Measuring Clonal Evolution in Cancer with Genomics

Exploring the role of m7G modification in Cancer: Mechanisms, regulatory proteins, and biomarker potential

The dysregulation of N(7)-methylguanosine (m7G) modification is increasingly recognized as a key factor in the pathogenesis of cancers. Aberrant expression of these regulatory proteins in various cancers, including lung, liver, and bladder cancers, suggests a universal role in tumorigenesis. Studies have established a strong correlation between the expression levels of m7G regulatory proteins, such as Methyltransferase like 1 (METTL1) and WD repeat domain 4 (WDR4), and clinical parameters including tumor stage, grade, and patient prognosis. For example, in hepatocellular carcinoma, high METTL1 expression is associated with advanced tumor stage and poor prognosis. Similarly, WDR4 overexpression in colorectal cancer correlates with increased tumor invasiveness and reduced patient survival. This correlation underscores the potential of these proteins as valuable biomarkers for cancer diagnosis and prognosis. Additionally, m7G modification regulatory proteins influence cancer progression by modulating the expression of target genes involved in critical biological processes, including cell proliferation, apoptosis, migration, and invasion. Their ability to regulate these processes highlights their significance in the intricate network of molecular interactions driving tumor development and metastasis. Given their pivotal role in cancer biology, m7G modification regulatory proteins are emerging as promising therapeutic targets. Targeting these proteins could offer a novel approach to disrupt the malignant behavior of cancer cells and enhance treatment outcomes. Furthermore, their diagnostic and prognostic value could aid in the early detection of cancer and the selection of appropriate therapeutic strategies, ultimately enhancing patient management and survival rates. This review aims to explore the mechanisms of action of RNA m7G modification regulatory proteins in tumors and their potential applications in cancer progression and treatment. By delving into the roles of these regulatory proteins, we intend to provide a theoretical foundation for the development of novel cancer treatment strategies.

Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice

Quantitative predictive modeling of cancer growth, progression, and individual response to therapy is a rapidly growing field. Researchers from mathematical modeling, systems biology, pharmaceutical industry, and regulatory bodies, are collaboratively working on predictive models that could be applied for drug development and, ultimately, the clinical management of cancer patients. A plethora of modeling paradigms and approaches have emerged, making it challenging to compile a comprehensive review across all subdisciplines. It is therefore critical to gauge fundamental design aspects against requirements, and weigh opportunities and limitations of the different model types. In this review, we discuss three fundamental types of cancer models: space-structured models, ecological models, and immune system focused models. For each type, it is our goal to illustrate which mechanisms contribute to variability and heterogeneity in cancer growth and response, so that the appropriate architecture and complexity of a new model becomes clearer. We present the main features addressed by each of the three exemplary modeling types through a subjective collection of literature and illustrative exercises to facilitate inspiration and exchange, with a focus on providing a didactic rather than exhaustive overview. We close by imagining a future multi-scale model design to impact critical decisions in oncology drug development.

Stochastic modelling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones

Cancer progression is an evolutionary process driven by the selection of cells adapted to gain growth advantage. We present the first formal study on the adaptation of gene expression in subclonal evolution. We model evolutionary changes in gene expression as stochastic Ornstein-Uhlenbeck processes, jointly leveraging the evolutionary history of subclones and single-cell expression data. Applying our model to sublines derived from single cells of a mouse melanoma revealed that sublines with distinct phenotypes are underlined by different patterns of gene expression adaptation, indicating non-genetic mechanisms of cancer evolution. Interestingly, sublines previously observed to be resistant to anti-CTLA-4 treatment showed adaptive expression of genes related to invasion and non-canonical Wnt signaling, whereas sublines that responded to treatment showed adaptive expression of genes related to proliferation and canonical Wnt signaling. Our results suggest that clonal phenotypes emerge as the result of specific adaptivity patterns of gene expression.

Phenotypic Heterogeneity, Bidirectionality, Universal Cues, Plasticity, Mechanics, and the Tumor Microenvironment Drive Cancer Metastasis

Tumor diseases become a huge problem when they embark on a path that advances to malignancy, such as the process of metastasis. Cancer metastasis has been thoroughly investigated from a biological perspective in the past, whereas it has still been less explored from a physical perspective. Until now, the intraluminal pathway of cancer metastasis has received the most attention, while the interaction of cancer cells with macrophages has received little attention. Apart from the biochemical characteristics, tumor treatments also rely on the tumor microenvironment, which is recognized to be immunosuppressive and, as has recently been found, mechanically stimulates cancer cells and thus alters their functions. The review article highlights the interaction of cancer cells with other cells in the vascular metastatic route and discusses the impact of this intercellular interplay on the mechanical characteristics and subsequently on the functionality of cancer cells. For instance, macrophages can guide cancer cells on their intravascular route of cancer metastasis, whereby they can help to circumvent the adverse conditions within blood or lymphatic vessels. Macrophages induce microchannel tunneling that can possibly avoid mechanical forces during extra- and intravasation and reduce the forces within the vascular lumen due to vascular flow. The review article highlights the vascular route of cancer metastasis and discusses the key players in this traditional route. Moreover, the effects of flows during the process of metastasis are presented, and the effects of the microenvironment, such as mechanical influences, are characterized. Finally, the increased knowledge of cancer metastasis opens up new perspectives for cancer treatment.

A comprehensive characterisation of phaeochromocytoma and paraganglioma tumours through histone protein profiling, DNA methylation and transcriptomic analysis genome wide

BACKGROUND

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours. Pathogenic variants have been identified in more than 15 susceptibility genes; associated tumours are grouped into three Clusters, reinforced by their transcriptional profiles. Cluster 1A PPGLs have pathogenic variants affecting enzymes of the tricarboxylic acid cycle, including succinate dehydrogenase. Within inherited PPGLs, these are the most common. PPGL tumours are known to undergo epigenetic reprograming, and here, we report on global histone post-translational modifications and DNA methylation levels, alongside clinical phenotypes.

