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Jani Y, Jansen CS, Gerke MB, Bilen MA. Established and emerging biomarkers of immunotherapy in renal cell carcinoma. Immunotherapy 2024; 16:405-426. [PMID: 38264827 DOI: 10.2217/imt-2023-0267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024] Open
Abstract
Immunotherapies, such as immune checkpoint inhibitors, have heralded impressive progress for patient care in renal cell carcinoma (RCC). Despite this success, some patients' disease fails to respond, and other patients experience significant side effects. Thus, development of biomarkers is needed to ensure that patients can be selected to maximize benefit from immunotherapies. Improving clinicians' ability to predict which patients will respond to immunotherapy and which are most at risk of adverse events - namely through clinical biomarkers - is indispensable for patient safety and therapeutic efficacy. Accordingly, an evolving suite of therapeutic biomarkers continues to be investigated. This review discusses biomarkers for immunotherapy in RCC, highlighting current practices and emerging innovations, aiming to contribute to improved outcomes for patients with RCC.
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Affiliation(s)
- Yash Jani
- Mercer University, Macon, GA 31207, USA
| | - Caroline S Jansen
- Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
| | - Margo B Gerke
- Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Mehmet Asim Bilen
- Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
- Department of Hematology & Medical Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
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Grizzi F, Bax C, Hegazi MAAA, Lotesoriere BJ, Zanoni M, Vota P, Hurle RF, Buffi NM, Lazzeri M, Tidu L, Capelli L, Taverna G. Early Detection of Prostate Cancer: The Role of Scent. CHEMOSENSORS 2023; 11:356. [DOI: 10.3390/chemosensors11070356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
Prostate cancer (PCa) represents the cause of the second highest number of cancer-related deaths worldwide, and its clinical presentation can range from slow-growing to rapidly spreading metastatic disease. As the characteristics of most cases of PCa remains incompletely understood, it is crucial to identify new biomarkers that can aid in early detection. Despite the prostate-specific antigen serum (PSA) levels, prostate biopsy, and imaging representing the actual gold-standard for diagnosing PCa, analyzing volatile organic compounds (VOCs) has emerged as a promising new frontier. We and other authors have reported that highly trained dogs can recognize specific VOCs associated with PCa with high accuracy. However, using dogs in clinical practice has several limitations. To exploit the potential of VOCs, an electronic nose (eNose) that mimics the dog olfactory system and can potentially be used in clinical practice was designed. To explore the eNose as an alternative to dogs in diagnosing PCa, we conducted a systematic literature review and meta-analysis of available studies. PRISMA guidelines were used for the identification, screening, eligibility, and selection process. We included six studies that employed trained dogs and found that the pooled diagnostic sensitivity was 0.87 (95% CI 0.86–0.89; I2, 98.6%), the diagnostic specificity was 0.83 (95% CI 0.80–0.85; I2, 98.1%), and the area under the summary receiver operating characteristic curve (sROC) was 0.64 (standard error, 0.25). We also analyzed five studies that used an eNose to diagnose PCa and found that the pooled diagnostic sensitivity was 0.84 (95% CI, 0.80–0.88; I2, 57.1%), the diagnostic specificity was 0.88 (95% CI, 0.84–0.91; I2, 66%), and the area under the sROC was 0.93 (standard error, 0.03). These pooled results suggest that while highly trained dogs have the potentiality to diagnose PCa, the ability is primarily related to olfactory physiology and training methodology. The adoption of advanced analytical techniques, such as eNose, poses a significant challenge in the field of clinical practice due to their growing effectiveness. Nevertheless, the presence of limitations and the requirement for meticulous study design continue to present challenges when employing eNoses for the diagnosis of PCa.
