Eco-evolutionary causes and consequences of temporal changes in intratumoural blood flow

Tumor microtubes: A new potential therapeutic target for high-grade gliomas

High-grade infiltrating gliomas are highly aggressive and fatal brain tumors that present significant challenges for research and treatment due to their complex microenvironment and tissue structure. Recent discovery of tumor microtubes (TMs) has provided new insights into how high-grade gliomas develop in the brain and resist treatment. TMs are unique, ultra-long, and highly functional membrane protrusions that form multicellular networks and play crucial roles in glioma invasiveness, drug resistance, recurrence, and heterogeneity. This review focuses on the different roles that TMs play in glioma cell communication, material transport, and tumor cell behavior. Specifically, non-connecting TMs primarily promote glioma invasiveness, likely related to their role in enhancing cell motility. On the other hand, interconnecting TMs form functional and communication networks by connecting with surrounding astrocytes and neurons, thereby promoting glioma malignancy. We summarize the factors that influence the formation of TMs in gliomas and current strategies targeting TMs. As the understanding of TMs advances, we are closer to uncovering whether they might be the long-sought Achilles' heel of treatment-resistant gliomas. By delving deeper into TMs research, we hope to develop more effective therapeutic strategies for patients with malignant gliomas.

Agent-based modeling for the tumor microenvironment (TME)

Cancer is a disease that arises from the uncontrolled growth of abnormal (tumor) cells in an organ and their subsequent spread into other parts of the body. If tumor cells spread to surrounding tissues or other organs, then the disease is life-threatening due to limited treatment options. This work applies an agent-based model to investigate the effect of intra-tumoral communication on tumor progression, plasticity, and invasion, with results suggesting that cell-cell and cell-extracellular matrix (ECM) interactions affect tumor cell behavior. Additionally, the model suggests that low initial healthy cell densities and ECM protein densities promote tumor progression, cell motility, and invasion. Furthermore, high ECM breakdown probabilities of tumor cells promote tumor invasion. Understanding the intra-tumoral communication under cellular stress can potentially lead to the design of successful treatment strategies for cancer.

Post-Transcriptional Regulation of Rab7a in Lysosomal Positioning and Drug Resistance in Nutrient-Limited Cancer Cells

Limited nutrient availability in the tumor microenvironment can cause the rewiring of signaling and metabolic networks to confer cancer cells with survival advantages. We show here that the limitation of glucose, glutamine and serum from the culture medium resulted in the survival of a population of cancer cells with high viability and capacity to form tumors in vivo. These cells also displayed a remarkable increase in the abundance and size of lysosomes. Moreover, lysosomes were located mainly in the perinuclear region in nutrient-limited cells; this translocation was mediated by a rapid post-transcriptional increase in the key endolysosomal trafficking protein Rab7a. The acidic lysosomes in nutrient-limited cells could trap weakly basic drugs such as doxorubicin, mediating resistance of the cells to the drug, which could be partially reversed with the lysosomal inhibitor bafilomycin A1. An in vivo chorioallantoic membrane (CAM) assay indicated a remarkable decrease in microtumor volume when nutrient-limited cells were treated with 5-Fluorouracil (5-FU) and bafilomycin A1 compared to cells treated with either agent alone. Overall, our data indicate the activation of complementary pathways with nutrient limitation that can enable cancer cells to survive, proliferate and acquire drug resistance.

Polyester nanoparticles delivering chemotherapeutics: Learning from the past and looking to the future to enhance their clinical impact in tumor therapy

Polymeric nanoparticles (NPs), specifically those comprised of biodegradable and biocompatible polyesters, have been heralded as a game-changing drug delivery platform. In fact, poly(α-hydroxy acids) such as polylactide (PLA), poly(lactide-co-glycolide) (PLGA), and poly(ε-caprolactone) (PCL) have been heavily researched in the past three decades as the material basis of polymeric NPs for drug delivery applications. As materials, these polymers have found success in resorbable sutures, biodegradable implants, and even monolithic, biodegradable platforms for sustained release of therapeutics (e.g., proteins and small molecules) and diagnostics. Few fields have gained more attention in drug delivery through polymeric NPs than cancer therapy. However, the clinical translational of polymeric nanomedicines for treating solid tumors has not been congruent with the fervor or funding in this particular field of research. Here, we attempt to provide a comprehensive snapshot of polyester NPs in the context of chemotherapeutic delivery. This includes a preliminary exploration of the polymeric nanomedicine in the cancer research space. We examine the various processes for producing polyester NPs, including methods for surface-functionalization, and related challenges. After a detailed overview of the multiple factors involved with the delivery of NPs to solid tumors, the crosstalk between particle design and interactions with biological systems is discussed. Finally, we report state-of-the-art approaches toward effective delivery of NPs to tumors, aiming at identifying new research areas and re-evaluating the reasons why some research avenues have underdelivered. We hope our effort will contribute to a better understanding of the gap to fill and delineate the future research work needed to bring polyester-based NPs closer to clinical application. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Emerging Technologies.

Carcinoma-associated mesenchymal stem cells promote ovarian cancer heterogeneity and metastasis through mitochondrial transfer

Ovarian cancer is characterized by early metastatic spread. This study demonstrates that carcinoma-associated mesenchymal stromal cells (CA-MSCs) enhance metastasis by increasing tumor cell heterogeneity through mitochondrial donation. CA-MSC mitochondrial donation preferentially occurs in ovarian cancer cells with low levels of mitochondria ("mito poor"). CA-MSC mitochondrial donation rescues the phenotype of mito poor cells, restoring their proliferative capacity, resistance to chemotherapy, and cellular respiration. Receipt of CA-MSC-derived mitochondria induces tumor cell transcriptional changes leading to the secretion of ANGPTL3, which enhances the proliferation of tumor cells without CA-MSC mitochondria, thus amplifying the impact of mitochondrial transfer. Donated CA-MSC mitochondrial DNA persisted in recipient tumor cells for at least 14 days. CA-MSC mitochondrial donation occurs in vivo, enhancing tumor cell heterogeneity and decreasing mouse survival. Collectively, this work identifies CA-MSC mitochondrial transfer as a critical mediator of ovarian cancer cell survival, heterogeneity, and metastasis and presents a unique therapeutic target in ovarian cancer.

PI-YOLO: dynamic sparse attention and lightweight convolutional based YOLO for vessel detection in pathological images

Vessel density within tumor tissues strongly correlates with tumor proliferation and serves as a critical marker for tumor grading. Recognition of vessel density by pathologists is subject to a strong inter-rater bias, thus limiting its prognostic value. There are many challenges in the task of object detection in pathological images, including complex image backgrounds, dense distribution of small targets, and insignificant differences between the features of the target to be detected and the image background. To address these problems and thus help physicians quantify blood vessels in pathology images, we propose Pathological Images-YOLO (PI-YOLO), an enhanced detection network based on YOLOv7. PI-YOLO incorporates the BiFormer attention mechanism, enhancing global feature extraction and accelerating processing for regions with subtle differences. Additionally, it introduces the CARAFE upsampling module, which optimizes feature utilization and information retention for small targets. Furthermore, the GSConv module improves the ELAN module, reducing model parameters and enhancing inference speed while preserving detection accuracy. Experimental results show that our proposed PI-YOLO network has higher detection accuracy compared to Faster-RCNN, SSD, RetinaNet, YOLOv5 network, and the latest YOLOv7 network, with a mAP value of 87.48%, which is 2.83% higher than the original model. We also validated the performance of this network on the ICPR 2012 mitotic dataset with an F1 value of 0.8678, outperforming other methods, demonstrating the advantages of our network in the task of target detection in complex pathology images.