RESULTS

Out of the 25 histone post-translational modifications examined, Cluster 1A PPGLs were distinguished from other tumours by a decrease in hyper-acetylated peptides and an increase in H3K4me2. DNA methylation was compared between tumours from individuals who developed metastatic disease versus those that did not. The majority of differentially methylated sites identified tended to be completely methylated or unmethylated in non-metastatic tumours, with low inter-sample variance. Metastatic tumours by contrast consistently had an intermediate DNA methylation state, including the ephrin receptor EPHA4 and its ligand EFNA3. Gene expression analyses performed to identify genes involved in metastatic tumour behaviour pin-pointed a number of genes previously described as mis-regulated in Cluster 1A tumours, as well as highlighting the tumour suppressor RGS22 and the pituitary tumour-transforming gene PTTG1.

CONCLUSIONS

Combined transcriptomic and DNA methylation analyses revealed aberrant pathways, including ones that could be implicated in metastatic phenotypes and, for the first time, we report a decrease in hyper-acetylated histone marks in Cluster 1 PPGLs.

Elucidating the clonal relationship of esophageal second primary tumors in patients with laryngeal squamous cell carcinoma

Laryngeal cancer ranks as the second most prevalent upper airway malignancy, following Lung cancer. Although some progress has been made in managing laryngeal cancer, the 5-year survival rate is disappointing. The gradual increase in the incidence of second primary tumors (SPTs) plays a crucial role in determining survival outcomes during long-term follow-up, and the esophagus was the most common site with a worse prognosis. In clinical practice, the treatment of esophageal second primary tumors (ESPT) in patients with laryngeal squamous cell carcinoma (LSCC) has always been challenging. For patients with synchronous tumors, several treatment modalities, such as radiotherapy, chemotherapy and potentially curative surgery are necessary but are typically poorly tolerated. Secondary cancer therapy options for metachronous patients are always constrained by index cancer treatment indications. Therefore, understanding the clonal origin of the second primary tumor may be an important issue in the treatment of patients. LSCC cells demonstrate genetic instability because of two distinct aetiologies (human papillomavirus (HPV)-negative and HPV-positive) disease. Various etiologies exhibit distinct oncogenic mechanisms, which subsequently impact the tissue microenvironment. The condition of the tissue microenvironment plays a crucial role in determining the destiny and clonal makeup of mutant cells during the initial stages of tumorigenesis. This review focuses on the genetic advances of LSCC, the current research status of SPT, and the influence of key carcinogenesis of HPV-positive and HPV-negative LSCC on clonal evolution of ESPT cells. The objective is to gain a comprehensive understanding of the molecular basis underlying the clonal origins of SPT, thereby offering novel perspectives for future investigations in this field.

Characterization of Cancer Evolution Landscape Based on Accurate Detection of Somatic Mutations in Single Tumor Cells

Accurate detection of somatic mutations in single tumor cells is greatly desired as it allows us to quantify the single-cell mutation burden and construct the mutation-based phylogenetic tree. Here we developed scNanoSeq chemistry and profiled 842 single cells from 21 human breast cancer samples. The majority of the mutation-based phylogenetic trees comprise a characteristic stem evolution followed by the clonal sweep. We observed the subtype-dependent lengths in the stem evolution. To explain this phenomenon, we propose that the differences are related to different reprogramming required for different subtypes of breast cancer. Furthermore, we reason that the time that the tumor-initiating cell took to acquire the critical clonal-sweep-initiating mutation by random chance set the time limit for the reprogramming process. We refer to this model as a reprogramming and critical mutation co-timing (RCMC) subtype model. Next, in the sweeping clone, we observed that tumor cells undergo a branched evolution with rapidly decreasing selection. In the most recent clades, effectively neutral evolution has been reached, resulting in a substantially large number of mutational heterogeneities. Integrative analysis with 522-713X ultra-deep bulk whole genome sequencing (WGS) further validated this evolution mode. Mutation-based phylogenetic trees also allow us to identify the early branched cells in a few samples, whose phylogenetic trees support the gradual evolution of copy number variations (CNVs). Overall, the development of scNanoSeq allows us to unveil novel insights into breast cancer evolution.

Single-cell phylogenies reveal changes in the evolutionary rate within cancer and healthy tissues

Cell lineages accumulate somatic mutations during organismal development, potentially leading to pathological states. The rate of somatic evolution within a cell population can vary due to multiple factors, including selection, a change in the mutation rate, or differences in the microenvironment. Here, we developed a statistical test called the Poisson Tree (PT) test to detect varying evolutionary rates among cell lineages, leveraging the phylogenetic signal of single-cell DNA sequencing (scDNA-seq) data. We applied the PT test to 24 healthy and cancer samples, rejecting a constant evolutionary rate in 11 out of 15 cancer and five out of nine healthy scDNA-seq datasets. In six cancer datasets, we identified subclonal mutations in known driver genes that could explain the rate accelerations of particular cancer lineages. Our findings demonstrate the efficacy of scDNA-seq for studying somatic evolution and suggest that cell lineages often evolve at different rates within cancer and healthy tissues.

The mutational landscape of the adult healthy parous and nulliparous human breast

The accumulation of somatic mutations in healthy human tissues has been extensively characterized, but the mutational landscape of the healthy breast is still poorly understood. Our analysis of whole-genome sequencing shows that in line with other healthy organs, the healthy breast during the reproduction years accumulates mutations with age, with the rate of accumulation in the epithelium of 15.24 ± 5 mutations/year. Both epithelial and stromal compartments contain mutations in breast-specific driver genes, indicative of subsequent positive selection. Parity- and age-associated differences are evident in the mammary epithelium, partly explaining the observed difference in breast cancer risk amongst women of different childbearing age. Parity is associated with an age-dependent increase in the clone size of mutated epithelial cells, suggesting that older first-time mothers have a higher probability of accumulating oncogenic events in the epithelium compared to younger mothers or nulliparous women. In conclusion, we describe the reference genome of the healthy female human breast during reproductive years and provide evidence of how parity affects the genomic landscape of the mammary gland.

