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Yorio J, Lofgren KT, Lee JK, Tolba K, Oxnard GR, Schrock AB, Huang RS, Brisbin L. Association of Timely Comprehensive Genomic Profiling With Precision Oncology Treatment Use and Patient Outcomes in Advanced Non-Small-Cell Lung Cancer. JCO Precis Oncol 2024; 8:e2300292. [PMID: 38452312 PMCID: PMC10939592 DOI: 10.1200/po.23.00292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 12/11/2023] [Accepted: 01/04/2024] [Indexed: 03/09/2024] Open
Abstract
PURPOSE Timely biomarker testing remains out of reach for many patients with advanced non-small-cell lung cancer (aNSCLC). Here, we studied the quality-of-care implications of closing the gap in timely receipt of comprehensive genomic profiling (CGP) to inform first-line (1L) decisions. METHODS Using a real-world clinicogenomic database, we studied testing and 1L treatment patterns in aNSCLC after the approval of pembrolizumab in combination with pemetrexed and carboplatin (May 10, 2017). To estimate the association of timely CGP results with therapy selection and patient outcomes, we identified patients with no previous genomic testing beyond PD-L1 immunohistochemistry and dichotomized patients by whether CGP results were available before or after 1L therapy initiation. RESULTS In total, 2,694 patients were included in the 1L therapy decision impact assessment. Timely CGP increased matched targeted therapy use by 14 percentage points (17% with CGP v 2.8% without) and precision immune checkpoint inhibitor (ICPI) use by 14 percentage points (18% with CGP v 3.9% without). Receipt of timely CGP resulted in an estimated 31 percentage point decrease in ICPI use among ALK/EGFR/RET/ROS1-positive patients at an expected per-patient reduction in ineffective ICPI therapy cost of $13,659.37 with timely CGP to inform 1L treatment selection. Patient benefit of CGP extended to real-world time to therapy discontinuation (median time to therapy discontinuation: 3.9 v 10 months [hazard ratio, HR, 0.54 [95% CI, 0.42 to 0.70]; P = 1.9E-06; adjusted hazard ratio [aHR], 0.50 [95% CI, 0.38 to 0.67]; P = 2.0E-06) in 1L driver-positive patients. This effect was not significant for real-world overall survival (median overall survival: 32 v 29 months [HR, 1.2 [95% CI, 0.84 to 1.67]; P = .33; aHR, 1.4 [95% CI, 0.92 to 1.99]; P = .12). CONCLUSION Timely CGP is associated with the quality of patient care as measured by 1L matched targeted therapy use, time to therapy discontinuation, and avoidance of ineffective, costly ICPIs.
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Zhang H, Hu Y, Wu T, Chen Y, Yang B, Xie T. Clinical characteristics and novel strategies of immune checkpoint inhibitor rechallenge therapy for non-small cell lung cancer: a comprehensive review. Front Immunol 2024; 14:1309055. [PMID: 38283354 PMCID: PMC10811167 DOI: 10.3389/fimmu.2023.1309055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 12/22/2023] [Indexed: 01/30/2024] Open
Abstract
Treatment of non-small-cell lung cancer (NSCLC) has entered the immunotherapy era, marked by significant survival improvements due to the use of immune checkpoint inhibitors (ICIs). However, owing to factors, such as disease progression, long-term use, and side effects, some patients discontinue immunotherapy, resulting in limited subsequent treatment option and a negative impact on their survival and quality of life. We have collected relevant data which reveal that ICI rechallenge may be an effective clinical strategy. However, many factors affect the efficacy of rechallenge, including patient characteristics, initial treatment drugs, treatment duration, efficacy, toxicity, and side effects. Additionally, the side effects of rechallenge and mechanisms of reversing drug resistance play crucial roles. Identifying suitable candidates, optimizing treatment plans and duration, enhancing treatment efficacy, and minimizing toxicity and adverse effects in rechallenges are pressing clinical needs. Addressing these issues can provide guidance for the clinical use of immunotherapy rechallenges to better serve patients. This review focuses on the clinical considerations and strategies for immune therapy rechallenges in NSCLC.