A gene for all seasons: The evolutionary consequences of HIF-1 in carcinogenesis, tumor growth and metastasis

Oxygen played a pivotal role in the evolution of multicellularity during the Cambrian Explosion. Not surprisingly, responses to fluctuating oxygen concentrations are integral to the evolution of cancer-a disease characterized by the breakdown of multicellularity. Poorly organized tumor vasculature results in chaotic patterns of blood flow characterized by large spatial and temporal variations in intra-tumoral oxygen concentrations. Hypoxia-inducible growth factor (HIF-1) plays a pivotal role in enabling cells to adapt, metabolize, and proliferate in low oxygen conditions. HIF-1 is often constitutively activated in cancers, underscoring its importance in cancer progression. Here, we argue that the phenotypic changes mediated by HIF-1, in addition to adapting the cancer cells to their local environment, also "pre-adapt" them for proliferation at distant, metastatic sites. HIF-1-mediated adaptations include a metabolic shift towards anaerobic respiration or glycolysis, activation of cell survival mechanisms like phenotypic plasticity and epigenetic reprogramming, and formation of tumor vasculature through angiogenesis. Hypoxia induced epigenetic reprogramming can trigger epithelial to mesenchymal transition in cancer cells-the first step in the metastatic cascade. Highly glycolytic cells facilitate local invasion by acidifying the tumor microenvironment. New blood vessels, formed due to angiogenesis, provide cancer cells a conduit to the circulatory system. Moreover, survival mechanisms acquired by cancer cells in the primary site allow them to remodel tissue at the metastatic site generating tumor promoting microenvironment. Thus, hypoxia in the primary tumor promoted adaptations conducive to all stages of the metastatic cascade from the initial escape entry into a blood vessel, intravascular survival, extravasation into distant tissues, and establishment of secondary tumors.

Integration of deep learning and habitat radiomics for predicting the response to immunotherapy in NSCLC patients

BACKGROUND

The non-invasive biomarkers for predicting immunotherapy response are urgently needed to prevent both premature cessation of treatment and ineffective extension. This study aimed to construct a non-invasive model for predicting immunotherapy response, based on the integration of deep learning and habitat radiomics in patients with advanced non-small cell lung cancer (NSCLC).

METHODS

Independent patient cohorts from three medical centers were enrolled for training (n = 164) and test (n = 82). Habitat imaging radiomics features were derived from sub-regions clustered from individual's tumor by K-means method. The deep learning features were extracted based on 3D ResNet algorithm. Pearson correlation coefficient, T test and least absolute shrinkage and selection operator regression were used to select features. Support vector machine was applied to implement deep learning and habitat radiomics, respectively. Then, a combination model was developed integrating both sources of data.

RESULTS

The combination model obtained a strong well-performance, achieving area under receiver operating characteristics curve of 0.865 (95% CI 0.772-0.931). The model significantly discerned high and low-risk patients, and exhibited a significant benefit in the clinical use.

CONCLUSION

The integration of deep-leaning and habitat radiomics contributed to predicting response to immunotherapy in patients with NSCLC. The developed integration model may be used as potential tool for individual immunotherapy management.

Multiparametric MR-based feature fusion radiomics combined with ADC maps-based tumor proliferative burden in distinguishing TNBC versus non-TNBC

Objective.To investigate the incremental value of quantitative stratified apparent diffusion coefficient (ADC) defined tumor habitats for differentiating triple negative breast cancer (TNBC) from non-TNBC on multiparametric MRI (mpMRI) based feature-fusion radiomics (RFF) model.Approach.466 breast cancer patients (54 TNBC, 412 non-TNBC) who underwent routine breast MRIs in our hospital were retrospectively analyzed. Radiomics features were extracted from whole tumor on T2WI, diffusion-weighted imaging, ADC maps and the 2nd phase of dynamic contrast-enhanced MRI. Four models including the RFFmodel (fused features from all MRI sequences), RADCmodel (ADC radiomics feature), StratifiedADCmodel (tumor habitas defined on stratified ADC parameters) and combinational RFF-StratifiedADCmodel were constructed to distinguish TNBC versus non-TNBC. All cases were randomly divided into a training (n= 337) and test set (n= 129). The four competing models were validated using the area under the curve (AUC), sensitivity, specificity and accuracy.Main results.Both the RFFand StratifiedADCmodels demonstrated good performance in distinguishing TNBC from non-TNBC, with best AUCs of 0.818 and 0.773 in the training and test sets. StratifiedADCmodel revealed significant different tumor habitats (necrosis/cysts habitat, chaotic habitat or proliferative tumor core) between TNBC and non-TNBC with its top three discriminative parameters (p <0.05). The integrated RFF-StratifiedADCmodel demonstrated superior accuracy over the other three models, with higher AUCs of 0.832 and 0.784 in the training and test set, respectively (p <0.05).Significance.The RFF-StratifiedADCmodel through integrating various tumor habitats' information from whole-tumor ADC maps-based StratifiedADCmodel and radiomics information from mpMRI-based RFFmodel, exhibits tremendous promise for identifying TNBC.

Tumor-immune metaphenotypes orchestrate an evolutionary bottleneck that promotes metabolic transformation

Introduction

Metabolism plays a complex role in the evolution of cancerous tumors, including inducing a multifaceted effect on the immune system to aid immune escape. Immune escape is, by definition, a collective phenomenon by requiring the presence of two cell types interacting in close proximity: tumor and immune. The microenvironmental context of these interactions is influenced by the dynamic process of blood vessel growth and remodelling, creating heterogeneous patches of well-vascularized tumor or acidic niches.

Methods

Here, we present a multiscale mathematical model that captures the phenotypic, vascular, microenvironmental, and spatial heterogeneity which shapes acid-mediated invasion and immune escape over a biologically-realistic time scale. The model explores several immune escape mechanisms such as i) acid inactivation of immune cells, ii) competition for glucose, and iii) inhibitory immune checkpoint receptor expression (PD-L1). We also explore the efficacy of anti-PD-L1 and sodium bicarbonate buffer agents for treatment. To aid in understanding immune escape as a collective cellular phenomenon, we define immune escape in the context of six collective phenotypes (termed "meta-phenotypes"): Self-Acidify, Mooch Acid, PD-L1 Attack, Mooch PD-L1, Proliferate Fast, and Starve Glucose.

Results

Fomenting a stronger immune response leads to initial benefits (additional cytotoxicity), but this advantage is offset by increased cell turnover that leads to accelerated evolution and the emergence of aggressive phenotypes. This creates a bimodal therapy landscape: either the immune system should be maximized for complete cure, or kept in check to avoid rapid evolution of invasive cells. These constraints are dependent on heterogeneity in vascular context, microenvironmental acidification, and the strength of immune response.

Discussion

This model helps to untangle the key constraints on evolutionary costs and benefits of three key phenotypic axes on tumor invasion and treatment: acid-resistance, glycolysis, and PD-L1 expression. The benefits of concomitant anti-PD-L1 and buffer treatments is a promising treatment strategy to limit the adverse effects of immune escape.

Comparison of the somatic genomic landscape between central- and peripheral-type non-small cell lung cancer

OBJECTIVE

Lung cancer is classified into central and peripheral types based on the anatomic location. The present study aimed to explore the distinct patterns of genomic alterations between central- and peripheral-type non-small cell lung cancers (NSCLCs) with negative driver genes and identify potential driver genes and biomarkers to improve therapy strategies for NSCLC.

METHODS

Whole-exome sequencing (WES) was performed with 182 tumor/control pairs of samples from 145 Chinese NSCLC patients without EGFR, ALK, or ROS1 alterations. Significantly mutated genes (SMGs) and somatic copy number alterations (SCNAs) were identified. Subsequently, tumor mutation burden (TMB), weighted genome integrity index (wGII), copy number alteration (CNA) burden, Shannon diversity index (SDI), intratumor heterogeneity (ITH), neoantigen load (NAL), and clonal variations were evaluated in central- and peripheral-type NSCLCs. Furthermore, mutational signature analysis and survival analysis were performed.

RESULTS

TP53 was the most frequently mutated gene in NSCLC and more frequently mutated in central-type NSCLC. Higher wGII, ITH, and SDI were found in central-type lung adenocarcinoma (LUAD) than in peripheral-type LUAD. The NAL of central-type lung squamous cell carcinoma (LUSC) with stage III/IV was significantly higher than that of peripheral-type LUSC. Mutational signature analysis revealed that SBS10b, SBS24, and ID7 were significantly different in central- and peripheral-type NSCLCs. Furthermore, central-type NSCLC was found to evolve at a higher level with fewer clones and more subclones, particularly in central-type LUSC. Survival analysis revealed that TMB, CNA burden, NAL, subclonal driver mutations, and subclonal mutations were negatively related to the overall survival (OS) and the progression-free survival (PFS) of central-type LUAD.