Next-Generation Sequencing Technology: Current Trends and Advancements

The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.

Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools

Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate. The development of technologies such as high-throughput sequencing has provided a powerful means to measure subclonal evolutionary dynamics across space and time. Here, we review the patterns that may be observed in cancer evolution and the methods available for quantifying the evolutionary dynamics of cancer. An improved understanding of the evolutionary trajectories of cancer will enable us to explore the molecular mechanism of tumorigenesis and to design tailored treatment strategies.

Advances in the Anti-Tumor Activity of Biflavonoids in Selaginella

Despite the many strategies employed to slow the spread of cancer, the development of new anti-tumor drugs and the minimization of side effects have been major research hotspots in the anti-tumor field. Natural drugs are a huge treasure trove of drug development, and they have been widely used in the clinic as anti-tumor drugs. Selaginella species in the family Selaginellaceae are widely distributed worldwide, and they have been well-documented in clinical practice for the prevention and treatment of cancer. Biflavonoids are the main active ingredients in Selaginella, and they have good biological and anti-tumor activities, which warrant extensive research. The promise of biflavonoids from Selaginella (SFB) in the field of cancer therapy is being realized thanks to new research that offers insights into the multi-targeting therapeutic mechanisms and key signaling pathways. The pharmacological effects of SFB against various cancers in vitro and in vivo are reviewed in this review. In addition, the types and characteristics of biflavonoid structures are described in detail; we also provide a brief summary of the efforts to develop drug delivery systems or combinations to enhance the bioavailability of SFB monomers. In conclusion, SFB species have great potential to be developed as adjuvant or even primary therapeutic agents for cancer, with promising applications.

Comprehensive pan-cancer analysis identifies centromere associated protein E as a novel prognostic and immunological biomarker in human tumors

Centromere-associated protein E (CENP-E), a core component of the kinetochore, mediates chromosome congression and spindle microtubule capture during mitosis. Partial experimental evidence has illustrated the carcinogenic effects of CENPE in tumors, but the corresponding pan-cancer analysis of CENPE still lacking. Based on public databases, including the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA), we take an array of bioinformatics methods to investigate the potential oncogenic roles of CENPE. Then, we validated CENPE, cell cycle-related proteins, and immune checkpoint molecule findings expression in clinical colon cancer samples by western blot. Our results showed that CENPE was up-regulated in almost all tumors, and the expression level of CENPE was associated with worse overall survival (OS) and disease-specific survival (DSS) in patients. The strong relationship between CENPE with gene mutation and MMR has also been validated. Moreover, CENPE gene expression was positively correlated with immune checkpoint molecular, and reversely correlated with infiltration levels of most immune cells. In the human colon cancer tissues, the expression of CENPE, cell cycle-related proteins, and immune checkpoint molecules were significantly higher than in the adjacent normal tissues. Our results indicated that CENPE can function as an oncogene in various cancers, and may be regarded as a promising prognostic and diagnostic biomarker in cancer treatment.

Current Status of the Bioactive Properties of Royal Jelly: A Comprehensive Review with a Focus on Its Anticancer, Anti-Inflammatory, and Antioxidant Effects

Royal jelly (RJ) has been one of the most widely used natural products in alternative medicine for centuries. Being produced by both hypopharyngeal and mandibular glands, RJ exhibits an extraordinary complexity in terms of its composition, including proteins, lipids, carbohydrates, polyphenols, vitamins, and hormones. Due to its heterogeneous structure, RJ displays various functional roles for honeybees, including being involved in nutrition, learning, memory, and social behavior. Furthermore, a wide range of studies reported its therapeutic properties, including anticancer, anti-inflammatory, and antioxidant activities, to name a few. In this direction, there is a wide range of health-related problems for which the medical area specialists and researchers are continuously trying to find a cure, such as cancer, atherosclerosis, or infertility. For the mentioned diseases and more, it has been proven that RJ is a key player in finding a valuable treatment. In this review, the great impact of RJ as an alternative medicine agent is highlighted, with a focus on its anticancer, anti-inflammatory, and antioxidant activities. Moreover, we link it to its apitherapeutic potential by discussing its composition. Herein, we discuss a wide range of novel studies and present the latest research work.

Phenotypic plasticity and genetic control in colorectal cancer evolution

Genetic and epigenetic variation, together with transcriptional plasticity, contribute to intratumour heterogeneity1. The interplay of these biological processes and their respective contributions to tumour evolution remain unknown. Here we show that intratumour genetic ancestry only infrequently affects gene expression traits and subclonal evolution in colorectal cancer (CRC). Using spatially resolved paired whole-genome and transcriptome sequencing, we find that the majority of intratumour variation in gene expression is not strongly heritable but rather 'plastic'. Somatic expression quantitative trait loci analysis identified a number of putative genetic controls of expression by cis-acting coding and non-coding mutations, the majority of which were clonal within a tumour, alongside frequent structural alterations. Consistently, computational inference on the spatial patterning of tumour phylogenies finds that a considerable proportion of CRCs did not show evidence of subclonal selection, with only a subset of putative genetic drivers associated with subclone expansions. Spatial intermixing of clones is common, with some tumours growing exponentially and others only at the periphery. Together, our data suggest that most genetic intratumour variation in CRC has no major phenotypic consequence and that transcriptional plasticity is, instead, widespread within a tumour.

