Genetic and Non-Genetic Mechanisms Underlying Cancer Evolution

Evolution of phenotypic plasticity leads to tumor heterogeneity with implications for therapy

Cancer is a significant global health issue, with treatment challenges arising from intratumor heterogeneity. This heterogeneity stems mainly from somatic evolution, causing genetic diversity within the tumor, and phenotypic plasticity of tumor cells leading to reversible phenotypic changes. However, the interplay of both factors has not been rigorously investigated. Here, we examine the complex relationship between somatic evolution and phenotypic plasticity, explicitly focusing on the interplay between cell migration and proliferation. This type of phenotypic plasticity is essential in glioblastoma, the most aggressive form of brain tumor. We propose that somatic evolution alters the regulation of phenotypic plasticity in tumor cells, specifically the reaction to changes in the microenvironment. We study this hypothesis using a novel, spatially explicit model that tracks individual cells' phenotypic and genetic states. We assume cells change between migratory and proliferative states controlled by inherited and mutation-driven genotypes and the cells' microenvironment. We observe that cells at the tumor edge evolve to favor migration over proliferation and vice versa in the tumor bulk. Notably, different genetic configurations can result in this pattern of phenotypic heterogeneity. We analytically predict the outcome of the evolutionary process, showing that it depends on the tumor microenvironment. Synthetic tumors display varying levels of genetic and phenotypic heterogeneity, which we show are predictors of tumor recurrence time after treatment. Interestingly, higher phenotypic heterogeneity predicts poor treatment outcomes, unlike genetic heterogeneity. Our research offers a novel explanation for heterogeneous patterns of tumor recurrence in glioblastoma patients.

Molecular insights to therapeutic in cancer: role of exosomes in tumor microenvironment, metastatic progression and drug resistance

Exosomes play a pivotal part in cancer progression and metastasis by transferring various biomolecules. Recent research highlights their involvement in tumor microenvironment remodeling, mediating metastasis, tumor heterogeneity and drug resistance. The unique cargo carried by exosomes garners the interest of researchers owing to its potential as a stage-specific biomarker for early cancer detection and its role in monitoring personalized treatment. However, unanswered questions hinder a comprehensive understanding of exosomes and their cargo in this context. This review discusses recent advancements and proposes novel ideas for exploring exosomes in cancer progression, aiming to deepen our understanding and improve treatment approaches.

Emerging Therapeutic Strategies to Overcome Drug Resistance in Cancer Cells

The rise of drug resistance in cancer cells presents a formidable challenge in modern oncology, necessitating the exploration of innovative therapeutic strategies. This review investigates the latest advancements in overcoming drug resistance mechanisms employed by cancer cells, focusing on emerging therapeutic modalities. The intricate molecular insights into drug resistance, including genetic mutations, efflux pumps, altered signaling pathways, and microenvironmental influences, are discussed. Furthermore, the promising avenues offered by targeted therapies, combination treatments, immunotherapies, and precision medicine approaches are highlighted. Specifically, the synergistic effects of combining traditional cytotoxic agents with molecularly targeted inhibitors to circumvent resistance pathways are examined. Additionally, the evolving landscape of immunotherapeutic interventions, including immune checkpoint inhibitors and adoptive cell therapies, is explored in terms of bolstering anti-tumor immune responses and overcoming immune evasion mechanisms. Moreover, the significance of biomarker-driven strategies for predicting and monitoring treatment responses is underscored, thereby optimizing therapeutic outcomes. For insights into the future direction of cancer treatment paradigms, the current review focused on prevailing drug resistance challenges and improving patient outcomes, through an integrative analysis of these emerging therapeutic strategies.

High-fat diet during early life reshapes the gut microbiome and is associated with the disrupted mammary microenvironment in later life in mice

The influence of gut microbiota on gut health is well-documented, but it remains obscure for extraintestinal diseases such as breast cancer. Moreover, it is entirely unknown how gut dysbiosis during early life contributes to breast tumorigenesis later in life. In this study, we hypothesized that a high-fat diet during early life leads to alterations in the gut microbiome and is associated with disruptions in the mammary microenvironment. Female C57BL/6 mice were fed a low-fat diet (10% kcal fat) or a high-fat diet (HF, 60% kcal fat) for 8 weeks from the age of 4 to 12 weeks, which is equivalent to human childhood and adolescence. Twelve mice were sacrificed immediately after the 8-week feeding, the remainder were euthanized after switching to a normal lifecycle-supporting diet for an additional 12 weeks; the gut microbiome was then sequenced. The 8-week HF diet feeding altered the beta-diversity (Bray & Jaccard P < .01), and the difference remained significant after switching the diet (Bray & Jaccard P < .05). Immediately after HF feeding, a greater number of microbial taxa (>50) were altered, and about half of the taxa (25) remained significantly changed after switching the diet. The abundance of Alistipes, Bilophila, and Rikenellaceae stood out as significantly associated with multiple metabolic and inflammatory biomarkers in mammary tissue, including aromatase, Ccl2, and Cox2. In conclusion, an 8-week early-life HF feeding reshaped the gut microbiome, which connected with disrupted mammary microenvironments.

Extracellular Microenvironment Alterations in Ductal Carcinoma In Situ and Invasive Breast Cancer Pathologies by Multiplexed Spatial Proteomics

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.