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Affiliation(s)
- Hao Zhang
- Department of Radiation Oncology, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yujun Hu
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Tingting Wu
- Department of Health Management, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yeshan Chen
- Institute of Radiation Oncology, Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Bin Yang
- Department of Thoracic Oncology, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Tao Xie
- Department of Radiation Oncology, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Shirasawa M, Yoshida T, Ohe Y. Biomarkers of immunotherapy for non-small cell lung cancer. Jpn J Clin Oncol 2024; 54:13-22. [PMID: 37823218 DOI: 10.1093/jjco/hyad134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 09/22/2023] [Indexed: 10/13/2023] Open
Abstract
Immunotherapy is revolutionizing the treatment of non-small cell lung cancer by targeting immune checkpoint proteins, including programmed death-1, programmed death ligand 1 and cytotoxic T-lymphocyte-associated antigen 4. Several immune checkpoint inhibitors, including programmed death ligand 1 inhibitors, programmed death-1 inhibitors and cytotoxic T-lymphocyte-associated antigen 4 inhibitors, were approved for the treatment of patients with advanced non-small cell lung cancer. Programmed death ligand 1 expression is currently the only predictive biomarker for immune checkpoint inhibitors to guide the treatment strategy in these patients. However, programmed death ligand 1 expression is not a perfect biomarker for predicting the efficacy of immunotherapy. Therefore, various biomarkers such as tumour mutation burden, tumour microenvironment, gut microbiome and T-cell receptor repertoire have been proposed to predict the efficacy of immunotherapy more accurately. Additionally, combining different biomarkers may provide a more accurate prediction of response to immunotherapy. This article reports the review of the latest evidence of the predictive marker of immunotherapy in patients with advanced non-small cell lung cancer.
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Affiliation(s)
- Masayuki Shirasawa
- Department of Thoracic Oncology, National Cancer Center Hospital, Chuo-ku, Tokyo 104-0045 Japan
- Department of Respiratory Medicine, Kitasato University School of Medicine, Sagamihara City, Kanagawa 252-0375, Japan
| | - Tatsuya Yoshida
- Department of Thoracic Oncology, National Cancer Center Hospital, Chuo-ku, Tokyo 104-0045 Japan
| | - Yuichiro Ohe
- Department of Thoracic Oncology, National Cancer Center Hospital, Chuo-ku, Tokyo 104-0045 Japan
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Xiong Y, Kong X, Mei H, Wang J, Zhou S. Bioinformatics-based analysis of the relationship between disulfidptosis and prognosis and treatment response in pancreatic cancer. Sci Rep 2023; 13:22218. [PMID: 38097783 PMCID: PMC10721597 DOI: 10.1038/s41598-023-49752-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 12/12/2023] [Indexed: 12/17/2023] Open
Abstract
Tumor formation is closely associated with disulfidptosis, a new form of cell death induced by disulfide stress-induced. The exact mechanism of action of disulfidptosis in pancreatic cancer (PCa) is not clear. This study analyzed the impact of disulfidptosis-related genes (DRGs) on the prognosis of PCa and identified clusters of DRGs, and based on this, a risk score (RS) signature was developed to assess the impact of RS on the prognosis, immune and chemotherapeutic response of PCa patients. Based on transcriptomic data and clinical information from PCa tissue and normal pancreatic tissue samples obtained from the TCGA and GTEx databases, differentially expressed and differentially surviving DRGs in PCa were identified from among 15 DRGs. Two DRGs clusters were identified by consensus clustering by merging the PCa samples in the GSE183795 dataset. Analysis of DRGs clusters about the PCa tumor microenvironment and differential analysis to obtain differential genes between the two DRG clusters. Patients were then randomized into the training and testing sets, and a prognostic prediction signature associated with disulfidptosis was constructed in the training set. Then all samples were divided into high-disulfidptosis-risk (HDR) and low-disulfidptosis-risk (LDR) subgroups based on the RS calculated from the signature. The predictive efficacy of the signature was assessed by survival analysis, nomograms, correlation analysis of clinicopathological characteristics, and the receiver operating characteristic (ROC) curves. To assess differences between different risk subgroups in immune cell infiltration, expression of immune checkpoint molecules, somatic gene mutations, and effectiveness of immunotherapy and chemotherapy. The GSE57495 dataset was used as external validation, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression levels of DRGs. A total of 12 DRGs with differential expression and prognosis in PCa were identified, based on which a risk-prognosis signature containing five differentially expressed genes (DEGs) was developed. The signature was a good predictor and an independent risk factor. The nomogram and calibration curve shows the signature's excellent clinical applicability. Functional enrichment analysis showed that RS was associated with tumor and immune-related pathways. RS was strongly associated with the tumor microenvironment, and analysis of response to immunotherapy and chemotherapy suggests that the signature can be used to assess the sensitivity of treatments. External validation further demonstrated the model's efficacy in predicting the prognosis of PCa patients, with RT-qPCR and immunohistochemical maps visualizing the expression of each gene in PCa cell lines and the tissue. Our study is the first to apply the subtyping model of disulfidptosis to PCa and construct a signature based on the disulfidptosis subtype, which can provide an accurate assessment of prognosis, immunotherapy, and chemotherapy response in PCa patients, providing new targets and directions for the prognosis and treatment of PCa.
