Showing papers on "Tumour heterogeneity published in 2021"

Single-cell profiling of tumor heterogeneity and the microenvironment in advanced non-small cell lung cancer

Abstract: Lung cancer is a highly heterogeneous disease. Cancer cells and cells within the tumor microenvironment together determine disease progression, as well as response to or escape from treatment. To map the cell type-specific transcriptome landscape of cancer cells and their tumor microenvironment in advanced non-small cell lung cancer (NSCLC), we analyze 42 tissue biopsy samples from stage III/IV NSCLC patients by single cell RNA sequencing and present the large scale, single cell resolution profiles of advanced NSCLCs. In addition to cell types described in previous single cell studies of early stage lung cancer, we are able to identify rare cell types in tumors such as follicular dendritic cells and T helper 17 cells. Tumors from different patients display large heterogeneity in cellular composition, chromosomal structure, developmental trajectory, intercellular signaling network and phenotype dominance. Our study also reveals a correlation of tumor heterogeneity with tumor associated neutrophils, which might help to shed light on their function in NSCLC. Comprehensive profiles of tumour and microenvironment are critical to understand heterogeneity in non-small cell lung cancer (NSCLC). Here, the authors profile 42 late-stage NSCLC patients with single-cell RNA-seq, revealing immune landscapes that are associated with cancer subtype or heterogeneity.

Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing

Abstract: Objective Tumour heterogeneity represents a major obstacle to accurate diagnosis and treatment in gastric adenocarcinoma (GA). Here, we report a systematic transcriptional atlas to delineate molecular and cellular heterogeneity in GA using single-cell RNA sequencing (scRNA-seq). Design We performed unbiased transcriptome-wide scRNA-seq analysis on 27 677 cells from 9 tumour and 3 non-tumour samples. Analysis results were validated using large-scale histological assays and bulk transcriptomic datasets. Results Our integrative analysis of tumour cells identified five cell subgroups with distinct expression profiles. A panel of differentiation-related genes reveals a high diversity of differentiation degrees within and between tumours. Low differentiation degrees can predict poor prognosis in GA. Among them, three subgroups exhibited different differentiation grade which corresponded well to histopathological features of Lauren’s subtypes. Interestingly, the other two subgroups displayed unique transcriptome features. One subgroup expressing chief-cell markers (eg, LIPF and PGC) and RNF43 with Wnt/β-catenin signalling pathway activated is consistent with the previously described entity fundic gland-type GA (chief cell-predominant, GA-FG-CCP). We further confirmed the presence of GA-FG-CCP in two public bulk datasets using transcriptomic profiles and histological images. The other subgroup specifically expressed immune-related signature genes (eg, LY6K and major histocompatibility complex class II) with the infection of Epstein-Barr virus. In addition, we also analysed non-malignant epithelium and provided molecular evidences for potential transition from gastric chief cells into MUC6+TFF2+ spasmolytic polypeptide expressing metaplasia. Conclusion Altogether, our study offers valuable resource for deciphering gastric tumour heterogeneity, which will provide assistance for precision diagnosis and prognosis.

Breast cancer as an example of tumour heterogeneity and tumour cell plasticity during malignant progression.

Abstract: Heterogeneity within a tumour increases its ability to adapt to constantly changing constraints, but adversely affects a patient’s prognosis, therapy response and clinical outcome. Intratumoural heterogeneity results from a combination of extrinsic factors from the tumour microenvironment and intrinsic parameters from the cancer cells themselves, including their genetic, epigenetic and transcriptomic traits, their ability to proliferate, migrate and invade, and their stemness and plasticity attributes. Cell plasticity constitutes the ability of cancer cells to rapidly reprogramme their gene expression repertoire, to change their behaviour and identities, and to adapt to microenvironmental cues. These features also directly contribute to tumour heterogeneity and are critical for malignant tumour progression. In this article, we use breast cancer as an example of the origins of tumour heterogeneity (in particular, the mutational spectrum and clonal evolution of progressing tumours) and of tumour cell plasticity (in particular, that shown by tumour cells undergoing epithelial-to-mesenchymal transition), as well as considering interclonal cooperativity and cell plasticity as sources of cancer cell heterogeneity. We review current knowledge on the functional contribution of cell plasticity and tumour heterogeneity to malignant tumour progression, metastasis formation and therapy resistance.

Genetic and non-genetic clonal diversity in cancer evolution.