In silico approaches for drug repurposing in oncology: a scoping review

Introduction: Cancer refers to a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. Due to its complexity, it has been hard to find an ideal medicine to treat all cancer types, although there is an urgent need for it. However, the cost of developing a new drug is high and time-consuming. In this sense, drug repurposing (DR) can hasten drug discovery by giving existing drugs new disease indications. Many computational methods have been applied to achieve DR, but just a few have succeeded. Therefore, this review aims to show in silico DR approaches and the gap between these strategies and their ultimate application in oncology. Methods: The scoping review was conducted according to the Arksey and O'Malley framework and the Joanna Briggs Institute recommendations. Relevant studies were identified through electronic searching of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We included peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between 1 January 2003, and 31 December 2021. Results: We identified 238 studies for inclusion in the review. Most studies revealed that the United States, India, China, South Korea, and Italy are top publishers. Regarding cancer types, breast cancer, lymphomas and leukemias, lung, colorectal, and prostate cancer are the top investigated. Additionally, most studies solely used computational methods, and just a few assessed more complex scientific models. Lastly, molecular modeling, which includes molecular docking and molecular dynamics simulations, was the most frequently used method, followed by signature-, Machine Learning-, and network-based strategies. Discussion: DR is a trending opportunity but still demands extensive testing to ensure its safety and efficacy for the new indications. Finally, implementing DR can be challenging due to various factors, including lack of quality data, patient populations, cost, intellectual property issues, market considerations, and regulatory requirements. Despite all the hurdles, DR remains an exciting strategy for identifying new treatments for numerous diseases, including cancer types, and giving patients faster access to new medications.

Leveraging Cancer Phenotypic Plasticity for Novel Treatment Strategies

Cancer cells, like all other organisms, are adept at switching their phenotype to adjust to the changes in their environment. Thus, phenotypic plasticity is a quantitative trait that confers a fitness advantage to the cancer cell by altering its phenotype to suit environmental circumstances. Until recently, new traits, especially in cancer, were thought to arise due to genetic factors; however, it is now amply evident that such traits could also emerge non-genetically due to phenotypic plasticity. Furthermore, phenotypic plasticity of cancer cells contributes to phenotypic heterogeneity in the population, which is a major impediment in treating the disease. Finally, plasticity also impacts the group behavior of cancer cells, since competition and cooperation among multiple clonal groups within the population and the interactions they have with the tumor microenvironment also contribute to the evolution of drug resistance. Thus, understanding the mechanisms that cancer cells exploit to tailor their phenotypes at a systems level can aid the development of novel cancer therapeutics and treatment strategies. Here, we present our perspective on a team medicine-based approach to gain a deeper understanding of the phenomenon to develop new therapeutic strategies.

A blueprint for a new commercial driving epidemiology: An emerging paradigm grounded in integrative exposome and network epistemologies

Excess health and safety risks of commercial drivers are largely determined by, embedded in, or operate as complex, dynamic, and randomly determined systems with interacting parts. Yet, prevailing epidemiology is entrenched in narrow, deterministic, and static exposure-response frameworks along with ensuing inadequate data and limiting methods, thereby perpetuating an incomplete understanding of commercial drivers' health and safety risks. This paper is grounded in our ongoing research that conceptualizes health and safety challenges of working people as multilayered "wholes" of interacting work and nonwork factors, exemplified by complex-systems epistemologies. Building upon and expanding these assumptions, herein we: (a) discuss how insights from integrative exposome and network-science-based frameworks can enhance our understanding of commercial drivers' chronic disease and injury burden; (b) introduce the "working life exposome of commercial driving" (WLE-CD)-an array of multifactorial and interdependent work and nonwork exposures and associated biological responses that concurrently or sequentially impact commercial drivers' health and safety during and beyond their work tenure; (c) conceptualize commercial drivers' health and safety risks as multilayered networks centered on the WLE-CD and network relational patterns and topological properties-that is, arrangement, connections, and relationships among network components-that largely govern risk dynamics; and (d) elucidate how integrative exposome and network-science-based innovations can contribute to a more comprehensive understanding of commercial drivers' chronic disease and injury risk dynamics. Development, validation, and proliferation of this emerging discourse can move commercial driving epidemiology to the frontier of science with implications for policy, action, other working populations, and population health at large.

Multiomics approach towards characterization of tumor cell plasticity and its significance in precision and personalized medicine

Cellular plasticity refers to the ability of cells to change their identity or behavior, which can be advantageous in some cases (e.g., tissue regeneration) but detrimental in others (e.g., cancer metastasis). With a better understanding of cellular plasticity, the complexity of cancer cells, their heterogeneity, and their role in metastasis is being unraveled. The plasticity of the cells could also prove as a nemesis to their characterization. In this review, we have attempted to highlight the possibilities and benefits of using multiomics approach in characterizing the plastic nature of cancer cells. There is a need to integrate fragmented evidence at different levels of cellular organization (DNA, RNA, protein, metabolite, epigenetics, etc.) to facilitate the characterization of different forms of plasticity and cell types. We have discussed the role of cellular plasticity in generating intra-tumor heterogeneity. Different omics level evidence is being provided to highlight the variety of molecular determinants discovered using different techniques. Attempts have been made to integrate some of this information to provide a quantitative assessment and scoring of the plastic nature of the cells. However, there is a huge gap in our understanding of mechanisms that lead to the observed heterogeneity. Understanding of these mechanism(s) is necessary for finding targets for early detection and effective therapeutic interventions in metastasis. Targeting cellular plasticity is akin to neutralizing a moving target. Along with the advancements in precision and personalized medicine, these efforts may translate into better clinical outcomes for cancer patients, especially in metastatic stages.