CONCLUSIONS

Central-type NSCLC tended to evolve at a higher level and might suggest a favorable response to immunotherapy. Our study also identified several potential driver genes and promising biomarkers for the prognosis and prediction of chemotherapy responses in NSCLC.

Co-vulnerabilities of inhibiting carbonic anhydrase IX in ferroptosis-mediated tumor cell death

The tumour-associated carbonic anhydrases (CA) IX and XII are upregulated by cancer cells to combat cellular and metabolic stress imparted by hypoxia and acidosis in solid tumours. Owing to its tumour-specific expression and function, CAIX is an attractive therapeutic target and this has driven intense efforts to develop pharmacologic agents to target its activity, including small molecule inhibitors. Many studies in multiple solid tumour models have demonstrated that targeting CAIX activity with the selective CAIX/XII inhibitor, SLC-0111, results in anti-tumour efficacy, particularly when used in combination with chemotherapy or immune checkpoint blockade, and has now advanced to the clinic. However, it has been observed that sustainability and durability of CAIX inhibition, even in combination with chemotherapy agents, is limited by the occurrence of adaptive resistance, resulting in tumour recurrence. Importantly, the data from these models demonstrates that CAIX inhibition may sensitize tumour cells to cytotoxic drugs and evidence now points to ferroptosis, an iron-dependent form of regulated cell death (RCD) that results from accumulation of toxic levels of phospholipid peroxidation as a major mechanism involved in CAIX-mediated sensitization to cancer therapy. In this mini-review, we discuss recent advances demonstrating the mechanistic role CAIX plays in sensitizing cancer cells to ferroptosis.

Habitat-based radiomics enhances the ability to predict lymphovascular space invasion in cervical cancer: a multi-center study

Introduction

Lymphovascular space invasion (LVSI) is associated with lymph node metastasis and poor prognosis in cervical cancer. In this study, we investigated the potential of radiomics, derived from magnetic resonance (MR) images using habitat analysis, as a non-invasive surrogate biomarker for predicting LVSI in cervical cancer.

Methods

This retrospective study included 300 patients with cervical cancer who underwent surgical treatment at two centres (centre 1 = 198 and centre 2 = 102). Using the k-means clustering method, contrast-enhanced T1-weighted imaging (CE-T1WI) images were segmented based on voxel and entropy values, creating sub-regions within the volume ofinterest. Radiomics features were extracted from these sub-regions. Pearson correlation coefficient and least absolute shrinkage and selection operator LASSO) regression methods were used to select features associated with LVSI in cervical cancer. Support vector machine (SVM) model was developed based on the radiomics features extracted from each sub-region in the training cohort.

Results

The voxels and entropy values of the CE-T1WI images were clustered into three sub-regions. In the training cohort, the AUCs of the SVM models based on radiomics features derived from the whole tumour, habitat 1, habitat 2, and habitat 3 models were 0.805 (95% confidence interval [CI]: 0.745-0.864), 0.873(95% CI: 0.824-0.922), 0.869 (95% CI: 0.821-0.917), and 0.870 (95% CI: 0.821-0.920), respectively. Compared with whole tumour model, the predictive performances of habitat 3 model was the highest in the external test cohort (0.780 [95% CI: 0.692-0.869]).

Conclusions

The radiomics model based on the tumour sub-regional habitat demonstrated superior predictive performance for an LVSI in cervical cancer than that of radiomics model derived from the whole tumour.

Serum/glucose starvation strikingly reduces heterogeneous nuclear ribonucleoprotein A1 protein and its target, cyclin D1

Our investigation to explore cellular alterations related to undernutrition in cancer cells revealed that the protein level of heterogenous nuclear ribonucleoprotein A1 (hnRNP A1) is drastically decreased by serum/glucose starvation. Its loss was reversible, serum/glucose starvation-specific and universal throughout cell types and species. The hnRNP A1 mRNA level and hnRNP A1 mRNA/protein stability were not altered under this condition. CCND1 mRNA, which we newly identified as the binding target of hnRNP A1, was decreased by serum/glucose starvation. Under similar conditions, CCND1 protein was reduced in vitro and in vivo, whereas hnRNP A1 mRNA level and CCND1 mRNA level revealed no correlation in most clinical samples. Functional analyses revealed that CCND1 mRNA stability is certainly dependent on hnRNP A1 protein level and that RNA recognition motif-1 (RRM1) in hnRNP A1 plays a central role in maintaining CCND1 mRNA stability and subsequent protein expression. The injection of RRM1-deleted hnRNP A1-expressing cancer cells in the mouse xenograft model did not form any tumours, and that of hnRNP A1-expressing cancer cells retained CCND1 expression at the lesion adjacent to necrosis with a slight increase in tumour volume. Furthermore, RRM1 deletion caused growth suppression with the induction of apoptosis and autophagy, whereas CCND1 restoration completely recovered it. Our results indicate that serum/glucose starvation triggers entire hnRNP A1 protein loss, and its loss may play a role in CCND1 mRNA destabilization and CCND1-mediated cellular event inhibition, i.e. growth promotion, apoptosis induction and autophagosome formation.

The fate of extra centrosomes in newly formed tetraploid cells: should I stay, or should I go?

An increase in centrosome number is commonly observed in cancer cells, but the role centrosome amplification plays along with how and when it occurs during cancer development is unclear. One mechanism for generating cancer cells with extra centrosomes is whole genome doubling (WGD), an event that occurs in over 30% of human cancers and is associated with poor survival. Newly formed tetraploid cells can acquire extra centrosomes during WGD, and a generally accepted model proposes that centrosome amplification in tetraploid cells promotes cancer progression by generating aneuploidy and chromosomal instability. Recent findings, however, indicate that newly formed tetraploid cells in vitro lose their extra centrosomes to prevent multipolar cell divisions. Rather than persistent centrosome amplification, this evidence raises the possibility that it may be advantageous for tetraploid cells to initially restore centrosome number homeostasis and for a fraction of the population to reacquire additional centrosomes in the later stages of cancer evolution. In this review, we explore the different evolutionary paths available to newly formed tetraploid cells, their effects on centrosome and chromosome number distribution in daughter cells, and their probabilities of long-term survival. We then discuss the mechanisms that may alter centrosome and chromosome numbers in tetraploid cells and their relevance to cancer progression following WGD.

Polysaccharide-Based Stimulus-Responsive Nanomedicines for Combination Cancer Immunotherapy

Cancer immunotherapy is a promising antitumor approach, whereas nontherapeutic side effects, tumor microenvironment (TME) intricacy, and low tumor immunogenicity limit its therapeutic efficacy. In recent years, combination immunotherapy with other therapies has been proven to considerably increase antitumor efficacy. However, achieving codelivery of the drugs to the tumor site remains a major challenge. Stimulus-responsive nanodelivery systems show controlled drug delivery and precise drug release. Polysaccharides, a family of potential biomaterials, are widely used in the development of stimulus-responsive nanomedicines due to their unique physicochemical properties, biocompatibility, and modifiability. Here, the antitumor activity of polysaccharides and several combined immunotherapy strategies (e.g., immunotherapy combined with chemotherapy, photodynamic therapy, or photothermal therapy) are summarized. More importantly, the recent progress of polysaccharide-based stimulus-responsive nanomedicines for combination cancer immunotherapy is discussed, with the focus on construction of nanomedicine, targeted delivery, drug release, and enhanced antitumor effects. Finally, the limitations and application prospects of this new field are discussed.