Abstract: The observation and analysis of intra-tumour heterogeneity (ITH), particularly in genomic studies, has advanced our understanding of the evolutionary forces that shape cancer growth and development. However, only a subset of the variation observed in a single tumour will have an impact on cancer evolution, highlighting the need to distinguish between functional and non-functional ITH. Emerging studies highlight a role for the cancer epigenome, transcriptome and immune microenvironment in functional ITH. Here, we consider the importance of both genetic and non-genetic ITH and their role in tumour evolution, and present the rationale for a broad research focus beyond the cancer genome. Systems-biology analytical approaches will be necessary to outline the scale and importance of functional ITH. By allowing a deeper understanding of tumour evolution this will, in time, encourage development of novel therapies and improve outcomes for patients.

Applying high-dimensional single-cell technologies to the analysis of cancer immunotherapy.

Abstract: Advances in molecular biology, microfluidics and bioinformatics have empowered the study of thousands or even millions of individual cells from malignant tumours at the single-cell level of resolution. This high-dimensional, multi-faceted characterization of the genomic, transcriptomic, epigenomic and proteomic features of the tumour and/or the associated immune and stromal cells enables the dissection of tumour heterogeneity, the complex interactions between tumour cells and their microenvironment, and the details of the evolutionary trajectory of each tumour. Single-cell transcriptomics, the ability to track individual T cell clones through paired sequencing of the T cell receptor genes and high-dimensional single-cell spatial analysis are all areas of particular relevance to immuno-oncology. Multidimensional biomarker signatures will increasingly be crucial to guiding clinical decision-making in each patient with cancer. High-dimensional single-cell technologies are likely to provide the resolution and richness of data required to generate such clinically relevant signatures in immuno-oncology. In this Perspective, we describe advances made using transformative single-cell analysis technologies, especially in relation to clinical response and resistance to immunotherapy, and discuss the growing utility of single-cell approaches for answering important research questions. The availability of ever more sensitive cell sorting and sequencing technologies has enabled the interrogation of tumour cell biology at the highest possible level of resolution — analysis of a single cell. In this Perspective, the authors describe the application of such approaches to the analysis of single tumour-associated immune cells and their potential for improving the outcomes in patients receiving anti-cancer immunotherapies.

A nanotherapeutic strategy to overcome chemotherapeutic resistance of cancer stem-like cells.

Abstract: Tumour heterogeneity remains a major challenge in cancer therapy owing to the different susceptibility of cells to chemotherapy within a solid tumour. Cancer stem-like cells (CSCs), which reside in hypoxic tumour regions, are characterized by high tumourigenicity and chemoresistance and are often responsible for tumour progression and recurrence. Here we report a nanotherapeutic strategy to kill CSCs in tumours using nanoparticles that are co-loaded with the differentiation-inducing agent, all-trans retinoic acid, and the chemotherapeutic drug, camptothecin. All-trans retinoic acid is released under hypoxic conditions, leading to CSC differentiation in the hypoxic niche. In differentiating CSC, the reactive oxygen species levels increase, which then causes the release of camptothecin and subsequent cell death. This dual strategy enables controlled drug release in CSCs and reduces stemness-related drug resistance, enhancing the chemotherapeutic response. In breast tumour mouse models, treatment with the nanoparticles suppresses tumour growth and prevents post-surgical tumour relapse and metastasis. Chemoresistant cancer stem-like cells (CSCs) can be selectively killed by a nanoparticle, which releases an agent under hypoxic conditions that induces CSC differentiation, and a chemotherapeutic drug in response to reactive oxygen species in differentiating CSCs.

Breast tumours maintain a reservoir of subclonal diversity during expansion

Abstract: Our knowledge of copy number evolution during the expansion of primary breast tumours is limited1,2. Here, to investigate this process, we developed a single-cell, single-molecule DNA-sequencing method and performed copy number analysis of 16,178 single cells from 8 human triple-negative breast cancers and 4 cell lines. The results show that breast tumours and cell lines comprise a large milieu of subclones (7–22) that are organized into a few (3–5) major superclones. Evolutionary analysis suggests that after clonal TP53 mutations, multiple loss-of-heterozygosity events and genome doubling, there was a period of transient genomic instability followed by ongoing copy number evolution during the primary tumour expansion. By subcloning single daughter cells in culture, we show that tumour cells rediversify their genomes and do not retain isogenic properties. These data show that triple-negative breast cancers continue to evolve chromosome aberrations and maintain a reservoir of subclonal diversity during primary tumour growth. Single-cell analysis of genomes from primary human breast tumours and cell lines shows that chromosomal aberrations continue to evolve during primary tumour expansion, resulting in a milieu of subclones within the tumour.

