MDA-9/Syntenin in the tumor and microenvironment defines prostate cancer bone metastasis.

Bone metastasis is a frequent and incurable consequence of advanced prostate cancer (PC). An interplay between disseminated tumor cells and heterogeneous bone resident cells in the metastatic niche initiates this process. Melanoma differentiation associated gene-9 (mda-9/Syntenin/syndecan binding protein) is a prometastatic gene expressed in multiple organs, including bone marrow-derived mesenchymal stromal cells (BM-MSCs), under both physiological and pathological conditions. We demonstrate that PDGF-AA secreted by tumor cells induces CXCL5 expression in BM-MSCs by suppressing MDA-9-dependent YAP/MST signaling. CXCL5-derived tumor cell proliferation and immune suppression are consequences of the MDA-9/CXCL5 signaling axis, promoting PC disease progression. mda-9 knockout tumor cells express less PDGF-AA and do not develop bone metastases. Our data document a previously undefined role of MDA-9/Syntenin in the tumor and microenvironment in regulating PC bone metastasis. This study provides a framework for translational strategies to ameliorate health complications and morbidity associated with advanced PC.

Cytoplasmic-delivery of polyinosine-polycytidylic acid inhibits pancreatic cancer progression increasing survival by activating Stat1-CCL2-mediated immunity.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer without effective therapies and with poor prognosis, causing 7% of all cancer-related fatalities in the USA. Considering the lack of effective therapies for this aggressive cancer, there is an urgent need to define newer and more effective therapeutic strategies. Polyinosine-polycytidylic acid (pIC) is a synthetic double-stranded RNA (dsRNA) which directly activates dendritic cells and natural killer cells inhibiting tumor growth. When pIC is delivered into the cytoplasm using polyethyleneimine (PEI), pIC-PEI, programmed-cell death is induced in PDAC. Transfection of [pIC]PEI into PDAC cells inhibits growth, promotes toxic autophagy and also induces apoptosis in vitro and in vivo in animal models. METHODS: The KPC transgenic mouse model that recapitulates PDAC development in patients was used to interrogate the role of an intact immune system in vivo in PDAC in response to [pIC]PEI. Antitumor efficacy and survival were monitored endpoints. Comprehensive analysis of the tumor microenvironment (TME) and immune cells, cytokines and chemokines in the spleen, and macrophage polarization were analyzed. RESULTS: Cytosolic delivery of [pIC]PEI induces apoptosis and provokes strong antitumor immunity in vivo in immune competent mice with PDAC. The mechanism underlying the immune stimulatory properties of [pIC]PEI involves Stat1 activation resulting in CCL2 and MMP13 stimulation thereby provoking macrophage polarization. [pIC]PEI induces apoptosis via the AKT-XIAP pathway, as well as macrophage differentiation and T-cell activation via the IFNγ-Stat1-CCL2 signaling pathways in PDAC. In transgenic tumor mouse models, [pIC]PEI promotes robust and profound antitumor activity implying that stimulating the immune system contributes to biological activity. The [pIC]PEI anti-PDAC effects are enhanced when used in combination with a standard of care (SOC) treatment, that is, gemcitabine. CONCLUSIONS: In summary, [pIC]PEI treatment is non-toxic toward normal pancreatic cells while displaying strong cytotoxic and potent immune activating activities in PDAC, making it an attractive therapeutic when used alone or in conjunction with SOC therapeutic agents, potentially providing a safe and effective treatment protocol with translational potential for the effective therapy of PDAC.

CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data.

Cells have evolved their communication methods to sense their microenvironments and send biological signals. In addition to communication using ligands and receptors, cells use diverse channels including gap junctions to communicate with their immediate neighbors. Current approaches, however, cannot effectively capture the influence of various microenvironments. Here, we propose a novel approach to investigate cell neighbor-dependent gene expression (CellNeighborEX) in spatial transcriptomics (ST) data. To categorize cells based on their microenvironment, CellNeighborEX uses direct cell location or the mixture of transcriptome from multiple cells depending on ST technologies. For each cell type, CellNeighborEX identifies diverse gene sets associated with partnering cell types, providing further insight. We found that cells express different genes depending on their neighboring cell types in various tissues including mouse embryos, brain, and liver cancer. Those genes are associated with critical biological processes such as development or metastases. We further validated that gene expression is induced by neighboring partners via spatial visualization. The neighbor-dependent gene expression suggests new potential genes involved in cell-cell interactions beyond what ligand-receptor co-expression can discover.

