Tumor Microenvironment In Lung Cancer Research Articles

Abstract 2800: Shotgun metagenomics of COPD-associated lung cancer tissue microbiome

Abstract The gut microbiome plays a crucial role in the development of multiple chronic diseases. Several solid tumors including lung cancer are also implicated in the gut microbiome in cancer initiation and progression, possibly affecting signaling pathways in the tumor microenvironment. However, the microbiome in the peripheral lung tissue is unexplored and their relationship to the lung tumor microenvironment is still unknown. Thus, to explore the relationship between the microbiome and the tumor microenvironment of lung cancer, we performed shotgun metagenomic sequencing of the lung cancer tissue, especially in lung cancer patients accompanied by chronic obstructive pulmonary disease (COPD). We confirmed the presence of a diverse microbiome in peripheral lung cancer tissue. Next, we focused on individual species. We observed significant differences in the relative abundance of several species between COPD and non-COPD patients, and cancer and non-cancer tissue. Then, we focused on the metagenomic diversity between samples. The number of species in COPD patients and cancer tissue were decreased. And the bacterial total abundance in each sample were observed similar trend. On the other hand, alpha diversity in each sample were showed different trend to them. In the analysis of beta diversity using Principal Coordinate Analysis (PCoA), clusters were formed in each group. These findings suggest that microbiome imbalance known as dysbiosis in the peripheral lung tissue may affect the tumor microenvironment resulting in cancer progression. Citation Format: Atsushi Matsuoka, Kazuhiko Shien, Shuta Tomida, Daisuke Mizuno, Masayoshi Ohki, Ryo Yoshichika, Tomohiro Higashihara, Naohiro Hayashi, Fumiaki Mukohara, Mao Yoshikawa, Ken Suzawa, Hiromasa Yamamoto, Shinichi Toyooka. Shotgun metagenomics of COPD-associated lung cancer tissue microbiome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2800.

Paracrine Regulation and Immune System Pathways in the Inflammatory Tumor Microenvironment of Lung Cancer: Insights into Oncogenesis and Immunotherapeutic Strategies.

The intricate interplay between inflammatory processes and the tumor microenvironment (TME) in lung cancer has garnered increasing attention due to its implications for both oncogenesis and therapeutic strategies. In this review, we explore recent advances in understanding the paracrine regulation and immune system pathways within the inflammatory TME of lung cancer. We delve into the molecular mechanisms underpinning oncogenesis, highlighting the role of immune cell populations, cancer-associated fibroblasts, and endothelial cells, as well as their interactions through immune system pathways regulated in a paracrine pattern. Additionally, we discuss emerging immunotherapeutic strategies with a specific focus on the potential of leveraging the inflammatory TME through these pathways to enhance treatment efficacy in lung cancer.

Rab37 mediates trafficking and membrane presentation of PD-1 to sustain T cell exhaustion in lung cancer

BackgroundProgrammed cell death protein 1 (PD-1) is an immune checkpoint receptor expressed on the surface of T cells. High expression of PD-1 leads to T-cell dysfunction in the tumor microenvironment (TME). However, the mechanism of intracellular trafficking and plasma membrane presentation of PD-1 remains unclear.MethodsMultiple databases of lung cancer patients were integratively analyzed to screen Rab proteins and potential immune-related signaling pathways. Imaging and various biochemical assays were performed in Jurkat T cells, splenocytes, and human peripheral blood mononuclear cells (PBMCs). Rab37 knockout mice and specimens of lung cancer patients were used to validate the concept.ResultsHere, we identify novel mechanisms of intracellular trafficking and plasma membrane presentation of PD-1 mediated by Rab37 small GTPase to sustain T cell exhaustion, thereby leading to poor patient outcome. PD-1 colocalized with Rab37-specific vesicles of T cells in a GTP-dependent manner whereby Rab37 mediated dynamic trafficking and membrane presentation of PD-1. However, glycosylation mutant PD-1 delayed cargo recruitment to the Rab37 vesicles, thus stalling membrane presentation. Notably, T cell proliferation and activity were upregulated in tumor-infiltrating T cells from the tumor-bearing Rab37 knockout mice compared to those from wild type. Clinically, the multiplex immunofluorescence-immunohistochemical assay indicated that patients with high Rab37+/PD-1+/TIM3+/CD8+ tumor infiltrating T cell profile correlated with advanced tumor stages and poor overall survival. Moreover, human PBMCs from patients demonstrated high expression of Rab37, which positively correlated with elevated levels of PD-1+ and TIM3+ in CD8+ T cells exhibiting reduced tumoricidal activity.ConclusionsOur results provide the first evidence that Rab37 small GTPase mediates trafficking and membrane presentation of PD-1 to sustain T cell exhaustion, and the tumor promoting function of Rab37/PD-1 axis in T cells of TME in lung cancer. The expression profile of Rab37high/PD-1high/TIM3high in tumor-infiltrating CD8+ T cells is a biomarker for poor prognosis in lung cancer patients.

