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1Department of Orthopedics, The 923rd Hospital of the Joint Logistics Support Force of the Peoples Liberation Army, Nanning, Peoples Republic of China; 2Department of Orthopedics, Peoples Hospital of Guilin, Guilin, Guangxi, 541001, Peoples Republic of China; 3Department of Orthopedics, Fifth Clinical Medical College, Guilin Medical University, Guilin, Guangxi, 541001, Peoples Republic of China; 4Department of Orthopedics, The Tenth Peoples Hospital of Nanning, Nanning, Guangxi, 530105, Peoples Republic of China

Correspondence: Bo LvPeoples Hospital of Guilin, 12 Wenming Road, Guilin, Guangxi, 541001, Peoples Republic of ChinaTel +867738997962Email [emailprotected]

Purpose: Osteosarcoma is the most common malignant bone cancer affecting adolescents and young adults. This study aimed to screen potential diagnostic and therapeutic markers for osteosarcoma.Methods: Differential expression analysis between osteosarcoma and control was performed in GSE99671, the differentially expressed genes (DEGs) were subjected to co-expression analysis. Enrichment analysis was employed to identify the biological functions and KEGG signaling pathways of module genes. In addition, a differential analysis was also performed between recurrent and non-recurrent osteosarcoma samples in GSE39055, and enrichment analysis was performed for DEGs. Further, KaplanMeier curve analysis was performed on the module genes, and receiver operating characteristic (ROC) curve was drawn. Comparison of the module with the highest correlation to osteosarcoma identified key genes. Cox regression model was utilized to identify the predictive ability of key genes for the prognosis of osteosarcoma.Results: A total of 13 co-expression modules were identified from 4871 DEGs of GSE99671, module 1 had the highest positive correlation with osteosarcoma. Module genes were mainly enriched in autophagy and macrophage migration functions. A total of 1126 DEGs were obtained from GSE39055, significantly involved in neutrophil mediated immunity. Screening of genes with area under the ROC curve (AUC) values greater than 0.73 in both GSE99671 and GSE39055 identified 5 key genes when compared with genes from module 1. The nomogram results showed that ATF5, CHCHD8, ENOPH1, and LOC286367 might predict 5-year or 8-year survival time of osteosarcoma patients. The Cox model results confirmed that the signals of ATF5, CHCHD8, and LOC286367 were robust, and it may be used in the diagnosis, treatment, and prognosis of osteosarcoma.Conclusion: We found that ATF5, CHCHD8, and LOC286367 can effectively identify osteosarcoma tumorigenesis and even recurrence status. This is helpful for early diagnosis and treatment, improving the clinical treatment of patients with osteosarcoma.

Keywords: osteosarcoma, predictive biomarkers, recurrence, weighted co-expressed network analysis

Osteosarcoma is the most common primary bone malignancy, mainly affecting children and young adults.1 Osteosarcoma consists of malignant osteoblasts producing immature bone and bone tissue.2 Although standard treatment with surgical resection and adjuvant chemotherapy has significantly improved the 5-year survival rate of osteosarcoma patients to approximately 6070%, no significant progress has been made in improving the survival rate of patients with recurrence or metastasis over the past 30 years.3,4 The lack of understanding of the molecular mechanisms underlying the occurrence and recurrence of osteosarcoma has severely hampered improved patient survival. When diagnosed, 40% of metastases occur in patients with advanced osteosarcoma.5 Therefore, elucidating the functions of osteosarcoma-related genes and exploring the possible pathological mechanisms of osteosarcoma initiation, development and recurrence are crucial for the future detection and treatment of osteosarcoma.

Depending on the histological morphology, three main categories can be distinguished: high-grade, which includes most subtypes, and intermediate and low-grade, which include periosteal and periosteal.6 Conventional osteosarcoma refers to high-grade tumors with intramedullary growth and is the most common type, accounting for 85% of all osteosarcoma cases during childhood and adolescence.7 The osteosarcoma tumor microenvironment is composed of osteosarcoma cells, osteocytes, stromal cells, vascular cells, immune cells, and the extracellular matrix (ECM).8 This creates a complex environment for tumor growth. More immune infiltration is found in osteosarcoma tumors to promote a local immune tolerant environment.9 Given the close connection between bone tissue and the immune system, it has been speculated that osteosarcoma may use similar mechanisms to evade immune recognition.10