Advances in Anti-Cancer Activities of Flavonoids in Scutellariae radix: Perspectives on Mechanism

Despite encouraging progresses in the development of novel therapies, cancer remains the dominant cause of disease-related mortality and has become a leading economic and healthcare burden worldwide. Scutellariae radix (SR, Huangqin in Chinese) is a common herb used in traditional Chinese medicine, with a long history in treating a series of symptoms resulting from cancer, like dysregulated immune response and metabolic abnormalities. As major bioactive ingredients extracted from SR, flavonoids, including baicalein, wogonin, along with their glycosides (baicalin and wogonoside), represent promising pharmacological and anti-tumor activities and deserve extensive research attention. Emerging evidence has made great strides in elucidating the multi-targeting therapeutic mechanisms and key signaling pathways underlying the efficacious potential of flavonoids derived from SR in the field of cancer treatment. In this current review, we aim to summarize the pharmacological actions of flavonoids against various cancers in vivo and in vitro. Moreover, we also make a brief summarization of the endeavor in developing a drug delivery system or structural modification to enhance the bioavailability and biological activities of flavonoid monomers. Taken together, flavonoid components in SR have great potential to be developed as adjuvant or even primary therapies for the clinical management of cancers and have a promising prospect.

Clone Phylogenetics Reveals Metastatic Tumor Migrations, Maps, and Models

Simple Summary

Metastasis is the spread of cancer cells across organs and is a major cause of cancer mortality. Analysis of tumor sequencing data provides a means toward the reconstruction of routes of metastatic cell migrations. Our reconstructions demonstrated that many metastases were likely seeded from pre-existing metastasis of primary tumors. Additionally, multiple clone exchanges between tumor sites were common. In conclusion, the pattern of cancer cell migrations is often complex and is highly variable among patients.

Abstract

Dispersal routes of metastatic cells are not medically detected or even visible. A molecular evolutionary analysis of tumor variation provides a way to retrospectively infer metastatic migration histories and answer questions such as whether the majority of metastases are seeded from clones within primary tumors or seeded from clones within pre-existing metastases, as well as whether the evolution of metastases is generally consistent with any proposed models. We seek answers to these fundamental questions through a systematic patient-centric retrospective analysis that maps the dynamic evolutionary history of tumor cell migrations in many cancers. We analyzed tumor genetic heterogeneity in 51 cancer patients and found that most metastatic migration histories were best described by a hybrid of models of metastatic tumor evolution. Synthesizing across metastatic migration histories, we found new tumor seedings arising from clones of pre-existing metastases as often as they arose from clones from primary tumors. There were also many clone exchanges between the source and recipient tumors. Therefore, a molecular phylogenetic analysis of tumor variation provides a retrospective glimpse into general patterns of metastatic migration histories in cancer patients.

Therapeutic potential of naturally occurring lignans as anticancer agents

Cancer as a long-lasting and dramatic pandemic affects almost a third of the human being worldwide. At present, chemotherapy is the main clinical treatment strategy, but it is difficult to achieve satisfactory efficacy due to drug resistance and side effects. Natural products are becoming increasingly popular in cancer therapy due to their potent broad-spectrum anticancer potency and slight side effects. Lignans are complex diphenolic compounds, comprising a family of secondary metabolites existing widely in plants. Naturally occurring lignans have the potential to act on cancer cells by a range of mechanisms of action and could inhibit the colony formation, arrest the cell cycle in different phases, induce apoptosis, and suppress migration, providing privileged scaffolds for the discovery of novel anticancer agents. In recent five years, a variety of naturally occurring lignans were isolated and screened for their in vitro and/or in vivo anticancer efficacy, and some of them exhibited promising potential. This review has systematically summarized the resources, anticancer activity, and mechanisms of action of naturally occurring lignans, covering articles published between January 2017 and January 2022.

Phospholipid Scramblases: Role in Cancer Progression and Anticancer Therapeutics

Phospholipid scramblases (PLSCRs) that catalyze rapid mixing of plasma membrane lipids result in surface exposure of phosphatidyl serine (PS), a lipid normally residing to the inner plasma membrane leaflet. PS exposure provides a chemotactic eat-me signal for phagocytes resulting in non-inflammatory clearance of apoptotic cells by efferocytosis. However, metastatic tumor cells escape efferocytosis through alteration of tumor microenvironment and apoptotic signaling. Tumor cells exhibit altered membrane features, high constitutive PS exposure, low drug permeability and increased multidrug resistance through clonal evolution. PLSCRs are transcriptionally up-regulated in tumor cells leading to plasma membrane remodeling and aberrant PS exposure on cell surface. In addition, PLSCRs interact with multiple cellular components to modulate cancer progression and survival. While PLSCRs and PS exposed on tumor cells are novel drug targets, many exogenous molecules that catalyze lipid scrambling on tumor plasma membrane are potent anticancer therapeutic molecules. In this review, we provide a comprehensive analysis of scramblase mediated signaling events, membrane alteration specific to tumor development and possible therapeutic implications of scramblases and PS exposure.

Carcinogenic Potential Of Ovulation Stimulation In BRCA1/2 Gene Mutation Carriers In Assisted Reproductive Technology Programs

Mutations of the BRCA1/2 genes constitute a fundamental and independent risk factor in the genesis of both breast cancer and ovarian cancer. The specifics of the infertility treatment effect on the risk of developing cancer in carriers of mutations in the BRCA1/2 genes remain unclear and require a comprehensive investigation. In this review, we analyzed published sources on the possible relationship between the infertility treatment and the risk of ovarian and breast cancer in BRCA1/2 mutation carriers.