Tumour heterogeneity and intercellular networks of nasopharyngeal carcinoma at single cell resolution.

Abstract: The heterogeneous nature of tumour microenvironment (TME) underlying diverse treatment responses remains unclear in nasopharyngeal carcinoma (NPC). Here, we profile 176,447 cells from 10 NPC tumour-blood pairs, using single-cell transcriptome coupled with T cell receptor sequencing. Our analyses reveal 53 cell subtypes, including tumour-infiltrating CD8+ T, regulatory T (Treg), and dendritic cells (DCs), as well as malignant cells with different Epstein-Barr virus infection status. Trajectory analyses reveal exhausted CD8+ T and immune-suppressive TNFRSF4+ Treg cells in tumours might derive from peripheral CX3CR1+CD8+ T and naive Treg cells, respectively. Moreover, we identify immune-regulatory and tolerogenic LAMP3+ DCs. Noteworthily, we observe intensive inter-cell interactions among LAMP3+ DCs, Treg, exhausted CD8+ T, and malignant cells, suggesting potential cross-talks to foster an immune-suppressive niche for the TME. Collectively, our study uncovers the heterogeneity and interacting molecules of the TME in NPC at single-cell resolution, which provide insights into the mechanisms underlying NPC progression and the development of precise therapies for NPC.

Pancreatic cancer evolution and heterogeneity: integrating omics and clinical data.

Abstract: Pancreatic ductal adenocarcinoma (PDAC), already among the deadliest epithelial malignancies, is rising in both incidence and contribution to overall cancer deaths. Decades of research have improved our understanding of PDAC carcinogenesis, including characterizing germline predisposition, the cell of origin, precursor lesions, the sequence of genetic alterations, including simple and structural alterations, transcriptional changes and subtypes, tumour heterogeneity, metastatic progression and the tumour microenvironment. These fundamental advances inform contemporary translational efforts in primary prevention, screening and early detection, multidisciplinary management and survivorship, as prospective clinical trials begin to adopt molecular-based selection criteria to guide targeted therapies. Genomic and transcriptomic data on PDAC were also included in the international pan-cancer analysis of approximately 2,600 cancers, a milestone in cancer research that allows further insight through comparison with other tumour types. Thus, this is an ideal time to review our current knowledge of PDAC evolution and heterogeneity, gained from the study of preclinical models and patient biospecimens, and to propose a model of PDAC evolution that takes into consideration findings from varied sources, with a particular focus on the genomics of human PDAC. This Review outlines our current understanding of the evolution and heterogeneity of pancreatic ductal adenocarcinoma (PDAC), which has advanced owing to the study of preclinical models and patient samples, and presents an evolutionary model of PDAC progression based primarily on genomics studies of human PDAC.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC

Abstract: Triple-negative breast cancer (TNBC) is characterized by a more aggressive clinical course with extensive inter- and intra-tumour heterogeneity. Combination of single-cell and bulk tissue transcriptome profiling allows the characterization of tumour heterogeneity and identifies the association of the immune landscape with clinical outcomes. We identified inter- and intra-tumour heterogeneity at a single-cell resolution. Tumour cells shared a high correlation amongst stemness, angiogenesis, and EMT in TNBC. A subset of cells with concurrent high EMT, stemness and angiogenesis was identified at the single-cell level. Amongst tumour-infiltrating immune cells, M2-like tumour-associated macrophages (TAMs) made up the majority of macrophages and displayed immunosuppressive characteristics. CIBERSORT was applied to estimate the abundance of M2-like TAM in bulk tissue transcriptome file from The Cancer Genome Atlas (TCGA). M2-like TAMs were associated with unfavourable prognosis in TNBC patients. A TAM-related gene signature serves as a promising marker for predicting prognosis and response to immunotherapy. Two commonly used machine learning methods, random forest and SVM, were applied to find the genes that were mostly associated with M2-like TAM densities in the gene signature. A neural network-based deep learning framework based on the TAM-related gene signature exhibits high accuracy in predicting the immunotherapy response.

Metabolic reprogramming in prostate cancer.

