Suppression of tumor-associated neutrophils by lorlatinib attenuates pancreatic cancer growth and improves treatment with immune checkpoint blockade

AbstractPancreatic ductal adenocarcinoma (PDAC) patients have a 5-year survival rate of only 8% largely due to late diagnosis and insufficient therapeutic options. Neutrophils are among the most abundant immune cell type within the PDAC tumor microenvironment (TME), and are associated with a poor clinical prognosis. However, despite recent advances in understanding neutrophil biology in cancer, therapies targeting tumor-associated neutrophils are lacking. Here, we demonstrate, using pre-clinical mouse models of PDAC, that lorlatinib attenuates PDAC progression by suppressing neutrophil development and mobilization, and by modulating tumor-promoting neutrophil functions within the TME. When combined, lorlatinib also improves the response to anti-PD-1 blockade resulting in more activated CD8 + T cells in PDAC tumors. In summary, this study identifies an effect of lorlatinib in modulating tumor-associated neutrophils, and demonstrates the potential of lorlatinib to treat PDAC.

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Immune classification of clear cell renal cell carcinoma

Scientific Reports ◽

10.1038/s41598-021-83767-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sumeyye Su ◽

Shaya Akbarinejad ◽

Leili Shahriyari

Keyword(s):

T Cells ◽

Cd8 T Cells ◽

Renal Cell ◽

Cd4 T Cells ◽

Immune Cell ◽

Clear Cell ◽

P Value ◽

Cell Type ◽

Primary Tumors ◽

Immune Cell Type

AbstractSince the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of macrophages and CD8+ T-cells and and a slightly smaller number of CD4+ T cells than CD8+ T cells, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value $$<0.01$$ < 0.01 ). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value $$<0.01$$ < 0.01 ), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value $$<0.01$$ < 0.01 ). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value $$<0.01$$ < 0.01 ) compared to the patients with tumors for all groups of tumors except group 3.

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The Crosstalk Between Malignant Cells and Tumor-Promoting Immune Cells Relevant to Immunotherapy in Pancreatic Ductal Adenocarcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.821232 ◽

2022 ◽

Vol 9 ◽

Author(s):

Xuefei Liu ◽

Ziwei Luo ◽

Xuechen Ren ◽

Zhihang Chen ◽

Xiaoqiong Bao ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Rna Sequencing ◽

Immune Cells ◽

Immune Checkpoint ◽

Immune Cell ◽

Immune Checkpoint Blockade ◽

Ductal Adenocarcinoma ◽

Malignant Cells ◽

Sequencing Data ◽

Immunosuppressive Microenvironment

Background: Pancreatic ductal adenocarcinoma (PDAC) is dominated by an immunosuppressive microenvironment, which makes immune checkpoint blockade (ICB) often non-responsive. Understanding the mechanisms by which PDAC forms an immunosuppressive microenvironment is important for the development of new effective immunotherapy strategies.Methods: This study comprehensively evaluated the cell-cell communications between malignant cells and immune cells by integrative analyses of single-cell RNA sequencing data and bulk RNA sequencing data of PDAC. A Malignant-Immune cell crosstalk (MIT) score was constructed to predict survival and therapy response in PDAC patients. Immunological characteristics, enriched pathways, and mutations were evaluated in high- and low MIT groups.Results: We found that PDAC had high level of immune cell infiltrations, mainly were tumor-promoting immune cells. Frequent communication between malignant cells and tumor-promoting immune cells were observed. 15 ligand-receptor pairs between malignant cells and tumor-promoting immune cells were identified. We selected genes highly expressed on malignant cells to construct a Malignant-Immune Crosstalk (MIT) score. MIT score was positively correlated with tumor-promoting immune infiltrations. PDAC patients with high MIT score usually had a worse response to immune checkpoint blockade (ICB) immunotherapy.Conclusion: The ligand-receptor pairs identified in this study may provide potential targets for the development of new immunotherapy strategy. MIT score was established to measure tumor-promoting immunocyte infiltration. It can serve as a prognostic indicator for long-term survival of PDAC, and a predictor to ICB immunotherapy response.