Evaluating statistical approaches to define clonal origin of tumours using bulk DNA sequencing: context is everything

Clonal analysis of tumour sequencing data enables the evaluation of the relationship of histologically distinct synchronous lesions, such as co-existing benign areas, and temporally distinct tumours, such as primary-recurrence comparisons. In this review, we summarise statistical approaches that are commonly employed to define tumour clonal relatedness using data from bulk DNA technologies. We discuss approaches using total copy number, allele-specific copy number and mutation data, and the relative genomic resolution required for analysis and summarise some of the current tools for inferring clonal relationships. We argue that the impact of the biological context is critical in selecting any particular approach, such as the relative genomic complexity of the lesions being compared, and we recommend considering this context before employing any method to a new dataset.

Path to Clonal Theranostics in Luminal Breast Cancers

Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString^®) and CDx (Foundation One^®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.

microRNA-20b-5p overexpression combing Pembrolizumab potentiates cancer cells to radiation therapy via repressing programmed death-ligand 1

Radiation therapy (RT) is widely applied in cancer treatment. The sensitivity of tumor cells to RT is the key to the treatment. This study probes the role and mechanism of miR-20b-5p in Pembrolizumab’s affecting the radiosensitivity of tumor cells. After Pembrolizumab treatment or cell transfection (miR-20b-5p mimics and miR-20b-5p inhibitors), tumor cells (NCI-H460 and ZR-75-30) were exposed to RT. The sensitivity of NCI-H460 and ZR-75-30 to RT was evaluated by monitoring cell proliferation and apoptosis. The dual-luciferase reporter assay and RNA immunoprecipitation (RIP) were adopted to evaluate the binding relationship between miR-20b-5p and CD274 (PD-L1). The xenograft model was established in nude mice to examine the mechanism of action of Pembrolizumab in vivo. Our outcomes exhibited that either Pembrolizumab treatment or miR-20b-5p overexpression potentiated radiosensitivity of tumor cells. Overexpressing miR-20b-5p enhanced radiosensitization of Pembrolizumab in vivo and in vitro by targeting PD-L1 and inactivating PD-L1/PD1. Overall, miR-20b-5p overexpression combined with Pembrolizumab potentiated cancer cells’ sensitivity to RT by repressing PD-L1/PD1.Abbreviations Akt: serine/threonine kinase 1; cDNA: complementary DNA; CO₂: carbon dioxide; EDTA: Ethylene Diamine Tetraacetic Acid; ENCORI: The Encyclopedia of RNA Interactomes; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; IGF2BP2: insulin like growth factor 2 mRNA binding protein 2; IHC: Immunohistochemistry; LncRNA MALAT1: Long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1; miRNAs: MicroRNAs; Mt: Mutant type; MTT: 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide; NC: negative control; NR2F2: nuclear receptor subfamily 2 group F member 2; NSCLC: non-small cell lung cancer; OD: optical density; PBS: phosphate-buffered saline; PD-L1: Programmed death-ligand 1; PD-1: programmed death 1; PI3K: phosphatidylinositol 3-kinase; qRT-PCR: Quantitative reverse transcription-polymerase chain reaction; RIP: RNA immunoprecipitation; RIPA: Radio Immunoprecipitation Assay; RRM2: ribonucleotide reductase regulatory subunit M2; RT: Radiation therapy; U6: U6 small nuclear RNA; V: volume; WB: Western blot; Wt: wild type; x ± sd: mean ± standard deviation.

MFmap: A semi-supervised generative model matching cell lines to tumours and cancer subtypes

Translating in vitro results from experiments with cancer cell lines to clinical applications requires the selection of appropriate cell line models. Here we present MFmap (model fidelity map), a machine learning model to simultaneously predict the cancer subtype of a cell line and its similarity to an individual tumour sample. The MFmap is a semi-supervised generative model, which compresses high dimensional gene expression, copy number variation and mutation data into cancer subtype informed low dimensional latent representations. The accuracy (test set F₁ score >90%) of the MFmap subtype prediction is validated in ten different cancer datasets. We use breast cancer and glioblastoma cohorts as examples to show how subtype specific drug sensitivity can be translated to individual tumour samples. The low dimensional latent representations extracted by MFmap explain known and novel subtype specific features and enable the analysis of cell-state transformations between different subtypes. From a methodological perspective, we report that MFmap is a semi-supervised method which simultaneously achieves good generative and predictive performance and thus opens opportunities in other areas of computational biology.

Tumors Are Evolutionary Island-Like Ecosystems

Integration of ecological and evolutionary features has begun to understand the interplay of tumor heterogeneity, microenvironment, and metastatic potential. Developing a theoretical framework is intrinsic to deciphering tumors' tremendous spatial and longitudinal genetic variation patterns in patients. Here, we propose that tumors can be considered evolutionary island-like ecosystems, that is, isolated systems that undergo evolutionary and spatiotemporal dynamic processes that shape tumor microenvironments and drive the migration of cancer cells. We examine attributes of insular systems and causes of insularity, such as physical distance and connectivity. These properties modulate migration rates of cancer cells through processes causing spatial and temporal isolation of the organs and tissues functioning as a supply of cancer cells for new colonizations. We discuss hypotheses, predictions, and limitations of tumors as islands analogy. We present emerging evidence of tumor insularity in different cancer types and discuss their relevance to the islands model. We suggest that the engagement of tumor insularity into conceptual and mathematical models holds promise to illuminate cancer evolution, tumor heterogeneity, and metastatic potential of cells.

Intratumor Heterogeneity in Hepatocellular Carcinoma: Challenges and Opportunities

Hepatocellular carcinoma (HCC) represents a leading cause of cancer-related death, but it remains difficult to treat. Intratumor genetic and phenotypic heterogeneity are inherent properties of breast, skin, lung, prostate, and brain tumors, and intratumor heterogeneity (ITH) helps define prognosis and therapeutic response in these cancers. Several recent studies estimate that ITH is inherent to HCC and attribute the clinical intractability of HCC to this heterogeneity. In this review, we examine the evidence for genomic, phenotypic, and tumor microenvironment ITH in HCC, with a focus on two of the top molecular drivers of HCC: β-catenin (CTNNB1) and Telomerase reverse transcriptase (TERT). We discuss the influence of ITH on HCC diagnosis, prognosis, and therapy, while highlighting the gaps in knowledge and possible future directions.