With the development of molecular biology technology, tumor gene therapy for osteosarcoma has potential clinical applications.11,12 Accumulating evidence indicates that the occurrence, development and prognosis of osteosarcoma are closely related to molecular mechanisms.13,14 Through high-throughput sequencing, gene expression in osteosarcoma can be compared to normal samples, leading to an initial selection of potential targets for anticancer therapy.15 This also includes some common long non-coding RNAs (lncRNAs).16

This study aimed to discover the occurrence- or recurrence-related potential markers according to the osteosarcoma-related gene expression profiles in Gene Expression Omnibus (GEO) database. Multiple differentially expressed genes (DEGs) were screened using the weighted gene co-expression network analysis (WGCNA) algorithm. The main signaling pathways of osteosarcoma were analyzed by Gene Ontology (GO), function and Kyoto Encyclopedia of genes (KEGG) pathways. Subsequently, KaplanMeier and Cox models were utilized to screen the key genes related to the prognosis of osteosarcoma. The findings may provide new biomarkers and therapeutic target molecules for the occurrence and recurrence of osteosarcoma.

Osteosarcoma data were collected from the gene expression omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo) databases. GSE99671 included mRNA expression profiling of fresh-frozen bone samples from 18 tumoral samples and 18 non-tumoral paired samples by high throughput sequencing.17,18 The raw data were standardized and normalized through R package DEseq2;19 then, the gene expression profile was provided in Table S1. GSE39055 included mRNA expression profiling of formalin-fixed, paraffin-embedded (FFPE) samples from 37 unique diagnostic biopsy specimens of osteosarcoma with (n=18) or non-recurrence (n=19) by array.20 Expression data were processed using the R package lumi21 and provided in Table S2. All data were obtained from an open-access database, thus, acquiring ethical approval was not necessary.

Next, the DEseq2 package was used to identify differentially expressed genes (DEGs) in osteosarcoma (n = 18) and healthy controls (n = 18) in GSE99671 data. The limma package22 was used to screen DEGs between the recurrent osteosarcoma and non-recurrent osteosarcoma in GSE39055 data. P < 0.05 was set as the screening condition. The expression of DEGs was visualized with volcano plots.

The coexpression network for DEGs in GSE99671 was performed using Weighted correlation network analysis (WGCNA) by WGCNA R package.23 The samples were used to construct scale-free topology networks, and all gene adjacencies were calculated to make a topological overlap matrix (TOM). The soft-thresholding power was chosen and used as the correlation coefficient threshold. Then, a minimum number of genes in the modules were built. The expression pattern of eigengene in each module is condensed into module eigengene (ME). Genes in MEs were considered had similar expression patterns. The moduletrail relationships were demonstrated using Pearson correlation analysis.

The biological process (BP) in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for module genes or DEGs in GSE39055 were performed using R software package clusterProfiler.24 Gene set variation analysis (GSVA) was carried out using the GSVA package.25 For each sample, a score for the enrichment of a set of genes using gene expression profile was obtained. A P value < 0.05 was considered statistical significance. The R package clusterProfiler was used to obtain the background set for gene set enrichment analysis (GSEA). GSEA runs in Java environment and conducted between osteosarcoma and control samples.

KaplanMeier (K-M) survival analysis with the R package survival was applied to identify overall survival (OS) associated genes among the module genes. Prognostic relevant genes among the key genes were determined using Cox regression analysis in a survival package based on gene expression values and survival status data. P < 0.05 was considered to be a statistically significant difference. Based on the correlation coefficients of the risk model, a formula for calculating the prognostic risk score for each patient was established. According to the median value of the risk score, patients were divided into high- and low-risk groups.

To evaluate whether the identified survival-related genes have significant diagnostic value for osteosarcoma or recurrent osteosarcoma, we performed ROC analysis using the R software package pROC.26 The area under the ROC curve (AUC) was calculated for each gene. The diagnostic accuracy of key biomarkers was evaluated using AUC values. Here, this gene can distinguish osteosarcoma from healthy individuals or recurrent osteosarcoma from non-recurrent osteosarcoma when the AUC value is greater than 0.6.

The marker gene expression information for immune cell types was obtained by Bindea et al.27 The infiltration scores of immune cells were calculated using ssGSEA in GSVA R software package. Correlations between immune cells and key genes were calculated using Pearson correlation. P value <0.05 was considered significant.