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Affiliation(s)
- Yuanpeng Xiong
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Xiaoyu Kong
- School of Public Health, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Haoran Mei
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Jie Wang
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Shifa Zhou
- Department of Emergency Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China.
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Ahmed J, Das B, Shin S, Chen A. Challenges and Future Directions in the Management of Tumor Mutational Burden-High (TMB-H) Advanced Solid Malignancies. Cancers (Basel) 2023; 15:5841. [PMID: 38136385 PMCID: PMC10741991 DOI: 10.3390/cancers15245841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 11/28/2023] [Accepted: 12/11/2023] [Indexed: 12/24/2023] Open
Abstract
A standardized assessment of Tumor Mutational Burden (TMB) poses challenges across diverse tumor histologies, treatment modalities, and testing platforms, requiring careful consideration to ensure consistency and reproducibility. Despite clinical trials demonstrating favorable responses to immune checkpoint inhibitors (ICIs), not all patients with elevated TMB exhibit benefits, and certain tumors with a normal TMB may respond to ICIs. Therefore, a comprehensive understanding of the intricate interplay between TMB and the tumor microenvironment, as well as genomic features, is crucial to refine its predictive value. Bioinformatics advancements hold potential to improve the precision and cost-effectiveness of TMB assessments, addressing existing challenges. Similarly, integrating TMB with other biomarkers and employing comprehensive, multiomics approaches could further enhance its predictive value. Ongoing collaborative endeavors in research, standardization, and clinical validation are pivotal in harnessing the full potential of TMB as a biomarker in the clinic settings.
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Affiliation(s)
- Jibran Ahmed
- Developmental Therapeutics Clinic (DTC), National Cancer Institute (NCI), National Institute of Health (NIH), Bethesda, MD 20892, USA
| | - Biswajit Das
- Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
| | - Sarah Shin
- Developmental Therapeutics Clinic (DTC), National Cancer Institute (NCI), National Institute of Health (NIH), Bethesda, MD 20892, USA
| | - Alice Chen
- Developmental Therapeutics Clinic (DTC), National Cancer Institute (NCI), National Institute of Health (NIH), Bethesda, MD 20892, USA
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Pellini B, Madison RW, Childress MA, Miller ST, Gjoerup O, Cheng J, Huang RS, Krainock M, Gupta P, Zou W, Shames DS, Moshkevich S, Ballinger M, Liu MC, Young A, Srivastava MK, Oxnard GR, Socinski MA. Circulating Tumor DNA Monitoring on Chemo-immunotherapy for Risk Stratification in Advanced Non-Small Cell Lung Cancer. Clin Cancer Res 2023; 29:4596-4605. [PMID: 37702716 PMCID: PMC10643998 DOI: 10.1158/1078-0432.ccr-23-1578] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/21/2023] [Accepted: 09/08/2023] [Indexed: 09/14/2023]
Abstract
PURPOSE Chemoimmunotherapy (chemoIO) is a prevalent first-line treatment for advanced driver-negative non-small cell lung cancer (NSCLC), with maintenance therapy given after induction. However, there is significant clinical variability in the duration, dosing, and timing of maintenance therapy after induction chemoIO. We used circulating tumor DNA (ctDNA) monitoring to inform outcomes in patients with advanced NSCLC receiving chemoIO. EXPERIMENTAL DESIGN This retrospective study included 221 patients from a phase III trial of atezolizumab+carboplatin+nab-paclitaxel versus carboplatin+nab-paclitaxel in squamous NSCLC (IMpower131). ctDNA monitoring used the FoundationOne Tracker involving comprehensive genomic profiling of pretreatment tumor tissue, variant selection using an algorithm to exclude nontumor variants, and multiplex PCR of up to 16 variants to detect and quantify