Anti-ENO1 antibody combined with metformin against tumor resistance: a novel antibody-based platform

Background

Antibody-based platforms (i.e., ADC) have emerged as one of the most encouraging tools for the cancer resistance caused by cancer stem cells (CSCs) enrichment. Our study might provide a promising therapeutic direction against drug resistance and serve as a potential precursor platform for screening ADC.

Methods

The cell migration, invasion, drug resistance, and self-renewal were assessed by the cell invasion and migration assay, wound healing assay, CCK-8 assay, colony formation assay, and sphere formation assay, respectively. The expression profiles of CSCs (ALDH+ and CD44+) subpopulations were screened by flow cytometry. The western blot and cell immunofluorescence assay were used to evaluate pathway-related protein expression in both anti-ENO1 antibody, MET combined with DPP/CTX-treated CSCs.

Results

In the present study, western blot and flow cytometry verified that anti-ENO1 antibody target the CD44+ subpopulation by inhibiting the PI3K/AKT pathway, while metformin might target the ALDH+ subpopulation through activation of the AMPK pathway and thus reverse drug resistance to varying degrees. Subsequently, in vitro investigation indicated that anti-ENO1 antibody, metformin combined with cisplatin/cetuximab could simultaneously target ALDH+ and CD44+ subpopulations. The combination also inhibited the CSCs proliferation, migration, invasion, and sphere formation; which may result in overcoming the drug resistance. Then, molecular mechanism exploration verified that the anti-ENO1 antibody, metformin combined with cisplatin/cetuximab inhibited the Wnt/β-catenin signaling.

Conclusions

The study preliminarily revealed anti-ENO1 antibody combined with metformin could overcome drug resistance against CSCs by inhibiting the Wnt//β-catenin pathway and might serve as a potential precursor platform for screening ADC. More importantly, it is reasonably believed that antibody-based drug combination therapy might function as an encouraging tool for oncotherapy.

Protocol to study the inheritance and propagation of non-genetically encoded states using barcode decay lineage tracing

Here, we present a protocol to perform barcode decay lineage tracing followed by single-cell transcriptome analysis (BdLT-Seq). We describe steps for BdLT-Seq experimental design, building barcoded episome reporters, performing episome transfection, and barcode retrieval. We then describe procedures for sequencing library construction while providing options for sample multiplexing and data analysis. This BdLT-Seq technique enables the assessment of clonal evolution in a directional manner while preserving isogeneity, thus allowing the comparison of non-genetic molecular features between isogenic cell lineages. For complete details on the use and execution of this protocol, please refer to Shlyakhtina et al. (2023).1.

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.

Chitosan and hyaluronic acid-based nanocarriers for advanced cancer therapy and intervention

Cancer has become a major public health issue leading to one of the foremost causes of morbidity and death in the world. Despite the current advances in diagnosis using modern technologies and treatment via surgery or chemo- and radio-therapies, severe side effects or after-effects limit the application of these treatment modalities. Novel drug delivery systems have shown the potential to deliver chemotherapeutics directly to cancer cells, thus minimizing unnecessary exposure to healthy cells. Concurrently, to circumvent difficulties associated with conventional deliveries of cancer therapeutics, natural polysaccharides have gained attention for the fabrication of such deliveries owing to biocompatibility, low toxicity, and biodegradability. It has been exhibited that natural polysaccharides can deliver high therapeutic concentrations of the entrapped drug to the target cells by sustained and targeted release. Considering the immense potential of natural polymers, the present work focuses on naturally generated biopolymer carriers based on chitosan and hyaluronic acid. This review delineated on the role of chitosan and its derivation from renewable resources as a biocompatible, biodegradable, nonimmunogenic material with notable antitumor activity as a drug delivery carrier in oncotherapy. Moreover, hyaluronic acid, itself by its structure or when linked with other molecules contributes to developing promising pharmaceutical delivery systems to setback the restrictions related to conventional cancer treatment.

CD133-Dependent Activation of Phosphoinositide 3-Kinase /AKT/Mammalian Target of Rapamycin Signaling in Melanoma Progression and Drug Resistance

Melanoma frequently harbors genetic alterations in key molecules leading to the aberrant activation of PI3K and its downstream pathways. Although the role of PI3K/AKT/mTOR in melanoma progression and drug resistance is well documented, targeting the PI3K/AKT/mTOR pathway showed less efficiency in clinical trials than might have been expected, since the suppression of the PI3K/mTOR signaling pathway-induced feedback loops is mostly associated with the activation of compensatory pathways such as MAPK/MEK/ERK. Consequently, the development of intrinsic and acquired resistance can occur. As a solid tumor, melanoma is notorious for its heterogeneity. This can be expressed in the form of genetically divergent subpopulations including a small fraction of cancer stem-like cells (CSCs) and non-cancer stem cells (non-CSCs) that make the most of the tumor mass. Like other CSCs, melanoma stem-like cells (MSCs) are characterized by their unique cell surface proteins/stemness markers and aberrant signaling pathways. In addition to its function as a robust marker for stemness properties, CD133 is crucial for the maintenance of stemness properties and drug resistance. Herein, the role of CD133-dependent activation of PI3K/mTOR in the regulation of melanoma progression, drug resistance, and recurrence is reviewed.

