The Heterogeneity of the Tumor Microenvironment as Essential Determinant of Development, Progression and Therapy Response of Pancreatic Cancer

Wandmacher, Anna Maxi; Mehdorn, Anne-Sophie; Sebens, Susanne

doi:10.3390/cancers13194932

Cited by 19 publications

(18 citation statements)

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“…For example, PD-L1 expresses in at least 50% of tumor cells in patients with advanced NSCLC, only 45.2% of these patients benefited from the anti-PD-1 antibody, pembrolizumab ( Garon et al, 2015 ). The heterogeneity of TEX was considered an essential determinant of the immunotherapeutic response of cancer ( Liu et al, 2020 ; Inflammatory et al, 2021 ). Hence, developing a virtual microdissection analytical approach to resolve the heterogeneity of TEX is eminent.…”

Section: Discussionmentioning

confidence: 99%

Cuproptosis-related molecular subtypes direct T cell exhaustion phenotypes and therapeutic strategies for patients with lung adenocarcinoma

et al. 2023

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Background: T cell exhaustion (TEX) heterogeneity leads to unfavorable immunotherapeutic responses in patients with cancer. Classification of TEX molecular phenotypes is pivotal to overcoming TEX and improving immunotherapies in the clinical setting. Cuproptosis is a novel form of programmed cell death associated with tumor progression. However, the relation between cuproptosis-related genes (CuRGs) and the different TEX phenotypes has not been investigated in lung adenocarcinoma (LUAD).Methods: Unsupervised hierarchical clustering and principal component analysis (PCA) algorithm were performed to determine CuRGs-related molecular subtypes and scores for patients with LUAD. The tumor immune microenvironment (TIME) landscape in these molecular subtypes and scores was estimated using ESTIMATE and ssGSEA algorithms. Furthermore, TEX characteristics and phenotypes were evaluated in distinct molecular subtypes and scores through GSVA and Spearman correlation analysis. Finally, TIDE scores, immunophenoscore, pRRophetic, GSE78220, and IMvigor210 datasets were employed to appraise the distinguishing capacity of CuRGscore in immunotherapy and pharmacotherapy effectiveness.Results: We identified three CuRGclusters, three geneClusters, and CuRGscore based on 1012 LUAD transcriptional profiles from five datasets. Compared with other molecular subtypes, CuRGcluster B, geneCluster C, and low-CuRGscore group with good prognosis presented fewer TEX characteristics, including immunosuppressive cells infiltration and TEX-associated gene signatures, signal pathways, checkpoint genes, transcription and inflammatory factors. These molecular subtypes were also responsive in distinguishing TEX phenotype in the terminal, GZMK+, and OXPHOS- TEX subtypes, but not the TCF7+ TEX subtype. Notably, copper importer and exporter, SLC31A1 and ATP7B, were remarkably associated with four TEX phenotypes and nine checkpoint genes such as PDCD1, CTLA4, HAVCR2, TIGIT, LAG3, IDO1, SIGLEC7, CD274, PDCD1LG2, indicating that cuproptosis was involved in the development of TEX and immunosuppressive environment in patients with LUAD. Moreover, CuRGscore was significantly related to the TIDE score, immunophenoscore, and terminal TEX score (Spearman R = 0.62, p < 0.001) to effectively predict immunotherapy and drug sensitivity in both training and external validation cohorts.Conclusion: Our study demonstrated the extensive effect of cuproptosis on TEX. CuRGs-related molecular subtypes and scores could illuminate the heterogeneity of TEX phenotype as reliable tools in predicting prognosis and directing more effective immunotherapeutic and chemotherapeutic strategies for patients with LUAD.

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Section: Discussionmentioning

confidence: 99%

Cuproptosis-related molecular subtypes direct T cell exhaustion phenotypes and therapeutic strategies for patients with lung adenocarcinoma

et al. 2023

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“…Traditional methods for studying tumor heterogeneity mainly include immunofluorescence staining and flow cytometry (FCM) ( Aldag et al, 2021 ). However, several major limitations of these methods exist, such as laborious and time-consuming processes, as well as low throughput in terms of genes that can be analyzed simultaneously, thereby holding back their wide applications in tumor heterogeneity study.…”

Section: Methods For Tumor Heterogeneity Dissectionmentioning

confidence: 99%

Spatial Transcriptomics for Tumor Heterogeneity Analysis

Zhang

2022

Front. Genet.

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The molecular heterogeneity of cancer is one of the major causes of drug resistance that leads to treatment failure. Thus, better understanding the heterogeneity of cancer will contribute to more precise diagnosis and improved patient outcomes. Although single-cell sequencing has become an important tool for investigating tumor heterogeneity recently, it lacks the spatial information of analyzed cells. In this regard, spatial transcriptomics holds great promise in deciphering the complex heterogeneity of cancer by providing localization-indexed gene expression information. This study reviews the applications of spatial transcriptomics in the study of tumor heterogeneity, discovery of novel spatial-dependent mechanisms, tumor immune microenvironment, and matrix microenvironment, as well as the pathological classification and prognosis of cancer. Finally, future challenges and opportunities for spatial transcriptomics technology’s applications in cancer are also discussed.