The Genomic Processes of Biological Invasions: From Invasive Species to Cancer Metastases and Back Again

The concept of invasion is useful across a broad range of contexts, spanning from the fine scale landscape of cancer tumors up to the broader landscape of ecosystems. Invasion biology provides extraordinary opportunities for studying the mechanistic basis of contemporary evolution at the molecular level. Although the field of invasion genetics was established in ecology and evolution more than 50 years ago, there is still a limited understanding of how genomic level processes translate into invasive phenotypes across different taxa in response to complex environmental conditions. This is largely because the study of most invasive species is limited by information about complex genome level processes. We lack good reference genomes for most species. Rigorous studies to examine genomic processes are generally too costly. On the contrary, cancer studies are fortified with extensive resources for studying genome level dynamics and the interactions among genetic and non-genetic mechanisms. Extensive analysis of primary tumors and metastatic samples have revealed the importance of several genomic mechanisms including higher mutation rates, specific types of mutations, aneuploidy or whole genome doubling and non-genetic effects. Metastatic sites can be directly compared to primary tumor cell counterparts. At the same time, clonal dynamics shape the genomics and evolution of metastatic cancers. Clonal diversity varies by cancer type, and the tumors’ donor and recipient tissues. Still, the cancer research community has been unable to identify any common events that provide a universal predictor of “metastatic potential” which parallels findings in evolutionary ecology. Instead, invasion in cancer studies depends strongly on context, including order of events and clonal composition. The detailed studies of the behavior of a variety of human cancers promises to inform our understanding of genome level dynamics in the diversity of invasive species and provide novel insights for management.

Multi-scale modeling of hippo signaling identifies homeostatic control by YAP-LATS negative feedback

The Hippo signaling primarily includes LATS1/2 and YAP1. Recent work has demonstrated a novel negative feedback between YAP1 and LATS1/2. However, how YAP-LATS negative feedback regulates cancer progression remains elusive. We constructed a multi-scale model which integrates angiogenesis, spatiotemporal variation of microenvironmental factors and phenotypic switch of tumor cells. Our simulation replicated the findings that YAP overexpression markedly attenuated cell proliferation owing to elevated negative feedback strength. After disruption of YAP-LATS negative feedback loop, however, YAP overexpression would promote cell proliferation. Consistently, LATS overexpression inhibited cell growth and lowered the proliferation potential. We also employed a putative LATS agonist and identified its dose-dependent tumor suppressive effects. Furthermore, targeted delivery could more effectively inhibit tumor growth. Our model has reconciled experimental findings and implied that reconstruction of functional and/or hyperactivated YAP-LATS negative feedback might be a promising strategy to homeostatic maintenance and tumor suppression.

Multifunctional barcoding with ClonMapper enables high-resolution study of clonal dynamics during tumor evolution and treatment

Lineage-tracing methods have enabled characterization of clonal dynamics in complex populations, but generally lack the ability to integrate genomic, epigenomic and transcriptomic measurements with live-cell manipulation of specific clones of interest. We developed a functionalized lineage-tracing system, ClonMapper, which integrates DNA barcoding with single-cell RNA sequencing and clonal isolation to comprehensively characterize thousands of clones within heterogeneous populations. Using ClonMapper, we identified subpopulations of a chronic lymphocytic leukemia cell line with distinct clonal compositions, transcriptional signatures and chemotherapy survivorship trajectories; patterns that were also observed in primary human chronic lymphocytic leukemia. The ability to retrieve specific clones before, during and after treatment enabled direct measurements of clonal diversification and durable subpopulation transcriptional signatures. ClonMapper is a powerful multifunctional approach to dissect the complex clonal dynamics of tumor progression and therapeutic response.

Tumor Classification Should Be Based on Biology and Not Consensus: Re-Defining Tumors Based on Biology May Accelerate Progress, An Experience of Gastric Cancer

Simple Summary

Rational treatment of diseases including cancers depends on knowledge of their cause as well as their development. The present review is based upon more than 40 years’ work in clinical gastroenterology, gastric physiology, and pathology. The central role of hormones as well as local endocrine cells in cancer development has become apparent. Moreover, the classification of tumors should focus not only on the organ of origin but also on the cell of origin. All cells with the ability to divide may give rise to tumors. Based upon knowledge of the growth regulation of the cell of origin, prophylaxis and treatment may be tailored. Presently, there is hope for individual treatment of cancer patients based upon genetic analyses of tumors. However, with correct identification of the cell of origin, this may not be necessary.

Abstract

Malignant tumors are a consequence of genetic changes mainly occurring during cell division, sometimes with a congenital component. Therefore, accelerated cell divisions will necessarily predispose individuals, whether due to conditions of chronic cell destruction or hormonal overstimulation. It has been postulated that two genetic hits are necessary for the development of malignancy (Knudson). The correct view is probably that the number of genetic changes needed depends on the role the mutated genes have in proliferation and growth control. Hormones should accordingly be regarded as complete carcinogens. In this review based upon experience of gastric cancer where gastrin is central in the pathogenesis, it is argued that oxyntic atrophy—and not metaplasia as postulated by Correa—is the central precancer change in gastric mucosa. Moreover, the target cell of gastrin, the enterochromaffin-like (ECL) cell, is central in gastric carcinogenesis and most probably the cell of origin of gastric carcinomas of the diffuse type according to Lauren (a classification probable in accordance with biology). The distinction between adenocarcinomas and neuroendocrine carcinomas based upon a certain percentage of cancer cells with neuroendocrine differentiation is questioned. To make progress in the treatment of cancer, a correct classification system and knowledge of the pathogenesis are necessary.