The flowchart of this study is shown in Figure 1. To identify differences in gene expression between osteosarcoma and controls, we performed a differential analysis of the osteosarcoma and control groups in GSE99671. Using threshold screening, we obtained 4871 differentially expressed genes (DEGs) between osteosarcoma and controls (Figure 2A). The co-expression behaviors of these genes were identified by performing WGCNA on the DEGs. To ensure that the coexpression network could obey the scale-free criterion, we selected = 9 as a soft-thresholding (Figure 2B). We identified a total of 13 coexpression modules (Figure 2C). Pearson correlation analysis showed that MEturquoise (M1) had the highest positive correlation with osteosarcoma (Figure 2D).

Figure 1 The flowchart of this study. The GSE99671 data and GSE39055 data were used to identify potential biomarkers related to the occurrence and recurrence of osteosarcoma. The module genes identified in GSE99671 were used to evaluate their prognostic and diagnostic value in GSE39055. Further screening of key genes may be a target for diagnosis and treatment of osteosarcoma.

Abbreviations: WGCNA, weighted gene co-expression network analysis; GSEA, gene set enrichment analysis; ROC, receiver operating characteristic curve; AUC, area under the ROC curve.

Figure 2 Coexpression modules of differentially expressed genes. (A) The differentially expressed genes between osteosarcoma and controls in GSE99671. (B) The scale-free fit index and the mean connectivity for various soft-thresholding powers. (C) Common genes were identified for thirteen coexpression modules by WGCNA. (D) Correlations between modules and clinical trait were analyzed by Pearson correlation.

To identify the biological roles of module genes, we performed enrichment analysis. It was found that module genes were significantly enriched in activated positive regulation of macrophage migration, chaperone mediated autophagy, MHC protein complex assembly biological processes; and inhibited neutrophil aggregation, regulation of vascular permeability, regulation of cell killing in osteosarcoma (Figure 3A). Using KEGG enrichment results, we found that activated HIF-1 signaling pathway, PI3K-Akt signaling pathway, and autophagy animal were significantly enriched by module genes, and inhibited B cell receptor signaling pathway, Rap1 signaling pathway, and ECM receptor interaction were also significantly enriched in osteosarcoma (Figure 3B). GSEA results showed that protein export, RNA polymerase, and proteasome were significantly enriched in osteosarcoma, primary immunodeficiency, PPAR signaling pathway, and neutrophil extracellular trap formation were significantly enriched in control samples (Figure 3C).

Figure 3 Biological functions of module gene enrichment. (A) Module genes significantly enriched for activated and inhibited biological processes. (B) Module genes significantly enriched for activated and inhibited KEGG pathway. (C) The activated and inhibited KEGG pathways in GSEA of module genes involved. P < 0.05 was considered statistically significant.

Abbreviation: GSVA, gene set variation analysis.

To identify molecular alterations associated with osteosarcoma recurrence, we performed a differential analysis of recurrent and non-recurrent osteosarcoma gene expression in GSE39055. A total of 1126 differentially expressed genes were obtained (Figure 4A). In GO enrichment results, the activated neutrophil mediated immunity, skeletal muscle fiber differentiation, response to iron (III) ion and inhibited neutrophil apoptotic process, leukocyte homeostasis, mitochondrial organization were significantly enriched by differentially expressed genes (Figure 4B). KEGG enrichment results identified that the differentially expressed genes were significantly involved in the activated endocrine resistance, oxidative phosphorylation, renin angiotensin system; and inhibited p53 signaling pathway, cell cycle, FOXO signaling pathway in recurrent osteosarcoma (Figure 4C).

Figure 4 The potential molecular changes in osteosarcoma recurrence. (A) Volcano plot of differentially expressed genes between recurrent osteosarcoma and non-recurrent osteosarcoma. Red for activated and green for inhibited. The four genes with the largest fold change of activated or inhibited were labeled. (B) Differentially expressed genes involved in activated and inhibited biological processes quantified by gene set variation analysis (GSVA). The longer the column, the more genes involved in this term. (C) Differentially expressed genes involved in activated and inhibited KEGG pathway quantified by gene set variation analysis (GSVA). The longer the column, the more genes involved in this term.

Abbreviation: BP, biological processes.

