the fetal origin of the cells.

Results

Applying our fetal cell isolation method to a series of 125 maternal blood samples, we detected on average 4.17 putative fetal cells/sample. The series included 15 cases with clinically diagnosed fetal aneuploidies and five cases with subchromosomal abnormalities. This method was capable of detecting findings that were 1 to 2 Mb in size, and all were concordant with the microarray or karyotype data obtained on a fetal sample. A minority of fetal cells showed evidence of genome degradation likely related to apoptosis.

Conclusion

We demonstrate that this cell‐based NIPT method has the capacity to reliably diagnose fetal chromosomal abnormalities down to 1 to 2 Mb in size.

What is already known about this topic?

Fetal trophoblastic cells can be isolated from maternal blood and be used for the detection of fetal aneuploidies and copy number variants. The data on the detection of subchromosomal deletions and duplications is currently limited.

What does this study add?

Cell‐based NIPT can be used for the detection of copy number abnormalities of greater than or equal to 1 Mb in the fetus by low‐coverage next‐generation sequencing after single cell whole genome amplification. Data are provided here for five cases in which different subchromosomal deletions and duplications ranging from 1.2 to 18.9 Mb were detected in single cells.

PHLI-seq: constructing and visualizing cancer genomic maps in 3D by phenotype-based high-throughput laser-aided isolation and sequencing

Spatial mapping of genomic data to tissue context in a high-throughput and high-resolution manner has been challenging due to technical limitations. Here, we describe PHLI-seq, a novel approach that enables high-throughput isolation and genome-wide sequence analysis of single cells or small numbers of cells to construct genomic maps within cancer tissue in relation to the images or phenotypes of the cells. By applying PHLI-seq, we reveal the heterogeneity of breast cancer tissues at a high resolution and map the genomic landscape of the cells to their corresponding spatial locations and phenotypes in the 3D tumor mass.

Progression of ductal carcinoma in situ to invasive breast cancer: comparative genomic sequencing

Several models have been described as potential mechanisms for the progression of ductal carcinoma in situ (DCIS) to invasive breast cancer (IBC). The aim of our study was to increase our understanding of DCIS progression by using massive parallel sequencing of synchronous DCIS and IBC. We included patients with synchronous DCIS and IBC (n = 4). Initially, IBC and normal tissue were subjected to whole exome sequencing. Subsequently, targeted sequencing was performed to validate those tumor-specific variants identified by whole exome sequencing. Finally, we analyzed whether those specific variants of the invasive component were also present in the DCIS component. There was a high genomic concordance between synchronous DCIS and IBC (52 out of 92 mutations were present in both components). However, the remaining mutations (40 out of 92) were restricted to the invasive component. The proportion of tumor cells with these mutations was higher in the invasive component compared to the DCIS component in a subset of patients. Our findings support the theory that the progression from DCIS to IBC could be driven by the selection of subclones with specific genetic aberrations. This knowledge improves our understanding of DCIS progression, which may lead to the identification of potential markers of progression and novel therapeutic targets in order to develop a more personalized treatment of patients with DCIS.

A Markov chain for numerical chromosomal instability in clonally expanding populations

Cancer cells frequently undergo chromosome missegregation events during mitosis, whereby the copies of a given chromosome are not distributed evenly among the two daughter cells, thus creating cells with heterogeneous karyotypes. A stochastic model tracing cellular karyotypes derived from clonal populations over hundreds of generations was recently developed and experimentally validated, and it was capable of predicting favorable karyotypes frequently observed in cancer. Here, we construct and study a Markov chain that precisely describes karyotypic evolution during clonally expanding cancer cell populations. The Markov chain allows us to directly predict the distribution of karyotypes and the expected size of the tumor after many cell divisions without resorting to computationally expensive simulations. We determine the limiting karyotype distribution of an evolving tumor population, and quantify its dependency on several key parameters including the initial karyotype of the founder cell, the rate of whole chromosome missegregation, and chromosome-specific cell viability. Using this model, we confirm the existence of an optimal rate of chromosome missegregation probabilities that maximizes karyotypic heterogeneity, while minimizing the occurrence of nullisomy. Interestingly, karyotypic heterogeneity is significantly more dependent on chromosome missegregation probabilities rather than the number of cell divisions, so that maximal heterogeneity can be reached rapidly (within a few hundred generations of cell division) at chromosome missegregation rates commonly observed in cancer cell lines. Conversely, at low missegregation rates, heterogeneity is constrained even after thousands of cell division events. This leads us to conclude that chromosome copy number heterogeneity is primarily constrained by chromosome missegregation rates and the risk for nullisomy and less so by the age of the tumor. This model enables direct integration of karyotype information into existing models of tumor evolution based on somatic mutations.

