Not only tumor but also therapy heterogeneity

Engineering Heterogeneous Tumor Models for Biomedical Applications

Tumor tissue engineering holds great promise for replicating the physiological and behavioral characteristics of tumors in vitro. Advances in this field have led to new opportunities for studying the tumor microenvironment and exploring potential anti-cancer therapeutics. However, the main obstacle to the widespread adoption of tumor models is the poor understanding and insufficient reconstruction of tumor heterogeneity. In this review, the current progress of engineering heterogeneous tumor models is discussed. First, the major components of tumor heterogeneity are summarized, which encompasses various signaling pathways, cell proliferations, and spatial configurations. Then, contemporary approaches are elucidated in tumor engineering that are guided by fundamental principles of tumor biology, and the potential of a bottom-up approach in tumor engineering is highlighted. Additionally, the characterization approaches and biomedical applications of tumor models are discussed, emphasizing the significant role of engineered tumor models in scientific research and clinical trials. Lastly, the challenges of heterogeneous tumor models in promoting oncology research and tumor therapy are described and key directions for future research are provided.

Identifying brain tumor patients' subtypes based on pre-diagnostic history and clinical characteristics: a pilot hierarchical clustering and association analysis

Introduction

Central nervous system (CNS) tumors are severe health conditions with increasing incidence in the last years. Different biological, environmental and clinical factors are thought to have an important role in their epidemiology, which however remains unclear.

Objective

The aim of this pilot study was to identify CNS tumor patients' subtypes based on this information and to test associations with tumor malignancy.

Methods

90 patients with suspected diagnosis of CNS tumor were recruited by the Neurosurgery Unit of IRCCS Neuromed. Patients underwent anamnestic and clinical assessment, to ascertain known or suspected risk factors including lifestyle, socioeconomic, clinical and psychometric characteristics. We applied a hierarchical clustering analysis to these exposures to identify potential groups of patients with a similar risk pattern and tested whether these clusters associated with brain tumor malignancy.

Results

Out of 67 patients with a confirmed CNS tumor diagnosis, we identified 28 non-malignant and 39 malignant tumor cases. These subtypes showed significant differences in terms of gender (with men more frequently presenting a diagnosis of cancer; p = 6.0 ×10-3) and yearly household income (with non-malignant tumor patients more frequently earning ≥25k Euros/year; p = 3.4×10-3). Cluster analysis revealed the presence of two clusters of patients: one (N=41) with more professionally active, educated, wealthier and healthier patients, and the other one with mostly retired and less healthy men, with a higher frequency of smokers, personal history of cardiovascular disease and cancer familiarity, a mostly sedentary lifestyle and generally lower income, education and cognitive performance. The former cluster showed a protective association with the malignancy of the disease, with a 74 (14-93) % reduction in the prevalent risk of CNS malignant tumors, compared to the other cluster (p=0.026).

Discussion

These preliminary data suggest that patients' profiling through unsupervised machine learning approaches may somehow help predicting the risk of being affected by a malignant form. If confirmed by further analyses in larger independent cohorts, these findings may be useful to create potential intelligent ranking systems for treatment priority, overcoming the lack of histopathological information and molecular diagnosis of the tumor, which are typically not available until the time of surgery.

Can Precision Oncology Benefit Patients With Cancers of Unknown Primary?

This editorial calls for a strategic shift in our approach to cancers of unknown primary (CUP), one that generates a comprehensive multidimensional portrait of cancer in patients with CUP, to model the biology at the individual level and identify the right therapeutic target accordingly. The framework of this approach is based on the integration of basic biology, biotechnologies, data sciences, clinical research, and social sciences.