From the survival information of 37 osteosarcoma patients obtained from GSE39055, we found that the patients 5-year overall survival (OS) was 35% (Figure 5A). The survival probability increased per year already survival related to the total survival time. To identify key genes involved in the prognosis of osteosarcoma, we performed KM curve analysis of module genes. Among the module genes, we identified 262 genes that significantly affected osteosarcoma survival. By plotting the ROC curves of these survival-related genes, we screened for genes with AUC values greater than 0.73 in both GSE99671 and GSE39055 (Figure 5B). Including AEBP1, ATF5, CHCHD8, DYRK3, ENOPH1, GMIP, LOC286367, PKP4, R3HDM1, TRIM66, and ZMYND17. They were also differentially expressed genes in GSE39055 and thus may predict both osteosarcoma occurrence and recurrence. In addition, five genes (ATF5, CHCHD8, ENOPH1, LOC286367, and R3HDM1) were identified as potentially most strongly associated with osteosarcoma by contrasting with the gene for module 1. They were identified as key genes. Nomograms were constructed using Cox regression analysis results, and differential expression of ATF5, CHCHD8, ENOPH1, and LOC286367 could predict 5 - and 8-year OS of osteosarcoma patients (Figure 5C).

Figure 5 Screening of key genes predicting the occurrence and recurrence of osteosarcoma. (A) KaplanMeier estimates for conditional survival up to 6 years in 37 patients given 05 years survival of osteosarcoma. Each column represents the survival time, and each row represents the percentage reaching the specified survival time. (B) On the left are survival associated genes with AUC values in GSE99671 and GSE39055 and on the right are genes with AUC values greater than 0.73 in both datasets. Red represents up-regulated expression and blue represents down regulated expression. The length of the column represents the mean AUC value. (C) Nomogram for the prediction of overall survival to achieve 5-year or 8-year survival time.

Abbreviation: AUC, area under the ROC curve.

On the other hand, osteosarcoma patients in GSE39055 were divided into high-risk and low-risk groups according to the median risk score which calculated by the Cox model (Figure 6A). The expressions of key genes in the high-risk and low-risk groups were different. Patients with death status were significantly higher in the high-risk group than in the low-risk group. In addition, we calculated the correlation of key genes and immune cells, LOC286367 was positively correlated with most immune cells, other key genes were negatively correlated with more immune cells (Figure 6B). The prediction capability of the key genes was evaluated by calculating the area under the ROC curve (AUC). The AUC values of ATF5, CHCHD8, and LOC286367 for predicting OS were greater than 0.6 in the first, third, and fifth year of osteosarcoma, indicating that they had good performance (Figure 6C). High expression of ATF5, CHCHD8, and LOC286367 was associated with the worst OS in osteosarcoma patients (Figure 6D). ATF5, CHCHD8, and LOC286367 were expressed at significantly higher levels of osteosarcoma compared with the normal group in GSE99671 (Figure 6E).

Figure 6 Diagnostic role of key genes predicting the survival of osteosarcoma. (A) Distribution of risk score, overall survival, and overall survival status and heatmap of the five key genes in the GSE39055. (B) Correlations between immune infiltrating cells and key genes were calculated using Pearson. *P < 0.05, **P < 0.01. (C) Time-dependent ROC curves measuring the predictive value of key genes in GSE39055 for 3-year, 5-year or 10-year survival time. (D) Effect of key genes expression on overall survival by KaplanMeier analysis in 37 patients with osteosarcoma. (E) The expression levels of ATF5, CHCHD8, and LOC286367 in osteosarcoma and normal of GSE99671. ***P < 0.001.

Abbreviation: OS, overall survival.

Osteosarcoma is one of the most common aggressive bone tumors and is currently treated with chemical drugs combined with surgical resection. A major unsolved problem is the poor prognosis characterized by drug resistance, recurrence and metastasis.28 The identification of gene signatures is crucial both for a better understanding of the molecular basis of osteosarcoma progression and for the discovery of novel targets.29 In the present study, we focused on the potential target genes with prognostic value for osteosarcoma. Gene expression profiling of differentially expressed genes detected by GSE99671 in osteosarcoma tissue samples established 13 coexpression modules. Module genes were mainly enriched in immune, inflammatory and metabolic responses. In the gene co-expression network, module 1 was most significantly associated with osteosarcoma, in which genes significantly affecting survival may be potential target genes. Furthermore, combining GSE39055, we identified 5 key genes that may serve as diagnostic markers for the occurrence and recurrence of osteosarcoma. Finally, high expression of ATF5, CHCHD8, and LOC286367 was associated with worse prognosis in osteosarcoma.

