Addressing intra-tumoral heterogeneity and therapy resistance

Histology-Based Radiomics for [18F]FDG PET Identifies Tissue Heterogeneity in Pancreatic Cancer

Radiomics features can reveal hidden patterns in a tumor but usually lack an underlying biologic rationale. In this work, we aimed to investigate whether there is a correlation between radiomics features extracted from [18F]FDG PET images and histologic expression patterns of a glycolytic marker, monocarboxylate transporter-4 (MCT4), in pancreatic cancer. Methods: A cohort of pancreatic ductal adenocarcinoma patients (n = 29) for whom both tumor cross sections and [18F]FDG PET/CT scans were available was used to develop an [18F]FDG PET radiomics signature. By using immunohistochemistry for MCT4, we computed density maps of MCT4 expression and extracted pathomics features. Cluster analysis identified 2 subgroups with distinct MCT4 expression patterns. From corresponding [18F]FDG PET scans, radiomics features that associate with the predefined MCT4 subgroups were identified. Results: Complex heat map visualization showed that the MCT4-high/heterogeneous subgroup was correlating with a higher MCT4 expression level and local variation. This pattern linked to a specific [18F]FDG PET signature, characterized by a higher SUVmean and SUVmax and second-order radiomics features, correlating with local variation. This MCT4-based [18F]FDG PET signature of 7 radiomics features demonstrated prognostic value in an independent cohort of pancreatic cancer patients (n = 71) and identified patients with worse survival. Conclusion: Our cross-modal pipeline allows the development of PET scan signatures based on immunohistochemical analysis of markers of a particular biologic feature, here demonstrated on pancreatic cancer using intratumoral MCT4 expression levels to select [18F]FDG PET radiomics features. This study demonstrated the potential of radiomics scores to noninvasively capture intratumoral marker heterogeneity and identify a subset of pancreatic ductal adenocarcinoma patients with a poor prognosis.

Selection of optimal quantile protein biomarkers based on cell-level immunohistochemistry data

BACKGROUND

Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expression in tissues at the single-cell level. However, this rich quantitative cell-by-cell biomarker information is most often not exploited. Instead, it is reduced to a single mean across the cells of interest or converted into a simple proportion of binary biomarker-positive or -negative cells.

RESULTS

We investigated the utility of retaining all quantitative information at the single-cell level by considering the values of the quantile function (inverse of the cumulative distribution function) estimated from a sample of cell signal intensity levels in a tumor tissue. An algorithm was developed for selecting optimal cutoffs for dichotomizing cell signal intensity distribution quantiles as predictors of continuous, categorical or survival outcomes. The proposed algorithm was used to select optimal quantile biomarkers of breast cancer progression based on cancer cells' cell signal intensity levels of nuclear protein Ki-67, Proliferating cell nuclear antigen, Programmed cell death 1 ligand 2, and Progesterone receptor. The performance of the resulting optimal quantile biomarkers was validated and compared to the standard cancer compartment mean signal intensity markers using an independent external validation cohort. For Ki-67, the optimal quantile biomarker was also compared to established biomarkers based on percentages of Ki67-positive cells. For proteins significantly associated with PFS in the external validation cohort, the optimal quantile biomarkers yielded either larger or similar effect size (hazard ratio for progression-free survival) as compared to cancer compartment mean signal intensity biomarkers.

CONCLUSION

The optimal quantile protein biomarkers yield generally improved prognostic value as compared to the standard protein expression markers. The proposed methodology has a broad application to single-cell data from genomics, transcriptomics, proteomics, or metabolomics studies at the single cell level.

Intratumor Heterogeneity and Treatment Resistance of Solid Tumors with a Focus on Polyploid/Senescent Giant Cancer Cells (PGCCs)

Single cell biology has revealed that solid tumors and tumor-derived cell lines typically contain subpopulations of cancer cells that are readily distinguishable from the bulk of cancer cells by virtue of their enormous size. Such cells with a highly enlarged nucleus, multiple nuclei, and/or multiple micronuclei are often referred to as polyploid giant cancer cells (PGCCs), and may exhibit features of senescence. PGCCs may enter a dormant phase (active sleep) after they are formed, but a subset remain viable, secrete growth promoting factors, and can give rise to therapy resistant and tumor repopulating progeny. Here we will briefly discuss the prevalence and prognostic value of PGCCs across different cancer types, the current understanding of the mechanisms of their formation and fate, and possible reasons why these tumor repopulating "monsters" continue to be ignored in most cancer therapy-related preclinical studies. In addition to PGCCs, other subpopulations of cancer cells within a solid tumor (such as oncogenic caspase 3-activated cancer cells and drug-tolerant persister cancer cells) can also contribute to therapy resistance and pose major challenges to the delivery of cancer therapy.

Expression of Amine Oxidase Proteins in Adrenal Cortical Neoplasm and Pheochromocytoma

We delved into the expression of amine oxidase family proteins and their potential significance in adrenal gland neoplasm. Tissue microarrays were prepared for 132 cases of adrenal cortical neoplasm (ACN) consisting of 115 cases of adrenal cortical adenoma (ACA), 17 cases of adrenal cortical carcinoma (ACC), and 163 cases of pheochromocytoma (PCC). Immunohistochemical stainings for MAOA, MAOB, LOX, and AOC3 were performed to evaluate the H-scores and compare them with clinicopathological parameters. The H-scores of MAOA (T; p = 0.005) and MAOB (T; p = 0.006) in tumor cells (T) were high in ACN, whereas LOX (T, S; p < 0.001) in tumor and stromal cells (S) and AOC3 (T; p < 0.001) were higher in PCC. In stromal cells, MAOA (S; p < 0.001) and AOC3 (S; p = 0.010) were more expressed in ACA than in ACC. MAOB (S) in PCC showed higher H-scores when the grading of adrenal pheochromocytoma and paraganglioma (GAPP) score was 3 or higher (p = 0.027). In the univariate analysis, low MAOA expression in stromal cells of ACN was associated with shorter overall survival (p = 0.008). In conclusion, monoamine oxidase proteins revealed differences in expression between ACN and PCC and also between benign and malignant cells.

Comparative evaluation of the therapeutic strategies using a minimal model of luminal-A breast cancer

Cellular behavior is heavily influenced by cellular interactions, which are often lost in conventional cell culture methods. As a result, in vitro cellular behavior may not accurately reflect in vivo conditions. Three-dimensional (3D) culture, on the other hand, is better suited for studying cellular behavior as it allows for more comprehensive cell communication. In this study, we utilized 3D culture of the MCF-7 cell line to create a minimal model of luminal-A breast cancer and evaluated its histopathological and morphological features using various methods. To determine the optimal therapeutic strategies for eliminating cancer cells, we assessed the effectiveness of diverse therapeutic approaches, including targeting distinct phases of the cell cycle, endocrine therapy, and gene therapy in both 2D and 3D culture systems. Our findings indicate that cells derived from mammospheres respond differently to their parent cells in monolayer culture depending on the therapeutic strategy used. This variability in drug response may be due to the altered microenvironment created by heterogeneous cellular makeup and emerging cellular interactions in the 3D culture. Therefore, it is important to administer a therapeutic approach that can eradicate cells regardless of the microenvironment.

αCT1 peptide sensitizes glioma cells to temozolomide in a glioblastoma organoid platform

Glioblastoma (GBM) is the most common form of brain cancer. Even with aggressive treatment, tumor recurrence is almost universal and patient prognosis is poor because many GBM cell subpopulations, especially the mesenchymal and glioma stem cell populations, are resistant to temozolomide (TMZ), the most commonly used chemotherapeutic in GBM. For this reason, there is an urgent need for the development of new therapies that can more effectively treat GBM. Several recent studies have indicated that high expression of connexin 43 (Cx43) in GBM is associated with poor patient outcomes. It has been hypothesized that inhibition of the Cx43 hemichannels could prevent TMZ efflux and sensitize otherwise resistance cells to the treatment. In this study, we use a three-dimensional organoid model of GBM to demonstrate that combinatorial treatment with TMZ and αCT1, a Cx43 mimetic peptide, significantly improves treatment efficacy in certain populations of GBM. Confocal imaging was used to visualize changes in Cx43 expression in response to combinatorial treatment. These results indicate that Cx43 inhibition should be pursued further as an improved treatment for GBM.

