Targeting the Temporal Dynamics of Hypoxia-Induced Tumor-Secreted Factors Halts Tumor Migration

The relevance between hypoxia-dependent spatial transcriptomics and the prognosis and efficacy of immunotherapy in claudin-low breast cancer

Introduction

Hypoxia is an important characteristic of solid tumors. However, spatial transcriptomics (ST) of hypoxia-associated heterogeneity is not clear.

Methods

This study integrated Spatial Transcriptomics (ST) with immunofluorescence to demonstrate their spatial distribution in human claudin-low breast cancer MDA-MB-231 engraft. ST spots were clustered with differentially expression genes. The data were combined with hypoxia-specific marker and angiogenesis marker-labeled serial sections to indicate the spatial distribution of hypoxia and hypoxia-inducted transcriptional profile. Moreover, marker genes, cluster-specific hypoxia genes, and their co-essential relationship were identified and mapped in every clusters. The clinicopathological association of marker genes of hypoxia-dependent spatial clusters was explored in 1904 breast cancers from METABRIC database.

Results

The tumor from center to periphery were enriched into five hypoxia-dependent subgroups with differentially expressed genes, which were matched to necrosis, necrosis periphery, hypoxic tumor, adaptive survival tumor, and invasive tumor, respectively. Different subgroups demonstrated distinct hypoxia condition and spatial heterogeneity in biological behavior and signaling pathways. Cox regression analysis showed that the invasive tumor (cluster 0) and hypoxic tumor (cluster 6) score could be served as independent prognostic factors in claudin-low patients. KM analysis indicated that high invasive tumor (cluster 0) and hypoxic tumor (cluster 6) score was associated with poor prognoses of claudin-low patients. Further analysis showed that hypoxia-induced immune checkpoints, such as CD276 and NRP1, upregulation in invasive tumor to block infiltration and activation of B cells and CD8+ T cells to change tumor immune microenvironment.

Discussion

This study reveals hypoxia-dependent spatial heterogeneity in claudin-low breast cancer and highlights its potential value as a predictive biomarker of clinical outcomes and immunotherapy response. The molecules found in this study also provided potential molecular mechanisms and therapeutic targets for subsequent studies.

Optimization on the dose and time of nicaraven administration for mitigating the side effects of radiotherapy in a preclinical tumor-bearing mouse model

OBJECTIVE

Radiation-induced lung injury (RILI) is one of the serious complications of radiotherapy. We have recently demonstrated that nicaraven can effectively mitigate RILI in healthy mice. Here, we further tried to optimize the dose and time of nicaraven administration for alleviating the side effects of radiotherapy in tumor-bearing mice.

METHODS AND RESULTS

A subcutaneous tumor model was established in the back of the chest in C57BL/6N mice by injecting Lewis lung cancer cells. Therapeutic thoracic irradiations were done, and placebo or different doses of nicaraven (20, 50, 100 mg/kg) were administrated intraperitoneally pre-irradiation (at almost 5-10 min before irradiation) or post-irradiation (within 5 min after irradiation). Mice that received radiotherapy and nicaraven were sacrificed on the 30th day, but control mice were sacrificed on the 15th day. Serum and lung tissues were collected for evaluation. Nicaraven significantly decreased the level of CCL8, but did not clearly change the levels of 8-OHdG, TGF-β, IL-1β, and IL-6 in serum. Besides these, nicaraven effectively decreased the levels of TGF-β, IL-1β, and SOD2 in the lungs, especially by post-irradiation administration with the dose of 20 mg/kg. Although there was no significant difference, the expression of SOD1, 53BP1, and caspase 3 was detected lower in the lungs of mice received nicaraven post-irradiation than that of pre-irradiation.

CONCLUSION

According to our data, the administration of nicaraven at a relatively low dose soon after radiotherapy will be recommended for attenuating the side effects of radiotherapy.