Tumor microenvironment interactions with cancer stem cells in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer in the United States. Additionally, the low survival rate makes PDAC the third-leading cause of cancer-related mortality in the United States, and it is projected that by 2030, it will become the second-leading cause of cancer mortality. Several biological factors contribute to PDAC aggressiveness, and their understanding will narrow the gap from biology to clinical care of PDAC, leading to earlier diagnoses and the development of better treatment options. In this review, we describe the origins of PDAC highlighting the role of cancer stem cells (CSC). CSC, also known as tumor initiating cells, which exhibit a unique metabolism that allows them to maintain a highly plastic, quiescent, immune- and therapy-evasive state. However, CSCs can exit quiescence during proliferation and differentiation, with the capacity to form tumors while constituting a small population in tumor tissues. Tumorigenesis depends on the interactions between CSCs and other cellular and non-cellular components in the microenvironment. These interactions are fundamental to support CSC stemness and are maintained throughout tumor development and metastasis. PDAC is characterized by a massive desmoplastic reaction, which result from the deposition of high amounts of extracellular matrix components by stromal cells. Here we review how this generates a favorable environment for tumor growth by protecting tumor cells from immune responses and chemotherapy and inducing tumor cell proliferation and migration, leading to metastasis formation ultimately leading to death. We emphasize the interactions between CSCs and the tumor microenvironment leading to metastasis formation and posit that better understanding and targeting of these interactions will improve patient outcomes.

Risk Classification of Bladder Cancer by Gene Expression and Molecular Subtype.

This study evaluated a panel including the molecular taxonomy subtype and the expression of 27 genes as a diagnostic tool to stratify bladder cancer patients at risk of aggressive behavior, using a well-characterized series of non-muscle invasive bladder cancer (NMIBC) as well as muscle-invasive bladder cancer (MIBC). The study was conducted using the novel NanoString nCounter gene expression analysis. This technology allowed us to identify the molecular subtype and to analyze the gene expression of 27 bladder-cancer-related genes selected through a recent literature search. The differential gene expression was correlated with clinicopathological variables, such as the molecular subtypes (luminal, basal, null/double negative), histological subtype (conventional urothelial carcinoma, or carcinoma with variant histology), clinical subtype (NMIBC and MIBC), tumor stage category (Ta, T1, and T2-4), tumor grade, PD-L1 expression (high vs. low expression), and clinical risk categories (low, intermediate, high and very high). The multivariate analysis of the 19 genes significant for cancer-specific survival in our cohort study series identified TP53 (p = 0.0001), CCND1 (p = 0.0001), MKI67 (p < 0.0001), and molecular subtype (p = 0.005) as independent predictors. A scoring system based on the molecular subtype and the gene expression signature of TP53, CCND1, or MKI67 was used for risk assessment. A score ranging from 0 (best prognosis) to 7 (worst prognosis) was obtained and used to stratify our patients into two (low [score 0-2] vs. high [score 3-7], model A) or three (low [score 0-2] vs. intermediate [score 3-4] vs. high [score 5-7], model B) risk categories with different survival characteristics. Mean cancer-specific survival was longer (122 + 2.7 months) in low-risk than intermediate-risk (79.4 + 9.4 months) or high-risk (6.2 + 0.9 months) categories (p < 0.0001; model A); and was longer (122 + 2.7 months) in low-risk than high-risk (58 + 8.3 months) (p < 0.0001; model B). In conclusion, the molecular risk assessment model, as reported here, might be used better to select the appropriate management for patients with bladder cancer.

Neighbor-specific gene expression revealed from physically interacting cells during mouse embryonic development.