The hypoxia-inducible factor-1α in stemness and resistance to chemotherapy in gastric cancer: Future directions for therapeutic targeting

Hypoxia-inducible factor-1α (HIF-1α) is a crucial mediator of intra-tumoral heterogeneity, tumor progression, and unresponsiveness to therapy in tumors with hypoxia. Gastric tumors, one of the most aggressive tumors in the clinic, are highly enriched in hypoxic niches, and the degree of hypoxia is strongly correlated with poor survival in gastric cancer patients. Stemness and chemoresistance in gastric cancer are the two root causes of poor patient outcomes. Based on the pivotal role of HIF-1α in stemness and chemoresistance in gastric cancer, the interest in identifying critical molecular targets and strategies for surpassing the action of HIF-1α is expanding. Despite that, the understanding of HIF-1α induced signaling in gastric cancer is far from complete, and the development of efficacious HIF-1α inhibitors bears various challenges. Hence, here we review the molecular mechanisms by which HIF-1α signaling stimulates stemness and chemoresistance in gastric cancer, with the clinical efforts and challenges to translate anti-HIF-1α strategies into the clinic.

Lactobacillus for ribosome peptide editing cancer

This study reviews newly discovered insect peptide point mutations as new possible cancer research targets. To interpret newly discovered peptide point mutations in insects as new possible cancer research targets, we focused on the numerous peptide changes found in the 'CSP' family on the sex pheromone gland of the female silkworm moth Bombyx mori. We predict that the Bombyx peptide modifications will have a significant effect on cancer CUP (cancers of unknown primary) therapy and that bacterial peptide editing techniques, specifically Lactobacillus combined to CRISPR, will be used to regulate ribosomes and treat cancer in humans.

CTC-5: A novel digital pathology approach to characterise circulating tumour cell biodiversity

Metastatic progression and tumor evolution complicates the clinical management of cancer patients. Circulating tumor cell (CTC) characterization is a growing discipline that aims to elucidate tumor metastasis and evolution processes. CTCs offer the clinical potential to monitor cancer patients for therapy response, disease relapse, and screen 'at risk' groups for the onset of malignancy. However, such clinical utility is currently limited to breast, prostate, and colorectal cancer patients. Further understanding of the basic CTC biology of other malignancies is required to progress them towards clinical utility. Unfortunately, such basic clinical research is often limited by restrictive characterization methods and high-cost barrier to entry for CTC isolation and imaging infrastructure. As experimental clinical results on applications of CTC are accumulating, it is becoming clear that a two-tier system of CTC isolation and characterization is required. The first tier is to facilitate basic research into CTC characterization. This basic research then informs a second tier specialised in clinical prognostic and diagnostic testing. This study presented in this manuscript describes the development and application of a low-cost, CTC isolation and characterization pipeline; CTC-5. This approach uses an established 'isolation by size' approach (ScreenCell Cyto) and combines histochemical morphology stains and multiparametric immunofluorescence on the same isolated CTCs. This enables capture and characterization of CTCs independent of biomarker-based pre-selection and accommodates both single CTCs and clusters of CTCs. Additionally, the developed open-source software is provided to facilitate the synchronization of microscopy data from multiple sources (https://github.com/CTC5/). This enables high parameter histochemical and immunofluorescent analysis of CTCs with existing microscopy infrastructure without investment in CTC specific imaging hardware. Our approach confirmed by the number of successful tests represents a potential major advance towards highly accessible low-cost technology aiming at the basic research tier of CTC isolation and characterization. The biomarker independent approach facilitates closing the gap between malignancies with poorly, and well-defined CTC phenotypes. As is currently the case for some of the most commonly occurring breast, prostate and colorectal cancers, such advances will ultimately benefit the patient, as early detection of relapse or onset of malignancy strongly correlates with their prognosis.

Inter and intra-tumor heterogeneity of paediatric type diffuse high-grade gliomas revealed by single-cell mass cytometry

Paediatric-type diffuse high-grade gliomas (PDHGG) are aggressive tumors affecting children and young adults, with no effective treatment. These highly heterogeneous malignancies arise in different sites of the Central Nervous System (CNS), carrying distinctive molecular alterations and clinical outcomes (inter-tumor heterogeneity). Moreover, deep cellular and molecular profiling studies highlighted the coexistence of genetically and phenotypically different subpopulations within the same tumor mass (intra-tumor heterogeneity). Despite the recent advances made in the field, the marked heterogeneity of PDHGGs still impedes the development of effective targeted therapies and the identification of suitable biomarkers. In order to fill the existing gap, we used mass cytometry to dissect PDHGG inter- and intra-heterogeneity. This is one of the most advanced technologies of the "-omics" era that, using antibodies conjugated to heavy metals, allows the simultaneous measurement of more than 40 markers at single-cell level. To this end, we analyzed eight PDHGG patient-derived cell lines from different locational and molecular subgroups. By using a panel of 15 antibodies, directly conjugated to metals or specifically customized to detect important histone variants, significant differences were highlighted in the expression of the considered antigens. The single-cell multiparametric approach realized has deepened our understanding of PDHGG, confirming a high degree of intra- and inter-tumoral heterogeneity and identifying some antigens that could represent useful biomarkers for the specific PDHGG locational or molecular subgroups.

What Are the Reasons for Continuing Failures in Cancer Therapy? Are Misleading/Inappropriate Preclinical Assays to Be Blamed? Might Some Modern Therapies Cause More Harm than Benefit?

Over 50 years of cancer research has resulted in the generation of massive amounts of information, but relatively little progress has been made in the treatment of patients with solid tumors, except for extending their survival for a few months at best. Here, we will briefly discuss some of the reasons for this failure, focusing on the limitations and sometimes misunderstanding of the clinical relevance of preclinical assays that are widely used to identify novel anticancer drugs and treatment strategies (e.g., "synthetic lethality"). These include colony formation, apoptosis (e.g., caspase-3 activation), immunoblotting, and high-content multiwell plate cell-based assays, as well as tumor growth studies in animal models. A major limitation is that such assays are rarely designed to recapitulate the tumor repopulating properties associated with therapy-induced cancer cell dormancy (durable proliferation arrest) reflecting, for example, premature senescence, polyploidy and/or multinucleation. Furthermore, pro-survival properties of apoptotic cancer cells through phoenix rising, failed apoptosis, and/or anastasis (return from the brink of death), as well as cancer immunoediting and the impact of therapeutic agents on interactions between cancer and immune cells are often overlooked in preclinical studies. A brief review of the history of cancer research makes one wonder if modern strategies for treating patients with solid tumors may sometimes cause more harm than benefit.

Anti-EGFR Targeted Multifunctional I-131 Radio-Nanotherapeutic for Treating Osteosarcoma: In Vitro 3D Tumor Spheroid Model

The systemic delivery of doxorubicin (DOX) to treat osteosarcoma requires an adequate drug concentration to be effective, but in doing so, it raises the risk of increasing organ off-target toxicity and developing drug resistance. Herein, this study reveals a multiple therapeutic nanocarrier delivery platform that overcomes off-target toxicity by providing good specificity and imparting enhanced tumor penetration in a three-dimensional (3D) human MG-63 spheroid model. By synthesizing PEG-PLGA nanoparticles by the double emulsion method, encapsulating DOX and Na131I in the inner core, and conjugating with an epidermal growth factor receptor (EGFR) antibody, it is intended to specifically target human MG-63 cells. The nanocarrier is biocompatible with blood and has good stability characteristics. Na131I encapsulation efficiency was >96%, and radiochemical purity was >96% over 96 h. A DOX encapsulation efficacy of ~80% was achieved, with a drug loading efficiency of ~3%, and a sustained DOX release over 5 days. The nanocarrier EGFR antibody achieved a ~80-fold greater targeting efficacy to MG-63 cells (EGFR+) than fibroblast cells (EGFR−). The targeted multiple therapeutic DIE-NPs have a higher penetration and uptake of Na131I to the 3D model and a ~3-fold higher cytotoxicity than the DOX monotherapy (D-NPs). The co-administration of DOX and Na131I (DIE-NPs) disrupts DNA repair and generates free radicals resulting in DNA damage, triggering the activation of apoptosis pathways. This leads to inhibition of MG-63 cell proliferation and promotes cell cycle arrest in the G0/G1 phase. Furthermore, the PEGylated anti-EGFR functionalized DIE-NPs were found to be biocompatible with red blood cells and to have no adverse effects. This anti-EGFR targeted multifunctional I-131 radio-nanotherapeutic signifies a customizable specific targeted treatment for osteosarcoma.