WGCNA is a systems biology approach that describes correlation patterns between genes in transcriptome samples with soft threshold algorithms.23 The results of GO and KEGG pathway enrichment analysis of the module genes led us to focus on the biological functions of autophagy and macrophage migration, as well as the HIF-1 signaling pathway and PI3K-Akt signaling pathway. Autophagy promotes the proliferation and development of osteosarcoma cells and resists tumor treatment.30 Autophagy may be involved in drug sensitivity or chemoresistance during osteosarcoma treatment.31 Macrophages are an important immune component in the osteosarcoma microenvironment. Macrophages are highly plastic and the inflammatory phenotype (M1) and anti-inflammatory phenotype (M2) may play opposite roles in the progression of osteosarcoma.32 Activation of the HIF-1 signaling pathway promotes osteosarcoma cell growth and is a promising therapeutic target.33 Accumulating evidence suggests that the PI3K/Akt pathway is involved in cancer initiation and progression, such as tumorigenesis, apoptosis inhibition, proliferation and drug resistance.34

To further identify the underlying molecular mechanisms of osteosarcoma recurrence, we performed enrichment analysis of the differentially expressed genes between recurrence and non-recurrence. We found multiple immune related pathways, neutrophil mediated immunity, neutrophil apoptotic process, and leukocyte homeostasis. They may be associated with metastasis and recurrence of osteosarcoma.35 In addition to a large number of aberrant biological functions, FOXO could control the expression of genes involved in cell death and cell cycle arrest, exerting tumor suppressor activity.36 Tumor suppressor p53 tumor cells have been reported to exert anticancer effects by inducing cell cycle arrest and apoptosis.37

Of the 13 coexpression modules we identified, module 1 was found to be strongly associated with osteosarcoma. Among the module genes identified to be significantly associated with OS of osteosarcoma, 11 genes were screened with high specificity and sensitivity as potential molecular markers for predicting the occurrence and recurrence of osteosarcoma. Among them, 5 genes were genes in module 1 and were considered as key genes. In the Cox regression model, high expression of CHCHD8 or ENOPH1 may benefit the prognosis of osteosarcoma patients, and low expression of ATF5 or LOC286367 may prolong patient survival. However, the K-M curve results differed from the Cox analysis results in that patients with low expression of the CHCHD8 gene had better overall survival. The risk assessment model constructed by 5 key genes clearly distinguished the status of osteosarcoma survival and death. Based on the time-dependent ROC curves results, we identified ATF5, CHCHD8, and LOC286367 as potential diagnostic and prognostic biomarkers for clinical outcome prediction. ATF5 is considered an anti-apoptotic factor because it regulates the expression of the anti-apoptotic components BCL2 and MCL1.38 Studies have reported ATF5 to promote tumor growth and survival and have been reported to be associated with recurrence of osteosarcoma.39,40 CHCHD8 has been reported to be associated with drug resistance in gastric cancer, but the association with osteosarcoma has not been reported.41 LOC286367 was reported to be associated with inflammatory response,42,43 the results of our analysis argued that it may be a potential marker for the occurrence and recurrence of osteosarcoma.

However, the present study has certain limitations. The first and most important is the lack of experimental validation. Second, the lack of detailed clinical data, such as chemotherapy regimens and tumor stages, limits in-depth association analyses. Finally, whether the biomarkers we identified can be applied in the clinic also needs a large number of samples to validate, which will be the focus of our future studies.

The present study identified potential diagnostic markers and useful therapeutic targets for osteosarcoma patients, and they may be able to predict patient prognosis. The mechanism of recurrence of osteosarcoma may be associated with neutrophil immunity and cell cycle arrest. In-depth exploration of the potential target genes and molecular deregulation mechanisms to develop corresponding prevention and treatment countermeasures can achieve breakthrough progress in the prognosis of osteosarcoma.

Data were downloaded from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/).

This study was supported by the Scientific Research Project of Guangxi Health Commission (Z20180799).

The authors report no conflicts of interest related to this work.

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Identification of Gene as Predictive Biomarkers for the Occurrence and | IJGM - Dove Medical Press

Cell and gene therapies rapid penetration in clinical trials globally is testimony to the incredible potential these in understanding, treating, and curing diseases. The cell and gene therapy clinical trials market is rapidly evolving, touching numerous frontiers in personalized medicine, especially for chronic diseases. A number of gene therapies approved by the U.S. FDA reinforces the potential. Pharmaceutical companies in clinical trials that test cell and gene therapies have bloomed strikingly, most notably in oncology, eye diseases, and rare hereditary diseases. A partial list of the top diseases that attract massive attention of contract research organizations in cell and gene therapy market are type 1 diabetes, Parkinsons disease, spinal cord injuries, amyotrophic lateral sclerosis, the Alzheimers disease, and osteoarthritis.