Mechanisms of Melanoma Progression and Treatment Resistance: Role of Cancer Stem-like Cells

Melanoma is the third most common type of skin cancer, characterized by its heterogeneity and propensity to metastasize to distant organs. Melanoma is a heterogeneous tumor, composed of genetically divergent subpopulations, including a small fraction of melanoma-initiating cancer stem-like cells (CSCs) and many non-cancer stem cells (non-CSCs). CSCs are characterized by their unique surface proteins associated with aberrant signaling pathways with a causal or consequential relationship with tumor progression, drug resistance, and recurrence. Melanomas also harbor significant alterations in functional genes (BRAF, CDKN2A, NRAS, TP53, and NF1). Of these, the most common are the BRAF and NRAS oncogenes, with 50% of melanomas demonstrating the BRAF mutation (BRAFV600E). While the successful targeting of BRAFV600E does improve overall survival, the long-term efficacy of available therapeutic options is limited due to adverse side effects and reduced clinical efficacy. Additionally, drug resistance develops rapidly via mechanisms involving fast feedback re-activation of MAPK signaling pathways. This article updates information relevant to the mechanisms of melanoma progression and resistance and particularly the mechanistic role of CSCs in melanoma progression, drug resistance, and recurrence.

Drugging the undruggable: Advances in targeting KRAS signaling in solid tumors

Cancer remains the leading cause of global mortality, prompting a paradigm shift in its treatment and outcomes with the advent of targeted therapies. Among the most prevalent mutations in RAS-driven cancers, Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations account for approximately 86% of cases worldwide, particularly in lung, pancreatic, and colon cancers, contributing to poor prognosis and reduced overall survival. Despite numerous efforts to understand the biology of KRAS mutants and their pivotal role in cancer development, the lack of well-defined drug-binding pockets has deemed KRAS an "undruggable" therapeutic target, presenting significant challenges for researchers and clinicians alike. Through significant biochemical and technological advances, the last decade has witnessed promising breakthroughs in targeted therapies for KRAS-mutated lung, colon, and pancreatic cancers, marking a critical turning point in the field. In this chapter, we provide an overview of the characteristics of KRAS mutations across various solid tumors, highlighting ongoing cutting-edge research on the immune microenvironment, the development of KRAS-driven mice models, and the recent progress in the exploration of specific KRAS mutant-targeted therapeutic approaches. By comprehensive understanding of the intricacies of KRAS signaling in solid tumors and the latest therapeutic developments, this chapter will shed light on the potential for novel therapeutic strategies to combat KRAS-driven tumors and improve patient outcomes.

A Review on Anaplastic Lymphoma Kinase (ALK) Rearrangements and Mutations: Implications for Gastric Carcinogenesis and Target Therapy

Gastric adenocarcinoma is a complex disease with diverse genetic modifications, including Anaplastic Lymphoma Kinase (ALK) gene changes. The ALK gene is located on chromosome 2p23 and encodes a receptor tyrosine kinase that plays a crucial role in embryonic development and cellular differentiation. ALK alterations can result from gene fusion, mutation, amplification, or overexpression in gastric adenocarcinoma. Fusion occurs when the ALK gene fuses with another gene, resulting in a chimeric protein with constitutive kinase activity and promoting oncogenesis. ALK mutations are less common but can also result in the activation of ALK signaling pathways. Targeted therapies for ALK variations in gastric adenocarcinoma have been developed, including ALK inhibitors that have shown promising results in pre-clinical studies. Future studies are needed to elucidate the ALK role in gastric cancer and to identify predictive biomarkers to improve patient selection for targeted therapy. Overall, ALK alterations are a relevant biomarker for gastric adenocarcinoma treatment and targeted therapies for ALK may improve patients' overall survival.

Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma

Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.

A Study on the Factors and Prediction Model of Triple-Negative Breast Cancer for Public Health Promotion

This study was conducted to identify the risk causes and predictive models based on the clinical features of patients with breast cancer classified as triple-negative breast cancer (TNBC) and non-triple-negative breast cancer (non-TNBCs) using Korean cancer statistics. A total of 2045 cases that underwent three types of hormone receptor tests were obtained from Korean cancer data in 2016. Research data were analyzed with the software SPSS Ver. 26.0. TNBC and non-TNBCs accounted for 12.4% and 87.6% of the data, respectively. Tubular and lobular tumors occurred most frequently in the external quadrant of the breast (C50.4-C50.5; 43.1%). Compared to non-TNBCs, the incidence of TNBC was the most common in patients under the age of 39 (19.5%), followed by those over the age of 70 (17.3%). Tumors larger than 2 cm accounted for 16.0%, which was higher than the number of tumors smaller than 2 cm. Cases in stage IV cancer represented 21.7% of the data. Additionally, 21.0% of the patients were in the SEER stage of distant metastasis, which was the most prevalent SEER (surveillance, epidemiology, and end outcomes) stage. Neoadjuvant therapy was administered more frequently, with a rate of 24.1%. In the logistic regression and decision-making tree model, the variables that affected TNBC were age, differentiation grade, and neoadjuvant therapy. The predictive accuracies of logistic regression and decision-making tree models were 87.8% and 87.6%, respectively. In a decision-marking tree model, the differentiation grades of TNBC affect neoadjuvant therapy, and neoadjuvant therapy affects the cancer stage. Therefore, in order to promote the health of breast cancer patients, it is urgent to apply an intensive early health check-up program for those in their 40s and 50s with a high prevalence of TNBC. For patients with breast cancer, in TNBC cases, except for poorly differentiated cases, neoadjuvant therapy must be applied first at all differentiation grades. The establishment of a policy system is necessary for the success of this process.