ctDNA. RESULTS ctDNA was detected (ctDNA+) in 96% of pretreatment samples (median, 93 mean tumor molecules/mL), and similar ctDNA dynamics were noted across treatment arms during chemoIO. ctDNA decrease from baseline to C4D1 was associated with improved outcomes across multiple cutoffs for patients treated with chemoIO. When including patients with missing plasma or ctDNA- at baseline, patients with ctDNA- at C4D1 (clearance), had more favorable progression-free survival (median 8.8 vs. 3.5 months; HR, 0.32;0.20-0.52) and OS (median not reached vs. 8.9 months; HR, 0.22; 0.12-0.39) from C4D1 than ctDNA+ patients. CONCLUSIONS ctDNA monitoring during induction chemoIO can inform treatment outcomes in patients with advanced NSCLC. Importantly, monitoring remains feasible and informative for patients missing baseline ctDNA. ctDNA testing during induction chemoIO identifies patients at higher risk for disease progression and may inform patient selection for novel personalized maintenance or second-line treatment strategies.
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Affiliation(s)
- Bruna Pellini
- Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
- Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tampa, Florida
| | | | | | | | - Ole Gjoerup
- Foundation Medicine, Inc., Cambridge, Massachusetts
| | - Jason Cheng
- Genentech, Inc., South San Francisco, California
| | | | | | | | - Wei Zou
- Genentech, Inc., South San Francisco, California
| | | | | | | | | | - Amanda Young
- Foundation Medicine, Inc., Cambridge, Massachusetts
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7
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Thummalapalli R, Ricciuti B, Bandlamudi C, Muldoon D, Rizvi H, Elkrief A, Luo J, Alessi JV, Pecci F, Lamberti G, Di Federico A, Hong L, Zhang J, Heymach JV, Gibbons DL, Plodkowski AJ, Ravichandran V, Donoghue MT, Vanderbilt C, Ladanyi M, Rudin CM, Kris MG, Riely GJ, Chaft JE, Hellmann MD, Vokes NI, Awad MM, Schoenfeld AJ. Clinical and Molecular Features of Long-term Response to Immune Checkpoint Inhibitors in Patients with Advanced Non-Small Cell Lung Cancer. Clin Cancer Res 2023; 29:4408-4418. [PMID: 37432985 PMCID: PMC10618656 DOI: 10.1158/1078-0432.ccr-23-1207] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/15/2023] [Accepted: 07/07/2023] [Indexed: 07/13/2023]
Abstract
PURPOSE We sought to identify features of patients with advanced non-small cell lung cancer (NSCLC) who achieve long-term response (LTR) to immune checkpoint inhibitors (ICI), and how these might differ from features predictive of short-term response (STR). EXPERIMENTAL DESIGN We performed a multicenter retrospective analysis of patients with advanced NSCLC treated with ICIs between 2011 and 2022. LTR and STR were defined as response ≥ 24 months and response < 12 months, respectively. Tumor programmed death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), next-generation sequencing (NGS), and whole-exome sequencing (WES) data were analyzed to identify characteristics enriched in patients achieving LTR compared with STR and non-LTR. RESULTS Among 3,118 patients, 8% achieved LTR and 7% achieved STR, with 5-year overall survival (OS) of 81% and 18% among LTR and STR patients, respectively. High TMB (≥50th percentile) enriched for LTR compared with STR (P = 0.001) and non-LTR (P < 0.001). Whereas PD-L1 ≥ 50% enriched for LTR compared with non-LTR (P < 0.001), PD-L1 ≥ 50% did not enrich for LTR compared with STR (P = 0.181). Nonsquamous histology (P = 0.040) and increasing depth of response [median best overall response (BOR) -65% vs. -46%, P < 0.001] also associated with LTR compared with STR; no individual genomic alterations were uniquely enriched among LTR patients. CONCLUSIONS Among patients with advanced NSCLC treated with ICIs, distinct features including high TMB, nonsquamous histology, and depth of radiographic improvement distinguish patients poised to achieve LTR compared with initial response followed by progression, whereas high PD-L1 does not.