SLC1A5 is a novel biomarker associated with ferroptosis and the tumor microenvironment: a pancancer analysis

Solute carrier family 1 member 5 (SLC1A5) is a member of the solute carrier (SLC) superfamily of transporters and plays an important role in tumors as a key transporter of glutamine into cells. However, the relationship between SLC1A5, which is involved in immune regulation, and immune cell infiltration in the tumor microenvironment has not been elucidated, and the relationship between SLC1A5 and ferroptosis is rarely reported. Therefore, we comprehensively analyzed the expression level of SLC1A5 across cancers and compared it with that in normal tissues. Then, the relationship between SLC1A5 expression and the tumor immune microenvironment was analyzed by single-cell analysis, gene set enrichment analysis (GSEA), and Tumor Immune Estimation Resource (TIMER). Next, the correlations of the SLC1A5 expression level with immunotherapy response, immunomodulator expression, tumor mutation burden (TMB) and microsatellite instability (MSI) were evaluated. Finally, in vitro experiments verified that SLC1A5 participates in ferroptosis of glioma cells to regulate tumor progression. Our results indicated that SLC1A5 is aberrantly expressed in most cancer types and closely associated with prognosis. The GSEA results showed that SLC1A5 is involved in immune activation processes and closely related to the infiltration levels of different immune cells in different cancer types. Upon further investigation, we found that SLC1A5 is a suppressor of ferroptosis in glioma, and SLC1A5 knockdown inhibited the proliferation and migration of glioma cells in vitro. In conclusion, we conducted a pancancer analysis of SLC1A5, demonstrated its role as a prognostic biomarker in cancer patients and explored its potential biological functions.

Organic Nanodelivery Systems as a New Platform in the Management of Breast Cancer: A Comprehensive Review from Preclinical to Clinical Studies

Breast cancer accounts for approximately 25% of cancer cases and 16.5% of cancer deaths in women, and the World Health Organization predicts that the number of new cases will increase by almost 70% over the next two decades, mainly due to an ageing population. Effective diagnostic and treatment strategies are, therefore, urgently required for improving cure rates among patients since current therapeutic modalities have many limitations and side effects. Nanomedicine is evolving as a promising approach for cancer management, including breast cancer, and various types of organic and inorganic nanomaterials have been investigated for their role in breast cancer diagnosis and treatment. Following an overview on breast cancer characteristics and pathogenesis and challenges of the current treatment strategies, the therapeutic potential of biocompatible organic-based nanoparticles such as liposomes and polymeric micelles that have been tested in breast cancer models are reviewed. The efficacies of different drug delivery and targeting strategies are documented, ranging from synthetic to cell-derived nanoformulations together with a summary of the interaction of nanoparticles with externally applied energy such as radiotherapy. The clinical translation of nanoformulations for breast cancer treatment is summarized including those undergoing clinical trials.

Liquid Biopsy for Oral Cancer Diagnosis: Recent Advances and Challenges

"Liquid biopsy" is an efficient diagnostic tool used to analyse biomaterials in human body fluids, such as blood, saliva, breast milk, and urine. Various biomaterials derived from a tumour and its microenvironment are released into such body fluids and contain important information for cancer diagnosis. Biomaterial detection can provide "real-time" information about individual tumours, is non-invasive, and is more repeatable than conventional histological analysis. Therefore, over the past two decades, liquid biopsy has been considered an attractive diagnostic tool for malignant tumours. Although biomarkers for oral cancer have not yet been adopted in clinical practice, many molecular candidates have been investigated for liquid biopsies in oral cancer diagnosis, such as the proteome, metabolome, microRNAome, extracellular vesicles, cell-free DNAs, and circulating tumour cells. This review will present recent advances and challenges in liquid biopsy for oral cancer diagnosis.

Capturing the spatial and temporal dynamics of tumor stroma for on-chip optimization of microenvironmental targeting nanomedicine

Malignant cells grow in a complex microenvironment that plays a key role in cancer progression. The "dynamic reciprocity" existing between cancer cells and their microenvironment is involved in cancer differentiation, proliferation, invasion, metastasis, and drug response. Therefore, understanding the molecular mechanisms underlying the crosstalk between cancer cells and their surrounding tissue (i.e., tumor stroma) and how this interplay affects the disease progression is fundamental to design and validate novel nanotherapeutic approaches. As an important regulator of tumor progression, metastasis and therapy resistance, the extracellular matrix of tumors, the acellular component of the tumor microenvironment, has been identified as very promising target of anticancer treatment, revolutionizing the traditional therapeutic paradigm that sees the neoplastic cells as the preferential objective to fight cancer. To design and to validate such a target therapy, advanced 3D preclinical models are necessary to correctly mimic the complex, dynamic and heterogeneous tumor microenvironment. In addition, the recent advancement in microfluidic technology allows fine-tuning and controlling microenvironmental parameters in tissue-on-chip devices in order to emulate the in vivo conditions. In this review, after a brief description of the origin of tumor microenvironment heterogeneity, some examples of nanomedicine approaches targeting the tumor microenvironment have been reported. Further, how advanced 3D bioengineered tumor models coupled with a microfluidic device can improve the design and testing of anti-cancer nanomedicine targeting the tumor microenvironment has been discussed. We highlight that the presence of a dynamic extracellular matrix, able to capture the spatiotemporal heterogeneity of tumor stroma, is an indispensable requisite for tumor-on-chip model and nanomedicine testing.