The HIF-1α as a Potent Inducer of the Hallmarks in Gastric Cancer

Simple Summary

Gastric cancer is one of the most aggressive tumors in the clinic that is resistant to chemotherapy. Gastric tumors are rich in hypoxic niches, and high expression of hypoxia-inducible factor-1α is associated with poor prognosis. Therefore, strategies that target hypoxia-inducible factor-1α signaling may be highly effective in gastric cancer treatment. However, the precise mechanisms by which hypoxia-inducible factor-1α induces tumor hallmarks in gastric cancer are yet unrevealed. Here, we review the role of hypoxia-inducible factor-1α as a potent inducer of the cancer hallmarks in gastric cancer to provide a broad perspective and reveal missing links investigating which may offer new strategies to target hypoxia-inducible factor-1α signaling in gastric cancer.

Abstract

Hypoxia is the principal architect of the topographic heterogeneity in tumors. Hypoxia-inducible factor-1α (HIF-1α) reinforces all hallmarks of cancer and donates cancer cells with more aggressive characteristics at hypoxic niches. HIF-1α potently induces sustained growth factor signaling, angiogenesis, epithelial–mesenchymal transition, and replicative immortality. Hypoxia leads to the selection of cancer cells that evade growth suppressors or apoptotic triggers and deregulates cellular energetics. HIF-1α is also associated with genetic instability, tumor-promoting inflammation, and escape from immunity. Therefore, HIF-1α may be an important therapeutic target in cancer. Despite that, the drug market lacks safe and efficacious anti-HIF-1α molecules, raising the quest for fully unveiling the complex interactome of HIF-1α in cancer to discover more effective strategies. The knowledge gap is even wider in gastric cancer, where the number of studies on hypoxia is relatively low compared to other well-dissected cancers. A comprehensive review of the molecular mechanisms by which HIF-1α induces gastric cancer hallmarks could provide a broad perspective to the investigators and reveal missing links to explore in future studies. Thus, here we review the impact of HIF-1α on the cancer hallmarks with a specific focus on gastric cancer.

Simulating the Dynamic Intra-Tumor Heterogeneity and Therapeutic Responses

A tumor is a complex tissue comprised of heterogeneous cell subpopulations which exhibit substantial diversity at morphological, genetic and epigenetic levels. Under the selective pressure of cancer therapies, a minor treatment-resistant subpopulation could survive and repopulate. Therefore, the intra-tumor heterogeneity is recognized as a major obstacle to effective treatment. In this paper, we propose a stochastic clonal expansion model to simulate the dynamic evolution of tumor subpopulations and the therapeutic effect at different times during tumor progression. The model is incorporated in the CES webserver, for the convenience of simulation according to initial user input. Based on this model, we investigate the influence of various factors on tumor progression and treatment consequences and present conclusions drawn from observations, highlighting the importance of treatment timing. The model provides an intuitive illustration to deepen the understanding of temporal intra-tumor heterogeneity dynamics and treatment responses, thus helping the improvement of personalized diagnostic and therapeutic strategies.

Modeling iPSC-derived human neurofibroma-like tumors in mice uncovers the heterogeneity of Schwann cells within plexiform neurofibromas

Plexiform neurofibromas (pNFs) are developmental tumors that appear in neurofibromatosis type 1 individuals, constituting a major source of morbidity and potentially transforming into a highly metastatic sarcoma (MPNST). pNFs arise after NF1 inactivation in a cell of the neural crest (NC)-Schwann cell (SC) lineage. Here, we develop an iPSC-based NC-SC in vitro differentiation system and construct a lineage expression roadmap for the analysis of different 2D and 3D NF models. The best model consists of generating heterotypic spheroids (neurofibromaspheres) composed of iPSC-derived differentiating NF1(-/-) SCs and NF1(+/-) pNF-derived fibroblasts (Fbs). Neurofibromaspheres form by maintaining highly proliferative NF1(-/-) cells committed to the NC-SC axis due to SC-SC and SC-Fb interactions, resulting in SC linage cells at different maturation points. Upon engraftment on the mouse sciatic nerve, neurofibromaspheres consistently generate human NF-like tumors. Analysis of expression roadmap genes in human pNF single-cell RNA-seq data uncovers the presence of SC subpopulations at distinct differentiation states.

Strategies for developing complex multi-component in vitro tumor models: Highlights in glioblastoma

In recent years, many research groups have begun to utilize bioengineered in vitro models of cancer to study mechanisms of disease progression, test drug candidates, and develop platforms to advance personalized drug treatment options. Due to advances in cell and tissue engineering over the last few decades, there are now a myriad of tools that can be used to create such in vitro systems. In this review, we describe the considerations one must take when developing model systems that accurately mimic the in vivo tumor microenvironment (TME) and can be used to answer specific scientific questions. We will summarize the importance of cell sourcing in models with one or multiple cell types and outline the importance of choosing biomaterials that accurately mimic the native extracellular matrix (ECM) of the tumor or tissue that is being modeled. We then provide examples of how these two components can be used in concert in a variety of model form factors and conclude by discussing how biofabrication techniques such as bioprinting and organ-on-a-chip fabrication can be used to create highly reproducible complex in vitro models. Since this topic has a broad range of applications, we use the final section of the review to dive deeper into one type of cancer, glioblastoma, to illustrate how these components come together to further our knowledge of cancer biology and move us closer to developing novel drugs and systems that improve patient outcomes.

Bacteriophages as Solid Tumor Theragnostic Agents

Cancer, especially the solid tumor sub-set, poses considerable challenges to modern medicine owing to the unique physiological characteristics and substantial variations in each tumor's microenvironmental niche fingerprints. Though there are many treatment methods available to treat solid tumors, still a considerable loss of life happens, due to the limitation of treatment options and the outcomes of ineffective treatments. Cancer cells evolve with chemo- or radiation-treatment strategies and later show adaptive behavior, leading to failed treatment. These challenges demand tailored and individually apt personalized treatment methods. Bacteriophages (or phages) and phage-based theragnostic vectors are gaining attention in the field of modern cancer medicine, beyond their bactericidal ability. With the invention of the latest techniques to fine-tune phages, such as in the field of genetic engineering, synthetic assembly methods, phage display, and chemical modifications, noteworthy progress in phage vector research for safe cancer application has been realized, including use in pre-clinical studies. Herein, we discuss the distinct fingerprints of solid tumor physiology and the potential for bacteriophage vectors to exploit specific tumor features for improvised tumor theragnostic applications.

Quantification of tumor heterogeneity: from data acquisition to metric generation

Tumors are unique and complex ecosystems, in which heterogeneous cell subpopulations with variable molecular profiles, aggressiveness, and proliferation potential coexist and interact. Understanding how heterogeneity influences tumor progression has important clinical implications for improving diagnosis, prognosis, and treatment response prediction. Several recent innovations in data acquisition methods and computational metrics have enabled the quantification of spatiotemporal heterogeneity across different scales of tumor organization. Here, we summarize the most promising efforts from a common experimental and computational perspective, discussing their advantages, shortcomings, and challenges. With personalized medicine entering a new era of unprecedented opportunities, our vision is that of future workflows integrating across modalities, scales, and dimensions to capture intricate aspects of the tumor ecosystem and to open new avenues for improved patient care.