P4HA2: A link between tumor-intrinsic hypoxia, partial EMT and collective migration

Epithelial-to-mesenchymal transition (EMT), a well-established phenomenon studied across pan-cancer types, has long been known to be a major player in driving tumor invasion and metastasis. Recent studies have highlighted the importance of partial EMT phenotypes in metastasis. Initially thought as a transitional state between epithelial and mesenchymal phenotypic states, partial EMT state is now widely recognized as a key driver of intra-tumoral heterogeneity and phenotypic plasticity, further accelerating tumor metastasis and therapeutic resistance. However, how tumor microenvironment regulates partial EMT phenotypes remains unclear. We have developed unique size-controlled three-dimensional microtumor models that recapitulate tumor-intrinsic hypoxia and the emergence of collectively migrating cells. In this study, we further interrogate these microtumor models to understand how tumor-intrinsic hypoxia regulates partial EMT and collective migration in hypoxic large microtumors fabricated from T47D breast cancer cells. We compared global gene expression profiles of hypoxic, migratory microtumors to that of non-hypoxic, non-migratory microtumors at early and late time-points. Using our microtumor models, we identified unique gene signatures for tumor-intrinsic hypoxia (early versus late), partial EMT and migration (pre-migratory versus migratory phenotype). Through differential gene expression analysis between the microtumor models with an overlap of hypoxia, partial EMT and migration signatures, we identified prolyl 4-hydroxylase subunit 2 (P4HA2), a hypoxia responsive gene, as a central regulator common to hypoxia, partial EMT and collective migration. Further, the inhibition of P4HA2 significantly blocked collective migration in hypoxic microtumors. Thus, using the integrated computational-experimental analysis, we identify the key role of P4HA2 in tumor-intrinsic hypoxia-driven partial EMT and collective migration.

In vitrobreast cancer model with patient-specific morphological features for personalized medicine

In vitro cancer models that can simulate patient-specific drug responses for personalized medicine have attracted significant attention. However, the technologies used to produce such models can only recapitulate the morphological heterogeneity of human cancer tissue. Here, we developed a novel 3D technique to bioprint an in vitro breast cancer model with patient-specific morphological features. This model can precisely mimic the cellular microstructures of heterogeneous cancer tissues and produce drug responses similar to those of human cancers. We established a bioprinting process for generating cancer cell aggregates with ductal and solid tissue microstructures that reflected the morphology of breast cancer tissues, and applied it to develop breast cancer models. The genotypic and phenotypic characteristics of the ductal and solid cancer aggregates bioprinted with human breast cancer cells (MCF7, SKBR3, MDA-MB-231) were respectively similar to those of early and advanced cancers. The bioprinted solid cancer cell aggregates showed significantly higher hypoxia (>8 times) and mesenchymal (>2-4 times) marker expressions, invasion activity (>15 times), and drug resistance than the bioprinted ductal aggregates. Co-printing the ductal and solid aggregates produced heterogeneous breast cancer tissue models that recapitulated three different stages of breast cancer tissue morphology. The bioprinted cancer tissue models representing advanced cancer were more and less resistant, respectively, to the anthracycline antibiotic doxorubicin and the hypoxia-activated prodrug tirapazamine; these were analogous to the results in human cancer. The present findings showed that cancer cell aggregates can mimic the pathological micromorphology of human breast cancer tissue and they can be bioprinted to produce breast cancer tissue in vitro that can morphologically represent the clinical stage of cancer in individual patients.

Regulation of epithelial-to-mesenchymal transition in hypoxia by the HIF-1α network

Epithelial-to-mesenchymal transition (EMT) plays a significant role in cancer metastasis. A series of models have focused on EMT regulation by TGF-β network. However, how EMT is regulated under hypoxia is less understood. We developed a model of HIF-1α network to explore the potential link between EMT and the network topology. Our results revealed that three positive feedback loops, composed of HIF-1α and its three targets SNAIL, TWIST, and miR-210, should be sequentially activated to induce EMT under aggravating hypoxia. We suggested that the number of the positive feedback loops is critical for determining the number of stable states in EMT. Our work may advance the understanding of the significance of network topology in the regulation of EMT.