Development of multicellular organisms is orchestrated by persistent cell-cell communication between neighboring partners. Direct interaction between different cell types can induce molecular signals that dictate lineage specification and cell fate decisions. Current single-cell RNA-seq technology cannot adequately analyze cell-cell contact-dependent gene expression, mainly due to the loss of spatial information. To overcome this obstacle and resolve cell-cell contact-specific gene expression during embryogenesis, we performed RNA sequencing of physically interacting cells (PIC-seq) and assessed them alongside similar single-cell transcriptomes derived from developing mouse embryos between embryonic day (E) 7.5 and E9.5. Analysis of the PIC-seq data identified gene expression signatures that were dependent on the presence of specific neighboring cell types. Our computational predictions, validated experimentally, demonstrated that neural progenitor (NP) cells upregulate Lhx5 and Nkx2-1 genes, when exclusively interacting with definitive endoderm (DE) cells. Moreover, there was a reciprocal impact on the transcriptome of DE cells, as they tend to upregulate Rax and Gsc when in contact with NP cells. Using individual cell transcriptome data, we formulated a means of computationally predicting the impact of one cell type on the transcriptome of its neighboring cell types. We have further developed a distinctive spatial-t-distributed stochastic neighboring embedding to display the pseudospatial distribution of cells in a 2-dimensional space. In summary, we describe an innovative approach to study contact-specific gene regulation during embryogenesis.

Cell Competition in Carcinogenesis.

The majority of human cancers evolve over time through the stepwise accumulation of somatic mutations followed by clonal selection akin to Darwinian evolution. However, the in-depth mechanisms that govern clonal dynamics and selection remain elusive, particularly during the earliest stages of tissue transformation. Cell competition (CC), often referred to as 'survival of the fittest' at the cellular level, results in the elimination of less fit cells by their more fit neighbors supporting optimal organism health and function. Alternatively, CC may allow an uncontrolled expansion of super-fit cancer cells to outcompete their less fit neighbors thereby fueling tumorigenesis. Recent research discussed herein highlights the various non-cell-autonomous principles, including interclonal competition and cancer microenvironment competition supporting the ability of a tumor to progress from the initial stages to tissue colonization. In addition, we extend current insights from CC-mediated clonal interactions and selection in normal tissues to better comprehend those factors that contribute to cancer development.

IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study.

Purpose: Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. Methods: We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients. Results: We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients. Conclusion: These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

Molecular Classification of Bladder Urothelial Carcinoma Using NanoString-Based Gene Expression Analysis.

Molecular classification of bladder carcinoma is a relevant topic in modern bladder cancer oncology due to its potential to improve oncological outcomes. The available molecular classifications are generally based on transcriptomic profiles, generating highly diverse categories with limited correlation. Implementation of molecular classification in practice is typically limited due to the high complexity of the required technology, the elevated costs, and the limited availability of this technology worldwide. We have conducted a gene expression analysis using a four-gene panel related to luminal and basal subtypes in a series of 91 bladder cancer cases. NanoString-based gene expression analysis using typically luminal (GATA3+/KRT20+) and basal markers (KRT14+/KRT5+/GATA3low/-/KRT20low/-) classified urothelial bladder carcinoma samples as luminal, basal, and a third category (KRT14-/KRT5-/GATA3-/KRT20-), null/double negative (non-luminal/non-basal). These three categories were meaningful in terms of overall cancer-specific survival (p < 0.0001) or when classified as conventional urothelial carcinoma and variant histology urothelial carcinoma (p < 0.0001), NMIBC vs. MIBC (p < 0.001), or by AJCC stage category Ta (p = 0.0012) and T1 (p < 0.0001) but did not reach significance in T2-T4 (p = 0.563). PD-L1 expression (low vs. high) was also different according to molecular subtype, with high PD-L1 expression mostly seen in basal and null subtypes and carcinomas with variant histology (p = 0.002). Additionally, the luminal subtype was enriched in NMIBC with favorable cancer-specific survival (p < 0.0001). In contrast, basal and null subtypes resulted in aggressive MIBC tumors with shorter cancer-specific survival (p < 0.0001), some of which presented variant histology. In conclusion, a comprehensive evaluation of a gene classifier related to molecular taxonomy using NanoString technology is feasible. Therefore, it might represent an accessible and affordable tool in this rapidly expanding area of precision genomics.

Flower lose, a cell fitness marker, predicts COVID-19 prognosis.