High-Dimensional Single-Cell Transcriptomics in Melanoma and Cancer Immunotherapy

Recent advances in single-cell transcriptomics have greatly improved knowledge of complex transcriptional programs, rapidly expanding our knowledge of cellular phenotypes and functions within the tumour microenvironment and immune system. Several new single-cell technologies have been developed over recent years that have enabled expanded understanding of the mechanistic cells and biological pathways targeted by immunotherapies such as immune checkpoint inhibitors, which are now routinely used in patient management with high-risk early-stage or advanced melanoma. These technologies have method-specific strengths, weaknesses and capabilities which need to be considered when utilising them to answer translational research questions. Here, we provide guidance for the implementation of single-cell transcriptomic analysis platforms by reviewing the currently available experimental and analysis workflows. We then highlight the use of these technologies to dissect the tumour microenvironment in the context of cancer patients treated with immunotherapy. The strategic use of single-cell analytics in clinical settings are discussed and potential future opportunities are explored with a focus on their use to rationalise the design of novel immunotherapeutic drug therapies that will ultimately lead to improved cancer patient outcomes.

Weakly supervised learning on unannotated hematoxylin and eosin stained slides predicts BRAF mutation in thyroid cancer with high accuracy

Deep neural networks (DNNs) that predict mutational status from H&E slides of cancers can enable inexpensive and timely precision oncology. Although expert knowledge is reliable for annotating regions informative of malignancy and other known histological patterns (strong supervision), it is unreliable for identifying regions informative of mutational status. This poses a serious impediment to obtaining higher prognostic accuracy and discovering new knowledge of pathobiology. We used a weakly supervised learning technique to train a DNN to predict BRAF V600E mutational status, determined using DNA testing, in H&E stained images of thyroid cancer tissue without regional annotations. Our discovery cohort was a tissue microarray of only 85 patients from a single hospital. Yet, on a large independent external cohort of 444 patients from other hospitals, the trained model gave an AUC = 0.98 (95% CI: 0.97-1.00), which is much higher than the previously reported results for detecting any mutation using H&E by DNNs trained using strong supervision. We also developed a visualization technique that can automatically highlight regions the DNN found most informative for predicting mutational status. Our visualization is spatially granular and highly specific in highlighting regions with strong negative and positive regions and move us towards explainable artificial intelligence. Using t-tests, we confirmed that the proportions of follicular or papillary histology and oncocytic cytology, as noted for each patient by a pathologist who was blinded to the mutational status, were significantly different between mutated and wildtype patients. However, based solely on these features noted by the pathologist, a logistic regression classifier gave an average AUC = 0.78 in 5-fold CV, which is much lower than that obtained using the DNN. These results highlight the potential of weakly supervised learning for training DNN models for problems where the informative visual patterns and their locations are not known a priori. This article is protected by copyright. All rights reserved.

Mapping Spatial Genetic Landscapes in Tissue Sections through Microscale Integration of Sampling Methodology into Genomic Workflows

In cancer research, genomic profiles are often extracted from homogenized macrodissections of tissues, with the histological context lost and a large fraction of material underutilized. Pertinently, the spatial genomic landscape provides critical complementary information in deciphering disease heterogeneity and progression. Microscale sampling methods such as microdissection to obtain such information are often destructive to a sizeable fraction of the biopsy sample, thus showing limited multiplexability and adaptability to different assays. A modular microfluidic technology is here implemented to recover cells at the microscale from tumor tissue sections, with minimal disruption of unsampled areas and tailored to interface with genome profiling workflows, which is directed here toward evaluating intratumoral genomic heterogeneity. The integrated workflow-GeneScape-is used to evaluate heterogeneity in a metastatic mammary carcinoma, showing distinct single nucleotide variants and copy number variations in different tumor tissue regions, suggesting the polyclonal origin of the metastasis as well as development driven by multiple location-specific drivers.

Contributions of the distinct biophysical phenotype of polyploidal giant cancer cells to cancer progression

Polyploid giant cancer cells (PGCCs) are a commonly observed histological feature of human tumors and are particularly prominent in late stage and drug resistant cancers. The chromosomal duplication conferred by their aneuploidy gives rise to DNA damage resistance and complex tumor cell karyotypes, a driving factor in chemotherapy resistance and disease relapse. Furthermore, PGCCs also exhibit key cytoskeletal features that give rise to a distinct biophysical phenotype, including increased density of polymerized actin and vimentin intermediate filaments, nuclear and cytoskeletal stiffening, increased traction force, and migratory persistence. Despite recent research highlighting the role PGCCs play in cancer progression, this population of tumor cells remains poorly characterized in terms of their biophysical properties. In this review, we will discuss the various aspects of their biomolecular phenotype, such as increased stemness as well as a mixed EMT signature. These features have been extensively associated with tumorigenesis and recurrence, and aggressive cancers. Additionally, we will also examine the distinct PGCC cytoskeletal features of actin and filamentous vimentin. Specifically, how the differential organization of these networks serve to support their increased size and drive migratory persistence. These findings could shed light on potential therapeutic strategies that allow for specific elimination or mitigation of the invasive potential of these polyploid cancer cells. Lastly, we will examine how the biophysical and molecular phenotype of PGCCs combine to tip the scale in favor of promoting cancer progression, presenting an important target in the clinical treatment of cancer.

A Comparison of Methods for Studying the Tumor Microenvironment's Spatial Heterogeneity in Digital Pathology Specimens

Background:

The tumor microenvironment is highly heterogeneous, and it is understood to affect tumor progression and patient outcome. A number of studies have reported the prognostic significance of tumor-infiltrating lymphocytes and tumor budding in colorectal cancer (CRC). However, the significance of the intratumoral heterogeneity present in the spatial distribution of these features within the tumor immune microenvironment (TIME) has not been previously reported. Evaluating this intratumoral heterogeneity may aid the understanding of the TIME's effect on patient prognosis as well as identify novel aggressive phenotypes which can be further investigated as potential targets for new treatment.

Methods:

In this study, we propose and apply two spatial statistical methodologies for the evaluation of the intratumor heterogeneity present in the distribution of CD3 ⁺ and CD8 ⁺ lymphocytes and tumor buds (TB) in 232 Stage II CRC cases. Getis-Ord hotspot analysis was applied to quantify the cold and hotspots, defined as regions with a significantly low or high number of each feature of interest, respectively. A novel spatial heatmap methodology for the quantification of the cold and hotspots of each feature of interest, which took into account both the interpatient heterogeneity and the intratumor heterogeneity, was further developed.

Results:

Resultant data from each analysis, characterizing the spatial intratumor heterogeneity of lymphocytes and TBs were used for the development of two new highly prognostic risk models.

Conclusions:

Our results highlight the value of applying spatial statistics for the assessment of the intratumor heterogeneity. Both Getis-Ord hotspot and our proposed spatial heatmap analysis are broadly applicable across other tissue types as well as other features of interest.

Availability:

The code underpinning this publication can be accessed at https://doi.org/10.17630/c2306fe9-66e2-4442-ad89-f986220053e2.

The Era of Radiogenomics in Precision Medicine: An Emerging Approach to Support Diagnosis, Treatment Decisions, and Prognostication in Oncology

With the rapid development of new technologies, including artificial intelligence and genome sequencing, radiogenomics has emerged as a state-of-the-art science in the field of individualized medicine. Radiogenomics combines a large volume of quantitative data extracted from medical images with individual genomic phenotypes and constructs a prediction model through deep learning to stratify patients, guide therapeutic strategies, and evaluate clinical outcomes. Recent studies of various types of tumors demonstrate the predictive value of radiogenomics. And some of the issues in the radiogenomic analysis and the solutions from prior works are presented. Although the workflow criteria and international agreed guidelines for statistical methods need to be confirmed, radiogenomics represents a repeatable and cost-effective approach for the detection of continuous changes and is a promising surrogate for invasive interventions. Therefore, radiogenomics could facilitate computer-aided diagnosis, treatment, and prediction of the prognosis in patients with tumors in the routine clinical setting. Here, we summarize the integrated process of radiogenomics and introduce the crucial strategies and statistical algorithms involved in current studies.

Tumor heterogeneity in muscle-invasive bladder cancer

Muscle-invasive bladder cancer (MIBC), a highly heterogeneous disease, shows genomic instability and a high mutation rate. Clinical outcomes are variable and responses to conventional chemotherapy differ among patients (due to inter-patient tumor heterogeneity and inter-tumor heterogeneity) and even within each individual tumor (intra-tumor heterogeneity). Emerging evidence indicates that tumor heterogeneity may play an important role in cancer progression, resistance to therapy, and metastasis. Comprehensive molecular subtyping classifies MIBC into distinct categories that have potential to guide prognosis, patient stratification, and treatment. Genomic characterization of time-series analyses at the single cell level, and of cell-free circulating tumor DNA or circulating tumor cells, are emerging technologies that enable dissection of the complex clonal architecture of MIBC. This review provides insight into the clinical significance of the molecular mechanisms underlying heterogeneity, focusing on inter- and intra-tumor heterogeneity, with special emphasis on molecular classification and methods used to analyze the complex patterns involved.

