The Lineage-Defining Transcription Factors SOX2 and NKX2-1 Determine Lung Cancer Cell Fate and Shape the Tumor Immune Microenvironment

Mollaoglu, Gürkan; Jones, Alex; Wait, Sarah J.; Mukhopadhyay, Anandaroop; Jeong, Sangmin; Arya, Rahul; Camolotto, Soledad A.; Mosbruger, Timothy; Stubben, Chris; Conley, Christopher J.; Bhutkar, Arjun; Vahrenkamp, Jeffery M.; Berrett, Kristofer C.; Cessna, Melissa H.; Lane, Thomas E.; Witt, Benjamin L.; Salama, Mohamed E.; Gertz, Jason; Jones, Kevin B.; Snyder, Eric L.; Oliver, Trudy G.

doi:10.1016/j.immuni.2018.09.020

Cited by 153 publications

(141 citation statements)

References 54 publications

(93 reference statements)

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“…In this context, inflammatory changes were promoted by the squamous lineage transcription factor SOX2 through activation of CXCL5 expression (Mollaoglu et al, 2018). Taken together with our findings, these results suggest that inflammation is more generally associated with squamous lineage tumors through multiple distinct mechanisms.…”

Section: Discussionsupporting

confidence: 84%

“…An association between squamous cell carcinomas and infiltrating inflammatory cells has been observed previously in other tumor contexts (Andreu et al, 2010;Coussens et al, 1999;Erez et al, 2010;Eruslanov et al, 2014;Ferone et al, 2016;Kargl et al, 2017;Xu et al, 2014;Yang et al, 2011). In one study, squamous trans-differentiation in a lung adenocarcinoma mouse model was associated with neutrophil infiltration and other markers of inflammation (Mollaoglu et al, 2018).…”

Section: Discussionsupporting

confidence: 59%

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Squamous trans-differentiation of pancreatic cancer cells promotes stromal inflammation

Somerville

Biffi

Daßler-Plenker

et al. 2019

Preprint

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AbstractA highly aggressive subset of pancreatic ductal adenocarcinomas undergo trans-differentiation into the squamous lineage during disease progression. While the tumorigenic consequences of this aberrant cell fate transition are poorly understood, recent studies have identified a role for the master regulator TP63 in this process. Here, we investigated whether squamous trans-differentiation of pancreatic cancer cells can influence the phenotype of non-neoplastic cells in the tumor microenvironment. Conditioned media experiments revealed that squamous-subtype pancreatic cancer cells secrete factors that convert quiescent pancreatic stellate cells into a specialized subtype of cancer-associated fibroblasts (CAFs) that express inflammatory genes at high levels. We use gain- and loss-of-function approaches in vivo to show that squamous-subtype pancreatic tumor models become enriched with inflammatory CAFs and neutrophils in a TP63-dependent manner. These non cell-autonomous effects occur, at least in part, through TP63-mediated activation of enhancers at pro-inflammatory cytokine loci, which includes IL1A as a key target. Taken together, our findings reveal enhanced tissue inflammation as a consequence of squamous trans-differentiation in pancreatic cancer, thus highlighting an instructive role of tumor cell lineage in reprogramming the stromal microenvironment.

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Section: Discussionsupporting

confidence: 84%

Section: Discussionsupporting

confidence: 59%

Squamous trans-differentiation of pancreatic cancer cells promotes stromal inflammation

Somerville

Biffi

Daßler-Plenker

et al. 2019

Preprint

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“…For example, replicate of UCEC GEMMs driven by Prg(cre/+)Pten(lox/lox) received almost identical general and subtype classification profiles ( Supp Fig 4, Supp Tab 6 ). GEMMs sharing genotypes across studies such as LUAD GEMMs driven by Kras mutation and loss of p53 49,55,57 received similar general and subtype classification scores ( Fig. 5A,B,D ).…”