Cancer Community Ecology

Here we advocate Cancer Community Ecology as a valuable focus of study in Cancer Biology. We hypothesize that the heterogeneity and characteristics of cancer cells within tumors should vary systematically in space and time and that cancer cells form local ecological communities within tumors. These communities possess limited numbers of species determined by local conditions, with each species in a community possessing predictable traits that enable them to cope with their particular environment and coexist with each other. We start with a discussion of concepts and assumptions that ecologists use to study closely related species. We then discuss the competitive exclusion principle as a means for knowing when two species should not coexist, and as an opening towards understanding how they can. We present the five major categories of mechanisms of coexistence that operate in nature and suggest that the same mechanisms apply towards understanding the diversification and coexistence of cancer cell species. They are: Food-Safety Tradeoffs, Diet Choice, Habitat Selection, Variance Partitioning, and Competition-Colonization Tradeoffs. For each mechanism, we discuss how it works in nature, how it might work in cancers, and its implications for therapy.

Analysis and Interpretation of the Impact of Missense Variants in Cancer

Large scale genome sequencing allowed the identification of a massive number of genetic variations, whose impact on human health is still unknown. In this review we analyze, by an in silico-based strategy, the impact of missense variants on cancer-related genes, whose effect on protein stability and function was experimentally determined. We collected a set of 164 variants from 11 proteins to analyze the impact of missense mutations at structural and functional levels, and to assess the performance of state-of-the-art methods (FoldX and Meta-SNP) for predicting protein stability change and pathogenicity. The result of our analysis shows that a combination of experimental data on protein stability and in silico pathogenicity predictions allowed the identification of a subset of variants with a high probability of having a deleterious phenotypic effect, as confirmed by the significant enrichment of the subset in variants annotated in the COSMIC database as putative cancer-driving variants. Our analysis suggests that the integration of experimental and computational approaches may contribute to evaluate the risk for complex disorders and develop more effective treatment strategies.

RGB-Marking to Identify Patterns of Selection and Neutral Evolution in Human Osteosarcoma Models

Osteosarcoma (OS) is a highly aggressive tumor characterized by malignant cells producing pathologic bone; the disease presents a natural tendency to metastasize. Genetic studies indicate that the OS genome is extremely complex, presenting signs of macro-evolution, and linear and branched patterns of clonal development. However, those studies were based on the phylogenetic reconstruction of next-generation sequencing (NGS) data, which present important limitations. Thus, testing clonal evolution in experimental models could be useful for validating this hypothesis. In the present study, lentiviral LeGO-vectors were employed to generate colorimetric red, green, blue (RGB)-marking in murine, canine, and human OS. With this strategy, we studied tumor heterogeneity and the clonal dynamics occurring in vivo in immunodeficient NOD.Cg-Prkdcscid-Il2rgtm1Wjl/SzJ (NSG) mice. Based on colorimetric label, tumor clonal composition was analyzed by confocal microscopy, flow cytometry, and different types of supervised and unsupervised clonal analyses. With this approach, we observed a consistent reduction in the clonal composition of RGB-marked tumors and identified evident clonal selection at the first passage in immunodeficient mice. Furthermore, we also demonstrated that OS could follow a neutral model of growth, where the disease is defined by the coexistence of different tumor sub-clones. Our study demonstrates the importance of rigorous testing of the selective forces in commonly used experimental models.

PathFinder: Bayesian inference of clone migration histories in cancer

SUMMARY

Metastases cause a vast majority of cancer morbidity and mortality. Metastatic clones are formed by dispersal of cancer cells to secondary tissues, and are not medically detected or visible until later stages of cancer development. Clone phylogenies within patients provide a means of tracing the otherwise inaccessible dynamic history of migrations of cancer cells. Here, we present a new Bayesian approach, PathFinder, for reconstructing the routes of cancer cell migrations. PathFinder uses the clone phylogeny, the number of mutational differences among clones, and the information on the presence and absence of observed clones in primary and metastatic tumors. By analyzing simulated datasets, we found that PathFinder performes well in reconstructing clone migrations from the primary tumor to new metastases as well as between metastases. It was more challenging to trace migrations from metastases back to primary tumors. We found that a vast majority of errors can be corrected by sampling more clones per tumor, and by increasing the number of genetic variants assayed per clone. We also identified situations in which phylogenetic approaches alone are not sufficient to reconstruct migration routes.In conclusion, we anticipate that the use of PathFinder will enable a more reliable inference of migration histories and their posterior probabilities, which is required to assess the relative preponderance of seeding of new metastasis by clones from primary tumors and/or existing metastases.

AVAILABILITY AND IMPLEMENTATION

PathFinder is available on the web at https://github.com/SayakaMiura/PathFinder.

Cancer evolution: A means by which tumors evade treatment

Although various methods have been tried to study and treat cancer, the cancer remains a major challenge for human medicine today. One important reason for this is the presence of cancer evolution. Cancer evolution is a process in which tumor cells adapt to the external environment, which can suppress the human immune system's ability to recognize and attack tumors, and also reduce the reproducibility of cancer research. Among them, heterogeneity of the tumor provides intrinsic motivation for this process. Recently, with the development of related technologies such as liquid biopsy, more and more knowledge about cancer evolution has been gained and interest in this topic has also increased. Therefore, starting from the causes of tumorigenesis, this paper introduces several tumorigenesis processes and pathways, as well as treatment options for different targets.