Abstract: Although low risk localised prostate cancer has an excellent prognosis owing to effective treatments, such as surgery, radiation, cryosurgery and hormone therapy, metastatic prostate cancer remains incurable. Existing therapeutic regimens prolong life; however, they are beset by problems of resistance, resulting in poor outcomes. Treatment resistance arises primarily from tumour heterogeneity, altered genetic signatures and metabolic reprogramming, all of which enable the tumour to serially adapt to drugs during the course of treatment. In this review, we focus on alterations in the metabolism of prostate cancer, including genetic signatures and molecular pathways associated with metabolic reprogramming. Advances in our understanding of prostate cancer metabolism might help to explain many of the adaptive responses that are induced by therapy, which might, in turn, lead to the attainment of more durable therapeutic responses.

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy

Abstract: Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished ‘classical’ from ‘basal-like’ tumors with more aggressive clinical behavior. We derive PDAC organoids from 18 primary tumors and two matched liver metastases, and show that ‘classical’ and ‘basal-like’ cells coexist in individual organoids. By single-cell transcriptome analysis of PDAC organoids and primary PDAC, we identify distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. Cell states are connected by a differentiation hierarchy, with ‘classical’ cells concentrated at the endpoint. In an imaging-based drug screen, expression of ‘classical’ subtype genes correlates with better drug response. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model for in vitro studies of tumor heterogeneity. Pancreatic tumors are frequently divided into basal and classical subtypes. Here, the authors use single cell sequencing to investigate organoids derived from pancreatic cancer tissue and find a hierarchy of distinct cell states, and classical and basal cells existing within the same tumor.

Single-Cell RNA Sequencing in Multiple Pathologic Types of Renal Cell Carcinoma Revealed Novel Potential Tumor-Specific Markers.

Abstract: Background: Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumour heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal some potential tumour-specific markers, especially single-cell RNA sequencing (scRNA-seq). Methods: We performed an exploratory study on three pathological types of RCC with a small sample size. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on normal kidneys. Tumour characteristics were well identified by the comparison between different pathological types of RCC and normal kidneys at the scRNA level. Results: Some new tumour-specific markers for different pathologic types of RCC, such as SPOCK1, PTGIS, REG1A, CP and SPAG4 were identified and validated. We also discovered that NDUFA4L2 both highly expressed in tumour cells of ccRCC and type 2 pRCC. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as POSTN and COL3A1. At last, by applying scRNA-seq results, the activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC. Conclusions: Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.

Beyond Just Peptide Antigens: The Complex World of Peptide-Based Cancer Vaccines.

Abstract: Peptide-based cancer vaccines rely upon the strong activation of the adaptive immune response to elicit its effector function. They have shown to be highly specific and safe, but have yet to prove themselves as an efficacious treatment for cancer in the clinic. This is for a variety of reasons, including tumour heterogeneity, self-tolerance, and immune suppression. Importance has been placed on the overall design of peptide-based cancer vaccines, which have evolved from simple peptide derivatives of a cancer antigen, to complex drugs; incorporating overlapping regions, conjugates, and delivery systems to target and stimulate different components of antigen presenting cells, and to bolster antigen cross-presentation. Peptide-based cancer vaccines are increasingly becoming more personalised to an individual’s tumour antigen repertoire and are often combined with existing cancer treatments. This strategy ultimately aids in combating the shortcomings of a more generalised vaccine strategy and provides a comprehensive treatment, taking into consideration cancer cell variability and its ability to avoid immune interrogation.

Conformable hierarchically engineered polymeric micromeshes enabling combinatorial therapies in brain tumours.