Mathematical Model of Clonal Evolution Proposes a Personalised Multi-Modal Therapy for High-Risk Neuroblastoma

Neuroblastoma is the most common extra-cranial solid tumour in children. Despite multi-modal therapy, over half of the high-risk patients will succumb. One contributing factor is the one-size-fits-all nature of multi-modal therapy. For example, during the first step (induction chemotherapy), the standard regimen (rapid COJEC) administers fixed doses of chemotherapeutic agents in eight two-week cycles. Perhaps because of differences in resistance, this standard regimen results in highly heterogeneous outcomes in different tumours. In this study, we formulated a mathematical model comprising ordinary differential equations. The equations describe the clonal evolution within a neuroblastoma tumour being treated with vincristine and cyclophosphamide, which are used in the rapid COJEC regimen, including genetically conferred and phenotypic drug resistance. The equations also describe the agents’ pharmacokinetics. We devised an optimisation algorithm to find the best chemotherapy schedules for tumours with different pre-treatment clonal compositions. The optimised chemotherapy schedules exploit the cytotoxic difference between the two drugs and intra-tumoural clonal competition to shrink the tumours as much as possible during induction chemotherapy and before surgical removal. They indicate that induction chemotherapy can be improved by finding and using personalised schedules. More broadly, we propose that the overall multi-modal therapy can be enhanced by employing targeted therapies against the mutations and oncogenic pathways enriched and activated by the chemotherapeutic agents. To translate the proposed personalised multi-modal therapy into clinical use, patient-specific model calibration and treatment optimisation are necessary. This entails a decision support system informed by emerging medical technologies such as multi-region sequencing and liquid biopsies. The results and tools presented in this paper could be the foundation of this decision support system.

The role of physics in multiomics and cancer evolution

Complex interactions between the physical environment and phenotype of a tumour, and genomics, transcriptomics, proteomics and epigenomics, are increasingly known to have a significant influence on cancer development, progression and evolution. For example, mechanical stress can alter both genome maintenance and histone modifications, which consequently affect transcription and the epigenome. Increased stiffness has been linked to genetic heterogeneity and is responsible for heterochromatin accumulations. Stiffness thereby leads to deregulation in gene expression, disrupts the proteome and can impact angiogenesis. Several studies have shown how the physics of cancer can influence diverse cancer hallmarks such as resistance to cell death, angiogenesis and evasion from immune destruction. In this review, we will explain the role that physics of cancer plays in cancer evolution and explore how multiomics are being used to elucidate the mechanisms underpinning them.

Metastasis from the tumor interior and necrotic core formation are regulated by breast cancer-derived angiopoietin-like 7

Necrosis in the tumor interior is a common feature of aggressive cancers that is associated with poor clinical prognosis and the development of metastasis. How the necrotic core promotes metastasis remains unclear. Here, we report that emergence of necrosis inside the tumor is correlated temporally with increased tumor dissemination in a rat breast cancer model and in human breast cancer patients. By performing spatially focused transcriptional profiling, we identified angiopoietin-like 7 (Angptl7) as a tumor-specific factor localized to the perinecrotic zone. Functional studies showed that Angptl7 loss normalizes central necrosis, perinecrotic dilated vessels, metastasis, and reduces circulating tumor cell counts to nearly zero. Mechanistically, Angptl7 promotes vascular permeability and supports vascular remodeling in the perinecrotic zone. Taken together, these findings show that breast tumors actively produce factors controlling central necrosis formation and metastatic dissemination from the tumor core.

Development of a coupled modeling for tumor growth, angiogenesis, oxygen delivery, and phenotypic heterogeneity

Analysis of the evolution and growth dynamics of tumors is crucial for understanding cancer and the development of individually optimized therapies. During tumor growth, a hypoxic microenvironment around cancer cells caused by excessive non-vascular tumor growth induces tumor angiogenesis that plays a key role in the ensuing tumor growth and its progression into higher stages. Various mathematical simulation models have been introduced to simulate these biologically and physically complex hallmarks of cancer. Here, we developed a hybrid two-dimensional computational model that integrates spatiotemporally different components of the tumor system to investigate both angiogenesis and tumor growth/proliferation. This spatiotemporal evolution is based on partial diffusion equations, the cellular automation method, transition and probabilistic rules, and biological assumptions. The new vascular network provided by angiogenesis affects tumor microenvironmental conditions and drives individual cells to adapt themselves to spatiotemporal conditions. Furthermore, some stochastic rules are involved besides microenvironmental conditions. Overall, the conditions promote some commonly observed cellular states, i.e., proliferative, migrative, quiescent, and cell death, depending on the condition of each cell. Altogether, our results offer a theoretical basis for the biological evidence that regions of the tumor tissue near blood vessels are densely populated by proliferative phenotypic variants, while poorly oxygenated regions are sparsely populated by hypoxic phenotypic variants.

Tumor Vasculature as an Emerging Pharmacological Target to Promote Anti-Tumor Immunity

Tumor vasculature abnormality creates a microenvironment that is not suitable for anti-tumor immune response and thereby induces resistance to immunotherapy. Remodeling of dysfunctional tumor blood vessels by anti-angiogenic approaches, known as vascular normalization, reshapes the tumor microenvironment toward an immune-favorable one and improves the effectiveness of immunotherapy. The tumor vasculature serves as a potential pharmacological target with the capacity of promoting an anti-tumor immune response. In this review, the molecular mechanisms involved in tumor vascular microenvironment-modulated immune reactions are summarized. In addition, the evidence of pre-clinical and clinical studies for the combined targeting of pro-angiogenic signaling and immune checkpoint molecules with therapeutic potential are highlighted. The heterogeneity of endothelial cells in tumors that regulate tissue-specific immune responses is also discussed. The crosstalk between tumor endothelial cells and immune cells in individual tissues is postulated to have a unique molecular signature and may be considered as a potential target for the development of new immunotherapeutic approaches.

Challenging breast cancer through novel sulfonamide-pyridine hybrids: design, synthesis, carbonic anhydrase IX inhibition and induction of apoptosis

Background: Among the important key modulators of the tumor microenvironment and hypoxia is a family of enzymes named carbonic anhydrases. Herein, 11 novel sulfonamide-pyridine hybrids (2-12) were designed, synthesized and biologically evaluated for their potential use in targeting breast cancer. Methods & results: The para chloro derivative 7 reported the highest cytotoxic activity against the three breast cancer cell lines used. In addition, compound 7 was found to induce cell cycle arrest and autophagy as well as delaying wound healing. The IC₅₀ of compound 7 against carbonic anhydrase IX was 253 ± 12 nM using dorzolamide HCl as control. Conclusion: This study encourages us to expand the designed library, where more sulfonamide derivatives would be synthesized and studied for their structure-activity relationships.

Enhanced Sensitivity of Tumor Cells to Autophagy Inhibitors Using Fasting-Mimicking Diet and Targeted Lysosomal Delivery Nanoplatform

Autophagy is one of the key pathways for tumor cell survival and proliferation. Therefore, inhibition of autophagy has been extensively studied for cancer therapy. However, current autophagy inhibitors lack specificity and are ineffective in limiting tumor progression. Herein, we report a nanoplatform for tumor-site-targeted delivery of hydroxychloroquine (HCQ) using insulin-like growth factors 2 receptor (IGF2R)-targeted liposomes (iLipo-H). A fasting-mimicking diet (FMD) is used to increase the autophagy levels in tumor cells, thereby increasing the sensitivity of tumor cells to HCQ. In addition, FMD treatment upregulates the expression of IGF2R in tumor cells, but not normal cells. Consequently, iLipo-H nanoparticles efficiently accumulate at the tumor site under FMD condition. In vivo studies demonstrate that iLipo-H nanoparticles efficiently inhibit 4T1 tumor growth without obvious side effects, especially under FMD condition. This study provides a promising strategy to increase the sensitivity of tumor cells to autophagy inhibitors for effective cancer therapy.

Carbonic anhydrase IX: A tumor acidification switch in heterogeneity and chemokine regulation

The primary physiological process of respiration produces carbon dioxide (CO₂) that reacts with water molecules which subsequently liberates bicarbonate (HCO-₃) and protons. Carbonic anhydrases (CAs) are the primary catalyst involved in this conversion. More than 16 isoforms of human CAs show organ or subcellular specific activity. Dysregulation of each CA is associated with multiple pathologies. Out of these members, the overexpression of membrane-bound carbonic anhydrase IX (CAIX) is associated explicitly with hypoxic tumors or various solid cancers. CAIX helps tumors deal with higher CO₂ by sequestering it with bicarbonate ions and helping cancer cells to grow in a comparatively hypoxic or acidic environment, thus acting as a pH adaptation switch. CAIX-mediated adaptations in cancer cells include angiogenesis, metabolic alterations, tumor heterogeneity, drug resistance, and regulation of cancer-specific chemokines. This review comprehensively collects and describe the cancer-specific expression mechanism and role of CAIX in cancer growth, progression, heterogeneity, and its structural insight to develop future combinatorial targeted cancer therapies.