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Cell And Gene Therapy Clinical Trials Market: Key Trends

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A prevalent trend over the past few years is the focus on oncology. Oncology--notably including haematological malignancies and solid tumourshave been at the center of ATMP clinical trials. Metabolic disease trials have also seen a significant increase, cementing revenue growth in the cell and gene therapy market. Advances made in gene therapy trials continue to pave way to new vistas for oncology research, both in vivo and in vitro.

Cell And Gene Therapy Clinical Trials Market: Competitive Dynamics and Key Developments

The profound potential of cell and gene therapies (CGT) notwithstanding, their successful clinical translation is, no doubt, rests on panoply of problems. These also determine the key restraints for the evolution of the cell and gene therapy market. The high degree of personalization that CGT entails, factors affecting their efficacy and safety are difficult to ascertain, if not impossible. For one, obtaining cells from donors is replete with some unique challenges, such as invasiveness of the process to patients. So are the lack of availability of cutting-edge biomarkers and targets anchored on which gene therapies will show their potential. The whole process of delivering CGT in clinical trials is itself associated with some tall challenges for contract research organizations.

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Having put these perspectives, the prospects have limitless potential waiting to be extracted, and researchers are not disheartened by the aforementioned challenges. In oncology alone, a number of new approaches have added liveliness to CGT clinical trials. Biotech companies are testing new waters in allogeneic therapies. T-cell receptor (TCR) are increasingly penetrating safety and feasibility trials, adding momentum to the cell and gene therapy market.

Some of the industry players likely to invade the space of these limitless possibilities are;

Cell And Gene Therapy Clinical Trials Market: Regional Assessment

North America has been at the cynosure of attention for CGT trials. European nations have also been showing substantial potential for generating revenues in the global market. In coming years, Asia Pacific is expected to show high growth potential

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Cell And Gene Therapy Clinical Trials Market in 2021 | Expansive Coverage on the Latest Developments in the Market - BioSpace

-Collaboration brings together breakthrough gene editing technology and leading natural killer (NK) cell and T cell discovery, development, and manufacturing capabilities-

-Companies to co-develop and co-commercialize two chimeric antigen receptor (CAR) NK cell product candidates, one targeting CD70, and a product candidate combining NK and T cells (NK+T)-

-Nkarta obtains a license to CRISPR gene editing technology for use in its own engineered NK cell therapy products-

-Nkarta to host conference call today at 4:30 p.m. ET-

ZUG, Switzerland, CAMBRIDGE, Mass., and SOUTH SAN FRANCISCO, Calif., May 06, 2021 (GLOBE NEWSWIRE) -- CRISPR Therapeutics (NASDAQ: CRSP), a biopharmaceutical company focused on developing transformative gene-based medicines for serious diseases, and Nkarta, Inc. (NASDAQ: NKTX), a biopharmaceutical company developing engineered NK cell therapies to treat cancer, today announced a strategic partnership to research, develop, and commercialize CRISPR/Cas9 gene-edited cell therapies for cancer.

Under the agreement, the companies will co-develop and co-commercialize two CAR NK cell product candidates, one targeting the CD70 tumor antigen and the other target to be determined. In addition, the companies will bring together their complementary cell therapy engineering and manufacturing capabilities to advance the development of a novel NK+T product candidate harnessing the synergies of the adaptive and innate immune systems. Finally, Nkarta obtains a license to CRISPR gene editing technology to edit five gene targets in an unlimited number of its own NK cell therapy products.

CRISPR Therapeutics and Nkarta will equally share all research and development costs and profits worldwide related to the collaboration products. For each non-collaboration product candidate incorporating a gene editing target licensed from CRISPR Therapeutics, Nkarta will retain worldwide rights and pay CRISPR Therapeutics milestones and royalties on net sales. The agreement includes a three-year exclusivity period between CRISPR Therapeutics and Nkarta covering the research, development, and commercialization of allogeneic, gene-edited, donor-derived NK cells and NK+T cells.

By bringing together CRISPR Therapeutics and Nkartas highly complementary expertise and proprietary platforms we plan to accelerate the development of potentially groundbreaking genome engineered NK cell therapies, said Samarth Kulkarni, Ph.D., Chief Executive Officer at CRISPR Therapeutics. This collaboration broadens the scope of our efforts in oncology cell therapy, and expands our efforts to discover and develop novel cancer therapies for patients.