Multidimensional progressive single-cell sequencing reveals cell microenvironment composition and cancer heterogeneity in lung cancer.

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single-cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re-dimensional grouping of cancer-associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell-to-cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer-associated endothelial and fibroblast cells showed a co-expression relationship with myeloid cells and B cells. Through cell-to-cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB-CD8 T cells, and GZMK-CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment.

2250P Exploring tumor microenvironment in lung cancer through patient-derived 3D models

2250P Exploring tumor microenvironment in lung cancer through patient-derived 3D models

Effect of Yifei Qinghua Granule on the Tumor Microenvironment in Lung Cancer by Regulating the Inflammatory Pathway.

To investigate the mechanism of action of inflammatory molecules regulating the tumor microenvironment and anti-tumor through Yifei Qinghua granules and phloroglucinol-containing serum intervening in the changes of tumor microenvironment in vitro in the co-culture of lung cancer cells and bone marrow cells. A549 lung adenocarcinoma cell line and ST2 bone marrow stromal cell line were selected and a transwell chamber was used to establish the co-culture system of the two kinds of cells. They were divided into normal saline, phloroglucinol, Qifei Qinghua granule, and phloroglucinol + Yifei Qinghua granule groups. They were given drug-containing serum interventions respectively. A549 cells and ST2 cells cultured separately were used as control. Flow cytometry was used to detect the proportions of MDSCs and Tregs in bone marrow cells of ST2 cells. ELISA was used to detect the levels of inflammatory factors in the culture supernatant. Western blot was used to detect the expressions of inflammatory pathways in A549 and ST2 cells. ST2 cells and A549 cells were co-cultured. The ratio of MDSCs and Treg in ST2 cells was increased. The levels of some inflammatory factors in the culture supernatant were increased. The expression level of the inflammatory pathway in ST2 cells was increased. However, the expression level of the inflammatory pathway in A549 cells had no obvious change. While Yifei Qinghua granule and phloroglucinol could partially reverse these changes. The combination of the two was more effective than a single drug. The conversion of cells to MDSCs and Treg was accelerated after the co-culture of ST2 cells and A549 cells. The combination of Yifei Qinghua granules with phloroglucinol can reshape the tumor microenvironment, prevent this phenomenon from occurring, reduce inflammatory secretion and inhibit tumor cell growth. This may be related to the inhibition of the expressions of TNF-α/IL-1- and NF-κB/STAT3 inflammatory pathways.

M2 tumor-associated macrophage promoted DNA methylation in lung cancer metastasis via intensifying EZH2.

This study aimed to explore the interaction between the tumor-associated macrophage (TAM) and enhancer of zeste homolog 2 (EZH2) in tumor microenvironment of lung cancer are obscure. M2 type of TAM was induced by interleukin-4 (IL-4) and interleukin-13 (IL-13) in RAW264.7 cells. Subsequently, the co-culture system of the M2 RAW264.7 treating LLC-1 cells were constructed to evaluate the cell proliferation, migration and invasion abilities. On top of that, the M2 RAW264.7 was injected into the LLC-1 cells-bearing mice. Tumor growth and the number of metastatic nodes were observed. Moreover, DNA methylation, EZH2 expression, target genes of EZH2 and the M2 type TAM-related markers were detected in vivo and in vitro . Further experiments of EZH2 function in lung cancer were carried out by the addition of EZH2 inhibitor (GSK126) and si-EZH2. M2 type of TAM was induced with IL-4 and IL-13 with increased expression of CD206, CD68, CD163 and Arg1. Following co-culture with M2 type TAM, the proliferative, invasive, migrative abilities, tumor growth and metastasis, and the DNA methylation, EZH2 level were strengthened whereas the target genes of EZH2, including p21, CDKN2A, CDKN2B were reduced in LLC-1 cells and LLC-1 cell-bearing mice. Of note, GSK126 and si-EZH2 offset the M2 type TAM's effects, and inhibited the LLC-1 cell metastasis, DNA methylation and tumor growth. M2 type TAM promoted DNA methylation in LLC-1 cells and LLC-1 cell-bearing mice, which is related to the intensified EZH2.