An Overview of Cancer in Djibouti: Current Status, Therapeutic Approaches, and Promising Endeavors in Local Essential Oil Treatment

Djibouti, a developing economy, grapples with significant socioeconomic obstacles and the prevalence of infectious pathologies, including certain forms of neoplasms. These challenges are exacerbated by limited access to affordable medical technologies for diagnosis, coupled with a lack of preventive interventions, particularly in disadvantaged areas. The attention devoted to local phytotherapeutic treatments underscores the uniqueness of Djibouti's flora, resulting from its distinctive geographical position. International focus specifically centers on harnessing this potential as a valuable resource, emphasizing the phytoconstituents used to counter pathologies, notably carcinomas. This comprehensive overview covers a broad spectrum, commencing with an examination of the current state of knowledge, namely an in-depth investigation of oncological risk factors. Essential elements of control are subsequently studied, highlighting the fundamental prerequisites for effective management. The significance of dietary habits in cancer prevention and support is explored in depth, while traditional methods are examined, highlighting the cultural significance of indigenous essential oil therapies and encouraging further research based on the promising results.

Stochastic epithelial-mesenchymal transitions diversify non-cancerous lung cell behaviours

Epithelial-mesenchymal plasticity (EMP) is a hallmark of cancer. By enabling cells to shift between different morphological and functional states, EMP promotes invasion, metastasis and therapy resistance. We report that near-diploid non-cancerous human epithelial lung cells spontaneously shift along the EMP spectrum without genetic changes. Strikingly, more than half of single cell-derived clones adopt a mesenchymal morphology. We independently characterise epithelial-like and mesenchymal-like clones. Mesenchymal clones lose epithelial markers, display larger cell aspect ratios and lower motility, with mostly unaltered proliferation rates. Stemness marker expression and metabolic rewiring diverge independently of phenotypes. In 3D culture, more epithelial clones become mesenchymal-like. Thus, non-cancerous epithelial cells may acquire cancer metastasis-associated features prior to genetic alterations and cancerous transformation.

Understanding and leveraging phenotypic plasticity during metastasis formation

Cancer metastasis is the process of detrimental systemic spread and the primary cause of cancer-related fatalities. Successful metastasis formation requires tumor cells to be proliferative and invasive; however, cells cannot be effective at both tasks simultaneously. Tumor cells compensate for this trade-off by changing their phenotype during metastasis formation through phenotypic plasticity. Given the changing selection pressures and competitive interactions that tumor cells face, it is poorly understood how plasticity shapes the process of metastasis formation. Here, we develop an ecology-inspired mathematical model with phenotypic plasticity and resource competition between phenotypes to address this knowledge gap. We find that phenotypically plastic tumor cell populations attain a stable phenotype equilibrium that maintains tumor cell heterogeneity. Considering treatment types inspired by chemo- and immunotherapy, we highlight that plasticity can protect tumors against interventions. Turning this strength into a weakness, we corroborate current clinical practices to use plasticity as a target for adjuvant therapy. We present a parsimonious view of tumor plasticity-driven metastasis that is quantitative and experimentally testable, and thus potentially improving the mechanistic understanding of metastasis at the cell population level, and its treatment consequences.

Statistical control of structural networks with limited interventions to minimize cellular phenotypic diversity represented by point attractors

The underlying genetic networks of cells give rise to diverse behaviors known as phenotypes. Control of this cellular phenotypic diversity (CPD) may reveal key targets that govern differentiation during development or drug resistance in cancer. This work establishes an approach to control CPD that encompasses practical constraints, including model limitations, the number of simultaneous control targets, which targets are viable for control, and the granularity of control. Cellular networks are often limited to the structure of interactions, due to the practical difficulty of modeling interaction dynamics. However, these dynamics are essential to CPD. In response, our statistical control approach infers the CPD directly from the structure of a network, by considering an ensemble average function over all possible Boolean dynamics for each node in the network. These ensemble average functions are combined with an acyclic form of the network to infer the number of point attractors. Our approach is applied to several known biological models and shown to outperform existing approaches. Statistical control of CPD offers a new avenue to contend with systemic processes such as differentiation and cancer, despite practical limitations in the field.