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Affiliation(s)
- Fabio Grizzi
- Department of Immunology and Inflammation, IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20072 Milan, Italy
| | - Carmen Bax
- Politecnico di Milano, Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, 20133 Milan, Italy
| | - Mohamed A. A. A. Hegazi
- Department of Immunology and Inflammation, IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy
| | - Beatrice Julia Lotesoriere
- Politecnico di Milano, Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, 20133 Milan, Italy
| | - Matteo Zanoni
- Department of Urology, Humanitas Mater Domini, 21100 Castellanza, Italy
| | - Paolo Vota
- Department of Urology, Humanitas Mater Domini, 21100 Castellanza, Italy
| | - Rodolfo Fausto Hurle
- Department of Urology, IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy
| | - Nicolò Maria Buffi
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20072 Milan, Italy
- Department of Urology, IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy
| | - Massimo Lazzeri
- Department of Urology, IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy
| | - Lorenzo Tidu
- Italian Ministry of Defenses, “Vittorio Veneto” Division, 50136 Firenze, Italy
| | - Laura Capelli
- Politecnico di Milano, Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, 20133 Milan, Italy
| | - Gianluigi Taverna
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20072 Milan, Italy
- Department of Urology, Humanitas Mater Domini, 21100 Castellanza, Italy
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Song R, Liu F, Ping Y, Zhang Y, Wang L. Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction. Biomark Res 2023; 11:57. [PMID: 37268978 DOI: 10.1186/s40364-023-00498-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 05/07/2023] [Indexed: 06/04/2023] Open
Abstract
Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15-60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid developments at the intersection of oncology, immunology, biology, and computer science have provided an abundance of predictive biomarkers for ICI efficacy. These biomarkers can be invasive or non-invasive, depending on the specific sample collection method. Compared with invasive markers, a host of non-invasive markers have been confirmed to have superior availability and accuracy in ICI efficacy prediction. Considering the outstanding advantages of dynamic monitoring of the immunotherapy response and the potential for widespread clinical application, we review the recent research in this field with the aim of contributing to the identification of patients who may derive the greatest benefit from ICI therapy.
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Affiliation(s)
- Ruixia Song
- Biotherapy Center and Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Henan Key Laboratory for Tumor Immunology and Biotherapy, Zhengzhou University, Zhengzhou, Henan, China
| | - Fengsen Liu
- Biotherapy Center and Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Henan Key Laboratory for Tumor Immunology and Biotherapy, Zhengzhou University, Zhengzhou, Henan, China
- School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Yu Ping
- Biotherapy Center and Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yi Zhang
- Biotherapy Center and Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
- Henan Key Laboratory for Tumor Immunology and Biotherapy, Zhengzhou University, Zhengzhou, Henan, China.
- School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China.
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou, Henan, China.
| | - Liping Wang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
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Rosellini M, Marchetti A, Mollica V, Rizzo A, Santoni M, Massari F. Prognostic and predictive biomarkers for immunotherapy in advanced renal cell carcinoma. Nat Rev Urol 2023; 20:133-157. [PMID: 36414800 DOI: 10.1038/s41585-022-00676-0] [Citation(s) in RCA: 53] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/24/2022] [Indexed: 11/23/2022]
Abstract
The therapeutic algorithm of renal cell carcinoma has been revolutionized by the approval of immunotherapy agents by regulatory agencies. However, objective and durable responses are still not observed in a large number of patients, and prognostic and predictive biomarkers for immunotherapy response are urgently needed. Prognostic models used in clinical practice are based on clinical and laboratory factors (such as hypercalcaemia, neutrophil count or Karnofsky Performance Status), but, with progress in molecular biology and genome sequencing techniques, new renal cell carcinoma molecular features that might improve disease course and outcomes prediction have been highlighted. An implementation of current models is needed to improve the accuracy of prognosis in the immuno-oncology era. Moreover, several potential biomarkers are currently under evaluation, but effective markers to select patients who might benefit from immunotherapy and to guide therapeutic strategies are still far from validation.