Chromosomal instability (CIN) is a hallmark of cancer and it results from persistent chromosome segregation errors during cell division. CIN has been shown to play a key role in drug resistance and tumor metastasis. While our understanding of CIN on the cellular level has grown over the past decade, our ability to predict the behavior of tumors containing billions of cells remains limited due to the paucity of adequate mathematical models. Here, we develop a Markov-chain model that is capable of providing exact solutions for long-term chromosome copy number distributions during tumor growth. Using this model we confirm the presence of optimal chromosome missegregation rates that balance genomic heterogeneity required for tumor evolution and survival. Interestingly, we show that chromosome copy number heterogeneity is primarily influenced by the rate of chromosome segregation errors rather than the age of the tumor. At chromosome missegregation rates frequently observed in cancer, tumors can acquire maximal genomic heterogeneity after a few hundred cell divisions. This model enables the integration of selection imparted by CIN into existing models of tumor evolution based on somatic mutations to explore their mutual effects.

Lobular Carcinomas In Situ Display Intralesion Genetic Heterogeneity and Clonal Evolution in the Progression to Invasive Lobular Carcinoma

PURPOSE

Lobular carcinoma in situ (LCIS) is a preinvasive lesion of the breast. We sought to define its genomic landscape, whether intralesion genetic heterogeneity is present in LCIS, and the clonal relatedness between LCIS and invasive breast cancers.Experimental Design: We reanalyzed whole-exome sequencing (WES) data and performed a targeted amplicon sequencing validation of mutations identified in 43 LCIS and 27 synchronous more clinically advanced lesions from 24 patients [9 ductal carcinomas in situ (DCIS), 13 invasive lobular carcinomas (ILC), and 5 invasive ductal carcinomas (IDC)]. Somatic genetic alterations, mutational signatures, clonal composition, and phylogenetic trees were defined using validated computational methods.

RESULTS

WES of 43 LCIS lesions revealed a genomic profile similar to that previously reported for ILCs, with CDH1 mutations present in 81% of the lesions. Forty-two percent (18/43) of LCIS were found to be clonally related to synchronous DCIS and/or ILCs, with clonal evolutionary patterns indicative of clonal selection and/or parallel/branched progression. Intralesion genetic heterogeneity was higher among LCIS clonally related to DCIS/ILC than in those nonclonally related to DCIS/ILC. A shift from aging to APOBEC-related mutational processes was observed in the progression from LCIS to DCIS and/or ILC in a subset of cases.

CONCLUSIONS

Our findings support the contention that LCIS has a repertoire of somatic genetic alterations similar to that of ILCs, and likely constitutes a nonobligate precursor of breast cancer. Intralesion genetic heterogeneity is observed in LCIS and should be considered in studies aiming to develop biomarkers of progression from LCIS to more advanced lesions.

Myoepithelial cells are a dynamic barrier to epithelial dissemination

Myoepithelial cells function collectively as a dynamic barrier to the invasion and dissemination of Twist1⁺ luminal epithelial cells and both luminal and basal phenotype breast cancer cells. Barrier function depends on myoepithelial abundance and both smooth muscle contractility and intercellular adhesion within the myoepithelium.

The mammary epithelium is composed of an inner luminal and surrounding myoepithelial cell layer. The presence of cancer cells beyond the myoepithelium defines invasive breast cancer, yet the role of the myoepithelium during invasion remains unclear. We developed a 3D organotypic culture assay to model this process through lineage-specific expression of the prometastatic transcription factor Twist1. We sought to distinguish the functional role of the myoepithelium in regulating invasion and local dissemination. Myoepithelial-specific Twist1 expression induced cell-autonomous myoepithelial cell escape. Remarkably, luminal-specific Twist1 expression was rarely sufficient for escape. Time-lapse microscopy revealed that myoepithelial cells collectively restrain and reinternalize invading Twist1⁺ luminal cells. Barrier function correlated with myoepithelial abundance and required the expression of α-smooth muscle actin and P-cadherin. We next demonstrated that myoepithelial cells can restrain and recapture invasive cancer cells. Our data establish the concept of the myoepithelium as a dynamic barrier to luminal dissemination and implicate both smooth muscle contractility and intercellular adhesion in barrier function.

Analyzing Circulating Tumor Cells One at a Time

Whole-genome sequencing has made a significant impact on cancer research, but traditional bulk methods fail to detect information from rare cells. Recently developed single-cell sequencing methods have provided new insights and unprecedented details about cancer progression and diversity. These advancements also enable the investigation of rare cells, such as circulating tumor cells (CTCs) derived from cancer patients. In this review, we outline various single-cell sequencing techniques that can elucidate the molecular properties of CTCs. In addition, we explain the drawbacks that need to be overcome for each method.