Argon gas plasma-treated physiological solutions stimulate immunogenic cell death and eradicates immunosuppressive CD47 protein in lung carcinoma

Cold atmospheric plasma-treated liquids (PTLs) exhibit selective toxicity toward tumor cells and are provoked by a cocktail of reactive oxygen and nitrogen species in such liquids. Compared to the gaseous phase, these reactive species are more persistent in the aqueous phase. This indirect plasma treatment method has gradually gathered interest in the discipline of plasma medicine to treat cancer. PTL's motivated effect on immunosuppressive proteins and immunogenic cell death (ICD) in solid cancer cells is still not explored. In this study, we aimed to induce immunomodulation by plasma-treated Ringer's lactate (PT-RL) and phosphate-buffered saline (PT-PBS) solutions for cancer treatment. PTLs induced minimum cytotoxicity in normal lung cells and inhibited cancer cell growth. ICD is confirmed by the enhanced expression of damage-associated molecular patterns (DAMPs). We evidenced that PTLs induce intracellular nitrogen oxide species accumulation and elevate immunogenicity in cancer cells owing to the production of pro-inflammatory cytokines, DAMPs, and reduced immunosuppressive protein CD47 expression. In addition, PTLs influenced A549 cells to elevate the organelles (mitochondria and lysosomes) in macrophages. Taken together, we have developed a therapeutic approach to potentially facilitate the selection of a suitable candidate for direct clinical applications.

Addressing the genetic/nongenetic duality in cancer with systems biology

The dogma that cancer is a genetic disease is being questioned. Recent findings suggest that genetic/nongenetic duality is necessary for cancer progression. A think tank organized by the Shraman Foundation's Institute for Theoretical Biology compiled key challenges and opportunities that theoreticians, experimentalists, and clinicians can explore from a systems biology perspective to provide a better understanding of the disease as well as help discover new treatment options and therapeutic strategies.

BdLT-Seq as a barcode decay-based method to unravel lineage-linked transcriptome plasticity

Cell plasticity is a core biological process underlying a myriad of molecular and cellular events taking place throughout organismal development and evolution. It has been postulated that cellular systems thrive to balance the organization of meta-stable states underlying this phenomenon, thereby maintaining a degree of populational homeostasis compatible with an ever-changing environment and, thus, life. Notably, albeit circumstantial evidence has been gathered in favour of the latter conceptual framework, a direct observation of meta-state dynamics and the biological consequences of such a process in generating non-genetic clonal diversity and divergent phenotypic output remains largely unexplored. To fill this void, here we develop a lineage-tracing technology termed Barcode decay Lineage Tracing-Seq. BdLT-Seq is based on episome-encoded molecular identifiers that, supported by the dynamic decay of the tracing information upon cell division, ascribe directionality to a cell lineage tree whilst directly coupling non-genetic molecular features to phenotypes in comparable genomic landscapes. We show that cell transcriptome states are both inherited, and dynamically reshaped following constrained rules encoded within the cell lineage in basal growth conditions, upon oncogene activation and throughout the process of reversible resistance to therapeutic cues thus adjusting phenotypic output leading to intra-clonal non-genetic diversity.

Rise of the natural red pigment 'prodigiosin' as an immunomodulator in cancer

Cancer is a heterogeneous disease with multifaceted drug resistance mechanisms (e.g., tumour microenvironment [TME], tumour heterogeneity, and immune evasion). Natural products are interesting repository of bioactive molecules, especially those with anticancer activities. Prodigiosin, a red pigment produced by Serratia marcescens, possesses inherent anticancer characteristics, showing interesting antitumour activities in different cancers (e.g., breast, gastric) with low or without harmful effects on normal cells. The present review discusses the potential role of prodigiosin in modulating and reprogramming the metabolism of the various immune cells in the TME, such as T and B lymphocytes, tumour-associated macrophages (TAMs), natural killer (NK) cells, and tumour-associated dendritic cells (TADCs), and myeloid-derived suppressor cells (MDSCs) which in turn might introduce as an immunomodulator in cancer therapy.

Addressing Drug Resistance in Cancer: A Team Medicine Approach

Drug resistance remains one of the major impediments to treating cancer. Although many patients respond well initially, resistance to therapy typically ensues. Several confounding factors appear to contribute to this challenge. Here, we first discuss some of the challenges associated with drug resistance. We then discuss how a ‘Team Medicine’ approach, involving an interdisciplinary team of basic scientists working together with clinicians, has uncovered new therapeutic strategies. These strategies, referred to as intermittent or ‘adaptive’ therapy, which are based on eco-evolutionary principles, have met with remarkable success in potentially precluding or delaying the emergence of drug resistance in several cancers. Incorporating such treatment strategies into clinical protocols could potentially enhance the precision of delivering personalized medicine to patients. Furthermore, reaching out to patients in the network of hospitals affiliated with leading academic centers could help them benefit from such innovative treatment options. Finally, lowering the dose of the drug and its frequency (because of intermittent rather than continuous therapy) can also have a significant impact on lowering the toxicity and undesirable side effects of the drugs while lowering the financial burden carried by the patient and insurance providers.

Stochastic population dynamics of cancer stemness and adaptive response to therapies

Intratumoral heterogeneity can exist along multiple axes: Cancer stem cells (CSCs)/non-CSCs, drug-sensitive/drug-tolerant states, and a spectrum of epithelial-hybrid-mesenchymal phenotypes. Further, these diverse cell-states can switch reversibly among one another, thereby posing a major challenge to therapeutic efficacy. Therefore, understanding the origins of phenotypic plasticity and heterogeneity remains an active area of investigation. While genomic components (mutations, chromosomal instability) driving heterogeneity have been well-studied, recent reports highlight the role of non-genetic mechanisms in enabling both phenotypic plasticity and heterogeneity. Here, we discuss various processes underlying phenotypic plasticity such as stochastic gene expression, chromatin reprogramming, asymmetric cell division and the presence of multiple stable gene expression patterns ('attractors'). These processes can facilitate a dynamically evolving cell population such that a subpopulation of (drug-tolerant) cells can survive lethal drug exposure and recapitulate population heterogeneity on drug withdrawal, leading to relapse. These drug-tolerant cells can be both pre-existing and also induced by the drug itself through cell-state reprogramming. The dynamics of cell-state transitions both in absence and presence of the drug can be quantified through mathematical models. Such a dynamical systems approach to elucidating patterns of intratumoral heterogeneity by integrating longitudinal experimental data with mathematical models can help design effective combinatorial and/or sequential therapies for better clinical outcomes.