If Artificial In Vitro Microenvironment Can Influence Tumor Drug Resistance Network via Modulation of lncRNA Expression?-Comparative Analysis of Glioblastoma-Derived Cell Culture Models and Initial Tumors In Vivo

The tumor resistance of glioblastoma cells in vivo is thought to be enhanced by their heterogeneity and plasticity, which are extremely difficult to curb in vitro. The external microenvironment shapes the molecular profile of tumor culture models, thus influencing potential therapy response. Our study examines the expression profile of selected lncRNAs involved in tumor resistance network in three different glioblastoma-derived models commonly utilized for testing drug response in vitro. Differential expression analysis revealed significant divergence in lncRNA profile between parental tumors and tumor-derived cell cultures in vitro, including the following particles: MALAT1, CASC2, H19, TUSC7, XIST, RP11-838N2.4, DLX6-AS1, GLIDR, MIR210HG, SOX2-OT. The examined lncRNAs influence the phenomenon of tumor resistance via their downstream target genes through a variety of processes: multi-drug resistance, epithelial-mesenchymal transition, autophagy, cell proliferation and viability, and DNA repair. A comparison of in vivo and in vitro expression identified differences in the levels of potential lncRNA targets, with the highest discrepancies detected for the MDR1, LRP1, BCRP and MRP1 genes. Co-expression analyses confirmed the following interrelations: MALAT1-TYMS, MALAT1-MRP5, H19-ZEB1, CASC2-VIM, CASC2-N-CAD; they additionally suggest the possibility of MALAT1-BCRP, MALAT1-mTOR and TUSC7-PTEN interconnections in glioblastoma. Although our results clearly demonstrate that the artificial ex vivo microenvironment changes the profile of lncRNAs related to tumor resistance, it is difficult to anticipate the final phenotypic effect, since this phenomenon is a complex one that involves a network of molecular interactions underlying a variety of cellular processes.

Preclinical Metrics Correlate With Drug Activity in Phase II Trials of Targeted Therapies for Non-Small Cell Lung Cancer

Novel oncology drugs often fail to progress from preclinical experiments to FDA approval. Therefore, determining which preclinical or clinical factors associate with drug activity could accelerate development of effective therapies. We investigated whether preclinical metrics and patient characteristics are associated with objective response rate (ORR) in phase II clinical trials of targeted therapies for non-small cell lung cancer (NSCLC). We developed a reproducible process to select a single phase II trial and supporting preclinical publication for a given drug-indication pair, which we defined as the pairing of a small molecule inhibitor (e.g., crizotinib) with the specific patient population for which it was designed to work (e.g., patients with an ALK aberration). We demonstrated that robust drug activity in mice, as measured by change in tumor size, is independently associated with improved ORR in phase II clinical trials. The number of mice utilized in experiments, the number of publications referencing the drug for NSCLC before the phase II clinical trial, and whether the drug was approved for a cancer other than NSCLC also significantly correlated with ORR. Among clinical characteristics, sex, race, histology, and smoking history were significantly associated with ORR. Further research into metrics that correlate with drug activity has the potential to optimize selection of novel therapies for clinical trials and enrich the drug development pipeline, particularly for patients with targetable genetic aberrations and rare cancers.

Value of volumetric and textural analysis in predicting the treatment response in patients with locally advanced rectal cancer

OBJECTIVE

The aim of this study was to assess the value of baseline 18F-FDG PET/CT in predicting the response to neoadjuvant chemo-radiotherapy (NCRT) in patients with locally advanced rectal cancer (LARC) via the volumetric and texture data obtained from 18F-FDG PET/CT images.

METHODS

 In total, 110 patients who had undergone NCRT after initial PET/CT and followed by surgical resection were included in this study. Patients were divided into two groups randomly as a train set (n: 88) and test set (n: 22). Pathological response using three-point tumor regression grade (TRG) and metastatic lymph nodes in PET/CT images were determined. TRG1 were accepted as responders and TRG2-3 as non-responders. Region of interest for the primary tumors was drawn and volumetric features (metabolic tumor volume (MTV) and total lesion glycolysis (TLG)) and texture features were calculated. In train set, the relationship between these features and TRG was investigated with Mann-Whitney U test. Receiver operating curve analysis was performed for features with p < 0.05. Correlation between features were evaluated with Spearman correlation test, features with correlation coefficient < 0.8 were evaluated with the logistic regression analysis for creating a model. The model obtained was tested with a test set that has not been used in modeling before.

RESULTS

 In train set 32 (36.4%) patients were responders. The rate of visually detected metastatic lymph node at baseline PET/CT was higher in non-responders than responders (71.4% and 46.9%, respectively, p = 0.022). There was a statistically significant difference between TLG, MTV, SHAPE_compacity, NGLDMcoarseness, GLRLM_GLNU, GLRLM_RLNU, GLZLM_LZHGE and GLZLM_GLNU between responders and non-responders. MTV and NGLDMcoarseness demonstrated the most significance (p = 0.011). A multivariate logistic regression analysis that included MTV, coarseness, GLZLM_LZHGE and lymph node metastasis was performed. Multivariate analysis demonstrated MTV and lymph node metastasis were the most meaningful parameters. The model's AUC was calculated as 0.714 (p = 0.001,0.606-0.822, 95% CI). In test set, AUC was determined 0.838 (p = 0.008,0.671-1.000, 95% CI) in discriminating non-responders.

CONCLUSIONS

Although there were points where textural features were found to be significant, multivariate analysis revealed no diagnostic superiority over MTV in predicting treatment response. In this study, it was thought higher MTV value and metastatic lymph nodes in PET/CT images could be a predictor of low treatment response in patients with LARC.

Integration of Multiple Platforms for the Analysis of Multifluorescent Marking Technology Applied to Pediatric GBM and DIPG

The intratumor heterogeneity represents one of the most difficult challenges for the development of effective therapies to treat pediatric glioblastoma (pGBM) and diffuse intrinsic pontine glioma (DIPG). These brain tumors are composed of heterogeneous cell subpopulations that coexist and cooperate to build a functional network responsible for their aggressive phenotype. Understanding the cellular and molecular mechanisms sustaining such network will be crucial for the identification of new therapeutic strategies. To study more in-depth these mechanisms, we sought to apply the Multifluorescent Marking Technology. We generated multifluorescent pGBM and DIPG bulk cell lines randomly expressing six different fluorescent proteins and from which we derived stable optical barcoded single cell-derived clones. In this study, we focused on the application of the Multifluorescent Marking Technology in 2D and 3D in vitro/ex vivo culture systems. We discuss how we integrated different multimodal fluorescence analysis platforms, identifying their strengths and limitations, to establish the tools that will enable further studies on the intratumor heterogeneity and interclonal interactions in pGBM and DIPG.

Multi-Cell Type Glioblastoma Tumor Spheroids for Evaluating Sub-Population-Specific Drug Response

Glioblastoma (GBM) is a lethal, incurable form of cancer in the brain. Even with maximally aggressive surgery and chemoradiotherapy, median patient survival is 14.5 months. These tumors infiltrate normal brain tissue, are surgically incurable, and universally recur. GBMs are characterized by genetic, epigenetic, and microenvironmental heterogeneity, and they evolve spontaneously over time and as a result of treatment. However, tracking such heterogeneity in real time in response to drug treatments has been impossible. Here we describe the development of an in vitro GBM tumor organoid model that is comprised of five distinct cellular subpopulations (4 GBM cell lines that represent GBM subpopulations and 1 astrocyte line), each fluorescently labeled with a different color. These multi-cell type GBM organoids are then embedded in a brain-like hyaluronic acid hydrogel for subsequent studies involving drug treatments and tracking of changes in relative numbers of each fluorescently unique subpopulation. This approach allows for the visual assessment of drug influence on individual subpopulations within GBM, and in future work can be expanded to supporting studies using patient tumor biospecimen-derived cells for personalized diagnostics.