Abstract: The poor transport of molecular and nanoscale agents through the blood–brain barrier together with tumour heterogeneity contribute to the dismal prognosis in patients with glioblastoma multiforme. Here, a biodegradable implant (μMESH) is engineered in the form of a micrometre-sized poly(lactic-co-glycolic acid) mesh laid over a water-soluble poly(vinyl alcohol) layer. Upon poly(vinyl alcohol) dissolution, the flexible poly(lactic-co-glycolic acid) mesh conforms to the resected tumour cavity as docetaxel-loaded nanomedicines and diclofenac molecules are continuously and directly released into the adjacent tumour bed. In orthotopic brain cancer models, generated with a conventional, reference cell line and patient-derived cells, a single μMESH application, carrying 0.75 mg kg−1 of docetaxel and diclofenac, abrogates disease recurrence up to eight months after tumour resection, with no appreciable adverse effects. Without tumour resection, the μMESH increases the median overall survival (∼30 d) as compared with the one-time intracranial deposition of docetaxel-loaded nanomedicines (15 d) or 10 cycles of systemically administered temozolomide (12 d). The μMESH modular structure, for the independent coloading of different molecules and nanomedicines, together with its mechanical flexibility, can be exploited to treat a variety of cancers, realizing patient-specific dosing and interventions. Surgical resection is the primary treatment strategy for glioblastoma multiforme, but the infiltrating nature of the tumour, coupled with its heterogeneity and the presence of the blood–brain barrier that hampers drug delivery, contributes to recurrence and poor prognosis. Here the authors engineer a mechanically flexible mesh that can adhere to the tumour resected cavity and release a combination of nanomedicines and small molecules in a controlled and sustained manner for tumour therapy.

Clinical impact of subclonal EGFR T790M mutations in advanced-stage EGFR-mutant non-small-cell lung cancers

Abstract: Advanced non-small-cell lung cancer (NSCLC) patients with EGFR T790M-positive tumours benefit from osimertinib, an epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI). Here we show that the size of the EGFR T790M-positive clone impacts response to osimertinib. T790M subclonality, as assessed by a retrospective NGS analysis of 289 baseline plasma ctDNA samples from T790M-positive advanced NSCLC patients from the AURA3 phase III trial, is associated with shorter progression-free survival (PFS), both in the osimertinib and the chemotherapy-treated patients. Both baseline and longitudinal ctDNA profiling indicate that the T790M subclonal tumours are enriched for PIK3CA alterations, which we demonstrate to confer resistance to osimertinib in vitro that can be partially reversed by PI3K pathway inhibitors. Overall, our results elucidate the impact of tumour heterogeneity on response to osimertinib in advanced stage NSCLC patients and could help define appropriate combination therapies in these patients.

Histone Modification in NSCLC: Molecular Mechanisms and Therapeutic Targets

Abstract: Lung cancer is the leading cause of cancer mortality in both genders, with non-small cell lung cancer (NSCLC) accounting for about 85% of all lung cancers. At the time of diagnosis, the tumour is usually locally advanced or metastatic, shaping a poor disease outcome. NSCLC includes adenocarcinoma, squamous cell carcinoma, and large cell lung carcinoma. Searching for novel therapeutic targets is mandated due to the modest effect of platinum-based therapy as well as the targeted therapies developed in the last decade. The latter is mainly due to the lack of mutation detection in around half of all NSCLC cases. New therapeutic modalities are also required to enhance the effect of immunotherapy in NSCLC. Identifying the molecular signature of NSCLC subtypes, including genetics and epigenetic variation, is crucial for selecting the appropriate therapy or combination of therapies. Epigenetic dysregulation has a key role in the tumourigenicity, tumour heterogeneity, and tumour resistance to conventional anti-cancer therapy. Epigenomic modulation is a potential therapeutic strategy in NSCLC that was suggested a long time ago and recently starting to attract further attention. Histone acetylation and deacetylation are the most frequently studied patterns of epigenetic modification. Several histone deacetylase (HDAC) inhibitors (HDIs), such as vorinostat and panobinostat, have shown promise in preclinical and clinical investigations on NSCLC. However, further research on HDIs in NSCLC is needed to assess their anti-tumour impact. Another modification, histone methylation, is one of the most well recognized patterns of histone modification. It can either promote or inhibit transcription at different gene loci, thus playing a rather complex role in lung cancer. Some histone methylation modifiers have demonstrated altered activities, suggesting their oncogenic or tumour-suppressive roles. In this review, patterns of histone modifications in NSCLC will be discussed, focusing on the molecular mechanisms of epigenetic modifications in tumour progression and metastasis, as well as in developing drug resistance. Then, we will explore the therapeutic targets emerging from studying the NSCLC epigenome, referring to the completed and ongoing clinical trials on those medications.