Harnessing Natural Killer Cells for Lung Cancer Therapy.

Lung cancer is the leading cause of cancer-related death worldwide. Although natural killer (NK) cells are garnering interest as a potential anticancer therapy because they selectively recognize and eliminate cancer cells, their use in treating solid tumors, including lung cancer, has been limited due to impediments to their efficacy, such as their limited ability to reach tumor tissues, the reduced antitumor activity of tumor-infiltrating NK cells, and the suppressive tumor microenvironment (TME). This comprehensive review provides an in-depth analysis of the cross-talk between the lung cancer TME and NK cells. We highlight the various mechanisms used by the TME to modulate NK-cell phenotypes and limit infiltration, explore the role of the TME in limiting the antitumor activity of NK cells, and discuss the current challenges and obstacles that hinder the success of NK-cell-based immunotherapy for lung cancer. Potential opportunities and promising strategies to address these challenges have been implemented or are being developed to optimize NK-cell-based immunotherapy for lung cancer. Through critical evaluation of existing literature and emerging trends, this review provides a comprehensive outlook on the future of NK-cell-based immunotherapy for treating lung cancer.

E-cadherin expression in the tumor microenvironment of advanced epidermal growth factor receptor-mutant lung adenocarcinoma and the association with prognosis

BackgroundThe expression of programmed death-ligand 1 (PD-L1), tumor-infiltrating lymphocytes (TILs), E-cadherin, and vimentin in lung cancer tumor microenvironment is known to impact patient survival or response to therapy. The expression of these biomarkers may also differ between primary lung tumors and brain metastatic tumors. In this study, we investigated the interaction between these biomarkers in lung tumors with or without concomitant brain metastasis and the interaction with paired brain metastatic tumors.MethodsThe study included 48 patients with stage IV epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. Sixteen of the forty-eight patients were diagnosed with brain metastasis, while the remaining thirty-two were not. All sixteen patients with brain metastasis had brain tumors. The expression of PD-L1, TILs (CD8+ T lymphocytes and FOXP3+ regulatory T lymphocytes), E-cadherin, and vimentin were evaluated using immunohistochemical (IHC) staining.ResultsPatients with brain metastasis exhibited a higher frequency of exon 19 deletion and uncommon EGFR mutations, a higher lung tumor vimentin score, worse progression-free survival (PFS), and overall survival (OS) than patients without brain metastasis. IHC staining showed no difference between paired lung and brain tumors. Patients with low PD-L1 expression had better PFS and OS. After multivariate analysis, higher body mass index, the presence of brain metastasis, bone metastasis, and uncommon EGFR mutations were correlated with worse PFS, while the presence of brain metastasis and high lung tumor E-cadherin score was associated with worse OS.ConclusionsIn patients with stage IV EGFR-mutant lung adenocarcinoma, high E-cadherin expression in the lung tumor might be associated with worse OS. Vimentin expression in the lung tumor was positively related to the risk of brain metastasis.

Using machine learning to characterize lung cancer microenvironment and the development of a model to predict the presence of similar microenvironment in other cancers.