Risk stratification of COVID-19 patients is essential for pandemic management. Changes in the cell fitness marker, hFwe-Lose, can precede the host immune response to infection, potentially making such a biomarker an earlier triage tool. Here, we evaluate whether hFwe-Lose gene expression can outperform conventional methods in predicting outcomes (e.g., death and hospitalization) in COVID-19 patients. We performed a post-mortem examination of infected lung tissue in deceased COVID-19 patients to determine hFwe-Lose's biological role in acute lung injury. We then performed an observational study (n = 283) to evaluate whether hFwe-Lose expression (in nasopharyngeal samples) could accurately predict hospitalization or death in COVID-19 patients. In COVID-19 patients with acute lung injury, hFwe-Lose is highly expressed in the lower respiratory tract and is co-localized to areas of cell death. In patients presenting in the early phase of COVID-19 illness, hFwe-Lose expression accurately predicts subsequent hospitalization or death with positive predictive values of 87.8-100% and a negative predictive value of 64.1-93.2%. hFwe-Lose outperforms conventional inflammatory biomarkers and patient age and comorbidities, with an area under the receiver operating characteristic curve (AUROC) 0.93-0.97 in predicting hospitalization/death. Specifically, this is significantly higher than the prognostic value of combining biomarkers (serum ferritin, D-dimer, C-reactive protein, and neutrophil-lymphocyte ratio), patient age and comorbidities (AUROC of 0.67-0.92). The cell fitness marker, hFwe-Lose, accurately predicts outcomes in COVID-19 patients. This finding demonstrates how tissue fitness pathways dictate the response to infection and disease and their utility in managing the current COVID-19 pandemic.

Cell competition in intratumoral and tumor microenvironment interactions.

Tumors are complex cellular and acellular environments within which cancer clones are under continuous selection pressures. Cancer cells are in a permanent mode of interaction and competition with each other as well as with the immediate microenvironment. In the course of these competitive interactions, cells share information regarding their general state of fitness, with less-fit cells being typically eliminated via apoptosis at the hands of those cells with greater cellular fitness. Competitive interactions involving exchange of cell fitness information have implications for tumor growth, metastasis, and therapy outcomes. Recent research has highlighted sophisticated pathways such as Flower, Hippo, Myc, and p53 signaling, which are employed by cancer cells and the surrounding microenvironment cells to achieve their evolutionary goals by means of cell competition mechanisms. In this review, we discuss these recent findings and explain their importance and role in evolution, growth, and treatment of cancer. We further consider potential physiological conditions, such as hypoxia and chemotherapy, that can function as selective pressures under which cell competition mechanisms may evolve differently or synergistically to confer oncogenic advantages to cancer.

Metabolic control of cancer progression as novel targets for therapy.

Metabolism is an important part of tumorigenesis as well as progression. The various cancer metabolism pathways, such as glucose metabolism and glutamine metabolism, directly regulate the development and progression of cancer. The pathways by which the cancer cells rewire their metabolism according to their needs, surrounding environment and host tissue conditions are an important area of study. The regulation of these metabolic pathways is determined by various oncogenes, tumor suppressor genes, as well as various constituent cells of the tumor microenvironment. Expanded studies on metabolism will help identify efficient biomarkers for diagnosis and strategies for therapeutic interventions and countering ways by which cancers may acquire resistance to therapy.

Assessment of proliferation in breast cancer: cell cycle or mitosis? An observational study.

BACKGROUND AND AIMS: Proliferation is an important indicator of breast cancer (BC) prognosis, but is assessed using different approaches. Not all cells in the cell cycle are committed to division. This study aimed to characterise quantitative differences between BC cells in the cell cycle and those in mitosis and assess their relationship with other pathological parameters. METHODS AND RESULTS: A cohort of BC sections (n = 621) was stained with haematoxylin and eosin and immunohistochemistry for Ki-67. The proportion of mitotic cells and Ki-67-positive cells was assessed in the same areas. The Cancer Genome Atlas (TCGA) BC cohort was used to assess MKI-67 transcriptome level and its association with the mitotic counts. The mean proportion of BC cells in the cell cycle was 24% (range = 1-90%), while the mean proportion of BC cells in mitosis was 5% (range = 0-73%). A low proportion of mitoses to whole cycling cells was associated with low histological grade tumours and the luminal A molecular subtype, while tumours with a high proportion of mitoses to the overall cycling cells were associated with triple-negative subtype, larger tumour size, grade 3 tumours and lymph node metastasis. The high mitosis/low Ki-67-positive cells tumours showed a significant association with variables of poor prognosis, including high-grade and triple-negative subtypes. CONCLUSION: The proportion of BC cells in the cell cycle and mitosis is variable. We show that not only the number of cells in the cell cycle or mitosis, but also the difference between them, provides valuable information on tumour aggressiveness.