Multifaceted microglia — key players in primary brain tumour heterogeneity

Abstract: Microglia are the resident innate immune cells of the immune-privileged CNS and, as such, represent the first line of defence against tissue injury and infection. Given their location, microglia are undoubtedly the first immune cells to encounter a developing primary brain tumour. Our knowledge of these cells is therefore important to consider in the context of such neoplasms. As the heterogeneous nature of the most aggressive primary brain tumours is thought to underlie their poor prognosis, this Review places a special emphasis on the heterogeneity of the tumour-associated microglia and macrophage populations present in primary brain tumours. Where available, specific information on microglial heterogeneity in various types and subtypes of brain tumour is included. Emerging evidence that highlights the importance of considering the heterogeneity of both the tumour and of microglial populations in providing improved treatment outcomes for patients is also discussed. Microglia are the first immune cells to encounter a developing primary brain tumour and have both tumour-supporting and antitumour effects. Here, Keane et al. consider the emerging evidence indicating that tumour-associated macrophages and microglia influence tumour initiation and progression as well as responses to therapy.

Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

Abstract: Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

Single cell RNA sequencing for breast cancer: present and future

Abstract: Breast cancer is one of the most common malignant tumors in women. It is a heterogeneous disease related to genetic and environmental factors. Presently, the treatment of breast cancer still faces challenges due to recurrence and metastasis. The emergence of single-cell RNA sequencing (scRNA-seq) technology has brought new strategies to deeply understand the biological behaviors of breast cancer. By analyzing cell phenotypes and transcriptome differences at the single-cell level, scRNA-seq reveals the heterogeneity, dynamic growth and differentiation process of cells. This review summarizes the application of scRNA-seq technology in breast cancer research, such as in studies on cell heterogeneity, cancer cell metastasis, drug resistance, and prognosis. scRNA-seq technology is of great significance to deeply analyze the mechanism of breast cancer occurrence and development, identify new therapeutic targets and develop new therapeutic approaches for breast cancer.

Chemotherapy induces canalization of cell state in childhood B-cell precursor acute lymphoblastic leukemia

Abstract: Comparison of intratumor genetic heterogeneity in cancer at diagnosis and relapse suggests that chemotherapy induces bottleneck selection of subclonal genotypes. However, evolutionary events subsequent to chemotherapy could also explain changes in clonal dominance seen at relapse. We therefore investigated the mechanisms of selection in childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL) during induction chemotherapy where maximal cytoreduction occurs. To distinguish stochastic versus deterministic events, individual leukemias were transplanted into multiple xenografts and chemotherapy administered. Analyses of the immediate post-treatment leukemic residuum at single-cell resolution revealed that chemotherapy has little impact on genetic heterogeneity. Rather, it acts on extensive, previously unappreciated, transcriptional and epigenetic heterogeneity in BCP-ALL, dramatically reducing the spectrum of cell states represented, leaving a genetically polyclonal but phenotypically uniform population, with hallmark signatures relating to developmental stage, cell cycle and metabolism. Hence, canalization of the cell state accounts for a significant component of bottleneck selection during induction chemotherapy. Enver and colleagues report that epigenetic cell state, rather than genetic diversity, drives bottleneck selection of subclonal genotypes during induction chemotherapy in childhood B-cell precursor acute lymphoblastic leukemia.

Induction of APOBEC3B expression by chemotherapy drugs is mediated by DNA-PK-directed activation of NF-κB.

Abstract: The mutagenic APOBEC3B (A3B) cytosine deaminase is frequently over-expressed in cancer and promotes tumour heterogeneity and therapy resistance. Hence, understanding the mechanisms that underlie A3B over-expression is important, especially for developing therapeutic approaches to reducing A3B levels, and consequently limiting cancer mutagenesis. We previously demonstrated that A3B is repressed by p53 and p53 mutation increases A3B expression. Here, we investigate A3B expression upon treatment with chemotherapeutic drugs that activate p53, including 5-fluorouracil, etoposide and cisplatin. Contrary to expectation, these drugs induced A3B expression and concomitant cellular cytosine deaminase activity. A3B induction was p53-independent, as chemotherapy drugs stimulated A3B expression in p53 mutant cells. These drugs commonly activate ATM, ATR and DNA-PKcs. Using specific inhibitors and gene knockdowns, we show that activation of DNA-PKcs and ATM by chemotherapeutic drugs promotes NF-κB activity, with consequent recruitment of NF-κB to the A3B gene promoter to drive A3B expression. Further, we find that A3B knockdown re-sensitises resistant cells to cisplatin, and A3B knockout enhances sensitivity to chemotherapy drugs. Our data highlight a role for A3B in resistance to chemotherapy and indicate that stimulation of A3B expression by activation of DNA repair and NF-κB pathways could promote cancer mutations and expedite chemoresistance.