Deciphering Tumour Heterogeneity: From Tissue to Liquid Biopsy

Simple Summary

Most malignant tumours are highly heterogeneous at molecular and phenotypic levels. Tumour variability poses challenges for the management of patients, as it arises between patients and even evolves in space and time within a single patient. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of tumour diversity in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate tumour heterogeneity.

Abstract

Human solid malignancies harbour a heterogeneous set of cells with distinct genotypes and phenotypes. This heterogeneity is installed at multiple levels. A biological diversity is commonly observed between tumours from different patients (inter-tumour heterogeneity) and cannot be fully captured by the current consensus molecular classifications for specific cancers. To extend the complexity in cancer, there are substantial differences from cell to cell within an individual tumour (intra-tumour heterogeneity, ITH) and the features of cancer cells evolve in space and time. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity with an emphasis on ITH and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of ITH in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate ITH.

Percutaneous Microwave Coagulation Therapy: A Promising Therapeutic Method for Breaking the Barrier of the Intertumor Heterogeneity

Intertumor heterogeneity is common in various cancers and has been widely accepted as the primary cause of the diversity and variation of the effect of the same treatment on patients with the same type of tumor. Percutaneous microwave coagulation therapy (PMCT) is a minimally invasive and effective approach for destroying tumors by microwave beam under image guidance, which has been applied in lung cancer. However, no previous study has investigated the capability of PMCT solving intertumor heterogeneity. Here, we performed a component analysis of four lung cancer patients' tumor microenvironment (TME) via single-cell RNA sequencing (scRNA-seq) and treated all four cases with PMCT. One patient's TME could be classified into a hot tumor, mainly proinflammatory cytokines, and T cell infiltration. The other three patients' TMEs were cold tumors, where immunosuppressive cells occupied a large proportion, including tumor-associated macrophages and cancer cells. Despite a high level of heterogeneity among their tumor microenvironment compositions, disease type and stage, and basic physical conditions, all four patients presented a stable disease (SD) without any cancer cell detected in the TME of cancer tissues after PMCT. In conclusion, this report uniquely contributed to the knowledge of the PMCT adaptation to tumor heterogeneity. Therefore, PMCT is promising to demonstrate a stable and robust antitumor efficacy in unresectable lung cancers with various TMEs.

PEGylated recombinant human hyaluronidase (PEGPH20) pre-treatment improves intra-tumour distribution and efficacy of paclitaxel in preclinical models

BACKGROUND

Scarce drug penetration in solid tumours is one of the possible causes of the limited efficacy of chemotherapy and is related to the altered tumour microenvironment. The abnormal tumour extracellular matrix (ECM) together with abnormal blood and lymphatic vessels, reactive stroma and inflammation all affect the uptake, distribution and efficacy of anticancer drugs.

METHODS

We investigated the effect of PEGylated recombinant human hyaluronidase PH20 (PEGPH20) pre-treatment in degrading hyaluronan (hyaluronic acid; HA), one of the main components of the ECM, to improve the delivery of antitumor drugs and increase their therapeutic efficacy. The antitumor activity of paclitaxel (PTX) in HA synthase 3-overexpressing and wild-type SKOV3 ovarian cancer model and in the BxPC3 pancreas xenograft tumour model, was evaluated by monitoring tumour growth with or without PEGPH20 pre-treatment. Pharmacokinetics and tumour penetration of PTX were assessed by HPLC and mass spectrometry imaging analysis in the same tumour models. Tumour tissue architecture and HA deposition were analysed by histochemistry.