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Metabolic Reprogramming of Cancer Associated Fibroblasts: The Slavery of Stromal Fibroblasts

BioMed Research International ◽

10.1155/2018/6075403 ◽

2018 ◽

Vol 2018 ◽

pp. 1-12 ◽

Cited By ~ 36

Author(s):

Angelica Avagliano ◽

Giuseppina Granato ◽

Maria Rosaria Ruocco ◽

Veronica Romano ◽

Immacolata Belviso ◽

...

Keyword(s):

Cancer Cells ◽

Stromal Cells ◽

Tumour Microenvironment ◽

Metabolic Reprogramming ◽

Cancer Growth ◽

Activation Process ◽

Cancer Therapies ◽

Cancer Associated Fibroblasts ◽

Cell Type ◽

Stromal Fibroblasts

Cancer associated fibroblasts (CAFs) are the main stromal cell type of solid tumour microenvironment and undergo an activation process associated with secretion of growth factors, cytokines, and paracrine interactions. One of the important features of solid tumours is the metabolic reprogramming that leads to changes of bioenergetics and biosynthesis in both tumour cells and CAFs. In particular, CAFs follow the evolution of tumour disease and acquire a catabolic phenotype: in tumour tissues, cancer cells and tumour microenvironment form a network where the crosstalk between cancer cells and CAFs is associated with cell metabolic reprogramming that contributes to CAFs activation, cancer growth, and progression and evasion from cancer therapies. In this regard, the study of CAFs metabolic reprogramming could contribute to better understand their activation process, the interaction between stroma, and cancer cells and could offer innovative tools for the development of new therapeutic strategies able to eradicate the protumorigenic activity of CAFs. Therefore, this review focuses on CAFs metabolic reprogramming associated with both differentiation process and cancer and stromal cells crosstalk. Finally, therapeutic responses and potential anticancer strategies targeting CAFs metabolic reprogramming are reviewed.

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Immune Classification of Clear Cell Renal Cell Carcinoma

10.1101/2020.07.03.187047 ◽

2020 ◽

Cited By ~ 2

Author(s):

Sumeyye Su ◽

Shaya Akbarinejad ◽

Leili Shahriyari

Keyword(s):

T Cells ◽

Cd8 T Cells ◽

Renal Cell ◽

Cd4 T Cells ◽

Immune Cell ◽

Clear Cell ◽

P Value ◽

Cell Type ◽

Primary Tumors ◽

Immune Cell Type

ABSTRACTSince the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of CD8+ T-cells, CD4+ T-cells, and macrophages, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value< 0.01). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value< 0.01), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value< 0.01). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value< 0.01) compared to the patients with tumors for all groups of tumors except group 3.

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Genomic analysis and clinical implications of immune cell infiltration in gastric cancer

Bioscience Reports ◽

10.1042/bsr20193308 ◽

2020 ◽

Vol 40 (5) ◽

Cited By ~ 1

Author(s):

Ming Wu ◽

Yadong Wang ◽

Hang Liu ◽

Jukun Song ◽

Jie Ding

Keyword(s):

Gastric Cancer ◽

Immune Cells ◽

Immune Cell ◽

R Package ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Cell Type ◽

Clinical Prognosis ◽

Immune Infiltration

Abstract The immune infiltration of patients with gastric cancer (GC) is closely associated with clinical prognosis. However, previous studies failed to explain the different subsets of immune cells involved in immune responses and diverse functions. The present study aimed to uncover the differences in immunophenotypes in a tumor microenvironment (TME) between adjacent and tumor tissues and to explore their therapeutic targets. In our study, the relative proportion of immune cells in 229 GC tumor samples and 22 paired matched tissues was evaluated with a Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) algorithm. The correlation between immune cell infiltration and clinical information was analyzed. The proportion of 22 immune cell subsets was assessed to determine the correlation between each immune cell type and clinical features. Three molecular subtypes were identified with ‘CancerSubtypes’ R-package. Functional enrichment was analyzed in each subtype. The profiles of immune infiltration in the GC cohort from The Cancer Genome Atlas (TCGA) varied significantly between the 22 paired tissues. TNM stage was associated with M1 macrophages and eosinophils. Follicular helper T cells were activated at the late stage. Monocytes were associated with radiation therapy. Three clustering processes were obtained via the ‘CancerSubtypes’ R-package. Each cancer subtype had a specific molecular classification and subtype-specific characterization. These findings showed that the CIBERSOFT algorithm could be used to detect differences in the composition of immune-infiltrating cells in GC samples, and these differences might be an important driver of GC progression and treatment response.