Single-Cell Transcriptomics Meets Lineage Tracing

Reconstructing lineage relationships between cells within a tissue or organism is a long-standing aim in biology. Traditionally, lineage tracing has been achieved through the (genetic) labeling of a cell followed by the tracking of its offspring. Currently, lineage trajectories can also be predicted using single-cell transcriptomics. Although single-cell transcriptomics provides detailed phenotypic information, the predicted lineage trajectories do not necessarily reflect genetic relationships. Recently, techniques have been developed that unite these strategies. In this Review, we discuss transcriptome-based lineage trajectory prediction algorithms, single-cell genetic lineage tracing, and the promising combination of these techniques for stem cell and cancer research.

Coexisting genomic aberrations associated with lymph node metastasis in breast cancer

Single cancer cell-sequencing studies currently use randomly selected cells, limiting correlations among genomic aberrations, morphology, and spatial localization. We laser-captured microdissected single cells from morphologically distinct areas of primary breast cancer and corresponding lymph node metastasis and performed whole-exome or deep-target sequencing of more than 100 such cells. Two major subclones coexisted in different areas of the primary tumor, and the lymph node metastasis originated from a minor subclone in the invasive front of the primary tumor, with additional copy number changes, including chr8q gain, but no additional point mutations in driver genes. Lack of metastasis-specific driver events led us to assess whether other clonal and subclonal genomic aberrations preexisting in primary tumors contribute to lymph node metastasis. Gene mutations and copy number variations analyzed in 5 breast cancer tissue sample sets revealed that copy number variations in several genomic regions, including areas within chr1p, chr8q, chr9p, chr12q, and chr20q, harboring several metastasis-associated genes, were consistently associated with lymph node metastasis. Moreover, clonal expansion was observed in an area of morphologically normal breast epithelia, likely driven by a driver mutation and a subsequent amplification in chr1q. Our study illuminates the molecular evolution of breast cancer and genomic aberrations contributing to metastases.

Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology

Increasing attention has been focused on cell type proteome profiling for understanding the heterogeneous multicellular microenvironment in tissue samples. However, current cell type proteome profiling methods need large amounts of starting materials which preclude their application to clinical tumor specimens with limited access. Here, by seamlessly combining laser capture microdissection and integrated proteomics sample preparation technology SISPROT, specific cell types in tumor samples could be precisely dissected with single cell resolution and processed for high-sensitivity proteome profiling. Sample loss and contamination due to the multiple transfer steps are significantly reduced by the full integration and noncontact design. H&E staining dyes which are necessary for cell type investigation could be selectively removed by the unique two-stage design of the spintip device. This easy-to-use proteome profiling technology achieved high sensitivity with the identification of more than 500 proteins from only 0.1 mm² and 10 μm thickness colon cancer tissue section. The first cell type proteome profiling of four cell types from one colon tumor and surrounding normal tissue, including cancer cells, enterocytes, lymphocytes, and smooth muscle cells, was obtained. 5271, 4691, 4876, and 2140 protein groups were identified, respectively, from tissue section of only 5 mm² and 10 μm thickness. Furthermore, spatially resolved proteome distribution profiles of enterocytes, lymphocytes, and smooth muscle cells on the same tissue slices and across four consecutive sections with micrometer distance were successfully achieved. This fully integrated proteomics technology, termed LCM-SISPROT, is therefore promising for spatial-resolution cell type proteome profiling of tumor microenvironment with a minute amount of clinical starting materials.

Sensitivity to sequencing depth in single-cell cancer genomics

BACKGROUND

Querying cancer genomes at single-cell resolution is expected to provide a powerful framework to understand in detail the dynamics of cancer evolution. However, given the high costs currently associated with single-cell sequencing, together with the inevitable technical noise arising from single-cell genome amplification, cost-effective strategies that maximize the quality of single-cell data are critically needed. Taking advantage of previously published single-cell whole-genome and whole-exome cancer datasets, we studied the impact of sequencing depth and sampling effort towards single-cell variant detection.

METHODS

Five single-cell whole-genome and whole-exome cancer datasets were independently downscaled to 25, 10, 5, and 1× sequencing depth. For each depth level, ten technical replicates were generated, resulting in a total of 6280 single-cell BAM files. The sensitivity of variant detection, including structural and driver mutations, genotyping, clonal inference, and phylogenetic reconstruction to sequencing depth was evaluated using recent tools specifically designed for single-cell data.

RESULTS

Altogether, our results suggest that for relatively large sample sizes (25 or more cells) sequencing single tumor cells at depths > 5× does not drastically improve somatic variant discovery, characterization of clonal genotypes, or estimation of single-cell phylogenies.

CONCLUSIONS

We suggest that sequencing multiple individual tumor cells at a modest depth represents an effective alternative to explore the mutational landscape and clonal evolutionary patterns of cancer genomes.