Cell Fitness: More Than Push-Ups.

Cell competition (CC) is a feature that allows tumor cells to outcompete and eliminate adjacent cells that are deemed less fit. Studies of CC, first described in Drosophila melanogaster, reveal a diversity of underlying mechanisms. In this review, we will discuss three recent studies that expand our understanding of the molecular features governing CC. In particular, we will focus on a molecular fitness fingerprint, oncogenic pathways, and the importance of cell junction stability. A fitness fingerprint, mediated by flower (hFWE) protein isoforms, dictates that cells expressing the flower-win isoforms will outcompete adjacent flower-loss-expressing cells. The impact of the flower protein isoforms is seen in cancer progression and may have diagnostic potential. The yes-associated protein (YAP) and TAZ transcription factors, central mediators of the oncogenic Hippo pathway, elevate peritumoral fitness thereby protecting against tumor progression and provide a suppressive barrier. Similarly, COL17A1 is a key component in hemidesmosome stability, and its expression in epidermal stem cells contributes to fitness competition and aging characteristics. The contributions of these pathways to disease development and progression will help define how CC is hijacked to favor cancer growth. Understanding these features will also help frame the diagnostic and therapeutic possibilities that may place CC in the crosshairs of cancer therapeutics.

Cell Competition Boosts Clonal Evolution and Hypoxic Selection in Cancer.

The comparison of fitness between cells leads to the elimination of less competent cells in the presence of more competent neighbors via cell competition (CC). This phenomenon has been linked with several cancer-related genes and thus may play an important role in cancer. Various processes are involved in the regulation of tumor initiation and growth, including tumor hypoxia, clonal stem cell selection, and immune cell response, all of which have been recently shown to have a potential connection with the mechanisms involved in CC. This review aims to unravel the relation between these processes and competitive cell interactions and how this affects disease progression.

SPARC-p53: The double agents of cancer.

Cancer is a complex disease with high incidence and mortality rates. The important role played by the tumor microenvironment in regulating oncogenesis, tumor growth, and metastasis is by now well accepted in the scientific community. SPARC is known to participate in tumor-stromal interactions and impact cancer growth in ambiguous ways, which either enhance or suppress cancer aggressiveness, in a context-dependent manner. p53 transcription factor, a well-established tumor suppressor, has been reported to promote tumor growth in certain situations, such as hypoxia, thus displaying a duality in its action. Although both proteins are being tested in clinical trials, the synergistic relation between them is yet to be explored in clinical practice. In this review, we address the controversial roles of SPARC and p53 as double agents in cancer, briefly summarizing the interaction found between these two molecules and its importance in cancer.

Cell Competition Spurs Selection of Aggressive Cancer Cells.

Within heterogeneous tumors, cancer cells are constantly interacting. Cell competition (CC) is a fitness-based selection mechanism that results in increased proliferation of discrete populations at the expense of their less fit neighbors. CC-based selection of fit cells may also drive selection of the most aggressive cancer cells.

Cell competition and tumor heterogeneity.

Cancers exhibit a remarkable degree of intratumoral heterogeneity (ITH), which results from complex cellular interactions amongst various cell types. This phenomenon provides an opportunity for clonal selection and growth advantages to aggressive cancer cell types, resulting in worse prognosis and challenges to anti-cancer therapy. Cell competition is a conserved mechanism operational in cellular and organ systems, which allows neighboring cells to compare their relative fitness levels and results in the elimination of viable but suboptimal cells. By abuse of this conserved homeostasis mechanism, aggressive cancer cell types gain an advantage over normal cell types by achieving traits like increased proliferation, de-differentiation, and stemness. This review presents recent evidence that cell competition mechanisms actively participate in the regulation of intratumoral cell-cell interactions and thus contribute to ITH, and this process is essential for cancer development and progression.