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828 Quantifying perivascular immune cells in the stroma of human triple negative breast tumors using deep learning spatial analytics

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-sitc2021.828 ◽

2021 ◽

Vol 9 (Suppl 3) ◽

pp. A867-A867

Author(s):

Anna Juncker-Jensen ◽

Nicholas Stavrou ◽

Mohammed Moamin ◽

Mate Nagy ◽

Richard Allen ◽

...

Keyword(s):

T Cells ◽

Cd8 T Cells ◽

Spatial Organization ◽

Triple Negative ◽

Immune Cell ◽

Cancer Therapies ◽

Antibody Staining ◽

Yield Information ◽

Prognosis And Prediction ◽

Immune Contexture

BackgroundThe spatial organization and density of the immune infiltrate in the tumor microenvironment, referred to as immune contexture, can yield information relevant to prognosis and prediction of response to immunotherapy in cancer. Specifically, a distinct subset of tumor-associated macrophages (TAMs) accumulate around blood vessels where they stimulate tumor angiogenesis and limit tumor responses to frontline anti-cancer therapies like irradiation and chemotherapy.MethodsIn this study we leveraged the NeoGenomics MultiOmyx Multiplex Immunofluorescence platform alongside artificial intelligence (AI) based quantitative image analysis. This AI platform was ultimately used to investigate the distribution of perivascular (PV) TAMs, CD4+ and CD8+ T cells, and CD4+FOXP3+ regulatory T cells (Tregs) of 40 human triple negative breast carcinomas (TNBCs), and how this changed following neoadjuvant chemotherapy. During the multiplexing phase, eleven rounds of paired antibody staining were performed in sequence on tumor sections. After each round of staining, high resolution images were captured for regions of interests (ROIs) selected by a pathologist. We used AI models to segment and classify cells for each biomarker and classify regions as tumor cell islands (TCIs) or stroma. First, each nucleus was segmented out using a convolutional neural network combined with watershed thresholding on the DAPI (diamidino-2-phenylindole) immunofluorescent image. From the resulting nuclear segmentation mask, a pixel dilation on cells classified as non-tumor was employed to generate a cellular segmentation mask. A list of neighbours within a specified distance for each cell was generated by radially expanding from the cellular segmentation mask. Finally, cell neighbour information was combined with the marker expression information to quantify the cell clusters of interest.ResultsWe discovered that in the PV areas, up to 30% of PD1-LAG3-CD3+CD8+ T cells formed direct contact with both CD163+TIM3+ TAMs and CD4+FOXP3+ Tregs. Furthermore, these immune cell triads preferentially accumulated in the PV stroma regions. It is likely that close interaction with immunosuppressive TAMs and Tregs would supress the function of T cells as they enter the PV region to reach the TCIs.ConclusionsUsing an advanced analytics platform, we invented a new method to quantify clusters of cells within various regions of a tumor section. Using this platform, we detected specific immune cell triads, the frequency and location of which could correlate with the efficacy of T-cell based immunotherapies in TNBC. These analyses will enable further investigation of numerous complex cell interactions in TMEs.

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53 Unique insights into PDAC development revealed by both InSituPlex® and imaging mass cytometry

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-sitc2021.053 ◽

2021 ◽

Vol 9 (Suppl 3) ◽

pp. A60-A60

Author(s):

Andrew Quong ◽

Mark Rees ◽

Kirsteen Maclean ◽

Mael Manesse ◽

Jordan Nieto ◽

...