RESULTS

Pre-treatment with PEGPH20 modified tumour tissue architecture and improved the antitumor activity of paclitaxel in the SKOV3/HAS3 tumour model, favouring its accumulation and more homogeneous intra-tumour distribution, as assessed by quantitative and qualitative analysis. PEGPH20 also reduced HA content influencing, though less markedly, PTX distribution and antitumor activity in the BxPC3 tumour model.

CONCLUSION

Remodelling the stroma of HA-rich tumours by depletion of HA with PEGPH20 pre-treatment, is a potentially successful strategy to improve the intra-tumour distribution of anticancer drugs, increasing their therapeutic efficacy, without increasing toxicity.

Mitochondria and Endoplastic Reticulum Targeting Strategy for Enhanced Phototherapy

To ensure improved efficacy and minimized toxicity of therapeutic molecules, it is generally accepted that specifically delivering them to the subcellular site of their action will be attractive. Phototherapy has received considerable attention because of its noninvasiveness, high temporal-spatial resolution, and minimal drug resistance. As important functional organelles in cells, mitochondria and endoplasmic reticulum (ER) participate in fundamental cellular processes, which make them much more sensitive to reactive oxygen species (ROS) and hyperthermia. Thus, mitochondria- or ER-targeted phototherapy will be rational strategies for synergetic cancer therapy. In this review, we focus on the latest advances in molecules and nanomaterials currently used for mitochondria- and ER-targeted phototherapy.

Precision Oncology Beyond Genomics: The Future Is Here-It Is Just Not Evenly Distributed

Cancer is a multifactorial disease with increasing incidence. There are more than 100 different cancer types, defined by location, cell of origin, and genomic alterations that influence oncogenesis and therapeutic response. This heterogeneity between tumors of different patients and also the heterogeneity within the same patient's tumor pose an enormous challenge to cancer treatment. In this review, we explore tumor heterogeneity on the longitudinal and the latitudinal axis, reviewing current and future approaches to study this heterogeneity and their potential to support oncologists in tailoring a patient's treatment regimen. We highlight how the ideal of precision oncology is reaching far beyond the knowledge of genetic variants to inform clinical practice and discuss the technologies and strategies already available to improve our understanding and management of heterogeneity in cancer treatment. We will focus on integrating multi-omics technologies with suitable in vitro models and their proficiency in mimicking endogenous tumor heterogeneity.

Radiotheranostic Agent 64Cu-cyclam-RAFT-c(-RGDfK-)4 for Management of Peritoneal Metastasis in Ovarian Cancer

PURPOSE

Ovarian cancer peritoneal metastases (OCPMs) are a pathophysiologically heterogeneous group of tumors that are rarely curable. α_Vβ₃ integrin (α_Vβ₃) is overexpressed on tumoral neovessels and frequently on ovarian cancer cells. Here, using two clinically relevant α_Vβ₃-positive OCPM mouse models, we studied the theranostic potential of an α_Vβ₃-specific radiopeptide, ⁶⁴Cu-cyclam-RAFT-c(-RGDfK-)₄ (⁶⁴Cu-RaftRGD), and its intra- and intertumoral distribution in relation to the tumor microenvironment.

EXPERIMENTAL DESIGN

α_Vβ₃-expressing peritoneal and subcutaneous models of ovarian carcinoma (IGR-OV1 and NIH:OVCAR-3) were established in nude mice. ⁶⁴Cu-RaftRGD was administered either intravenously or intraperitoneally. We performed intratumoral distribution (ITD) studies, PET/CT imaging and quantification, biodistribution assay and radiation dosimetry, and therapeutic efficacy and toxicity studies.

RESULTS

Intraperitoneal administration was an efficient route for targeting ⁶⁴Cu-RaftRGD to OCPMs with excellent tumor penetration. Using the fluorescence surrogate, Cy5.5-RaftRGD, in our unique high-resolution multifluorescence analysis, we found that the ITD of ⁶⁴Cu-RaftRGD was spatially distinct from, but complementary to, that of hypoxia. ⁶⁴Cu-RaftRGD-based PET enabled clear visualization of multiple OCPM deposits and ascites and biodistribution analysis demonstrated an inverse correlation between tumor uptake and tumor size (1.2-17.2 mm). ⁶⁴Cu-RaftRGD at a radiotherapeutic dose (148 MBq/0.357 nmol) showed antitumor activities by inhibiting tumor cell proliferation and inducing apoptosis, with negligible toxicity.