Lipid Metabolism and Cancer Immunotherapy: Immunosuppressive Myeloid Cells at the Crossroad

Cancer progression generates a chronic inflammatory state that dramatically influences hematopoiesis, originating different subsets of immune cells that can exert pro- or anti-tumor roles. Commitment towards one of these opposing phenotypes is driven by inflammatory and metabolic stimuli derived from the tumor-microenvironment (TME). Current immunotherapy protocols are based on the reprogramming of both specific and innate immune responses, in order to boost the intrinsic anti-tumoral activity of both compartments. Growing pre-clinical and clinical evidence highlights the key role of metabolism as a major influence on both immune and clinical responses of cancer patients. Indeed, nutrient competition (i.e., amino acids, glucose, fatty acids) between proliferating cancer cells and immune cells, together with inflammatory mediators, drastically affect the functionality of innate and adaptive immune cells, as well as their functional cross-talk. This review discusses new advances on the complex interplay between cancer-related inflammation, myeloid cell differentiation and lipid metabolism, highlighting the therapeutic potential of metabolic interventions as modulators of anticancer immune responses and catalysts of anticancer immunotherapy.

NIR Photodynamic Destruction of PDAC and HNSCC Nodules Using Triple-Receptor-Targeted Photoimmuno-Nanoconjugates: Targeting Heterogeneity in Cancer

Receptor heterogeneity in cancer is a major limitation of molecular targeting for cancer therapeutics. Single-receptor-targeted treatment exerts selection pressures that result in treatment escape for low-receptor-expressing tumor subpopulations. To overcome this potential for heterogeneity-driven resistance to molecular targeted photodynamic therapy (PDT), we present for the first time a triple-receptor-targeted photoimmuno-nanoconjugate (TR-PIN) platform. TR-PIN functionalization with cetuximab, holo-transferrin, and trastuzumab conferred specificity for epidermal growth factor receptor (EGFR), transferrin receptor (TfR), and human epidermal growth factor receptor 2 (HER-2), respectively. The TR-PINs exhibited up to a 24-fold improvement in cancer cell binding compared with EGFR-specific cetuximab-targeted PINs (Cet-PINs) in low-EGFR-expressing cell lines. Photodestruction using TR-PINs was significantly higher than the monotargeted Cet-PINs in heterocellular 3D in vitro models of heterogeneous pancreatic ductal adenocarcinoma (PDAC; MIA PaCa-2 cells) and heterogeneous head and neck squamous cell carcinoma (HNSCC, SCC9 cells) containing low-EGFR-expressing T47D (high TfR) or SKOV-3 (high HER-2) cells. Through their capacity for multiple tumor target recognition, TR-PINs can serve as a unique and amenable platform for the effective photodynamic eradication of diverse tumor subpopulations in heterogeneous cancers to mitigate escape for more complete and durable treatment responses.

[Pt(O,O'-acac)(γ-acac)(DMS)]: Alternative Strategies to Overcome Cisplatin-Induced Side Effects and Resistance in T98G Glioma Cells

Cisplatin (CDDP) is one of the most effective chemotherapeutic agents, used for the treatment of diverse tumors, including neuroblastoma and glioblastoma. CDDP induces cell death through different apoptotic pathways. Despite its clinical benefits, CDDP causes several side effects and drug resistance.[Pt(O,O'-acac)(γ-acac)(DMS)], namely PtAcacDMS, a new platinum(II) complex containing two acetylacetonate (acac) and a dimethylsulphide (DMS) in the coordination sphere of metal, has been recently synthesized and showed 100 times higher cytotoxicity than CDDP. Additionally, PtAcacDMS was associated to a decreased neurotoxicity in developing rat central nervous system, also displaying great antitumor and antiangiogenic activity both in vivo and in vitro. Thus, based on the knowledge that several chemotherapeutics induce cancer cell death through an aberrant increase in [Ca²⁺]_i, in the present in vitro study we compared CDDP and PtAcacDMS effects on apoptosis and intracellular Ca²⁺ dynamics in human glioblastoma T98G cells, applying a battery of complementary techniques, i.e., flow cytometry, immunocytochemistry, electron microscopy, Western blotting, qRT-PCR, and epifluorescent Ca²⁺ imaging. The results confirmed that (i) platinum compounds may induce cell death through an aberrant increase in [Ca²⁺]_i and (ii) PtAcacDMS exerted stronger cytotoxic effect than CDDP, associated to a larger increase in resting [Ca²⁺]_i. These findings corroborate the use of PtAcacDMS as a promising approach to improve Pt-based chemotherapy against gliomas, either by inducing a chemosensitization or reducing chemoresistance in cell lineages resilient to CDDP treatment.

Radiosensitising Cancer Using Phosphatidylinositol-3-Kinase (PI3K), Protein Kinase B (AKT) or Mammalian Target of Rapamycin (mTOR) Inhibitors

Radiotherapy is routinely used as a neoadjuvant, adjuvant or palliative treatment in various cancers. There is significant variation in clinical response to radiotherapy with or without traditional chemotherapy. Patients with a good response to radiotherapy demonstrate better clinical outcomes universally across different cancers. The PI3K/AKT/mTOR pathway upregulation has been linked to radiotherapy resistance. We reviewed the current literature exploring the role of inhibiting targets along this pathway, in enhancing radiotherapy response. We identified several studies using in vitro cancer cell lines, in vivo tumour xenografts and a few Phase I/II clinical trials. Most of the current evidence in this area comes from glioblastoma multiforme, non-small cell lung cancer, head and neck cancer, colorectal cancer, and prostate cancer. The biological basis for radiosensitivity following pathway inhibition was through inhibited DNA double strand break repair, inhibited cell proliferation, enhanced apoptosis and autophagy as well as tumour microenvironment changes. Dual PI3K/mTOR inhibition consistently demonstrated radiosensitisation of all types of cancer cells. Single pathway component inhibitors and other inhibitor combinations yielded variable outcomes especially within early clinical trials. There is ample evidence from preclinical studies to suggest that direct pharmacological inhibition of the PI3K/AKT/mTOR pathway components can radiosensitise different types of cancer cells. We recommend that future in vitro and in vivo research in this field should focus on dual PI3K/mTOR inhibitors. Early clinical trials are needed to assess the feasibility and efficacy of these dual inhibitors in combination with radiotherapy in brain, lung, head and neck, breast, prostate and rectal cancer patients.

Cancer-Targeting Nanoparticles for Combinatorial Nucleic Acid Delivery

Nucleic acids are a promising type of therapeutic for the treatment of a wide range of conditions, including cancer, but they also pose many delivery challenges. For efficient and safe delivery to cancer cells, nucleic acids must generally be packaged into a vehicle, such as a nanoparticle, that will allow them to be taken up by the target cells and then released in the appropriate cellular compartment to function. As with other types of therapeutics, delivery vehicles for nucleic acids must also be designed to avoid unwanted side effects; thus, the ability of such carriers to target their cargo to cancer cells is crucial. Classes of nucleic acids, hurdles that must be overcome for effective intracellular delivery, types of nonviral nanomaterials used as delivery vehicles, and the different strategies that can be employed to target nucleic acid delivery specifically to tumor cells are discussed. Additonally, nanoparticle designs that facilitate multiplexed delivery of combinations of nucleic acids are reviewed.

Induction of Myogenic Differentiation Improves Chemosensitivity of Chemoresistant Cells in Soft-Tissue Sarcoma Cell Lines

Rhabdomyosarcoma (RMS) and rhabdoid tumors (RT) are rare soft-tissue malignancies with the highest incidence in infants, children, and adolescents. Advanced, recurrent, and/or metastatic RMS and RT exhibit poor response to treatment. One of the main mechanisms behind resistance to treatment is believed to be intratumoral heterogeneity. In this study, we investigated the myogenic determination factor 1 (MYOD1) and Noggin (NOG) markers in an embryonal RMS (ERMS) cell line and an RT cell line and the differential response of the MYOD1 and NOG expressing subpopulations to chemotherapy. Importantly, we found that these markers together identify a subpopulation of cells (MYOD1+ NOG+ cells) with primary resistance to Vincristine and Doxorubicin, two commonly used chemotherapies for ERMS and RT. The chemoresistant MYOD1+ NOG+ cells express markers of undifferentiated cells such as myogenin and ID1. Combination of Vincristine with TPA/GSK126, a drug combination shown to induce differentiation of RMS cell lines, is able to partially overcome MYOD1/NOG cells chemoresistance.