2634 Background: Poor response to immune checkpoint inhibitors (ICI) in colorectal cancer (CRC) is believed to be due to lack of immune suppressive tumor microenvironment (TME). In contrast, lung cancer TME is believed to be significantly more immunologically active and responsible for the relative success of ICI in lung cancer. We evaluated the TME in lung cancer and CRC using 43 immune biomarkers quantified using RNA sequencing and developed a model to classify TME into immunologically active (similar to lung cancer) vs inactive (similar to colorectal). These 43 immune biomarkers included B- and T-cell markers, cytokines and chemokines. Methods: RNA was extracted from FFPE samples from 707 patients with lung cancer, 227 patients with CRC, 131 patients with breast cancer, 111 patients with ovarian cancer, and 72 patients with pancreatic cancer. The expression levels of the 42 immunological markers were quantified using next generation sequencing (NGS) as a part of larger targeted RNA sequencing panel of 1408 genes. Using a machine learning algorithm, we first selected the relative genes that distinguish between two classes using two criteria: performance of each gene with K-fold cross-validation (K=12) and second based on stability measure using statistical significance tests. The selected genes were then used to predict one class from the other using random forest classifier. Samples were divided into a training set (67%) and testing set (33%). Results: A Bayesian-based algorithm selected the expression of 20 genes that were significantly relevant in differentiating between immunologically active and inactive TME. Using these 20 genes in Random Forest model, we can distinguish between lung and CRC with AUC of 0.997 (95% CI: 0.992-1.00) in the training set and AUC of 0.923 (95% CI: 0.880-0.966) in the testing set. Testing 131 breast cancer samples showed 23 (18%) with TME that can be classified as immunologically active. Of 111 ovarian samples 13 (12%) showed immunologically active TME and of 72 pancreatic samples, 17 (24%) showed microenvironment classified as active. The 20 genes that were adequate to distinguish between TME active vs inactive are: CD74, FCGBP, IL1R1, CD44, CD274, FCGR2B, IL21R, IL1RAP, IL7R, CD79A, CCL2, CYFIP2, CD19, IL2RA, CD8A, CD79B, ID1, CD22, FZD10, and IL1B, listed in order of their importance. Conclusions: This data shows that lung cancer TME is significantly different from that of CRC. Only 20 immune biomarkers adequate to distinguish between the two TME. The relevant biomarkers included CD274 (PD-L1) as well as one marker for T-cells (CD8A) but three markers for B-cells (CD19, CD22 and CD79B). This suggests that B-cells play a significant role in immunologically active TME and should be explored further as biomarkers for predicting response to ICI therapy.

Abstract 3138: Topological analysis of spatial transcriptomics reveals different spatial interaction patterns in tumor microenvironment of lung cancer

Abstract Background: As the tumor microenvironment (TME) consists of various cell types with complex spatial interaction, its spatial organization patterns affect response to immune-oncology treatment. Therefore, describing the spatial composition and interaction of cells in the tumor microenvironment (TME) is necessary. Here, we developed a tool, STopover, which adopts topological analysis in spatial transcriptomics to reveal cell-cell colocalization patterns in TME and capture the key components and niche of intercellular communication, and applied it to human lung cancer data. Methods: The spatial colocalization pattern of pairs of features was defined using topological data analysis with Morse filtration. The spatial network of spatial gene expression data was generated for each sample and then the patterns were summarized as connected components (CCs) based on the spatial distance between unit tissue regions and the persistence of each CC. The global and local extent of spatial overlap of a feature pair was calculated as Jaccard indices between extracted CC pairs. We applied STopover to 11 barcode-based spatial transcriptomic data of human lung adenocarcinoma with different PD-L1 expressions. Spatial mapping of cell types in TME was performed by CellDART. In addition, image-based spatial transcriptomic data of lung cancer were also used to find key spatial molecular interactions in TME using STopover. Results: First, STopover disclosed the distinct immune and stromal infiltration patterns in lung cancer tissues. Spatial colocalization of cancer cells and T-cells was heterogeneous and correlated with the immune-related markers such as MHC class I signature. The cancer types were clustered according to spatial colocalization patterns of various immune cells with cancer cells, which showed different infiltration patterns of immune cells. Moreover, STopover could estimate the top cell-cell interaction and emphasize the key locations based on the literature-supported ligand-receptor database. Conclusion: STopover is expected to account for significant spatial cell interactions in tumor-immune and tumor-stromal components and could be utilized as a platform to decipher the mechanisms underlying immune-oncology treatment response. Citation Format: Sungwoo Bae, Hyekyoung Lee, Kwon Joong Na, Dong Soo Lee, Hongyoon Choi, Young Tae Kim. Topological analysis of spatial transcriptomics reveals different spatial interaction patterns in tumor microenvironment of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3138.