Proposal to Consider Chemical/Physical Microenvironment as a New Therapeutic Off-Target Approach

The molecular revolution could lead drug discovery from chance observation to the rational design of new classes of drugs that could simultaneously be more effective and less toxic. Unfortunately, we are witnessing some failure in this sense, and the causes of the crisis involve a wide range of epistemological and scientific aspects. In pharmacology, one key point is the crisis of the paradigm the “magic bullet”, which is to design therapies based on specific molecular targets. Drug repurposing is one of the proposed ways out of the crisis and is based on the off-target effects of known drugs. Here, we propose the microenvironment as the ideal place to direct the off-targeting of known drugs. While it has been extensively investigated in tumors, the generation of a harsh microenvironment is also a phenotype of the vast majority of chronic diseases. The hostile microenvironment, on the one hand, reduces the efficacy of both chemical and biological drugs; on the other hand, it dictates a sort of “Darwinian” selection of those cells armed to survive in such hostile conditions. This opens the way to the consideration of the microenvironment as a convenient target for pharmacological action, with a clear example in proton pump inhibitors.

Intermittent hypoxia enhances the expression of hypoxia inducible factor HIF1A through histone demethylation

The cellular response to hypoxia is regulated through enzymatic oxygen sensors, including the prolyl hydroxylases, which control degradation of the well-known hypoxia inducible factors (HIFs). Other enzymatic oxygen sensors have been recently identified, including members of the KDM histone demethylase family. Little is known about how different oxygen-sensing pathways interact and if this varies depending on the form of hypoxia, such as chronic or intermittent. In this study, we investigated how two proposed cellular oxygen-sensing systems, HIF-1 and KDM4A, KDM4B, and KDM4C, respond in cells exposed to rapid forms of intermittent hypoxia (minutes) and compared to chronic hypoxia (hours). We found that intermittent hypoxia increases HIF-1α protein through a pathway distinct from chronic hypoxia, involving the KDM4A, KDM4B, and KDM4C histone lysine demethylases. Intermittent hypoxia increases the quantity and activity of KDM4A, KDM4B, and KDM4C, resulting in a decrease in histone 3 lysine 9 (H3K9) trimethylation near the HIF1A locus. We demonstrate that this contrasts with chronic hypoxia, which decreases KDM4A, KDM4B, and KDM4C activity, leading to hypertrimethylation of H3K9 globally and at the HIF1A locus. Altogether, we found that demethylation of histones bound to the HIF1A gene in intermittent hypoxia increases HIF1A mRNA expression, which has the downstream effect of increasing overall HIF-1 activity and expression of HIF target genes. This study highlights how multiple oxygen-sensing pathways can interact to regulate and fine tune the cellular hypoxic response depending on the period and length of hypoxia.

Ecoevolutionary biology of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC), the most common histological subtype of pancreatic cancer, is an aggressive disease predicted to be the 2nd cause of cancer mortality in the US by 2040. While first-line therapy has improved, 5-year overall survival has only increased from 5 to ∼10%, and surgical resection is only available for ∼20% of patients as most present with advanced disease, which is invariably lethal. PDAC has well-established highly recurrent mutations in four driver genes including KRAS, TP53, CDKN2A, and SMAD4. Unfortunately, these genetic drivers are not currently therapeutically actionable. Despite extensive sequencing efforts, few additional significantly recurrent and druggable drivers have been identified. In the absence of targetable mutations, chemotherapy remains the mainstay of treatment for most patients. Further, the role of the above driver mutations on PDAC initiation and early development is well-established. However, these mutations alone cannot account for PDAC heterogeneity nor discern early from advanced disease. Taken together, management of PDAC is an example highlighting the shortcomings of the current precision medicine paradigm. PDAC, like other malignancies, represents an ecoevolutionary process. Better understanding the disease through this lens can facilitate the development of novel therapeutic strategies to better control and cure PDAC. This review aims to integrate the current understanding of PDAC pathobiology into an ecoevolutionary framework.

Tumor acidity: From hallmark of cancer to target of treatment

Tumor acidity is one of the cancer hallmarks and is associated with metabolic reprogramming and the use of glycolysis, which results in a high intracellular lactic acid concentration. Cancer cells avoid acid stress major by the activation and expression of proton and lactate transporters and exchangers and have an inverted pH gradient (extracellular and intracellular pHs are acid and alkaline, respectively). The shift in the tumor acid-base balance promotes proliferation, apoptosis avoidance, invasiveness, metastatic potential, aggressiveness, immune evasion, and treatment resistance. For example, weak-base chemotherapeutic agents may have a substantially reduced cellular uptake capacity due to "ion trapping". Lactic acid negatively affects the functions of activated effector T cells, stimulates regulatory T cells, and promotes them to express programmed cell death receptor 1. On the other hand, the inversion of pH gradient could be a cancer weakness that will allow the development of new promising therapies, such as tumor-targeted pH-sensitive antibodies and pH-responsible nanoparticle conjugates with anticancer drugs. The regulation of tumor pH levels by pharmacological inhibition of pH-responsible proteins (monocarboxylate transporters, H+-ATPase, etc.) and lactate dehydrogenase A is also a promising anticancer strategy. Another idea is the oral or parenteral use of buffer systems, such as sodium bicarbonate, to neutralize tumor acidity. Buffering therapy does not counteract standard treatment methods and can be used in combination to increase effectiveness. However, the mechanisms of the anticancer effect of buffering therapy are still unclear, and more research is needed. We have attempted to summarize the basic knowledge about tumor acidity.

Structural Features of Microvascular Networks Trigger Blood Flow Oscillations

We analyse mathematical models in order to understand how microstructural features of vascular networks may affect blood flow dynamics, and to identify particular characteristics that promote the onset of self-sustained oscillations. By focusing on a simple three-node motif, we predict that network “redundancy”, in the form of a redundant vessel connecting two main flow-branches, together with differences in haemodynamic resistance in the branches, can promote the emergence of oscillatory dynamics. We use existing mathematical descriptions for blood rheology and haematocrit splitting at vessel branch-points to construct our flow model; we combine numerical simulations and stability analysis to study the dynamics of the three-node network and its relation to the system’s multiple steady-state solutions. While, for the case of equal inlet-pressure conditions, a “trivial” equilibrium solution with no flow in the redundant vessel always exists, we find that it is not stable when other, stable, steady-state attractors exist. In turn, these “nontrivial” steady-state solutions may undergo a Hopf bifurcation into an oscillatory state. We use the branch diameter ratio, together with the inlet haematocrit rate, to construct a two-parameter stability diagram that delineates regimes in which such oscillatory dynamics exist. We show that flow oscillations in this network geometry are only possible when the branch diameters are sufficiently different to allow for a sufficiently large flow in the redundant vessel, which acts as the driving force of the oscillations. These microstructural properties, which were found to promote oscillatory dynamics, could be used to explore sources of flow instability in biological microvascular networks.

Photoacoustic Tomography Detects Response and Resistance to Bevacizumab in Breast Cancer Mouse Models

Angiogenesis is an established prognostic factor in advanced breast cancer, yet response to antiangiogenic therapies in this disease remains highly variable. Noninvasive imaging biomarkers could help identify patients that will benefit from antiangiogenic therapy and provide an ideal tool for longitudinal monitoring, enabling dosing regimens to be altered with real-time feedback. Photoacoustic tomography (PAT) is an emerging imaging modality that provides a direct readout of tumor hemoglobin concentration and oxygenation. We hypothesized that PAT could be used in the longitudinal setting to provide an early indication of response or resistance to antiangiogenic therapy. To test this hypothesis, PAT was performed over time in estrogen receptor-positive and estrogen receptor-negative breast cancer xenograft mouse models undergoing treatment with the antiangiogenic bevacizumab as a single agent. The cohort of treated tumors, which were mostly resistant to the treatment, contained a subset that demonstrated a clear survival benefit. At endpoint, the PAT data from the responding subset showed significantly lower oxygenation and higher hemoglobin content compared with both resistant and control tumors. Longitudinal analysis revealed that tumor oxygenation diverged significantly in the responding subset, identifying early treatment response and the evolution of different vascular phenotypes between the subsets. Responding tumors were characterized by a more angiogenic phenotype when analyzed with IHC, displaying higher vessel density, yet poorer vascular maturity and elevated hypoxia. Taken together, our findings indicate that PAT shows promise in providing an early indication of response or resistance to antiangiogenic therapy.