CONCLUSIONS

Collectively, these results demonstrate the all-in-one potential of ⁶⁴Cu-RaftRGD for imaging guided radiotherapy of OCPM by targeting both tumoral neovessels and cancerous cells. On the basis of the ITD finding, we propose that pairing α_Vβ₃- and hypoxia-targeted radiotherapies could improve therapeutic efficacy by overcoming the heterogeneity of ITD encountered with single-agent treatments.

In Vivo Tumor Vascular Imaging with Light Emitting Diode-Based Photoacoustic Imaging System

Photoacoustic (PA) imaging has shown tremendous promise for imaging tumor vasculature and its function at deeper penetration depths without the use of exogenous contrast agents. Traditional PA imaging systems employ expensive and bulky class IV lasers with low pulse repetition rate, due to which its availability for preclinical cancer research is hampered. In this study, we evaluated the capability of a Light-Emitting Diode (LED)-based PA and ultrasound (US) imaging system for monitoring heterogeneous microvasculature in tumors (up to 10 mm in depth) and quantitatively compared the PA images with gold standard histology images. We used a combination of a 7 MHz linear array US transducer and 850 nm excitation wavelength LED arrays to image blood vessels in a subcutaneous tumor model. After imaging, the tumors were sectioned and stained for endothelial cells to correlate with PA images across similar cross-sections. Analysis of 30 regions of interest in tumors from different mice showed a statistically significant R-value of 0.84 where the areas with high blood vessel density had high PA response while low blood vessel density regions had low PA response. Our results confirm that LED-based PA and US imaging can provide 2D and 3D images of tumor vasculature and the potential it has as a valuable tool for preclinical cancer research.

Predicting Therapeutic Antibody Delivery into Human Head and Neck Cancers

PURPOSE

The efficacy of antibody-based therapeutics depends on successful drug delivery into solid tumors; therefore, there is a clinical need to measure intratumoral antibody distribution. This study aims to develop and validate an imaging and computation platform to directly quantify and predict antibody delivery into human head and neck cancers in a clinical study.

EXPERIMENTAL DESIGN

Twenty-four patients received systemic infusion of a near-infrared fluorescence-labeled therapeutic antibody followed by surgical tumor resection. A computational platform was developed to quantify the extent of heterogeneity of intratumoral antibody distribution. Both univariate and multivariate regression analyses were used to select the most predictive tumor biological factors for antibody delivery. Quantitative image features from the pretreatment MRI were extracted and correlated with fluorescence imaging of antibody delivery.

RESULTS

This study not only confirmed heterogeneous intratumoral antibody distribution in-line with many preclinical reports, but also quantified the extent of interpatient, intertumor, and intratumor heterogeneity of antibody delivery. This study demonstrated the strong predictive value of tumor size for intratumoral antibody accumulation and its significant impact on antibody distribution in both primary tumor and lymph node metastasis. Furthermore, this study established the feasibility of using contrast-enhanced MRI to predict antibody delivery.

CONCLUSIONS

This study provides a clinically translatable platform to measure antibody delivery into solid tumors and yields valuable insight into clinically relevant antibody tumor penetration, with implications in the selection of patients amenable to antibody therapy and the design of more effective dosing strategies.

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.

Overview on Clinical Relevance of Intra-Tumor Heterogeneity

Today, clinical evaluation of tumor heterogeneity is an emergent issue to improve clinical oncology. In particular, intra-tumor heterogeneity (ITH) is closely related to cancer progression, resistance to therapy, and recurrences. It is interconnected with complex molecular mechanisms including spatial and temporal phenomena, which are often peculiar for every single patient. This review tries to describe all the types of ITH including morphohistological ITH, and at the molecular level clonal ITH derived from genomic instability and nonclonal ITH derived from microenvironment interaction. It is important to consider the different types of ITH as a whole for any patient to investigate on cancer progression, prognosis, and treatment opportunities. From a practical point of view, analytical methods that are widely accessible today, or will be in the near future, are evaluated to investigate the complex pattern of ITH in a reproducible way for a clinical application.