DNA damage response and resistance of cancer stem cells

The cancer stem cell (CSC) model defines tumors as hierarchically organized entities, containing a small population of tumorigenic CSC, or tumour-initiating cells, placed at the apex of this hierarchy. These cells may share common qualities with chemo- and radio-resistant cancer cells and contribute to self-renewal activities resulting in tumour formation, maintenance, growth and metastasis. Yet, it remains obscure what self-defense mechanisms are utilized by these cells against the chemotherapeutic drugs or radiotherapy. Recently, attention has been focused on the pivotal role of the DNA damage response (DDR) in tumorigenesis. In line with this note, an increased DDR that prevents CSC and chemoresistant cells from genotoxic pressure of chemotherapeutic drugs or radiation may be responsible for cancer metastasis. In this review, we focus on the current knowledge concerning the role of DDR in CSC and resistant cancer cells and describe the existing opportunities of re-sensitizing such cells to modulate therapeutic treatment effects.

Spatial heterogeneity of nanomedicine investigated by multiscale imaging of the drug, the nanoparticle and the tumour environment

Genetic and phenotypic tumour heterogeneity is an important cause of therapy resistance. Moreover, non-uniform spatial drug distribution in cancer treatment may cause pseudo-resistance, meaning that a treatment is ineffective because the drug does not reach its target at sufficient concentrations. Together with tumour heterogeneity, non-uniform drug distribution causes “therapy heterogeneity”: a spatially heterogeneous treatment effect. Spatial heterogeneity in drug distribution occurs on all scales ranging from interpatient differences to intratumour differences on tissue or cellular scale. Nanomedicine aims to improve the balance between efficacy and safety of drugs by targeting drug-loaded nanoparticles specifically to tumours. Spatial heterogeneity in nanoparticle and payload distribution could be an important factor that limits their efficacy in patients. Therefore, imaging spatial nanoparticle distribution and imaging the tumour environment giving rise to this distribution could help understand (lack of) clinical success of nanomedicine. Imaging the nanoparticle, drug and tumour environment can lead to improvements of new nanotherapies, increase understanding of underlying mechanisms of heterogeneous distribution, facilitate patient selection for nanotherapies and help assess the effect of treatments that aim to reduce heterogeneity in nanoparticle distribution.

In this review, we discuss three groups of imaging modalities applied in nanomedicine research: non-invasive clinical imaging methods (nuclear imaging, MRI, CT, ultrasound), optical imaging and mass spectrometry imaging. Because each imaging modality provides information at a different scale and has its own strengths and weaknesses, choosing wisely and combining modalities will lead to a wealth of information that will help bring nanomedicine forward.

Balancing STAT Activity as a Therapeutic Strategy

Driven by dysregulated IL-6 family member cytokine signaling in the tumor microenvironment (TME), aberrant signal transducer and activator of transcription (STAT3) and (STAT5) activation have been identified as key contributors to tumorigenesis. Following transformation, persistent STAT3 activation drives the emergence of mesenchymal/cancer-stem cell (CSC) properties, important determinants of metastatic potential and therapy failure. Moreover, STAT3 signaling within tumor-associated macrophages and neutrophils drives secretion of factors that facilitate metastasis and suppress immune cell function. Persistent STAT5 activation is responsible for cancer cell maintenance through suppression of apoptosis and tumor suppressor signaling. Furthermore, STAT5-mediated CD4+/CD25+ regulatory T cells (T_regs) have been implicated in suppression of immunosurveillance. We discuss these roles for STAT3 and STAT5, and weigh the attractiveness of different modes of targeting each cancer therapy. Moreover, we discuss how anti-tumorigenic STATs, including STAT1 and STAT2, may be leveraged to suppress the pro-tumorigenic functions of STAT3/STAT5 signaling.

The Complexities of Metastasis

Therapies that prevent metastatic dissemination and tumor growth in secondary organs are severely lacking. A better understanding of the mechanisms that drive metastasis will lead to improved therapies that increase patient survival. Within a tumor, cancer cells are equipped with different phenotypic and functional capacities that can impact their ability to complete the metastatic cascade. That phenotypic heterogeneity can be derived from a combination of factors, in which the genetic make-up, interaction with the environment, and ability of cells to adapt to evolving microenvironments and mechanical forces play a major role. In this review, we discuss the specific properties of those cancer cell subgroups and the mechanisms that confer or restrict their capacity to metastasize.

Multifocal primary neuroblastoma tumor heterogeneity in siblings with co-occurring PHOX2B and NF1 genetic aberrations

Neuroblastoma, the most common extracranial solid tumor of childhood, can present in multiple primary sites, but the extent of genetic heterogeneity among tumor foci, as well as the presence or absence of common oncogenic drivers, remains unknown. Although PHOX2B genetic aberrations can cause familial neuroblastoma, they demonstrate incomplete penetrance with respect to neuroblastoma pathogenesis, suggesting that additional undescribed oncogenic drivers are necessary for tumor development. We performed comprehensive molecular characterization of neuroblastoma tumors from two siblings affected by familial multifocal neuroblastoma, including whole exome sequencing and single-nucleotide polymorphism (SNP) arrays of tumor and matched blood samples. Data were processed and analyzed using established bioinformatics algorithms to evaluate for germline and somatic mutations and copy number variations (CNVs). We confirmed the presence of a PHOX2B deletion and NF1 mutation across all tumor samples and the germline genome. Matched tumor-blood whole exome sequencing also identified 365 genes that contained nonsilent coding mutations across all tumor samples, with no recurrent mutations across all tumors. SNP arrays also showed significant heterogeneity with respect to CNVs. The only common CNV across all tumors was 17q gain, with differing chromosomal coordinates across samples but a common region of overlap distal to 17q21.31, suggesting this adverse prognostic biomarker may offer insight about additional drivers for multifocal neuroblastoma in patients with germline PHOX2B or NF1 aberrations. Molecular characterization of all tumors from patients with multifocal primary neuroblastoma has potential to yield novel insights on neuroblastoma pathogenesis.

Impact of Molybdenum Compounds as Anticancer Agents

The aim of this mini review was to report the molybdenum compound intervention to control cancer disease. The intervention explains its roles and progress from inorganic molybdenum compounds via organomolybdenum complexes to its nanoparticles to control oesophageal cancer and breast cancer as case studies. Main contributions of molybdenum compounds as anticancer agents could be observed in their nanofibrous support with suitable physicochemical properties, combination therapy, and biosensors (biomarkers). Recent areas in anticancer drug design, which entail the uses of selected targets, were also surveyed and proposed.

Radiomic Machine Learning and Texture Analysis - New Horizons for Head and Neck Oncology

Radiomics is a relatively new concept that consists of extracting data from images and applies advanced characterization algorithms to generate imaging features. These features are biomarkers with prognostic and predictive value, which provide a characterization of tumor phenotypes in a non-invasive manner. The clinical application of radiomics is hampered by challenges such as lack of image acquisition and analysis standardization. Textural features extracted from computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography-computed tomography (PET-CT) images of patients diagnosed with head and neck cancers can be used in the pre-therapeutic evaluation of the response to multimodal chemo-radiotherapy. For patients with positive HPV-oropharyngeal cancers, the correlation of the radiomic textural features from the tumor with p16 values from the pathological sample can identify tumor specific signatures in CT imaging, an entity with favorable prognosis and a better response to chemo-radiotherapy. Pretreatment contrast CT-scans were extracted and radiomics analysis of gross tumor volume were performed using MaZda package apart from MaZda software containing B11 program for texture analysis and visualization. Data set was randomly divided into a training dataset and a test dataset and machine learning algorithms were applied to identify a textural radiomic signature. Radiomic texture analysis and machine learning algorithms demonstrate a predictive potential related to the capability of stratification for subclasses of platinum-chemotherapy resistance and radioresistant head and neck cancers requiring an intensification of multimodal treatment.