Keyword(s):

Tumor Microenvironment ◽

Immune Cell ◽

Treatment Options ◽

Tumor Biology ◽

Membrane Integrity ◽

Ductal Adenocarcinoma ◽

Mass Cytometry ◽

Poor Overall Survival ◽

Immune Cell Population ◽

Clinical Prognosis

BackgroundPancreatic cancer remains a deadly disease due to difficulties hindering its early diagnosis, giving way to metastasis of the tumor and resulting in poor prognosis. While there are many neoplasms of the pancreas, pancreatic invasive ductal adenocarcinoma (PDAC) is the most common and treatment options are few, with poor overall survival. Aggressive surgeries such as the Whipple procedure coupled to systemic chemotherapy is one of the few treatment options. Recently, several publications have demonstrated improved outcomes with the inclusion of immunotherapy to cytotoxic drug combinations in some patients, however optimally selecting patients as candidates for immunotherapy-chemotherapy combinations remains a critical challenge. The complexities of the tumor microenvironment have been implicated in the failure of chemotherapy, radiation therapy, and immunotherapy. The tumor microenvironment of PDAC is especially rich with multiple interactions between pancreatic epithelial/cancer cells, stromal cells, immune cells and the extracellular matrix (ECM). PDACs are characterized by a complex ECM of desmoplastic reaction consisting of an extensive and dense fibrotic stroma that surrounds and infiltrates clusters of malignant epithelial cells, together with the loss of basement membrane integrity and an abnormal vasculature.MethodsIn the present study we demonstrate a tissue phenotyping workflow combining three complementary methods that can unravel novel insights in the complex tumor microenvironment. This novel translational workflow delivers tissue morphology information, spatial phenotyping of immune cell population on whole slides, and high dimensional imaging in selected regions of interest (ROI), by combining H&E, multiplex immunofluorescence (mIF), and Imaging Mass Cytometry (IMC™).ResultsThe use of the InSituPlex® UltiMapper® I/O PD-L1 kit enabled the streamlined combination and alignment of H&E and mIF data, leading to the strategic selection of relevant ROIs, while utility of IMC technology enabled downstream imaging of 35 protein markers associated with the ECM in the selected ROIs to provide a deeper understanding of the tumor microenvironment.ConclusionsThe incorporation of advanced multiplex imaging platforms such as mIF and IMC with routine H&E workflow in tumor biology can deliver some of the much-needed insight into tumor morphology, cellular composition, cellular functions, and cell-cell interactions and paves the way for potentially improved clinical prognosis and efficacy prediction in patients with cancer.

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Lipid nanoparticles delivering constitutively active STING mRNA as a novel anti-cancer therapeutic approach

10.1101/2022.01.08.475499 ◽

2022 ◽

Author(s):

Wei Liu ◽

Mohamad-Gabriel Alameh ◽

June F. Yang ◽

Jonathan R. Xu ◽

Paulo JC Lin ◽

...

Keyword(s):

Cd8 T Cells ◽

Lipid Nanoparticles ◽

Cell Entry ◽

Ductal Adenocarcinoma ◽

Cancer Therapies ◽

Therapeutic Tool ◽

Antitumor Response ◽

Cancer Cell Death ◽

Cytokines And Chemokines ◽

Anti Cancer

Treating immunosuppressive tumors represents a major challenge in cancer therapies. Activation of STING signaling has shown remarkable potential to invigorate the immunologically 'cold' tumor microenvironment (TME). However, we and others have shown that STING is silenced in many cancers, including pancreatic ductal adenocarcinoma (PDAC) and Merkel cell carcinoma (MCC), both of which are associated with an immune-dampened TME. In this study, we applied mRNA lipid nanoparticles (LNP) to deliver a permanently active gain-of-function STINGR284S mutant into PDAC and MCC cells. Expression of STINGR284S induces cytokines and chemokines crucial for promoting intratumoral infiltration of CD8+ T cells and, importantly, also leads to robust cancer cell death while avoiding T cell entry and toxicity. Our studies demonstrated that mRNA-LNP delivery of STINGR284S could be explored as a novel therapeutic tool to reactivate antitumor response in an array of STING-deficient cancers while overcoming the toxicity and limitations of conventional STING agonists.