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Affiliation(s)
- Rohit Thummalapalli
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Biagio Ricciuti
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Chaitanya Bandlamudi
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Daniel Muldoon
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Hira Rizvi
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Arielle Elkrief
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Jia Luo
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Joao V. Alessi
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Federica Pecci
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Giuseppe Lamberti
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | | | - Lingzhi Hong
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, Texas
| | - Jianjun Zhang
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, Texas
| | - John V. Heymach
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, Texas
| | - Don L. Gibbons
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, Texas
| | - Andrew J. Plodkowski
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Vignesh Ravichandran
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Mark T.A. Donoghue
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Chad Vanderbilt
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Marc Ladanyi
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Charles M. Rudin
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Mark G. Kris
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Gregory J. Riely
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Jamie E. Chaft
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Matthew D. Hellmann
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Natalie I. Vokes
- Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, Texas
| | - Mark M. Awad
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Adam J. Schoenfeld
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
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Wang D, Elenbaas B, Murugesan K, Shah K, Montesion M, Gounaris I, Scheuenpflug J, Locatelli G, Feng Z. Relationship among DDR gene mutations, TMB and PD-L1 in solid tumour genomes identified using clinically actionable biomarker assays. NPJ Precis Oncol 2023; 7:103. [PMID: 37821580 PMCID: PMC10567713 DOI: 10.1038/s41698-023-00442-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 08/31/2023] [Indexed: 10/13/2023] Open
Abstract
The DNA damage response (DDR) pathway regulates DNA repair and cell survival, and inactivating mutations in DDR genes can increase tumour mutational burden (TMB), a predictive biomarker of treatment benefit from anti-PD-1/PD-L1 immunotherapies. However, a better understanding of the relationship among specific DDR mutations, TMB and PD-L1 expression is needed to improve translational strategies. Here, we determined genomic alteration frequencies in selected DDR genes that are clinically actionable biomarkers and investigated their association with TMB and PD-L1 in bladder, colorectal, non-small cell lung, ovarian and prostate cancers using the FoundationInsights® web portal. Our results not only confirm known associations, such as mismatch repair and POLE gene mutations with high TMB, but also identify significant associations between mutations in the SWI/SNF chromatin remodelling genes ARID1A and SMARCA4 and high TMB in multiple tumour types. Mutations in the ATR gene were associated with high TMB in colorectal and prostate cancers; however, associations between individual DDR mutations and high PD-L1 expression were uncommon and tumour-type specific. Finally, we found that high TMB and high PD-L1 expression were poorly associated, emphasising their independence as predictive biomarkers for immune checkpoint inhibitor use.
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Affiliation(s)
- Danyi Wang
- Clinical Measurements Sciences, Global Research & Development, EMD Serono Research & Development Institute, Inc., an affiliate of Merck KGaA, Billerica, MA, USA
| | - Brian Elenbaas
- Research Unit Oncology, EMD Serono Research & Development Institute, Inc., an affiliate of Merck KGaA, Billerica, MA, USA
| | | | | | | | - Ioannis Gounaris
- Global Clinical Development, Merck Serono Ltd., an affiliate of Merck KGaA, Feltham, UK
| | - Juergen Scheuenpflug
- Clinical Measurements Sciences, Global Research & Development, Merck Healthcare KGaA, Darmstadt, Germany
| | - Giuseppe Locatelli
- Clinical Measurements Sciences, Global Research & Development, Merck Healthcare KGaA, Darmstadt, Germany
| | - Zheng Feng
- Clinical Measurements Sciences, Global Research & Development, EMD Serono Research & Development Institute, Inc., an affiliate of Merck KGaA, Billerica, MA, USA.