SIGNIFICANCE

Photoacoustic assessment of tumor oxygenation is a noninvasive early indicator of response to bevacizumab therapy, clearly distinguishing between control, responding, and resistant tumors within just a few weeks of treatment.

Measurement of Perfusion Heterogeneity within Tumor Habitats on Magnetic Resonance Imaging and Its Association with Prognosis in Breast Cancer Patients

Simple Summary

A habitat analysis reflects intratumoral heterogeneity more accurately than does a whole-tumor analysis. Perfusional heterogeneity using a habitat analysis is a rarely explored option and can affect patient outcomes. From two hospitals, 308 and 147 patients with invasive breast cancer who underwent preoperative MRI were included as development and validation cohorts, respectively. In our study, five habitats with distinct perfusion patterns were identified based on early and delayed phases of dynamic contrast material-enhanced MR images. A habitat risk score (HRS) was an independent risk factor for predicting worse disease-free survival outcomes in the HRS-only risk model (hazard ratio = 3.274 [95% CI = 1.378–7.782]; p = 0.014) and combined habitat risk model (hazard ratio = 4.128 [95% CI = 1.744–9.769]; p = 0.003) in the validation cohort.

Abstract

The purpose of this study was to identify perfusional subregions sharing similar kinetic characteristics from dynamic contrast-enhanced magnetic resonance imaging (MRI) using data-driven clustering, and to evaluate the effect of perfusional heterogeneity based on those subregions on patients’ survival outcomes in various risk models. From two hospitals, 308 and 147 women with invasive breast cancer who underwent preoperative MRI between October 2011 and July 2012 were retrospectively enrolled as development and validation cohorts, respectively. Using the Cox-least absolute shrinkage and selection operator model, a habitat risk score (HRS) was constructed from the radiomics features from the derived habitat map. An HRS-only, clinical, combined habitat, and two conventional radiomics risk models to predict patients’ disease-free survival (DFS) were built. Patients were classified into low-risk or high-risk groups using the median cutoff values of each risk score. Five habitats with distinct perfusion patterns were identified. An HRS was an independent risk factor for predicting worse DFS outcomes in the HRS-only risk model (hazard ratio = 3.274 [95% CI = 1.378–7.782]; p = 0.014) and combined habitat risk model (hazard ratio = 4.128 [95% CI = 1.744–9.769]; p = 0.003) in the validation cohort. In the validation cohort, the combined habitat risk model (hazard ratio = 4.128, p = 0.003, C-index = 0.760) showed the best performance among five different risk models. The quantification of perfusion heterogeneity is a potential approach for predicting prognosis and may facilitate personalized, tailored treatment strategies for breast cancer.

The Potential of Photoacoustic Imaging in Radiation Oncology

Radiotherapy is recognized globally as a mainstay of treatment in most solid tumors and is essential in both curative and palliative settings. Ionizing radiation is frequently combined with surgery, either preoperatively or postoperatively, and with systemic chemotherapy. Recent advances in imaging have enabled precise targeting of solid lesions yet substantial intratumoral heterogeneity means that treatment planning and monitoring remains a clinical challenge as therapy response can take weeks to manifest on conventional imaging and early indications of progression can be misleading. Photoacoustic imaging (PAI) is an emerging modality for molecular imaging of cancer, enabling non-invasive assessment of endogenous tissue chromophores with optical contrast at unprecedented spatio-temporal resolution. Preclinical studies in mouse models have shown that PAI could be used to assess response to radiotherapy and chemoradiotherapy based on changes in the tumor vascular architecture and blood oxygen saturation, which are closely linked to tumor hypoxia. Given the strong relationship between hypoxia and radio-resistance, PAI assessment of the tumor microenvironment has the potential to be applied longitudinally during radiotherapy to detect resistance at much earlier time-points than currently achieved by size measurements and tailor treatments based on tumor oxygen availability and vascular heterogeneity. Here, we review the current state-of-the-art in PAI in the context of radiotherapy research. Based on these studies, we identify promising applications of PAI in radiation oncology and discuss the future potential and outstanding challenges in the development of translational PAI biomarkers of early response to radiotherapy.

Novel humanized monoclonal antibodies for targeting hypoxic human tumors via two distinct extracellular domains of carbonic anhydrase IX

BACKGROUND

Hypoxia in the tumor microenvironment (TME) is often the main factor in the cancer progression. Moreover, low levels of oxygen in tumor tissue may signal that the first- or second-line therapy will not be successful. This knowledge triggers the inevitable search for different kinds of treatment that will successfully cure aggressive tumors. Due to its exclusive expression on cancer cells, carbonic anhydrase IX belongs to the group of the most precise targets in hypoxic tumors. CA IX possesses several exceptional qualities that predetermine its crucial role in targeted therapy. Its expression on the cell membrane makes it an easily accessible target, while its absence in healthy corresponding tissues makes the treatment practically harmless. The presence of CA IX in solid tumors causes an acidic environment that may lead to the failure of standard therapy.

METHODS

Parental mouse hybridomas (IV/18 and VII/20) were humanized to antibodies which were subsequently named CA9hu-1 and CA9hu-2. From each hybridoma, we obtained 25 clones. Each clone was tested for antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC) activity, affinity, extracellular pH measurement, multicellular aggregation analysis, and real-time monitoring of invasion with the xCELLigence system.

RESULTS

Based on the results from in vivo experiments, we have selected mouse monoclonal antibodies VII/20 and IV/18. The first one is directed at the conformational epitope of the catalytic domain, internalizes after binding to the antigen, and halts tumor growth while blocking extracellular acidification. The second targets the sequential epitope of the proteo-glycan domain, does not internalize, and is able to block the attachment of cancer cells to the matrix preventing metastasis formation. In vitro experiments prove that humanized versions of the parental murine antibodies, CA9hu-1 and CA9hu-2, have preserved these characteristics. They can reverse the failure of standard therapy as a result of an acidic environment by modulating the TME, and both are able to induce an immune response and have high affinity, as well as ADCC and CDC activity.

CONCLUSION

CA9hu-1 and CA9hu-2 are the very first humanized antibodies against CA IX that are likely to become suitable therapies for hypoxic tumors. These antibodies can be applied in the treatment therapy of primary tumors and suppression of metastases formation.

Understanding metabolic alterations and heterogeneity in cancer progression through validated immunodetection of key molecular components: a case of carbonic anhydrase IX

Cancer metabolic heterogeneity develops in response to both intrinsic factors (mutations leading to activation of oncogenic pathways) and extrinsic factors (physiological and molecular signals from the extracellular milieu). Here we review causes and consequences of metabolic alterations in cancer cells with focus on hypoxia and acidosis, and with particular attention to carbonic anhydrase IX (CA IX). CA IX is a cancer-associated enzyme induced and activated by hypoxia in a broad range of tumor types, where it participates in pH regulation as well as in molecular mechanisms supporting cancer cells’ invasion and metastasis. CA IX catalyzes reversible conversion of carbon dioxide to bicarbonate ion plus proton and cooperates with a spectrum of molecules transporting ions or metabolites across the plasma membrane. Thereby CA IX contributes to extracellular acidosis as well as to buffering intracellular pH, which is essential for cell survival, metabolic performance, and proliferation of cancer cells. Since CA IX expression pattern reflects gradients of oxygen, pH, and other intratumoral factors, we use it as a paradigm to discuss an impact of antibody quality and research material on investigating metabolic reprogramming of tumor tissue. Based on the validation, we propose the most reliable CA IX-specific antibodies and suggest conditions for faithful immunohistochemical analysis of molecules contributing to heterogeneity in cancer progression.