Uniting the best-in-class gene editing solution and allogeneic T cell therapy expertise of CRISPR with Nkartas best-in-class CAR NK cell therapy platform will be a major advantage to advancing the next wave of transformative cancer cell therapies, said Paul J. Hastings, President and Chief Executive Officer of Nkarta. With this partnership, Nkarta can systematically apply world-class gene editing across our entire pre-clinical pipeline going forward. CRISPRs deep understanding of CD70 biology and experience in allogeneic T cell clinical development can accelerate the development of early-stage Nkarta programs, to deliver innovative treatments to patients that much faster.

Nkarta Conference Call DetailsNkarta management will host a conference call to discuss the collaboration today at 4:30 p.m. Eastern Time (ET). The event will be simultaneously webcast and available for replay from the Nkarta website at http://www.nkartatx.com, under the Investors section. Investors may also participate in the conference call by calling 877-876-9174 (domestic) or +1-785-424-1669 (international). The conference ID is NKARTA.

AboutCRISPR TherapeuticsCRISPR Therapeuticsis a leading gene editing company focused on developing transformative gene-based medicines for serious diseases using its proprietary CRISPR/Cas9 platform. CRISPR/Cas9 is a revolutionary gene editing technology that allows for precise, directed changes to genomic DNA.CRISPR Therapeuticshas established a portfolio of therapeutic programs across a broad range of disease areas including hemoglobinopathies, oncology, regenerative medicine and rare diseases. To accelerate and expand its efforts,CRISPR Therapeuticshas established strategic collaborations with leading companies includingBayer, Vertex PharmaceuticalsandViaCyte, Inc.CRISPR Therapeutics AGis headquartered inZug, Switzerland, with its wholly-ownedU.S.subsidiary,CRISPR Therapeutics, Inc., and R&D operations based inCambridge, Massachusetts, and business offices inSan Francisco, CaliforniaandLondon, United Kingdom. For more information, please visitwww.crisprtx.com.

CRISPR THERAPEUTICS word mark and design logo are registered trademarks ofCRISPR Therapeutics AG. All other trademarks and registered trademarks are the property of their respective owners.

CRISPR Therapeutics Forward-Looking StatementThis press release may contain a number of forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, as amended, including statements made by Dr. Kulkarni and Mr. Hastings in this press release, as well as statements regarding CRISPR Therapeutics expectations about any or all of the following: (i) the future activities of the parties pursuant to the collaboration and the expected benefits of CRISPR Therapeutics collaboration with Nkarta; and (ii) the therapeutic value, development, and commercial potential of CRISPR/Cas9 gene editing technologies and therapies. Without limiting the foregoing, the words believes, anticipates, plans, expects and similar expressions are intended to identify forward-looking statements. You are cautioned that forward-looking statements are inherently uncertain. Although CRISPR Therapeutics believes that such statements are based on reasonable assumptions within the bounds of its knowledge of its business and operations, forward-looking statements are neither promises nor guarantees and they are necessarily subject to a high degree of uncertainty and risk. Actual performance and results may differ materially from those projected or suggested in the forward-looking statements due to various risks and uncertainties. These risks and uncertainties include, among others: CRISPR Therapeutics may not realize the potential benefits of the collaboration, uncertainties inherent in the initiation and completion of preclinical studies; availability and timing of results from preclinical studies; whether results from a preclinical study will be favorable and predictive of future results of future studies or clinical trials; uncertainties about regulatory approvals and that future competitive or other market factors may adversely affect the commercial potential for product candidates; potential impacts due to the coronavirus pandemic, such as the timing and progress of preclinical studies; uncertainties regarding the intellectual property protection for CRISPR Therapeutics technology and intellectual property belonging to third parties, and the outcome of proceedings (such as an interference, an opposition or a similar proceeding) involving all or any portion of such intellectual property; and those risks and uncertainties described under the heading "Risk Factors" in CRISPR Therapeutics most recent annual report on Form 10-K, quarterly report on Form 10-Q, and in any other subsequent filings made by CRISPR Therapeutics with the U.S. Securities and Exchange Commission, which are available on the SEC's website at http://www.sec.gov. Existing and prospective investors are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date they are made. CRISPR Therapeutics disclaims any obligation or undertaking to update or revise any forward-looking statements contained in this press release, other than to the extent required by law.