Integrating clinical, molecular, proteomic and histopathological data within the tissue context: tissunomics

Malignant tumours show a marked degree of morphological, molecular and proteomic heterogeneity. This variability is closely related to microenvironmental factors and the location of the tumour. The activation of genetic alterations is very tissue‐dependent and only few tumours have distinct genetic alterations. Importantly, the activation state of proteins and signaling factors is heterogeneous in the primary tumour and in metastases and recurrences. The molecular diagnosis based only on genetic alterations can lead to treatments with unpredictable responses, depending on the tumour location, such as the tumour response in melanomas versus colon carcinomas with BRAF mutations. Therefore, we understand that the correct evaluation of tumours requires a system that integrates both morphological, molecular and protein information in a clinical and pathological context, where intratumoral heterogeneity can be assessed. Thus, we propose the term ‘tissunomics’, where the diagnosis will be contextualised in each tumour based on the complementation of the pathological, molecular, protein expression, environmental cells and clinical data.

GSK3β regulates epithelial-mesenchymal transition and cancer stem cell properties in triple-negative breast cancer

Background

Triple-negative breast cancers (TNBCs), which lack receptors for estrogen, progesterone, and amplification of epidermal growth factor receptor 2, are highly aggressive. Consequently, patients diagnosed with TNBCs have reduced overall and disease-free survival rates compared to patients with other subtypes of breast cancer. TNBCs are characterized by the presence of cancer cells with mesenchymal properties, indicating that the epithelial to mesenchymal transition (EMT) plays a major role in the progression of this disease. The EMT program has also been implicated in chemoresistance, tumor recurrence, and induction of cancer stem cell (CSC) properties. Currently, there are no targeted therapies for TNBC, and hence, it is critical to identify the novel targets to treat TNBC.

Methods

A library of compounds was screened for their ability to inhibit EMT in cells with mesenchymal phenotype as assessed using the previously described Z-cad reporters. Of the several drugs tested, GSK3β inhibitors were identified as EMT inhibitors. The effects of GSK3β inhibitors on the properties of TNBC cells with a mesenchymal phenotype were assessed using qRT-PCR, flow cytometry, western blot, mammosphere, and migration and cell viability assays. Publicly available datasets also were analyzed to examine if the expression of GSK3β correlates with the overall survival of breast cancer patients.

Results

We identified a GSK3β inhibitor, BIO, in a drug screen as one of the most potent inhibitors of EMT. BIO and two other GSK3β inhibitors, TWS119 and LiCl, also decreased the expression of mesenchymal markers in several different cell lines with a mesenchymal phenotype. Further, inhibition of GSK3β reduced EMT-related migratory properties of cells with mesenchymal properties. To determine if GSK3β inhibitors target mesenchymal-like cells by affecting the CSC population, we employed mammosphere assays and profiled the stem cell-related cell surface marker CD44+/24− in cells after exposure to GSK3β inhibitors. We found that GSK3β inhibitors indeed decreased the CSC properties of cell types with mesenchymal properties. We treated cells with epithelial and mesenchymal properties with GSK3β inhibitors and found that GSK3β inhibitors selectively kill cells with mesenchymal attributes while sparing cells with epithelial properties. We analyzed patient data to identify genes predictive of poor clinical outcome that could serve as novel therapeutic targets for TNBC. The Wnt signaling pathway is critical to EMT, but among the various factors known to be involved in Wnt signaling, only the higher expression of GSK3β correlated with poorer overall patient survival.

Conclusions

Taken together, our data demonstrate that GSK3β is a potential target for TNBCs and suggest that GSK3β inhibitors could serve as selective inhibitors of EMT and CSC properties for the treatment of a subset of aggressive TNBC. GSK3β inhibitors should be tested for use in combination with standard-of-care drugs in preclinical TNBC models.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1125-0) contains supplementary material, which is available to authorized users.

Composition and Clinical Impact of the Immunologic Tumor Microenvironment in Oral Squamous Cell Carcinoma

Immunotherapy shows promising results and revolutionizes treatment of oral squamous cell carcinoma (OSCC). The immunologic microenvironment might have prognostic/predictive implications. Morphologic immunologic parameters (inflammatory infiltrate, stromal content, and budding activity [BA] [potentially indicating epithelial-mesenchymal transition]) were evaluated in 66 human primary therapy-naive OSCCs. Intraepithelial/stromal tumor-infiltrating lymphocytes (TILs; CD3⁺/CD4⁺/CD8⁺/CD4⁺FOXP3⁺/IL-17A⁺) were quantified, and ratios were calculated. HLA class I in tumor cells was evaluated immunohistochemically. mRNA in situ hybridization to detect IFN-γ was performed. Analysis was performed within invasive front (IF) and tumor center (TCe). Decreased HLA expression was associated with low TIL density, pronounced stromal content, and high BA; IFN-γ in TILs was correlated with high-density TILs; and IFN-γ in tumor cells was correlated with absence of BA (p < 0.05). Heterogeneity of parameters (TCe/IF) was rare. Low density of stromal CD4⁺FOXP3⁺ TILs within TCe and IF was identified as an independent prognostic factor for poor overall, disease-specific, and disease-free survival (p ≤ 0.011). Refining prognostication in OSCC with high-density CD4⁺FOXP3⁺ infiltrate within TCe and/or IF, high FOXP3:CD4 ratio was significantly correlated with favorable outcome in this subgroup. Furthermore, high-stromal CD8:CD4 ratio was found to be an independent favorable prognostic factor. In summary, immunologic parameters were closely intertwined. Morphologic correlates of epithelial-mesenchymal transition were associated with downregulation of HLA and decreased inflammation. Heterogeneity was infrequent. Low-density stromal CD4⁺FOXP3⁺ infiltrate within TCe and IF was an independent poor prognostic factor. Stratification of cases with high-density CD4⁺FOXP3⁺ TILs by FOXP3:CD4 ratio enables refinement of prognostication of this subgroup. CD8:CD4 ratio was identified as an independent prognostic factor.

Chemotherapeutic resistance: a nano-mechanical point of view

Chemotherapeutic resistance is one of the main obstacles for cancer remission. To understand how cancer cells acquire chemotherapeutic resistance, biochemical studies focusing on drug target alteration, altered cell proliferation, and reduced susceptibility to apoptosis were performed. Advances in nano-mechanobiology showed that the enhanced mechanical deformability of cancer cells accompanied by cytoskeletal alteration is a decisive factor for cancer development. Furthermore, atomic force microscopy (AFM)–based nano-mechanical studies showed that chemotherapeutic treatments reinforced the mechanical stiffness of drug-sensitive cancer cells. However, drug-resistant cancer cells did not show such mechanical responses following chemotherapeutic treatments. Interestingly, drug-resistant cancer cells are mechanically heterogeneous, with a subpopulation of resistant cells showing higher stiffness than their drug-sensitive counterparts. The signaling pathways involving Rho, vinculin, and myosin II were found to be responsible for these mechanical alterations in drug-resistant cancer cells. In the present review, we highlight the mechanical aspects of chemotherapeutic resistance, and suggest how mechanical studies can contribute to unravelling the multifaceted nature of chemotherapeutic resistance.

Circulating Cell-Free DNA and Colorectal Cancer: A Systematic Review

There is a strong demand for the identification of new biomarkers in colorectal cancer (CRC) diagnosis. Among all liquid biopsy analysts, cell-free circulating DNA (cfDNA) is probably the most promising tool with respect to the identification of minimal residual diseases, assessment of treatment response and prognosis, and identification of resistance mechanisms. Circulating cell-free tumor DNA (ctDNA) maintains the same genomic signatures that are present in the matching tumor tissue allowing for the quantitative and qualitative evaluation of mutation burdens in body fluids. Thus, ctDNA-based research represents a non-invasive method for cancer detection. Among the numerous possible applications, the diagnostic, predictive, and/or prognostic utility of ctDNA in CRC has attracted intense research during the last few years. In the present review, we will describe the different aspects related to cfDNA research and evidence from studies supporting its potential use in CRC diagnoses and the improvement of therapy efficacy. We believe that ctDNA-based research should be considered as key towards the introduction of personalized medicine and patient benefits.