Abstract 5943: Plasma cell repertoire in the lung cancer tumor microenvironment

Abstract Background: Post-operative recurrence in lung cancer continues to pose a major clinical challenge. B cell and plasma cell presence has been shown to correlate with improved survival and lower relapse rates in solid cancers and with improved response to checkpoint blockade. The aim of this study was to identify distinct immune cell compositions in the circulation and tumor microenvironment and make correlations with clinical and disease specific outcomes. Methods: In this study, utilizing high-dimensional deep immunophenotyping techniques (mass cytometry), multispectral immunofluorescence based imaging and bulk RNA sequencing, we explored the B cell repertoire in the circulation and tumor microenvironment in early-stage lung cancer patients undergoing radical surgical resection. Results: We demonstrate using high-dimensional deep phenotyping, clear differences in B cell composition between the circulation and the intratumoural microenvironment. Intratumoural predominant populations include plasma cells, from CD38var immature to CD138+ mature cells. B cells undergoing germinal center and follicular maturation as well as class-switched memory cells were predominantly found in the circulation. Eight key populations were significantly differentially abundant between compartments on generalized linear mixed modelling (p<0.0001 with BH correction). These differences were observed in an external validation set. Plasma cell infiltration existed on a phenotypic spectrum from natural regulatory suppressive cells to antibody producing effector phenotypes. The latter correlating with better outcomes. Higher B cell expression of CD138 and Ig was noted within the tumor microenvironment in patients who did not experience early relapse. Significantly higher levels of circulating ki67+ CD27hi CD38hi CD95hi IL10int plasmablasts were noted in recurrence patients (p=0.02). Geospatial mapping identified clusters of suppressive plasma cells localized to the tumor stroma, likely regulating entry of effector cells into the tumor nest. Conclusions: Our data has demonstrated the unique roles of effector and suppressive B cell subsets in NSCLC and the clear difference in surrogacy between tissue compartments. The lesser infiltration of suppressive phenotypes into the tumor nest may be to prevent the subsequent infiltration of effector plasma and effector B cells into the tumor nest. This tumor line of defense would be in keeping with the observation that higher levels of suppressive B cell subsets in the circulation links to higher rates of recurrence and a higher tumor effector plasma cell infiltrate correlates with protection against recurrent disease. The ambiguous role of B cells in the tumor environment predetermines the multidirectional development of immunotherapeutic approaches, either supporting positive B cell types or inhibiting the suppressive B cell phenotypes. Citation Format: Akshay J. Patel, Naeem Khan, Alex G. Richter, Babu Naidu, Mark T. Drayson, Gary W. Middleton. Plasma cell repertoire in the lung cancer tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5943.

Nanoparticles overcome adaptive immune resistance and enhance immunotherapy via targeting tumor microenvironment in lung cancer.

Lung cancer is one of the common malignant cancers worldwide. Immune checkpoint inhibitor (ICI) therapy has improved survival of lung cancer patients. However, ICI therapy leads to adaptive immune resistance and displays resistance to PD-1/PD-L1 blockade in lung cancer, leading to less immune response of lung cancer patients. Tumor microenvironment (TME) is an integral tumor microenvironment, which is involved in immunotherapy resistance. Nanomedicine has been used to enhance the immunotherapy in lung cancer. In this review article, we described the association between TME and immunotherapy in lung cancer. We also highlighted the importance of TME in immunotherapy in lung cancer. Moreover, we discussed how nanoparticles are involved in regulation of TME to improve the efficacy of immunotherapy, including Nanomedicine SGT-53, AZD1080, Nanomodulator NRF2, Cisplatin nanoparticles, Au@PG, DPAICP@ME, SPIO NP@M-P, NBTXR3 nanoparticles, ARAC nanoparticles, Nano-DOX, MS NPs, Nab-paclitaxel, GNPs-hPD-L1 siRNA. Furthermore, we concluded that targeting TME by nanoparticles could be helpful to overcome resistance to PD-1/PD-L1 blockade in lung cancer.