Identifying Molecular Signatures of Distinct Modes of Collective Migration in Response to the Microenvironment Using Three-Dimensional Breast Cancer Models

Simple Summary

The objective of this study was to investigate the role of two microenvironmental factors, namely, tumor-intrinsic hypoxia and secretome in inducing collective migration. We utilized three-dimensional (3D) discrete-sized microtumor models, which recapitulate hallmarks of transition of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC). Tumor-intrinsic hypoxia induced directional migration in large hypoxic microtumors while secretome from large microtumors induced radial migration in non-hypoxic microtumors. This highlights the emergence phenotypic heterogeneity and plasticity in cancer cells in response to different microenvironmental stimuli. To unravel mechanisms underlying these two distinct modes of migration, we performed differential gene expression analysis of hypoxia- and secretome-induced migratory phenotypes using non-migratory, non-hypoxic microtumors as controls. We proposed unique gene signature sets related to tumor-intrinsic hypoxia, hypoxia-induced epithelial-mesenchymal transition (EMT), as well as hypoxia-induced directional migration and secretome-induced radial migration.

Abstract

Collective cell migration is a key feature of transition of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) among many other cancers, yet the microenvironmental factors and underlying mechanisms that trigger collective migration remain poorly understood. Here, we investigated two microenvironmental factors, tumor-intrinsic hypoxia and tumor-secreted factors (secretome), as triggers of collective migration using three-dimensional (3D) discrete-sized microtumor models that recapitulate hallmarks of DCIS-IDC transition. Interestingly, the two factors induced two distinct modes of collective migration: directional and radial migration in the 3D microtumors generated from the same breast cancer cell line model, T47D. Without external stimulus, large (600 µm) T47D microtumors exhibited tumor-intrinsic hypoxia and directional migration, while small (150 µm), non-hypoxic microtumors exhibited radial migration only when exposed to the secretome of large microtumors. To investigate the mechanisms underlying hypoxia- and secretome-induced directional vs. radial migration modes, we performed differential gene expression analysis of hypoxia- and secretome-induced migratory microtumors compared with non-hypoxic, non-migratory small microtumors as controls. We propose unique gene signature sets related to tumor-intrinsic hypoxia, hypoxia-induced epithelial-mesenchymal transition (EMT), as well as hypoxia-induced directional migration and secretome-induced radial migration. Gene Set Enrichment Analysis (GSEA) and protein-protein interaction (PPI) network analysis revealed enrichment and potential interaction between hypoxia, EMT, and migration gene signatures for the hypoxia-induced directional migration. In contrast, hypoxia and EMT were not enriched in the secretome-induced radial migration, suggesting that complete EMT may not be required for radial migration. Survival analysis identified unique genes associated with low survival rate and poor prognosis in TCGA-breast invasive carcinoma dataset from our tumor-intrinsic hypoxia gene signature (CXCR4, FOXO3, LDH, NDRG1), hypoxia-induced EMT gene signature (EFEMP2, MGP), and directional migration gene signature (MAP3K3, PI3K3R3). NOS3 was common between hypoxia and migration gene signature. Survival analysis from secretome-induced radial migration identified ATM, KCNMA1 (hypoxia gene signature), and KLF4, IFITM1, EFNA1, TGFBR1 (migration gene signature) to be associated with poor survival rate. In conclusion, our unique 3D cultures with controlled microenvironments respond to different microenvironmental factors, tumor-intrinsic hypoxia, and secretome by adopting distinct collective migration modes and their gene expression analysis highlights the phenotypic heterogeneity and plasticity of epithelial cancer cells.