About Nkartas NK Cell TechnologiesNkarta has pioneered a novel discovery and development platform for the engineering and efficient production of allogeneic, off-the-shelf natural killer (NK) cell therapy candidates. The approach harnesses the innate ability of NK cells to recognize and kill tumor cells. To enhance the inherent biological activity of NK cells, Nkarta genetically engineers the cells with a targeting receptor designed to recognize and bind to specific proteins on the surface of cancerous cells. This receptor is fused to co-stimulatory and signaling domains to amplify cell signaling and NK cell cytotoxicity. Upon binding the target, NK cells become activated and release cytokines that enhance the immune response and cytotoxic granules that lead to killing of the target cell. All of Nkartas NK current cell therapy candidates are also engineered with a membrane-bound IL15, a proprietary version of a cytokine known for activating NK cell growth, to enhance the persistence and activity of the NK cells.

Nkartas manufacturing process generates an abundant supply of NK cells that, at commercial scale, is expected to be significantly lower in cost than other current allogeneic and autologous cell therapies. Key to this efficiency is the rapid expansion of donor-derived NK cells using a proprietary NKSTIM cell line, leading to the production of hundreds of individual doses from a single manufacturing run. The platform also features the ability to freeze and store CAR NK cells for an extended period of time and is designed to enable immediate, off-the-shelf administration to patients at the point of care.

About NkartaNkarta is a clinical-stage biotechnology company advancing the development of allogeneic, off the shelf natural killer (NK) cell therapies for cancer. By combining its cell expansion and cryopreservation platform with proprietary cell engineering technologies, Nkarta is building a pipeline of cell therapy candidates generated by efficient manufacturing processes, which are engineered to enhance tumor targeting and improve persistence for sustained activity in the body. For more information, please visit http://www.nkartatx.com.

Nkarta, Inc. Cautionary Note on Forward-Looking StatementsStatements contained in this press release regarding matters that are not historical facts are forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, as amended. Words such as "anticipates," "believes," "expects," "intends," plans, potential, "projects, would and "future" or similar expressions are intended to identify forward-looking statements. Examples of these forward-looking statements include statements concerning: Nkartas expectations regarding its ability to advance the development and commercialization of two gene-edited CAR-NK cell therapies and an NK+T cell therapy under the collaboration with CRISPR Therapeutics, and the ability of Nkarta and CRISPR Therapeutics to leverage the combination of their respective expertise and platforms to accelerate that development; Nkartas application of gene-editing across its preclinical pipeline; the ability of Nkartas technology to enhance the persistence and anti-tumor activity of NK cells and enable off-the-shelf, point-of-care administration; the efficiency and cost of Nkartas manufacturing processes; the number of doses generated from a manufacturing run; and the proprietary nature of Nkartas technology. Because such statements are subject to risks and uncertainties, actual results may differ materially from those expressed or implied by such forward-looking statements. These risks and uncertainties include, among others: Nkartas limited operating history and historical losses; Nkartas ability to raise additional funding to complete the development and any commercialization of its product candidates; Nkartas dependence on the success of its co-lead product candidates, NKX101 and NKX019; that Nkarta may be delayed in initiating, enrolling or completing any clinical trials; competition from third parties that are developing products for similar uses; Nkartas ability to obtain, maintain and protect its intellectual property; Nkartas dependence on third parties in connection with manufacturing, clinical trials and pre-clinical studies; the complexity of the manufacturing process for CAR NK cell therapies; and risks relating to the impact on Nkartas business of the COVID-19 pandemic or similar public health crises.

These and other risks are described more fully in Nkartas filings with the Securities and Exchange Commission (SEC), including the Risk Factors section of Nkartas Annual Report on Form 10-K for the year ended December 31, 2020, filed with the SEC on March 25, 20201, and our other documents subsequently filed with or furnished to the SEC. All forward-looking statements contained in this press release speak only as of the date on which they were made. Except to the extent required by law, Nkarta undertakes no obligation to update such statements to reflect events that occur or circumstances that exist after the date on which they were made.

CRISPR Therapeutics Investor Contact:Susan Kim+1-617-307-7503susan.kim@crisprtx.com

CRISPR Therapeutics Media Contact:Jennifer PaganelliReal Chemistry on behalf of CRISPR+1-347-658-8290jpaganelli@realchemistry.com

Nkarta Media/Investor Contact:Greg MannNkarta, Inc.+1-415-317-3675gmann@nkartatx.com

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CRISPR Therapeutics and Nkarta Announce Global Collaboration to Develop Gene-Edited Cell Therapies for Cancer - GlobeNewswire