First Author Highlights

AnnouncementFirst Author HighlightsPublished Online:17 Mar 2023https://doi.org/10.1152/ajprenal.2023.324.3.AUMoreSectionsPDF (404 KB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInWeChat MOLLY BINGHAMSystems Biology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United StatesFigure 1.Molly BinghamDownload figureDownload PowerPointMolly Bingham is a Postbaccalaureate Research Fellow at the National Cancer Institute. As an intern in the National Institute of Health’s 2021 Biomedical Engineering Summer Internship Program (led by Dr. Robert Lutz), she was mentored by Dr. Mark Knepper and studied circadian changes in gene expression in the kidney proximal tubule. Currently, Molly is investigating the tumor microenvironment in lung cancer under the mentorship of Dr. Chen Zhao. She hopes to pursue a career as a physician-scientist. When not in the laboratory or analyzing data, Molly enjoys cooking and spending time outdoors [Photo: Fig. 1].https://doi.org/10.1152/ajprenal.00231.2022JEROEN H. F. DE BAAIJDepartment of Physiology, Radboud University Medical Center, Nijmegen, The NetherlandsFigure 2.Jeroen de BaaijDownload figureDownload PowerPointJeroen de Baaij is an Associate Professor in renal physiology at the Radboud University Medical Center in Nijmegen, The Netherlands. His research focusses on the identification and characterization of new genes involved in renal magnesium reabsorption. Using a wide range of molecular, cellular, and physiological techniques, he examines new genes or new regulatory pathways in magnesium (re)absorption in the kidney. In his spare time, he writes about art and visits museums [Photo: Fig. 2].https://doi.org/10.1152/ajprenal.00298.2022KYLE DICKINSONDivision of Experimental Medicine, McGill University, Montreal, Quebec, CanadaFigure 3.Kyle DickinsonDownload figureDownload PowerPointKyle Dickinson is a researcher and laboratory manager in Dr. Julia Burnier’s laboratory at McGill University. He completed his PhD in Dr. Paul Goodyer’s laboratory in Experimental Medicine at McGill University. During his PhD, his research focused on understanding key signalling and DNA damage response pathways active in nephron progenitor cells during kidney development. His current research focuses on using liquid biopsy for cancer detection and monitoring treatment responses. Away from the laboratory bench, he enjoys sports, video games, and horror movies [Photo: Fig. 3].https://doi.org/10.1152/ajprenal.00207.2022MACKENZIE KUIDepartment of Physiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United StatesFigure 4.Mackenzie KuiDownload figureDownload PowerPointMackenzie Kui is currently a third-year PhD student in Jennifer Pluznick’s laboratory at Johns Hopkins University. Mackenzie earned his Bachelor’s degree from the University of California-Santa Barbara, where he studied germline stem cell longevity in Drosophila diapause. After graduating, he worked as a Research Associate at City of Hope and then later at Oncovalent Therapeutics in small molecule discovery. Outside of the laboratory, Mackenzie enjoys climbing, volleyball, and swing dancing [Photo: Fig. 4].https://doi.org/10.1152/ajprenal.00272.2022ANDREW ORWICKDepartment of Pharmacology and Toxicology, University of Louisville, Louisville, KentuckyFigure 5.Andrew OrwickDownload figureDownload PowerPointAndrew Orwick is a PhD student in the Department of Pharmacology and Toxicology at the University of Louisville, mentored by Dr. Leah Siskind. He earned his PharmD from Sullivan University and practiced as a pharmacist for a number of years before deciding to go back to graduate school to obtain a PhD in the biomedical sciences. His PhD studies in chemotherapy-induced nephrotoxicity are supported by a National Institutes of Health National Institute of Diabetes and Digestive and Kidney Diseases F31 predoctoral fellowship. Andrew hopes to have his own research laboratory in academia one day. In his spare time, he enjoys playing soccer and spending time with his wife and two daughters [Photo: Fig. 5].https://doi.org/10.1152/ajprenal.00317.2022This article has no references to display. Download PDF Back to Top Next FiguresReferencesRelatedInformation Related ArticlesCircadian gene expression in mouse renal proximal tubule 01 Mar 2023American Journal of Physiology-Renal PhysiologyMagnesium reabsorption in the kidney 17 Feb 2023American Journal of Physiology-Renal PhysiologyWT1 regulates expression of DNA repair gene Neil3 during nephrogenesis 17 Feb 2023American Journal of Physiology-Renal PhysiologyThe transcription factor Foxi1 promotes expression of V-ATPase and Gpr116 in M-1 cells 17 Feb 2023American Journal of Physiology-Renal PhysiologyLung cancer-kidney cross talk induces kidney injury, interstitial fibrosis, and enhances cisplatin-induced nephrotoxicity 01 Mar 2023American Journal of Physiology-Renal Physiology More from this issue > Volume 324Issue 3March 2023Pages i-ii Crossmark Copyright & PermissionsCopyright © 2023 the American Physiological Society.https://doi.org/10.1152/ajprenal.2023.324.3.AUPubMed36929919History Published online 17 March 2023 Published in print 1 March 2023 Metrics

Generation and analysis of context-specific genome-scale metabolic models derived from single-cell RNA-Seq data