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Affiliation(s)
- Matteo Rosellini
- Medical Oncology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Andrea Marchetti
- Medical Oncology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Veronica Mollica
- Medical Oncology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Alessandro Rizzo
- Struttura Semplice Dipartimentale di Oncologia Medica per la Presa in Carico Globale del Paziente Oncologico "Don Tonino Bello", I.R.C.C.S. Istituto Tumori "Giovanni Paolo II", Bari, Italy
| | | | - Francesco Massari
- Medical Oncology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
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Kort S, Brusse-Keizer M, Schouwink H, Citgez E, de Jongh FH, van Putten JWG, van den Borne B, Kastelijn EA, Stolz D, Schuurbiers M, van den Heuvel MM, van Geffen WH, van der Palen J. Diagnosing Non-Small Cell Lung Cancer by Exhaled Breath Profiling Using an Electronic Nose: A Multicenter Validation Study. Chest 2023; 163:697-706. [PMID: 36243060 DOI: 10.1016/j.chest.2022.09.042] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 09/02/2022] [Accepted: 09/23/2022] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Despite the potential of exhaled breath analysis of volatile organic compounds to diagnose lung cancer, clinical implementation has not been realized, partly due to the lack of validation studies. RESEARCH QUESTION This study addressed two questions. First, can we simultaneously train and validate a prediction model to distinguish patients with non-small cell lung cancer from non-lung cancer subjects based on exhaled breath patterns? Second, does addition of clinical variables to exhaled breath data improve the diagnosis of lung cancer? STUDY DESIGN AND METHODS In this multicenter study, subjects with non-small cell lung cancer and control subjects performed 5 min of tidal breathing through the aeoNose, a handheld electronic nose device. A training cohort was used for developing a prediction model based on breath data, and a blinded cohort was used for validation. Multivariable logistic regression analysis was performed, including breath data and clinical variables, in which the formula and cutoff value for the probability of lung cancer were applied to the validation data. RESULTS A total of 376 subjects formed the training set, and 199 subjects formed the validation set. The full training model (including exhaled breath data and clinical parameters from the training set) were combined in a multivariable logistic regression analysis, maintaining a cut off of 16% probability of lung cancer, resulting in a sensitivity of 95%, a specificity of 51%, and a negative predictive value of 94%; the area under the receiver-operating characteristic curve was 0.87. Performance of the prediction model on the validation cohort showed corresponding results with a sensitivity of 95%, a specificity of 49%, a negative predictive value of 94%, and an area under the receiver-operating characteristic curve of 0.86. INTERPRETATION Combining exhaled breath data and clinical variables in a multicenter, multi-device validation study can adequately distinguish patients with lung cancer from subjects without lung cancer in a noninvasive manner. This study paves the way to implement exhaled breath analysis in the daily practice of diagnosing lung cancer. CLINICAL TRIAL REGISTRATION The Netherlands Trial Register; No.: NL7025; URL: https://trialregister.nl/trial/7025.
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Affiliation(s)
- Sharina Kort
- Department of Respiratory Medicine, Medisch Spectrum Twente Enschede, Enschede, The Netherlands.