Placing RNA in context and space - methods for spatially resolved transcriptomics

Single-cell transcriptomics provides us with completely new insights into the molecular diversity of different cell types and the different states they can adopt. The technique generates inventories of cells that constitute the building blocks of multicellular organisms. However, since the method requires isolation of discrete cells, information about the original location within tissue is lost. Therefore, it is not possible to draw detailed cellular maps of tissue architecture and their positioning in relation to other cells. In order to better understand the cellular and tissue function of multicellular organisms, we need to map the cells within their physiological, morphological, and anatomical context and space. In this review, we will summarize and compare the different methods of in situ RNA analysis and the most recent developments leading to more comprehensive and highly multiplexed spatially resolved transcriptomic approaches. We will discuss their highlights and advantages as well as their limitations and challenges and give an outlook on promising future applications and directions both within basic research as well as clinical integration.

Mutant p53 in breast cancer: potential as a therapeutic target and biomarker

OBJECTIVE

The aim of this article is to discuss mutant p53 as a possible therapeutic target and biomarker for breast cancer.

RESULTS

TP53 (p53) is the most frequently mutated gene in invasive breast cancer. Although mutated in 30-35% of all cases, p53 is mutated in approximately 80% of triple-negative (TN) tumors (i.e., tumors negative for ER, PR, and HER2). Because of this high prevalence, mutated p53 is both a potential biomarker and therapeutic target for patients with breast cancer, especially for those with the TN subtype. Although several retrospective studies have investigated a potential prognostic and therapy predictive role for mutant p53 in breast cancer, the results to date are mixed. Thus, at present, mutant p53 cannot be recommended as a prognostic or therapy predictive biomarker in breast cancer. In contrast to the multiple reports on a potential biomarker role, few studies had until recently, investigated mutant p53 as a potential target for breast cancer treatment. In the last decade, however, several compounds have become available which can reactivate mutant p53 protein and convert it to a conformation with wild-type properties. Some of these compounds, especially PRIMA-1, APR-246 PK11007, and COTI-2, have been found to exhibit anticancer activity in preclinical models of breast cancer.

CONCLUSION

Since p53 is mutated in the vast majority of TN breast cancers, compounds such as APR-246, PK11007, and COTI-2 are potential treatments for patients with this subform of the disease. Further research is necessary to identify a potential biomarker role for mutant p53 in breast cancer.

Characterizing the efficacy of cancer therapeutics in patient-derived xenograft models of metastatic breast cancer

PURPOSE

Basal-like breast cancers are aggressive and often metastasize to vital organs. Treatment is largely limited to chemotherapy. This study aims to characterize the efficacy of cancer therapeutics in vitro and in vivo within the primary tumor and metastatic setting, using patient-derived xenograft (PDX) models.

METHODS

We employed two basal-like, triple-negative PDX models, WHIM2 and WHIM30. PDX cells, obtained from mammary tumors grown in mice, were treated with twelve cancer therapeutics to evaluate their cytotoxicity in vitro. Four of the effective drugs-carboplatin, cyclophosphamide, bortezomib, and dacarbazine-were tested in vivo for their efficacy in treating mammary tumors, and metastases generated by intracardiac injection of tumor cells.

RESULTS

RNA sequencing showed that global gene expression of PDX cells grown in the mammary gland was similar to those tested in culture. In vitro, carboplatin was cytotoxic to WHIM30 but not WHIM2, whereas bortezomib, dacarbazine, and cyclophosphamide were cytotoxic to both lines. Yet, these drugs were ineffective in treating both primary and metastatic WHIM2 tumors in vivo. Carboplatin and cyclophosphamide were effective in treating WHIM30 mammary tumors and reducing metastatic burden in the brain, liver, and lungs. WHIM2 and WHIM30 metastases showed distinct patterns of cytokeratin and vimentin expression, regardless of treatment, suggesting that different tumor cell subpopulations may preferentially seed in different organs.

CONCLUSIONS

This study highlights the utility of PDX models for studying the efficacy of therapeutics in reducing metastatic burden in specific organs. The differential treatment responses between two PDX models of the same intrinsic subtype, in both the primary and metastatic setting, recapitulates the challenges faced in treating cancer patients and highlights the need for combination therapies and predictive biomarkers.

Impact of the Microenvironment on Tumour Budding in Colorectal Cancer

Tumour Budding (TB) is recognized as an adverse prognostic factor in colorectal cancer (CRC). TB is the detachment of isolated cancer cells or small clusters of such cells mainly at the invasion front. One question that arises is of the role of the tumour stroma regarding the permissiveness of the formation and progression of TB. In this review, we will examine potential factors affecting TB, in particular we will analyse the potential effect of inflammation, hypoxia, extracellular matrix and Cancer-Associated Fibroblasts (CAFs).