ctDNA-Based Liquid Biopsy of Cerebrospinal Fluid in Brain Cancer

Abstract: The correct characterisation of central nervous system (CNS) malignancies is crucial for accurate diagnosis and prognosis and also the identification of actionable genomic alterations that can guide the therapeutic strategy. Surgical biopsies are performed to characterise the tumour; however, these procedures are invasive and are not always feasible for all patients. Moreover, they only provide a static snapshot and can miss tumour heterogeneity. Currently, monitoring of CNS cancer is performed by conventional imaging techniques and, in some cases, cytology analysis of the cerebrospinal fluid (CSF); however, these techniques have limited sensitivity. To overcome these limitations, a liquid biopsy of the CSF can be used to obtain information about the tumour in a less invasive manner. The CSF is a source of cell-free circulating tumour DNA (ctDNA), and the analysis of this biomarker can characterise and monitor brain cancer. Recent studies have shown that ctDNA is more abundant in the CSF than plasma for CNS malignancies and that it can be sequenced to reveal tumour heterogeneity and provide diagnostic and prognostic information. Furthermore, analysis of longitudinal samples can aid patient monitoring by detecting residual disease or even tracking tumour evolution at relapse and, therefore, tailoring the therapeutic strategy. In this review, we provide an overview of the potential clinical applications of the analysis of CSF ctDNA and the challenges that need to be overcome in order to translate research findings into a tool for clinical practice.

The co-evolution of the genome and epigenome in colorectal cancer

Abstract: Colorectal malignancies are a leading cause of cancer death. Despite large-scale genomic efforts, DNA mutations do not fully explain malignant evolution. Here we study the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,373 samples from 30 primary cancers and 9 concomitant adenomas and generated 1,212 chromatin accessibility profiles, 527 whole-genomes and 297 whole-transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent chromatin changes in regulatory regions of cancer drivers with otherwise no mutation. Genome-wide alterations in transcription factor binding accessibility involved CTCF, downregulation of interferon, and increased accessibility for SOX and HOX, indicating developmental genes reactivation. Epigenetic aberrations were heritable, distinguishing adenomas from cancers. Mutational signature analysis showed the epigenome influencing DNA mutation accumulation. This study provides a map of (epi)genetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.

Studying local tumour heterogeneity on MRI and FDG-PET/CT to predict response to neoadjuvant chemoradiotherapy in rectal cancer.

Abstract: To investigate whether quantifying local tumour heterogeneity has added benefit compared to global tumour features to predict response to chemoradiotherapy using pre-treatment multiparametric PET and MRI data. Sixty-one locally advanced rectal cancer patients treated with chemoradiotherapy and staged at baseline with MRI and FDG-PET/CT were retrospectively analyzed. Whole-tumour volumes were segmented on the MRI and PET/CT scans from which global tumour features (T2Wvolume/T2Wentropy/ADCmean/SUVmean/TLG/CTmean-HU) and local texture features (histogram features derived from local entropy/mean/standard deviation maps) were calculated. These respective feature sets were combined with clinical baseline parameters (e.g. age/gender/TN-stage) to build multivariable prediction models to predict a good (Mandard TRG1-2) versus poor (Mandard TRG3-5) response to chemoradiotherapy. Leave-one-out cross-validation (LOOCV) with bootstrapping was performed to estimate performance in an ‘independent’ dataset. When using only imaging features, local texture features showed an AUC = 0.81 versus AUC = 0.74 for global tumour features. After internal cross-validation (LOOCV), AUC to predict a good response was the highest for the combination of clinical baseline variables + global tumour features (AUC = 0.83), compared to AUC = 0.79 for baseline + local texture and AUC = 0.76 for all combined (baseline + global + local texture). In imaging-based prediction models, local texture analysis has potential added value compared to global tumour features to predict response. However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture analysis appears to be limited. The overall performance to predict response when combining baseline variables with quantitative imaging parameters is promising and warrants further research. • Quantification of local tumour texture on pre-therapy FDG-PET/CT and MRI has potential added value compared to global tumour features to predict response to chemoradiotherapy in rectal cancer. • However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture over global tumour features is limited. • Predictive performance of our optimal model—combining clinical baseline variables with global quantitative tumour features—was encouraging (AUC 0.83), warranting further research in this direction on a larger scale.