Single-cell RNA sequencing combined with genome-scale metabolic models (GEMs) has the potential to unravel the differences in metabolism across both cell types and cell states but requires new computational methods. Here, we present a method for generating cell-type-specific genome-scale models from clusters of single-cell RNA-Seq profiles. Specifically, we developed a method to estimate the minimum number of cells required to pool to obtain stable models, a bootstrapping strategy for estimating statistical inference, and a faster version of the task-driven integrative network inference for tissuesalgorithm for generating context-specific GEMs. In addition, we evaluated the effect of different RNA-Seq normalization methods on model topology and differences in models generated from single-cell and bulk RNA-Seq data. We applied our methods on data from mouse cortex neurons and cells from the tumor microenvironment of lung cancer and in both cases found that almost every cell subtype had a unique metabolic profile. In addition, our approach was able to detect cancer-associated metabolic differences between cancer cells and healthy cells, showcasing its utility. We also contextualized models from 202 single-cell clusters across 19 human organs using data from Human Protein Atlas and made these available in the web portal Metabolic Atlas, thereby providing a valuable resource to the scientific community. With the ever-increasing availability of single-cell RNA-Seq datasets and continuously improved GEMs, their combination holds promise to become an important approach in the study of human metabolism.

Therapeutic Targeting of Cancer-Associated Fibroblasts in the Non-Small Cell Lung Cancer Tumor Microenvironment.

Lung cancer is the most frequently diagnosed cancer and the leading cause of cancer death worldwide. The most common lung cancer is non-small cell lung cancer (NSCLC), with an overall 5-year survival rate of around 20% because NSCLC is a metastatic disease. A better understanding of the mechanism underlying lung cancer metastasis is therefore urgently needed. The tumor microenvironment involves different types of stromal cells and functions as key components in the progression of NSCLC. Through epithelial-mesenchymal transition (EMT), in which epithelial cells lose their polarity and acquire mesenchymal potential, cancer cells acquire metastatic abilities, as well as cancer stem-cell-like potential. We previously reported that cancer-associated fibroblasts (CAFs) interact with lung cancer cells to allow for the acquisition of malignancy and treatment resistance by paracrine loops via EMT signals in the tumor microenvironment. Furthermore, CAFs regulate the cytotoxic activity of immune cells via various cytokines and chemokines, creating a microenvironment of immune tolerance. Regulation of CAFs can therefore affect immune responses. Recent research has shown several roles of CAFs in NSCLC tumorigenesis, owing to their heterogeneity, so molecular markers of CAFs should be elucidated to better classify tumor-promoting subtypes and facilitate the establishment of CAF-specific targeted therapies. CAF-targeted cancer treatments may suppress EMT and regulate the niche of cancer stem cells and the immunosuppressive network and thus may prove useful for NSCLC treatment through multiple mechanisms.

EGFR-Tyrosine Kinase Inhibitors Induced Activation of the Autocrine CXCL10/CXCR3 Pathway through Crosstalk between the Tumor and the Microenvironment in EGFR-Mutant Lung Cancer

CXCL10 is a cytokine that is elevated during EGFR-TKI treatment in the tumor microenvironment of lung cancer. Here, we report an original study that the impact of the CXCL10/CXCR3 pathway on EGFR-TKI resistance in EGFR-mutant lung cancer through a cytokine array analysis during in vitro coculture with tumor cells and activated PBMCs treated with EGFR-TKI, as well as the serial analysis of CXCL10 in EGFR-mutant lung cancer transgenic mice during EGFR-TKI treatment. In EGFR-mutant tumor cells cocultured with activated PBMCs, EGFR-TKI treatment increased CXCL10 in the supernatant; this activated CXCR3 in the tumor cells to induce the phosphorylation of Src and the NF-κB subunit, p65, and the expression of HIF-1α. CXCL10 siRNA treatment of EGFR-mutant tumor cells also decreased CXCL10 in the supernatant from coculturing with activated PBMCs, suggesting that the effects of CXCL10 occur via autocrine and paracrine pathways. Importantly, elevated CXCL10/CXCR3 signaling was recapitulated in a transgenic lung cancer mouse model. Our results show that increased CXCL10 levels during early EGFR-TKI treatment stimulate oncogenic signaling of persistent tumor cells to contribute to EGFR-TKI resistance via autocrine and paracrine pathways.

Immunotherapy and targeted therapy for lung cancer: Current status and future perspectives.