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Peng H, Wu X, Liu S, He M, Tang C, Wen Y, Xie C, Zhong R, Li C, Xiong S, Liu J, Zheng H, He J, Lu X, Liang W. Cellular dynamics in tumour microenvironment along with lung cancer progression underscore spatial and evolutionary heterogeneity of neutrophil. Clin Transl Med 2023; 13:e1340. [PMID: 37491740 PMCID: PMC10368809 DOI: 10.1002/ctm2.1340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/21/2023] [Accepted: 07/12/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND The cellular dynamics in the tumour microenvironment (TME) along with non-small cell lung cancer (NSCLC) progression remain unclear. METHODS Multiplex immunofluorescence test detecting 10 immune-related markers on 553 primary tumour (PT) samples of NSCLC was conducted and spatial information in TME was assessed by the StarDist depth learning model. The single-cell transcriptomic atlas of PT (n = 4) and paired tumour-draining lymph nodes (TDLNs) (n = 5 for tumour-invaded, n = 3 for tumour-free) microenvironment was profiled. Various bioinformatics analyses based on Gene Expression Omnibus, TCGA and Array-Express databases were also used to validate the discoveries. RESULTS Spatial distances of CD4+ T cells-CD38+ T cells, CD4+ T cells-neutrophils and CD38+ T cells-neutrophils prolonged and they were replaced by CD163+ macrophages in PT along with tumour progression. Neutrophils showed unique stage and location-dependent prognostic effects. A high abundance of stromal neutrophils improved disease-free survival in the early-stage, whereas high intratumoural neutrophil infiltrates predicted poor prognosis in the mid-to-late-stage. Significant molecular and functional reprogramming in PT and TDLN microenvironments was observed. Diverse interaction networks mediated by neutrophils were found between positive and negative TDLNs. Five phenotypically and functionally heterogeneous subtypes of tumour-associated neutrophil (TAN) were further identified by pseudotime analysis, including TAN-0 with antigen-presenting function, TAN-1 with strong expression of interferon (IFN)-stimulated genes, the pro-tumour TAN-2 subcluster, the classical subset (TAN-3) and the pro-inflammatory subtype (TAN-4). Loss of IFN-stimulated signature and growing angiogenesis activity were discovered along the transitional trajectory. Eventually, a robust six neutrophil differentiation relevant genes-based model was established, showing that low-risk patients had longer overall survival time and may respond better to immunotherapy. CONCLUSIONS The cellular composition, spatial location, molecular and functional changes in PT and TDLN microenvironments along with NSCLC progression were deciphered, highlighting the immunoregulatory roles and evolutionary heterogeneity of TANs.
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Affiliation(s)
- Haoxin Peng
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
- Deparment of Clinical MedicineNanshan SchoolGuangzhou Medical UniversityGuangzhouChina
- Department of OncologyPeking University Cancer Hospital & InstitutePeking University Health Science Center, Peking UniversityBeijingChina
| | - Xiangrong Wu
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
- Deparment of Clinical MedicineNanshan SchoolGuangzhou Medical UniversityGuangzhouChina
- Department of OncologyShanghai Medical College, Fudan UniversityShanghaiChina
| | - Shaopeng Liu
- Department of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina
- Department of Artificial Intelligence ResearchPazhou LabGuangzhouChina
| | - Miao He
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
- Deparment of Clinical MedicineNanshan SchoolGuangzhou Medical UniversityGuangzhouChina
| | - Chenshuo Tang
- Department of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina
| | - Yaokai Wen
- Deparment of Clinical MedicineTongji UniversityShanghaiChina
- Department of Medical OncologyShanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University, School of MedicineShanghaiChina
| | - Chao Xie
- Department of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina
| | - Ran Zhong
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Caichen Li
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Shan Xiong
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Jun Liu
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Hongbo Zheng
- Medical DepartmentGenecast Biotechnology Co., LtdBeijingChina
| | - Jianxing He
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Xu Lu
- Department of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina
- Department of Artificial Intelligence ResearchPazhou LabGuangzhouChina
| | - Wenhua Liang
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
- Department of Medical OncologyThe First People's Hospital of ZhaoqingZhaoqingChina
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