Novel Driver Strength Index highlights important cancer genes in TCGA PanCanAtlas patients

Background

Cancer driver genes are usually ranked by mutation frequency, which does not necessarily reflect their driver strength. We hypothesize that driver strength is higher for genes preferentially mutated in patients with few driver mutations overall, because these few mutations should be strong enough to initiate cancer.

Methods

We propose formulas for the Driver Strength Index (DSI) and the Normalized Driver Strength Index (NDSI), the latter independent of gene mutation frequency. We validate them using TCGA PanCanAtlas datasets, established driver prediction algorithms and custom computational pipelines integrating SNA, CNA and aneuploidy driver contributions at the patient-level resolution.

Results

DSI and especially NDSI provide substantially different gene rankings compared to the frequency approach. E.g., NDSI prioritized members of specific protein families, including G proteins GNAQ, GNA11 and GNAS, isocitrate dehydrogenases IDH1 and IDH2, and fibroblast growth factor receptors FGFR2 and FGFR3. KEGG analysis shows that top NDSI-ranked genes comprise EGFR/FGFR2/GNAQ/GNA11-NRAS/HRAS/KRAS-BRAF pathway, AKT1-MTOR pathway, and TCEB1-VHL-HIF1A pathway.

Conclusion

Our indices are able to select for driver gene attributes not selected by frequency sorting, potentially for driver strength. Genes and pathways prioritized are likely the strongest contributors to cancer initiation and progression and should become future therapeutic targets.

Immune Evasion as the Main Challenge for Immunotherapy of Cancer

Immune evasion is currently considered one of the most prominent hallmarks of cancer [...].

Call the Eckols: Present and Future Potential Cancer Therapies

In recent years, an increased interest in marine macroalgae bioactive compounds has been recorded due to their benefits to human health and welfare. Several of their bioactivities have been demonstrated, such as anti-inflammatory, antioxidant, anticarcinogenic, antibacterial and antiviral behavior. However, there still lacks a clear definition regarding how these compounds exert their bioactive properties. Of all the bioactive compounds derived from marine macroalgae, attention has been focused on phenolic compounds, specifically in phlorotannins, due to their potential for biomedical applications. Phlorotannins are a diverse and wide group of phenolic compounds, with several structural variations based on the monomer phloroglucinol. Among the diverse phlorotannin structures, the eckol-family of phlorotannins demonstrates remarkable bioactivity, notably their anti-tumoral properties. However, the molecular mechanisms by which this activity is achieved remain elusive and sparse. This review focuses on the described molecular mechanisms of anti-tumoral effects by the eckol family of compounds and the future prospects of these molecules for potential application in oncology therapies.

Emergence of hybrid states of stem-like cancer cells correlates with poor prognosis in oral cancer

Cancer cell state transitions emerged as powerful mechanisms responsible for drug tolerance and overall poor prognosis; however, evidences were largely missing in oral cancer. Here, by multiplexing phenotypic markers of stem-like cancer cells (SLCCs); CD44, CD24 and aldehyde dehydrogenase (ALDH), we characterized diversity among multiple oral tumor tissues and cell lines. Two distinct patterns of spontaneous transitions with stochastic bidirectional interconversions on ‘ALDH-axis’, and unidirectional non-interconvertible transitions on ‘CD24-axis’ were observed. Interestingly, plastic ‘ALDH-axis’ was harnessed by cells to adapt to a Cisplatin tolerant state. Furthermore, phenotype-specific RNA sequencing suggested the possible maintenance of intermediate hybrid cell states maintaining stemness within the differentiating subpopulations. Importantly, survival analysis with subpopulation-specific gene sets strongly suggested that cell-state transitions may drive non-genetic heterogeneity, resulting in poor prognosis. Therefore, we have described the phenotypic-composition of heterogeneous subpopulations critical for global tumor behavior in oral cancer; which may provide prerequisite knowledge for treatment strategies.

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Demonstrated population trajectory driven non-genetic heterogeneity in oral cancer

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Created transition maps for subpopulations using discrete time Markov chain model

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Demonstrated maintenance of stemness in cells undergoing differentiation

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Uniquely expressed genes of these subpopulations associated with disease prognosis

The Genetic Evolution of Metastasis

Cancer is an evolutionary process that is characterized by the emergence of multiple genetically distinct populations or clones within the primary tumor. Intratumor heterogeneity provides a substrate for the selection of adaptive clones, such as those that lead to metastasis. Comparative molecular studies of primary tumors and metastases have identified distinct genomic features associated with the development of metastases. In this review, we discuss how these insights could inform clinical decision-making and uncover rational antimetastasis treatment strategies.

Can aggressive cancers be identified by the "aggressiveness" of their chromatin?