Lung cancer has the highest incidence of morbidity and mortality throughout the globe. A large number of patients are diagnosed with lung cancer at the later stages of the disease. This eliminates surgery as an option and places complete dependence on radiotherapy or chemotherapy, and/or a combination of both, to halt disease progression by targeting the tumor cells. Unfortunately, these therapies have rarely proved to be effective, and this necessitates the search for alternative preventive approaches to reduce the mortality rate of lung cancer. One of the effective therapies against lung cancer comprises targeting the tumor microenvironment. Like any other cancer cells, lung cancer cells tend to use multiple pathways to maintain their survival and suppress different immune responses from the host's body. This review comprehensively covers the role and the mechanisms that involve the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) in lung adenocarcinoma and methods of treating it by altering the tumor microenvironment. It focuses on the insight and understanding of the lung cancer tumor microenvironment and chemokines, cytokines, and activating molecules that take part in angiogenesis and metastasis. The review paper accounts for the novel and current immunotherapy and targeted therapy available for lung cancer in clinical trials and in the research phases in depth. Special attention is being paid to mark out single or multiple genes that are required for malignancy and survival while developing targeted therapies for lung cancer treatment.

Molecular profiling of human non-small cell lung cancer by single-cell RNA-seq

BackgroundLung cancer, one of the most common malignant tumors, exhibits high inter- and intra-tumor heterogeneity which contributes significantly to treatment resistance and failure. Single-cell RNA sequencing (scRNA-seq) has been widely used to dissect the cellular composition and characterize the molecular properties of cancer cells and their tumor microenvironment in lung cancer. However, the transcriptomic heterogeneity among various cancer cells in non-small cell lung cancer (NSCLC) warrants further illustration.MethodsTo comprehensively analyze the molecular heterogeneity of NSCLC, we performed high-precision single-cell RNA-seq analyses on 7364 individual cells from tumor tissues and matched normal tissues from 19 primary lung cancer patients and 1 pulmonary chondroid hamartoma patient.ResultsIn 6 of 16 patients sequenced, we identified a significant proportion of cancer cells simultaneously expressing classical marker genes for two or even three histologic subtypes of NSCLC—adenocarcinoma (ADC), squamous cell carcinoma (SCC), and neuroendocrine tumor (NET) in the same individual cell, which we defined as mixed-lineage tumor cells; this was verified by both co-immunostaining and RNA in situ hybridization. These data suggest that mixed-lineage tumor cells are highly plastic with mixed features of different types of NSCLC. Both copy number variation (CNV) patterns and mitochondrial mutations clearly showed that the mixed-lineage and single-lineage tumor cells from the same patient had common tumor ancestors rather than different origins. Moreover, we revealed that patients with high mixed-lineage features of different cancer subtypes had worse survival than patients with low mixed-lineage features, indicating that mixed-lineage tumor features were associated with poorer prognosis. In addition, gene signatures specific to mixed-lineage tumor cells were identified, including AKR1B1. Gene knockdown and small molecule inhibition of AKR1B1 can significantly decrease cell proliferation and promote cell apoptosis, suggesting that AKR1B1 plays an important role in tumorigenesis and can serve as a candidate target for tumor therapy of NSCLC patients with mixed-lineage tumor features.ConclusionsIn summary, our work provides novel insights into the tumor heterogeneity of NSCLC in terms of the identification of prevalent mixed-lineage subpopulations of cancer cells with combined signatures of SCC, ADC, and NET and offers clues for potential treatment strategies in these patients.

Glutathione peroxidase 8 expression on cancer cells and cancer-associated fibroblasts facilitates lung cancer metastasis.

Lung cancer is the leading cause of cancer death worldwide, of which lung adenocarcinoma (LUAD) is the most common subtype. Metastasis is the major cause of poor prognosis and mortality for lung cancer patients, which urgently needs great efforts to be further explored. Herein, glutathione peroxidase 8 (GPX8) was identified as a novel potential pro‐metastatic gene in LUAD metastatic mice models from GEO database. GPX8 was highly expressed in tumor tissues, predicting poor prognosis in LUAD patients. Knockdown of GPX8 inhibited LUAD metastasis in vitro and in vivo, while it did not obviously affect tumor growth. Knockdown of GPX8 decreased the levels of p‐FAK and p‐Paxillin and disturbed the distribution of focal adhesion. Furthermore, GPX8 was overexpressed in cancer‐associated fibroblast (CAF) and associated with CAF infiltration in tumor microenvironment of lung cancer. GPX8 silence on fibroblasts suppressed lung cancer cell migration in the coculture system. BRD2 and RRD4 were the potential transcriptionally regulators for GPX8. Bromodomain extra‐terminal inhibitor JQ1 downregulated GPX8 expression and suppressed lung cancer cell migration. Our findings indicate that highly expressed GPX8 in lung cancer cells and fibroblasts functions as a pro‐metastatic factor in lung cancer. JQ1 is identified as a potential inhibitor against GPX8‐mediated lung cancer metastasis.