Visualizing Human Colorectal Cancer Intratumor Heterogeneity with Phylogeography

Phylogeography combines ancestry with location and can be translated to intratumor heterogeneity (ITH) to visualize how tumors spread. ITH is common in human tumors, with many genetic and phenotypic differences between regions. The roles of ITH in progression are uncertain because many subclones lack discernable driver mutations. ITH can be visualized by mapping mutations onto microscopic sections, where subclones are directly associated with phenotypes, especially the deeper areas with the more invasive cells that confer worst clinical outcomes. Instead of a stepwise hierarchy where subclones segregate by phenotype with later branching subclones in more invasive areas, multiple subclones share superficial and invasive phenotype and are jigsaw arrayed in vertical columns. Phylogeography shows that both early and late subclones extend from the surface to the invasive front, suggesting that founder cells start with phenotypic plasticity and essentially all the drivers necessary to rapidly grow into large invasive tumors.

Cancer cell lines show high heritability for motility but not generation time

Tumour evolution depends on heritable differences between cells in traits affecting cell survival or replication. It is well established that cancer cells are genetically and phenotypically heterogeneous; however, the extent to which this phenotypic variation is heritable is far less well explored. Here, we estimate the broad-sense heritability (H ²) of two cell traits related to cancer hallmarks--cell motility and generation time--within populations of four cancer cell lines in vitro and find that motility is strongly heritable. This heritability is stable across multiple cell generations, with heritability values at the high end of those measured for a range of traits in natural populations of animals or plants. These findings confirm a central assumption of cancer evolution, provide a first quantification of the evolvability of key traits in cancer cells and indicate that there is ample raw material for experimental evolution in cancer cell lines. Generation time, a trait directly affecting cell fitness, shows substantially lower values of heritability than cell speed, consistent with its having been under directional selection removing heritable variation.

Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios

The distribution of fitness effects (DFE) defines how new mutations spread through an evolving population. The ratio of non-synonymous to synonymous mutations (dN/dS) has become a popular method to detect selection in somatic cells. However the link, in somatic evolution, between dN/dS values and fitness coefficients is missing. Here we present a quantitative model of somatic evolutionary dynamics that determines the selective coefficients of individual driver mutations from dN/dS estimates. We then measure the DFE for somatic mutant clones in ostensibly normal oesophagus and skin. We reveal a broad distribution of fitness effects, with the largest fitness increases found for TP53 and NOTCH1 mutants (proliferative bias 1-5%). This study provides the theoretical link between dN/dS values and selective coefficients in somatic evolution, and measures the DFE of mutations in human tissues.

Mutagenesis by Microbe: the Role of the Microbiota in Shaping the Cancer Genome

Cancers arise through the process of somatic evolution fueled by the inception of somatic mutations. We lack a complete understanding of the sources of these somatic mutations. Humans host a vast repertoire of microbes collectively known as the microbiota. The microbiota plays a role in altering the tumor microenvironment and proliferation. In addition, microbes have been shown to elicit DNA damage which provides the driver for somatic mutations. An understanding of microbiota-driven mutational mechanisms would contribute to a more complete understanding of the origins of the cancer genome. Here, we review the modes by which microbes stimulate DNA damage and the effect of these phenomena upon the cancer genomic architecture, specifically in the form of mutational spectra and mutational signatures.

Delineation of Tumor Migration Paths by Using a Bayesian Biogeographic Approach

Understanding tumor progression and metastatic potential are important in cancer biology. Metastasis is the migration and colonization of clones in secondary tissues. Here, we posit that clone migration events between tumors resemble the dispersal of individuals between distinct geographic regions. This similarity makes Bayesian biogeographic analysis suitable for inferring cancer cell migration paths. We evaluated the accuracy of a Bayesian biogeography method (BBM) in inferring metastatic patterns and compared it with the accuracy of a parsimony-based approach (metastatic and clonal history integrative analysis, MACHINA) that has been specifically developed to infer clone migration patterns among tumors. We used computer-simulated datasets in which simple to complex migration patterns were modeled. BBM and MACHINA were effective in reliably reconstructing simple migration patterns from primary tumors to metastases. However, both of them exhibited a limited ability to accurately infer complex migration paths that involve the migration of clones from one metastatic tumor to another and from metastasis to the primary tumor. Therefore, advanced computational methods are still needed for the biologically realistic tracing of migration paths and to assess the relative preponderance of different types of seeding and reseeding events during cancer progression in patients.

Aging and cancer: Is glucose a mediator between them?

Aging can increase cancer incidence because of accumulated mutations that initiate cancer and via compromised body control of premalignant lesions development into cancer. Relative contributions of these two factors are debated. Recent evidence suggests that the latter is rate limiting. In particular, hyperglycemia caused by compromised body control of blood glucose may be a factor of selection of somatic mutation-bearing cells for the ability to use glucose for proliferation. High glucose utilization in aerobic glycolysis is a long known characteristic of cancer. The new evidence adds to the concepts that have been being developed starting from mid-1970ies to suggest that age-related shifts in glucose and lipid metabolism increase the risk of cancer and compromise prognoses for cancer patients and to propose antidiabetic biguanides, including metformin, for cancer prevention and as an adjuvant means of cancer treatment aimed at the metabolic rehabilitation of patients. The new evidence is consistent with several effects of glucose contributing to aging and acting synergistically to enhance carcinogenesis. Glucose can affect (i) separate cells (via promoting somatic mutagenesis and epigenetic instability), (ii) cell populations (via being a factor of selection of phenotypic variants in cell populations for higher glucose consumption and, ultimately, for high aerobic glycolysis); (iii) cell microenvironment (via modification of extracellular matrix proteins), and (iv) the systemic levels (via shifting the endocrine regulation of metabolism toward increasing blood lipids and body fat, which compromise immunological surveillance and promote inflammation). Thus, maintenance of youthful metabolic characteristics must be important for cancer prevention and treatment.