Autophagic Flux Unleashes GATA4-NF-κB Axis to Promote Antioxidant Defense-Dependent Survival of Colorectal Cancer Cells under Chronic Acidosis

Solid tumors are usually associated with extracellular acidosis due to their increased dependence on glycolysis and poor vascularization. Cancer cells gradually become adapted to acidic microenvironment and even acquire increased aggressiveness. They are resistant to apoptosis but exhibit increased autophagy that is essential for their survival. We here show that NF-κB, a master regulator of cellular responses to stress, is upregulated in colorectal cancer cells adapted to acidosis (CRC-AA). NF-κB is more relied upon for survival in CRC-AA than in their parental cells and drives a robust antioxidant response. Supplementation of antioxidant abolishes the increased sensitivity of CRC-AA to NF-κB inhibition or depletion, suggesting that NF-κB supports the survival of CRC-AA by maintaining redox homeostasis. Because SQSTM1/p62 is known to mediate the selective autophagy of GATA4 that augments NF-κB function, we tested whether the enhanced autophagic flux and consequently the reduction of SQSTM1/p62 in CRC-AA cells could activate the GATA4-NF-κB axis. Indeed, GATA4 is upregulated in CRC-AA cells and augments the NF-κB activity that underlies the increased expression of cytokines, inhibition of apoptosis, and reduction of reactive oxygen species. Interestingly, secretory factors derived from HCT15-AA cells, the soluble ICAM-1 in particular, also possess antioxidant cytoprotective effect against acidic stress. Together, our results demonstrate a prosurvival role of the p62-restricted GATA4-NF-κB axis in cancer cells adapted to acidic microenvironment.

Microenvironment of Cancer Stem Cells

Microenvironment of cancer stem cells (CSCs) consists of a variety of cells and inter-cellular matrix and communications of the components. The microenvironment of CSCs maintains the stemness feature of the CSCs. Several cell types which communicate each other via signaling molecules surrounding CSCs are main factors of the CSC microenvironment. A key question is "What kind of information the cells exchange in the CSC microenvironment?" to reveal the microenvironment and CSC features. Components and molecular markers of CSC microenvironment, signaling cross-talks in CSC microenvironment, and targeting CSC microenvironment are focused in this review.

Cell-of-Origin and Genetic, Epigenetic, and Microenvironmental Factors Contribute to the Intra-Tumoral Heterogeneity of Pediatric Intracranial Ependymoma

Intra-tumoral heterogeneity (ITH) is a complex multifaceted phenomenon that posits major challenges for the clinical management of cancer patients. Genetic, epigenetic, and microenvironmental factors are concurrent drivers of diversity among the distinct populations of cancer cells. ITH may also be installed by cancer stem cells (CSCs), that foster unidirectional hierarchy of cellular phenotypes or, alternatively, shift dynamically between distinct cellular states. Ependymoma (EPN), a molecularly heterogeneous group of tumors, shows a specific spatiotemporal distribution that suggests a link between ependymomagenesis and alterations of the biological processes involved in embryonic brain development. In children, EPN most often arises intra-cranially and is associated with an adverse outcome. Emerging evidence shows that EPN displays large intra-patient heterogeneity. In this review, after touching on EPN inter-tumoral heterogeneity, we focus on the sources of ITH in pediatric intra-cranial EPN in the framework of the CSC paradigm. We also examine how single-cell technology has shed new light on the complexity and developmental origins of EPN and the potential impact that this understanding may have on the therapeutic strategies against this deadly pediatric malignancy.

Cancer metabolism: looking forward

Tumour initiation and progression requires the metabolic reprogramming of cancer cells. Cancer cells autonomously alter their flux through various metabolic pathways in order to meet the increased bioenergetic and biosynthetic demand as well as mitigate oxidative stress required for cancer cell proliferation and survival. Cancer driver mutations coupled with environmental nutrient availability control flux through these metabolic pathways. Metabolites, when aberrantly accumulated, can also promote tumorigenesis. The development and application of new technologies over the last few decades has not only revealed the heterogeneity and plasticity of tumours but also allowed us to uncover new metabolic pathways involved in supporting tumour growth. The tumour microenvironment (TME), which can be depleted of certain nutrients, forces cancer cells to adapt by inducing nutrient scavenging mechanisms to sustain cancer cell proliferation. There is growing appreciation that the metabolism of cell types other than cancer cells within the TME, including endothelial cells, fibroblasts and immune cells, can modulate tumour progression. Because metastases are a major cause of death of patients with cancer, efforts are underway to understand how metabolism is harnessed by metastatic cells. Additionally, there is a new interest in exploiting cancer genetic analysis for patient stratification and/or dietary interventions in combination with therapies that target metabolism. In this Perspective, we highlight these main themes that are currently under investigation in the context of in vivo tumour metabolism, specifically emphasizing questions that remain unanswered.

Coexistence of “Cream Skimmer” and “Crumb Picker” Phenotypes in Nature and in Cancer

Over 40 years ago, seminal papers by Armstrong and McGehee and by Levins showed that temporal fluctuations in resource availability could permit coexistence of two species on a single resource. Such coexistence results from non-linearities or non-additivities in the way resource supply translates into fitness. These reflect trade-offs where one species benefits more than the other during good periods and suffers more (or does less well) than the other during less good periods, be the periods stochastic, unstable population dynamics, or seasonal. Since, coexistence based on fluctuating conditions has been explored under the guises of “grazers” and “diggers,” variance partitioning, relative non-linearity, “opportunists” and “gleaners,” and as the storage effect. Here we focus on two phenotypes, “cream skimmers” and “crumb pickers,” the former having the advantage in richer times and the latter in less rich times. In nature, richer and poorer times, with regular or stochastic appearances, are the norm and occur on many time scales. Fluctuations among richer and poorer times also appear to be the norm in cancer ecosystems. Within tumors, nutrient availability, oxygen, and pH can fluctuate stochastically or periodically, with swings occurring over seconds to minutes to hours. Despite interest in tumor heterogeneity and how it promotes the coexistence of different cancer cell types, the effects of fluctuating resource availability have not been explored for cancer. Here, in the context of pulsed resources, we (1) develop models of foraging consumers who experience pulsed resources to examine four types of trade-offs that can promote coexistence of phenotypes that do relatively better in richer versus in poorer times, (2) establish that conditions in tumors are conducive for this mechanism, (3) propose and empirically explore biomarkers indicative of the two phenotypes (HIF-1, GLUT-1, CA IX, CA XII), and (4) and compare cream skimmer and crumb picker biology and ecology in nature and cancer to provide cross-disciplinary insights into this interesting, and, we argue, likely very common, mechanism of coexistence.

The Evolutionary Ecology of Dormancy in Nature and in Cancer

Dormancy is an inactive period of an organism’s life cycle that permits it to survive through phases of unfavorable conditions in highly variable environments. Dormancy is not binary. There is a continuum of dormancy phenotypes that represent some degree of reduced metabolic activity (hypometabolism), reduced feeding, and reduced reproduction or proliferation. Similarly, normal cells and cancer cells exhibit a range of states from quiescence to long-term dormancy that permit survival in adverse environmental conditions. In contrast to organismal dormancy, which entails a reduction in metabolism, dormancy in cells (both normal and cancer) is primarily characterized by lack of cell division. “Cancer dormancy” also describes a state characterized by growth stagnation, which could arise from cells that are not necessarily hypometabolic or non-proliferative. This inconsistent terminology leads to confusion and imprecision that impedes progress in interdisciplinary research between ecologists and cancer biologists. In this paper, we draw parallels and contrasts between dormancy in cancer and other ecosystems in nature, and discuss the potential for studies in cancer to provide novel insights into the evolutionary ecology of dormancy.

Optical tissue clearing and machine learning can precisely characterize extravasation and blood vessel architecture in brain tumors

Precise methods for quantifying drug accumulation in brain tissue are currently very limited, challenging the development of new therapeutics for brain disorders. Transcardial perfusion is instrumental for removing the intravascular fraction of an injected compound, thereby allowing for ex vivo assessment of extravasation into the brain. However, pathological remodeling of tissue microenvironment can affect the efficiency of transcardial perfusion, which has been largely overlooked. We show that, in contrast to healthy vasculature, transcardial perfusion cannot remove an injected compound from the tumor vasculature to a sufficient extent leading to considerable overestimation of compound extravasation. We demonstrate that 3D deep imaging of optically cleared tumor samples overcomes this limitation. We developed two machine learning-based semi-automated image analysis workflows, which provide detailed quantitative characterization of compound extravasation patterns as well as tumor angioarchitecture in large three-dimensional datasets from optically cleared samples. This methodology provides a precise and comprehensive analysis of extravasation in brain tumors and allows for correlation of extravasation patterns with specific features of the heterogeneous brain tumor vasculature.