Phenotypic plasticity is a crucial feature of aggressive cancer, providing the means for cancer progression. Stochastic changes in tumor cell transcriptional programs increase the chances of survival under any condition. I hypothesize that unstable chromatin permits stochastic transitions between transcriptional programs in aggressive cancers and supports non-genetic heterogeneity of tumor cells as a basis for their adaptability. I present a mechanistic model for unstable chromatin which includes destabilized nucleosomes, mobile chromatin fibers and random enhancer-promoter contacts, resulting in stochastic transcription. I suggest potential markers for "unsettled" chromatin in tumors associated with poor prognosis. Although many of the characteristics of unstable chromatin have been described, they were mostly used to explain changes in the transcription of individual genes. I discuss approaches to evaluate the role of unstable chromatin in non-genetic tumor cell heterogeneity and suggest using the degree of chromatin instability and transcriptional noise in tumor cells to predict cancer aggressiveness.

Cancer Evolution in Precision Medicine Era

Recent advances in our understanding of cancer, driven mainly by the emergence of new technologies have highlighted that heterogeneity shapes not only the genetic profile of tumors but also their epigenetic and gene expression profile [...]

Population Dynamics of Epithelial-Mesenchymal Heterogeneity in Cancer Cells

Phenotypic heterogeneity is a hallmark of aggressive cancer behaviour and a clinical challenge. Despite much characterisation of this heterogeneity at a multi-omics level in many cancers, we have a limited understanding of how this heterogeneity emerges spontaneously in an isogenic cell population. Some longitudinal observations of dynamics in epithelial-mesenchymal heterogeneity, a canonical example of phenotypic heterogeneity, have offered us opportunities to quantify the rates of phenotypic switching that may drive such heterogeneity. Here, we offer a mathematical modeling framework that explains the salient features of population dynamics noted in PMC42-LA cells: (a) predominance of EpCAM^high subpopulation, (b) re-establishment of parental distributions from the EpCAM^high and EpCAM^low subpopulations, and (c) enhanced heterogeneity in clonal populations established from individual cells. Our framework proposes that fluctuations or noise in content duplication and partitioning of SNAIL—an EMT-inducing transcription factor—during cell division can explain spontaneous phenotypic switching and consequent dynamic heterogeneity in PMC42-LA cells observed experimentally at both single-cell and bulk level analysis. Together, we propose that asymmetric cell division can be a potential mechanism for phenotypic heterogeneity.

Interplay between Solid Tumors and Tumor Microenvironment

Over the past few decades, basic studies aimed at curing patients with cancer have been constantly evolving. A myriad of mechanistic studies on physiological changes and related factors in tumor growth and metastasis have been reported. Recently, several studies have been considerate to how tumors adapt to unfavorable environments, such as glucose deprivation, oxidative stress, hypoxic conditions, and immune responses. Tumors attempt to adapt to unfavorable environments with genetic or non-genetic changes, the alteration of metabolic signals, or the reconfiguration of their environment through migration to other organs. One of the distinct features in solid tumors is heterogeneity because their environments vary due to the characteristics of colony growth. For this reason, researchers are paying attention to the communication between growing tumors and neighboring environments, including stromal cells, immune cells, fibroblasts, and secreted molecules, such as proteins and RNAs. During cancer survival and progression, tumor cells undergo phenotype and molecular changes collectively referred to as cellular plasticity, which result from microenvironment signals, genetics and epigenetic alterations thereby contributing to tumor heterogeneity and therapy response. In this review, we herein discuss the adaptation process of tumors to adverse environments via communication with neighboring cells for overcoming unfavorable growth conditions. Understanding the physiology of these tumors and their communication with the tumor environment can help to develop promising tumor treatment strategies.

[Research Advances on Transformation to Small Cell Lung Cancer]

小细胞肺癌（small cell lung cancer, SCLC）转化是非小细胞肺癌尤其是表皮生长因子受体（epidermal growth factor receptor, EGFR）突变患者的重要耐药机制之一。目前发现转化性SCLC具有与原发性SCLC相似的临床特征，对化疗短期有效，中位生存期仅1年左右。RB1缺失、体细胞拷贝数改变与SCLC转化有关，但发生SCLC转化的确切分子机制仍不完全清楚。转化性SCLC的治疗也面临巨大的挑战，针对SCLC的化疗方案是目前的主要治疗选择，联合治疗、局部治疗以及预防SCLC转化的策略也在探索。本文将转化性SCLC的临床特征、分子机制和治疗选择进行综述。

Single-cell RNA sequencing and bioinformatics as tools to decipher cancer heterogenicity and mechanisms of drug resistance

It is well known that cancer is an aggressive disease, often associated with relapse, in many cases due to drug resistance. Cancer stem cell and clonal evolution are frequently causes of innate or acquired drug resistance. Current RNA sequencing technologies do not distinguish gene expression of different cell lineages because they are based on bulk cell studies. Single-cell RNA sequencing technologies and related bioinformatics clustering and differential expression analysis represent a turning point in cancer research. They are emerging as essential tools for dissecting tumors at single-cell resolution and represent novel tools to understand carcinogenesis and drug response. In this review, we will outline the role of these new technologies in addressing cancer heterogeneity and cell lineage-dependent drug resistance.

Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution

Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer's multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times. Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change. The surprisingly simple use-it or lose-it rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.

High-Resolution Cartography of the Transcriptome and Methylome Landscapes of Diffuse Gliomas

Molecular mechanisms of lower-grade (II-III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context.