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“…In the presence of Transforming Growth Factor-beta 1 (TGF-β1), Platelet-derived Growth Factor (PDGF), or Interleukin-6 (IL-6) HSC transdifferentiate into hepatic myofibroblasts (HMF). HMF are characterized by a high expression of alpha-smooth muscle actin (αSMA) as well as the secretion of various inflammatory mediators and ECM molecules, that have been reported to support tumor growth ( 11 , 12 ). Furthermore, cancer-associated fibroblasts (CAF) can impact the immune response by secreting cytokines, like IL-6, Granulocyte Colony-stimulating Factor (G-CSF), and Macrophage Colony-stimulating Factor (M-CSF), or inhibiting CD8 + T cells by either expressing PD-L1 or promoting expression of PD-1 and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) on CD8 + T cells ( 13 ).…”

Section: Introductionmentioning

confidence: 99%

Hepatic myofibroblasts exert immunosuppressive effects independent of the immune checkpoint regulator PD-L1 in liver metastasis of pancreatic ductal adenocarcinoma

et al. 2023

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IntroductionPancreatic ductal adenocarcinoma (PDAC) represents the 4th most common cause of cancer-related deaths in Western countries. Most patients are diagnosed at advanced stages, often already with metastases. The main site of metastasis is the liver and hepatic myofibroblasts (HMF) play a pivotal role in metastatic outgrowth. Immune checkpoint inhibitors (ICI) targeting programmed death ligand 1 (PD-L1) or programmed cell death protein 1 (PD-1) improved treatment of several cancers but not of PDAC. Therefore, this study aimed to better understand the impact of HMF on PD-L1 expression and immune evasion of PDAC cells during liver metastasis.MethodsFormalin-fixed and paraffin embedded biopsy samples or diagnostic resection specimens from liver metastases of 15 PDAC patients were used for immunohistochemical analyses. Serial sections were stained with antibodies directed against Pan-Cytokeratin, αSMA, CD8, and PD-L1. To investigate whether the PD-1/PD-L1 axis and HMF contribute to immune escape of PDAC liver metastases, a stroma enriched 3D spheroid coculture model was established in vitro, using two different PDAC cell lines, HMF, and CD8+ T cells. Here, functional and flow cytometry analyses were conducted.ResultsImmunohistochemical analysis of liver tissue sections of PDAC patients revealed that HMF represent an abundant stroma population in liver metastases, with clear differences in the spatial distribution in small (1500 µm) and large (> 1500 μm) metastases. In the latter, PD-L1 expression was mainly located at the invasion front or evenly distributed, while small metastases either lacked PD-L1 expression or showed mostly weak expression in the center. Double stainings revealed that PD-L1 is predominantly expressed by stromal cells, especially HMF. Small liver metastases with no or low PD-L1 expression comprised more CD8+ T cells in the tumor center, while large metastases exhibiting stronger PD-L1 expression comprised less CD8+ T cells being mostly located at the invasion front. HMF-enriched spheroid cocultures with different ratios of PDAC cells and HMF well mimicking conditions of hepatic metastases in situ. Here, HMF impaired the release of effector molecules by CD8+ T cells and the induction of PDAC cell death, an effect that was dependent on the amount of HMF but also of PDAC cells. ICI treatment led to elevated secretion of distinct CD8+ T cell effector molecules but did not increase PDAC cell death under either spheroid condition.ConclusionOur findings indicate a spatial reorganization of HMF, CD8+ T cells, and PD-L1 expression during progression of PDAC liver metastases. Furthermore, HMF potently impair the effector phenotype of CD8+ T cells but the PD-L1/PD-1 axis apparently plays a minor role in this scenario suggesting that immune evasion of PDAC liver metastases relies on other immunosuppressive mechanisms.

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The Heterogeneity of the Tumor Microenvironment as Essential Determinant of Development, Progression and Therapy Response of Pancreatic Cancer

Cited by 19 publications

References 323 publications

Cuproptosis-related molecular subtypes direct T cell exhaustion phenotypes and therapeutic strategies for patients with lung adenocarcinoma

Cuproptosis-related molecular subtypes direct T cell exhaustion phenotypes and therapeutic strategies for patients with lung adenocarcinoma

Spatial Transcriptomics for Tumor Heterogeneity Analysis

Hepatic myofibroblasts exert immunosuppressive effects independent of the immune checkpoint regulator PD-L1 in liver metastasis of pancreatic ductal adenocarcinoma

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