Section: Resultsmentioning

confidence: 84%

Evaluating the transcriptional fidelity of cancer models

Peng

Gleyzer

Tai

et al. 2020

Preprint

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33 34 35 * These authors made equal contributions. 36 37 38 Correspondence to: patrick.cahan@jhmi.edu 39 40 Article type: Analysis 41 42 Website: http://www.cahanlab.org/resources/cancerCellNet_web 43 44 Code: https://github.com/pcahan1/cancerCellNet 45 46 47 48 49 2 ABSTRACT 50 51Cancer researchers use cell lines, patient derived xenografts, and genetically engineered mice 52 as models to investigate tumor biology and to identify therapies. The generalizability and power 53 of a model derives from the fidelity with which it represents the tumor type of investigation, 54 however, the extent to which this is true is often unclear. The preponderance of models and the 55 ability to readily generate new ones has created a demand for tools that can measure the extent 56 and ways in which cancer models resemble or diverge from native tumors. Here, we present a 57 computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally 58 occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied 59 this tool to 657 cancer cell lines, 415 patient derived xenografts, and 26 distinct genetically 60 engineered mouse models, documenting the most faithful models, identifying cancers 61 underserved by adequate models, and finding models with annotations that do not match their 62 classification. By comparing models across modalities, we find that genetically engineered mice 63 have higher transcriptional fidelity than patient derived xenografts and cell lines in four out of 64 five tumor types. We have made CancerCellNet available as freely downloadable software and 65 as a web application that can be applied to new cancer models. 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81Models are widely used to investigate cancer biology and to identify potential therapeutics. 82Popular modeling modalities are cancer cell lines (CCLs) 1 , genetically engineered mouse 83 models (GEMMs) 2 , and patient derived xenografts (PDXs) 3 .These classes of models differ in the 84 types of questions that they are designed to address. CCLs are often used to address cell 85 intrinsic mechanistic questions 4 , GEMMs to chart progression of molecularly defined-disease 5 , 86 and PDXs to explore patient-specific response to therapy in a physiologically relevant context 6 . 87Models also differ in the extent to which the they represent specific aspects of a cancer type 7 . 88Even with this intra-and inter-class model variation, all models should represent the tumor type 89 or subtype under investigation, and not another type of tumor, and not a non-cancerous tissue. 90Therefore, cancer-models should be selected not only based on the specific biological question 91 but also based on the similarity of the model to the cancer type under investigation 8,9 . 92 Various methods have been proposed to determine the similarity of cancer models to 93 their intended subjects. Domcke et al devised a 'suitability score' as a metric of the molecular 94 similarity of CCLs to high grade serous ovarian carcinom...

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“…Neutrophils may be an important reason for the differences between in vivo and in vitro studies. CXCR2+ neutrophils are recruited by CXCL5 at tumor tissue, which then participate in tumor progression [30,42]. Hepatocellular carcinoma stem cell-like cells overexpress CXCL5, which thereafter recruits more tumor-associated neutrophils penetration through CXCR2 activation [43].…”

Section: The Role Of Cxcl5/cxcr2 Axis In Tmementioning

confidence: 99%

“…Promote tumor angiogenesis and lymphangiogenesis in TME [51,52] Regulate the function of neutrophil in TME [45] Positively related to the risk of metastasis [62,63,72] Recruit immune cells -Recruit neutrophils in TME and metastatic niche [30,[42][43][44][45] -Recruit granulocytes to promote the formation of early metastatic microenvironment [40,49] -Promote MDSCs infiltration in TME [47,48] -Positively related to the extent of macrophage infiltration in TME [50] Promote cell proliferation of primary tumors [26,[54][55][56][57] Abbreviations: CXCL5, CXC motif ligand 5; TME, tumor microenvironment; MDSC, myeloid-derived suppressor cell.…”

Section: Functions Of Cxcl5 Referencesmentioning

confidence: 99%

CXCL5/CXCR2 axis in tumor microenvironment as potential diagnostic biomarker and therapeutic target

Zhang

Wang

Sun

et al. 2020

Cancer Communications

147

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The components of the tumor microenvironment (TME) in solid tumors, especially chemokines, are currently attracting much attention from scientists. C-X-C motif chemokine ligand 5 (CXCL5) is one of the important chemokines in TME. Overexpression of CXCL5 is closely related to the survival time, recurrence and metastasis of cancer patients. In TME, CXCL5 binds to its receptors, such as C-X-C motif chemokine receptor 2 (CXCR2), to participate in the recruitment of immune cells and promote angiogenesis, tumor growth, and metastasis. The CXCL5/CXCR2 axis can act as a bridge between tumor cells and host cells in TME. Blocking the transmission of CXCL5/CXCR2 signals can increase the sensitivity and effectiveness of immunotherapy and slow down tumor progression. CXCL5 and CXCR2 are also regarded as biomarkers for predicting prognosis and molecular targets for customizing the treatment. In this review, we summarized the current literature regarding the biological functions and clinical significance of CXCL5/CXCR2 axis in TME. The possibility to use CXCL5 and CXCR2 as potential prognostic biomarkers and therapeutic targets in cancer is also discussed

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The Lineage-Defining Transcription Factors SOX2 and NKX2-1 Determine Lung Cancer Cell Fate and Shape the Tumor Immune Microenvironment

Cited by 153 publications

References 54 publications

Squamous trans-differentiation of pancreatic cancer cells promotes stromal inflammation

Squamous trans-differentiation of pancreatic cancer cells promotes stromal inflammation

Evaluating the transcriptional fidelity of cancer models

CXCL5/CXCR2 axis in tumor microenvironment as potential diagnostic biomarker and therapeutic target

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