Knowledge-Guided "Community Network" Analysis Reveals the Functional Modules and Candidate Targets in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies that are the leading cause of cancer-related death worldwide. Although many NSCLC-related genes and pathways have been identified, there remains an urgent need to mechanistically understand how these genes and pathways drive NSCLC. Here, we propose a knowledge-guided and network-based integration method, called the node and edge Prioritization-based Community Analysis, to identify functional modules and their candidate targets in NSCLC. The protein–protein interaction network was prioritized by performing a random walk with restart algorithm based on NSCLC seed genes and the integrating edge weights, and then a “community network” was constructed by combining Girvan–Newman and Label Propagation algorithms. This systems biology analysis revealed that the CCNB1-mediated network in the largest community provides a modular biomarker, the second community serves as a drug regulatory module, and the two are connected by some contextual signaling motifs. Moreover, integrating structural information into the signaling network suggested novel protein–protein interactions with therapeutic significance, such as interactions between GNG11 and CXCR2, CXCL3, and PPBP. This study provides new mechanistic insights into the landscape of cellular functions in the context of modular networks and will help in developing therapeutic targets for NSCLC.

Interplay between tumor microenvironment and partial EMT as the driver of tumor progression

Epithelial-to-mesenchymal transition (EMT), an evolutionary conserved phenomenon, has been extensively studied to address the unresolved variable treatment response across therapeutic regimes in cancer subtypes. EMT has long been envisaged to regulate tumor invasion, migration, and therapeutic resistance during tumorigenesis. However, recently it has been highlighted that EMT involves an intermediate partial EMT (pEMT) phenotype, defined by incomplete loss of epithelial markers and incomplete gain of mesenchymal markers. It has been further emphasized that pEMT transition involves a spectrum of intermediate hybrid states on either side of pEMT spectrum. Emerging evidence underlines bi-directional crosstalk between tumor cells and surrounding microenvironment in acquisition of pEMT phenotype. Although much work is still ongoing to gain mechanistic insights into regulation of pEMT phenotype, it is evident that pEMT plays a critical role in tumor aggressiveness, invasion, migration, and metastasis along with therapeutic resistance. In this review, we focus on important role of tumor-intrinsic factors and tumor microenvironment in driving pEMT and emphasize that engineered controlled microenvironments are instrumental to provide mechanistic insights into pEMT biology. We also discuss the significance of pEMT in regulating hallmarks of tumor progression i.e. cell cycle regulation, collective migration, and therapeutic resistance. Although constantly evolving, current progress and momentum in the pEMT field holds promise to unravel new therapeutic targets to halt tumor progression at early stages as well as tackle the complex therapeutic resistance observed across many cancer types.

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Partial EMT phenotype drives key hallmarks of tumor progression

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Role of tumor microenvironment in pEMT phenotype via cellular signaling pathways

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Engineering 3D in vitro models to study pEMT phenotype

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Opportunities and challenges in understanding pEMT phenotype

Hybrid-cell membrane-coated nanocomplex-loaded chikusetsusaponin IVa methyl ester for a combinational therapy against breast cancer assisted by Ce6

Hybrid-cell membrane coating nanocomplexes loading chikusetsusaponin IVa methyl ester for combinational therapy against breast cancer assisted with Ce6.

Hypoxia, partial EMT and collective migration: Emerging culprits in metastasis

Epithelial-mesenchymal transition (EMT) is a cellular biological process involved in migration of primary cancer cells to secondary sites facilitating metastasis. Besides, EMT also confers properties such as stemness, drug resistance and immune evasion which can aid a successful colonization at the distant site. EMT is not a binary process; recent evidence suggests that cells in partial EMT or hybrid E/M phenotype(s) can have enhanced stemness and drug resistance as compared to those undergoing a complete EMT. Moreover, partial EMT enables collective migration of cells as clusters of circulating tumor cells or emboli, further endorsing that cells in hybrid E/M phenotypes may be the 'fittest' for metastasis. Here, we review mechanisms and implications of hybrid E/M phenotypes, including their reported association with hypoxia. Hypoxia-driven activation of HIF-1α can drive EMT. In addition, cyclic hypoxia, as compared to acute or chronic hypoxia, shows the highest levels of active HIF-1α and can augment cancer aggressiveness to a greater extent, including enriching for a partial EMT phenotype. We also discuss how metastasis is influenced by hypoxia, partial EMT and collective cell migration, and call for a better understanding of interconnections among these mechanisms. We discuss the known regulators of hypoxia, hybrid EMT and collective cell migration and highlight the gaps which needs to be filled for connecting these three axes which will increase our understanding of dynamics of metastasis and help control it more effectively.