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Identification, Validation, and Utilization of Immune Cells in Pancreatic Ductal Adenocarcinoma Based on Marker Genes

Frontiers in Immunology ◽

10.3389/fimmu.2021.649061 ◽

2021 ◽

Vol 12 ◽

Author(s):

Willem de Koning ◽

Diba Latifi ◽

Yunlei Li ◽

Casper H. J. van Eijck ◽

Andrew P. Stubbs ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Immune Cells ◽

Immune Cell ◽

Ductal Adenocarcinoma ◽

Marker Genes ◽

Cell Type ◽

Tissue Samples ◽

Immune Cell Type ◽

Different Types ◽

Pdac Tissue

The immune response affects tumor biological behavior and progression. The specific immune characteristics of pancreatic ductal adenocarcinoma (PDAC) can determine the metastatic abilities of cancerous cells and the survival of patients. Therefore, it is important to characterize the specific immune landscape in PDAC tissue samples, and the effect of various types of therapy on that immune composition. Previously, a set of marker genes was identified to assess the immune cell composition in different types of cancer tissue samples. However, gene expression and subtypes of immune cells may vary across different types of cancers. The aim of this study was to provide a method to identify immune cells specifically in PDAC tissue samples. The method is based on defining a specific set of marker genes expressed by various immune cells in PDAC samples. A total of 90 marker genes were selected and tested for immune cell type-specific definition in PDAC; including 43 previously used, and 47 newly selected marker genes. The immune cell-type specificity was checked mathematically by calculating the “pairwise similarity” for all candidate genes using the PDAC RNA-sequenced dataset available at The Cancer Genome Atlas. A set of 55 marker genes that identify 22 different immune cell types for PDAC was created. To validate the method and the set of marker genes, an independent mRNA expression dataset of 24 samples of PDAC patients who received various types of (neo)adjuvant treatments was used. The results showed that by applying our method we were able to identify PDAC specific marker genes to characterize immune cell infiltration in tissue samples. The method we described enabled identifying different subtypes of immune cells that were affected by various types of therapy in PDAC patients. In addition, our method can be easily adapted and applied to identify the specific immune landscape in various types of tissue samples.

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Immune-Related Circulating miR-125b-5p and miR-99a-5p Reveal a High Recurrence Risk Group of Pancreatic Cancer Patients after Tumor Resection

Applied Sciences ◽

10.3390/app9224784 ◽

2019 ◽

Vol 9 (22) ◽

pp. 4784

Author(s):

Vietsch ◽

Peran ◽

Suker ◽

van den Bosch ◽

Sijde ◽

...

Keyword(s):

Cancer Progression ◽

B Lymphocyte ◽

Immune Cell ◽

Tumor Resection ◽

Progression Free Survival ◽

Tumor Stroma ◽

Recurrence Risk ◽

High Serum ◽

Ductal Adenocarcinoma ◽

Before And After

Clinical follow-up aided by changes in the expression of circulating microRNAs (miRs) may improve prognostication of pancreatic ductal adenocarcinoma (PDAC) patients. Changes in 179 circulating miRs due to cancer progression in the transgenic KrasG12D/+; Trp53R172H/+; P48-Cre (KPC) animal model of PDAC were analyzed for serum miRs that are altered in metastatic disease. In addition, expression levels of 250 miRs were profiled before and after pancreaticoduodenectomy in the serum of two patients with resectable PDAC with different progression free survival (PFS) and analyzed for changes indicative of PDAC recurrence after resection. Three miRs that were upregulated ≥3-fold in progressive PDAC in both mice and patients were selected for validation in 26 additional PDAC patients before and after resection. We found that high serum miR-125b-5p and miR-99a-5p levels after resection are significantly associated with shorter PFS (HR 1.34 and HR 1.73 respectively). In situ hybridization for miR detection in the paired resected human PDAC tissues showed that miR-125b-5p and miR-99a-5p are highly expressed in inflammatory cells in the tumor stroma, located in clusters of CD79A expressing cells of the B-lymphocyte lineage. In conclusion, we found that circulating miR-125b-5p and miR-99a-5p are potential immune-cell related prognostic biomarkers in PDAC patients after surgery.

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