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.

New hypotheses for cancer generation and progression

Since Nixon famously declared war on cancer in 1971, trillions of dollars have been spent on cancer research but the life expectancy for most forms of cancer is still poor. There are many reasons for the partial success of cancer translational research. One of these can be the predominance of certain paradigms that potentially narrowed the vision in interpreting cancer. The main paradigm to explain carcinogenesis is based on DNA mutations, which is well interpreted by the somatic mutation theory (SMT). However, a different theory claims that cancer is instead a tissue disease as proposed by the Tissue Organization Field Theory (TOFT). Here, we propose new hypotheses to explain the origin and pathogenesis of cancer. In this perspective, the systemic-evolutionary theory of cancer (SETOC) is discussed as well as how the microenvironment affects the adaptation of transformed cells and the reversion to a unicellular-like or embryo-like phenotype.

Diversity in cell differentiation, histology, phenotype and vasculature of mass-forming intrahepatic cholangiocarcinomas

AIMS

Mass-forming intrahepatic cholangiocarcinomas (MF-iCCAs), involving small bile ducts, bile ductules or canals of Hering, remain treated as a single entity. We aimed to examine the diversity in histology, phenotype and tumour vasculature of MF-iCCAs.

METHODS AND RESULTS

Based on morphology and immunophenotype, we classified MF-iCCAs into small bile duct (SBD), cholangiolocarcinoma (CLC), ductal plate malformation (DPM) and hepatocellular carcinoma (HCC)-like subtypes. Genetic correlations among the histological subtypes were examined by multi-region tumour sequencing. Vasculatures and other clinicopathological features were compared among tumour groups with various proportions of the histological subtypes in 62 MF-iCCAs. Cases of pure SBD, CLC, DPM and HCC-like subtypes numbered 18 (29%), seven (11.3%), none (0%) and two (3%), respectively; the remaining 35 (56.4%) cases comprised several components. Genetic alterations, isocitrate dehydrogenase (IDH)1/2, KRAS, TP53, polybromo-1 (PBRM1) and BRCA1-associated protein 1 (BAP1), were shared among SBD, CLC, DPM and hepatoid components within a tumour. We uncovered distinct vascularisation mechanisms among SBD, CLC and DPM subtypes with a prominent vessel co-option in CLC tumours. iCCA with a DPM pattern had the highest vascular densities (mean microvascular density,140/mm² ; arterial vessel density, 18.3/mm² ). Increased CLC component was correlated with longer overall survival time (r = 0.44, P = 0.006). Pure SBD tumours had a lower 5-year overall survival rate compared with MF-iCCA with CLC pattern (30.5 versus 72.4%, P = 0.011).

CONCLUSIONS

MF-iCCAs comprise four histological subtypes. Given their sharing some driver gene alterations, indicating they can have a common cell origin, SBD, CLC and DPM subtypes, however, differ in cell differentiation, histology, phenotype or tumour vasculature.

Testing Multi-Task Cancer Evolution: How Do We Test Ecological Hypotheses in Cancer?

Recently several authors described a family of models, according to which different cancer types and subtypes fall within a space of selective trade-offs between archetypes that maximize the performance of different tasks: cell division, biomass and energy production, lipogenesis, immune interaction, and invasion and tissue remodeling. On this picture, inter- and intratumor heterogeneity can be explained in part as a product of these selective trade-offs in different cancers, at different stages of cancer progression. The aim of this Perspective is to critically assess this approach. I use this case study to consider more generally both the advantages of using ecological models in the context of cancer, and the challenges facing testing of such models.

Treatment-induced evolutionary dynamics in nonmetastatic locally advanced rectal adenocarcinoma

Multi-modal treatment of non-metastatic locally advanced rectal adenocarcinoma (LARC) includes chemotherapy, radiation, and life-altering surgery. Although highly effective for local cancer control, metastatic failure remains significant and drives rectal cancer-related mortality. A consistent observation of this tri-modality treatment paradigm is that histologic response of the primary tumor to neoadjuvant treatment(s), which varies across patients, predicts overall oncologic outcome. In this chapter, we will examine this treatment response heterogeneity in the context of evolutionary dynamics. We hypothesize that improved understanding of eco-evolutionary pressures rendering small cancer cell populations vulnerable to extinction may influence treatment strategies and improve patient outcomes. Applying effective treatment(s) to cancer populations causes a "race to extinction." We explore principles of eco-evolutionary extinction in the context of these small cancer cell populations, evaluating how treatment(s) aim to eradicate the cancer populations to ultimately result in cure. In this chapter, we provide an evolutionary rationale for limiting continuous treatment(s) with the same agent or combination of agents to avoid selection of resistant cancer subpopulation phenotypes, allowing "evolutionary rescue." We draw upon evidence from nature demonstrating species extinction rarely occurring as a single event phenomenon, but rather a series of events in the slide to extinction. We posit that eradicating small cancer populations, similar to small populations in natural extinctions, will usually require a sequence of different external perturbations that produce negative, synergistic dynamics termed the "extinction vortex." By exploiting these unique extinction vulnerabilities of small cancer populations, the optimal therapeutic sequences may be informed by evolution-informed strategies for patients with LARC.

What Is the Storage Effect, Why Should It Occur in Cancers, and How Can It Inform Cancer Therapy?

Intratumor heterogeneity is a feature of cancer that is associated with progression, treatment resistance, and recurrence. However, the mechanisms that allow diverse cancer cell lineages to coexist remain poorly understood. The storage effect is a coexistence mechanism that has been proposed to explain the diversity of a variety of ecological communities, including coral reef fish, plankton, and desert annual plants. Three ingredients are required for there to be a storage effect: (1) temporal variability in the environment, (2) buffered population growth, and (3) species-specific environmental responses. In this article, we argue that these conditions are observed in cancers and that it is likely that the storage effect contributes to intratumor diversity. Data that show the temporal variation within the tumor microenvironment are needed to quantify how cancer cells respond to fluctuations in the tumor microenvironment and what impact this has on interactions among cancer cell types. The presence of a storage effect within a patient’s tumors could have a substantial impact on how we understand and treat cancer.

Deep-learning and MR images to target hypoxic habitats with evofosfamide in preclinical models of sarcoma

Rationale: Hypoxic regions (habitats) within tumors are heterogeneously distributed and can be widely variant. Hypoxic habitats are generally pan-therapy resistant. For this reason, hypoxia-activated prodrugs (HAPs) have been developed to target these resistant volumes. The HAP evofosfamide (TH-302) has shown promise in preclinical and early clinical trials of sarcoma. However, in a phase III clinical trial of non-resectable soft tissue sarcomas, TH-302 did not improve survival in combination with doxorubicin (Dox), possibly due to a lack of patient stratification based on hypoxic status. Therefore, we used magnetic resonance imaging (MRI) to identify hypoxic habitats and non-invasively follow therapies response in sarcoma mouse models. Methods: We developed deep-learning (DL) models to identify hypoxia, using multiparametric MRI and co-registered histology, and monitored response to TH-302 in a patient-derived xenograft (PDX) of rhabdomyosarcoma and a syngeneic model of fibrosarcoma (radiation-induced fibrosarcoma, RIF-1). Results: A DL convolutional neural network showed strong correlations (>0.76) between the true hypoxia fraction in histology and the predicted hypoxia fraction in multiparametric MRI. TH-302 monotherapy or in combination with Dox delayed tumor growth and increased survival in the hypoxic PDX model (p<0.05), but not in the RIF-1 model, which had a lower volume of hypoxic habitats. Control studies showed that RIF-1 resistance was due to hypoxia and not other causes. Notably, PDX tumors developed resistance to TH-302 under prolonged treatment that was not due to a reduction in hypoxic volumes. Conclusion: Artificial intelligence analysis of pre-therapy MR images can predict hypoxia and subsequent response to HAPs. This approach can be used to monitor therapy response and adapt schedules to forestall the emergence of resistance.