Three dimensional engineered models to study hypoxia biology in breast cancer

Breast cancer is the second leading cause of mortality among women worldwide. Despite the available therapeutic regimes, variable treatment response is reported among different breast cancer subtypes. Recently, the effects of the tumor microenvironment on tumor progression as well as treatment responses have been widely recognized. Hypoxia and hypoxia inducible factors in the tumor microenvironment have long been known as major players in tumor progression and survival. However, the majority of our understanding of hypoxia biology has been derived from two dimensional (2D) models. Although many hypoxia-targeted therapies have elicited promising results in vitro and in vivo, these results have not been successfully translated into clinical trials. These limitations of 2D models underscore the need to develop and integrate three dimensional (3D) models that recapitulate the complex tumor-stroma interactions in vivo. This review summarizes role of hypoxia in various hallmarks of cancer progression. We then compare traditional 2D experimental systems with novel 3D tissue-engineered models giving accounts of different bioengineering platforms available to develop 3D models and how these 3D models are being exploited to understand the role of hypoxia in breast cancer progression.

Orchestration of lincRNA-p21 and miR-155 in Modulating the Adaptive Dynamics of HIF-1α

Hypoxia-inducible factor-1 (HIF-1) is the key regulator of cellular adaptive response to hypoxia. Accumulating evidence shows that HIF-1 induces some non-coding RNAs (ncRNAs) including lncRNAs and miRNAs to modulate its own activity, enclosing several feedback loops. How the two classes of ncRNAs are orchestrated in the HIF-1-dependent adaptive response to hypoxia is poorly understood. By selecting lincRNA-p21 and miR-155 as the representatives, we develop an integrated model of the HIF-1 network comprising interlinked positive and negative feedback loops to clarify the interplay between the two ncRNAs in the hypoxic response. By numerical simulations, we find that coordination of lincRNA-p21 and miR-155 shapes the adaptive dynamics of HIF-1α: lincRNA-p21 induction in the early phase stimulates the upregulation of HIF-1α via stabilizing it, while miR-155 induction in the late phase promotes the recovery of HIF-1α via enhancing the degradation of its mRNA. Moreover, HIF-1α-induced PHD2 plays an auxiliary role in the decline of HIF-1α. In addition, lincRNA-p21 and miR-155 modulate each other via regulating HIF-1α activity. Together, lincRNA-p21 and miR-155 coordinate in modulating HIF-1α dynamics, and our work may shed light on the role for ncRNAs in the cellular adaptation to hypoxia.

Modeling HIV-1 neuropathogenesis using three-dimensional human brain organoids (hBORGs) with HIV-1 infected microglia

HIV-1 associated neurocognitive disorder (HAND) is characterized by neuroinflammation and glial activation that, together with the release of viral proteins, trigger a pathogenic cascade resulting in synaptodendritic damage and neurodegeneration that lead to cognitive impairment. However, the molecular events underlying HIV neuropathogenesis remain elusive, mainly due to lack of brain-representative experimental systems to study HIV-CNS pathology. To fill this gap, we developed a three-dimensional (3D) human brain organoid (hBORG) model containing major cell types important for HIV-1 neuropathogenesis; neurons and astrocytes along with incorporation of HIV-infected microglia. Both infected and uninfected microglia infiltrated into hBORGs resulting in a triculture system (MG-hBORG) that mirrors the multicellular network observed in HIV-infected human brain. Moreover, the MG-hBORG model supported productive viral infection and exhibited increased inflammatory response by HIV-infected MG-hBORGs, releasing tumor necrosis factor (TNF-α) and interleukin-1 (IL-1β) and thereby mimicking the chronic neuroinflammatory environment observed in HIV-infected individuals. This model offers great promise for basic understanding of how HIV-1 infection alters the CNS compartment and induces pathological changes, paving the way for discovery of biomarkers and new therapeutic targets.