| | - Marjolein Brusse-Keizer
- Medical School Twente, Enschede, The Netherlands; Universiteit of Twente, Faculty of Behavioural Management and Social Sciences, Enschede, The Netherlands
| | - Hugo Schouwink
- Department of Respiratory Medicine, Medisch Spectrum Twente Enschede, Enschede, The Netherlands
| | - Emanuel Citgez
- Department of Respiratory Medicine, Medisch Spectrum Twente Enschede, Enschede, The Netherlands
| | - Frans H de Jongh
- Department of Respiratory Medicine, Medisch Spectrum Twente Enschede, Enschede, The Netherlands; Universiteit of Twente, Faculty of Behavioural Management and Social Sciences, Enschede, The Netherlands
| | - Jan W G van Putten
- Department of Respiratory Medicine, Martini Ziekenhuis, Groningen, The Netherlands
| | - Ben van den Borne
- Department of Respiratory Medicine, Catharina Ziekenhuis, Eindhoven, The Netherlands
| | - Elisabeth A Kastelijn
- Department of Respiratory Medicine, Sint Antonius Ziekenhuis, Utrecht, The Netherlands
| | - Daiana Stolz
- Clinic for Pulmonary Medicine and Respiratory Cell Research, Universitätspital Basel, Basel, Switzerland; Clinic for Respiratory Medicine, Medical Center, University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Milou Schuurbiers
- Department of Respiratory Medicine, Radboud UMC, Nijmegen, The Netherlands
| | | | - Wouter H van Geffen
- Department of Respiratory Medicine, Medisch Centrum Leeuwarden, Leeuwarden, The Netherlands
| | - Job van der Palen
- Medical School Twente, Enschede, The Netherlands; Universiteit of Twente, Faculty of Behavioural Management and Social Sciences, Enschede, The Netherlands
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Safety and tolerability of stereotactic radiotherapy combined with durvalumab with or without tremelimumab in advanced non-small cell lung cancer, the phase I SICI trial. Lung Cancer 2023; 178:96-102. [PMID: 36806899 DOI: 10.1016/j.lungcan.2023.02.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/23/2022] [Accepted: 02/04/2023] [Indexed: 02/10/2023]
Abstract
INTRODUCTION This phase I study primarily addresses the safety and tolerability of Stereotactic radiotherapy on the primary tumor combined with double Immune Checkpoint Inhibition (SICI) in patients with non-small cell lung cancer (NSCLC). Increasing the release of neoantigens by radiotherapy might enhance response to immunotherapy. Especially, by targeting trunk mutations in the primary tumor. MATERIALS AND METHODS In three sequential cohorts, immunotherapy regimes combined with stereotactic body radiotherapy (SBRT) on the primary tumor (1x20 Gy on 9 cc) were studied in stage IIIB/IV NSCLC patients progressing on chemotherapy. The first cohort (n = 3) received durvalumab. The second (n = 6) received a combination of tremelimumab and durvalumab followed by durvalumab monotherapy. The third cohort (n = 6) was similar except that the combination was reversed. Descriptive statistics were used to assess safety parameters and the exploratory outcomes of efficacy. Adverse events were reported using NCI CTCAE version 4.03. Exhaled breath was analyzed at baseline. RESULTS Fifteen patients were included. Median irradiated volume was 9.13 cc, on a median primary tumor volume of 79 cc. There were seven patients with grade 1-2, and two patients with grade 3 treatment related adverse events. There was 1 dose limiting toxicity (colitis) with double immunotherapy. CONCLUSION The combination of SBRT to the primary tumor and double immunotherapy in advanced NSCLC patients is safe and feasible.
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Keogh RJ, Riches JC. The Use of Breath Analysis in the Management of Lung Cancer: Is It Ready for Primetime? Curr Oncol 2022; 29:7355-7378. [PMID: 36290855 PMCID: PMC9600994 DOI: 10.3390/curroncol29100578] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/22/2022] [Accepted: 09/28/2022] [Indexed: 11/07/2022] Open
Abstract
Breath analysis is a promising non-invasive method for the detection and management of lung cancer. Exhaled breath contains a complex mixture of volatile and non-volatile organic compounds that are produced as end-products of metabolism. Several studies have explored the patterns of these compounds and have postulated that a unique breath signature is emitted in the setting of lung cancer. Most studies have evaluated the use of gas chromatography and mass spectrometry to identify these unique breath signatures. With recent advances in the field of analytical chemistry and machine learning gaseous chemical sensing and identification devices have also been created to detect patterns of odorant molecules such as volatile organic compounds. These devices offer hope for a point-of-care test in the future. Several prospective studies have also explored the presence of specific genomic aberrations in the exhaled breath of patients with lung cancer as an alternative method for molecular analysis. Despite its potential, the use of breath analysis has largely been limited to translational research due to methodological issues, the lack of standardization or validation and the paucity of large multi-center studies. It is clear however that it offers a potentially non-invasive alternative to investigations such as tumor biopsy and blood sampling.
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