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Ge L, Wang L, Pei D. Pulmonary mucinous adenocarcinoma: An overview of pathophysiology and advancements in treatment. Heliyon 2024; 10:e28881. [PMID: 38694119 PMCID: PMC11058725 DOI: 10.1016/j.heliyon.2024.e28881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 02/21/2024] [Accepted: 03/26/2024] [Indexed: 05/03/2024] Open
Abstract
Pulmonary mucinous adenocarcinoma (PMA), a distinct subtype of non-small cell lung cancer (NSCLC), is characterized by an abundance of mucin-producing cells. Although this subtype comprises a relatively small fraction of lung adenocarcinomas, PMA stands apart due to its unique clinical, pathological, and molecular features. This review comprehensively discusses the pathophysiology and etiology, clinical features, diagnostic methods, treatment strategies, prognosis, and future directions for PMA, drawing from relevant literature and existing studies. Advances in PMA treatment includes surgical intervention, targeted therapy, immunotherapy, and adjuvant therapy. Particularly, we discussed factors influencing the prognosis of PMAs, such as molecular markers, pathological features, and the impact of the latest treatment advances on prognosis. Moreover, we intended this review to be a comprehensive reference for diagnosing, treating, and assessing the prognosis of PMA, providing valuable guidance for clinical practice.
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Affiliation(s)
- Lihui Ge
- Department of Health Management, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Linlin Wang
- Department of Thoracic Surgery, Shenyang Tenth People's Hospital, Shenyang, Liaoning, China
| | - Dongmei Pei
- Department of Health Management, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
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Bou-Samra P, Joffe J, Chang A, Guo E, Segil A, Azari F, Kennedy G, Din A, Hwang WT, Singhal S. Preoperative predictors of successful tumour localization by intraoperative molecular imaging with pafolacianine in lung cancer to create predictive nomogram. Eur J Cardiothorac Surg 2024; 65:ezad392. [PMID: 38191994 DOI: 10.1093/ejcts/ezad392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/17/2023] [Accepted: 01/05/2024] [Indexed: 01/10/2024] Open
Abstract
OBJECTIVES Intraoperative molecular imaging (IMI) uses cancer-targeted fluorescent probe to locate nodules. Pafolacianine is a Food and Drug Administration-approved fluorescent probe for lung cancer. However, it has a 8-12% false negative rate for localization. Our goal is to define preoperative predictors of tumour localization by IMI. METHODS We performed a retrospective review of patients who underwent IMI using pafolacianine for lung lesions from June 2015 to August 2019. Candidate predictors including sex, age, body mass index, smoking history, tumour size, distance of tumour from surface, use of neoadjuvant therapy and positron emission tomography avidity were included. The outcome was fluorescence in vivo and comprehensively included those who were true or false positives negatives. Multiple imputation was used to handle the missing data. The final model was evaluated using the area under the receiver operating characteristic curve. RESULTS Three hundred nine patients were included in our study. The mean age was 64 (standard deviation 13) and 68% had a smoking history. The mean distance of the tumours from the pleural surface was 0.4 cm (standard deviation 0.6). Smoking in pack-years and distance from pleura had an odds ratio of 0.99 [95% confidence interval: 0.98-0.99; P = 0.03] and 0.46 [95% confidence interval: 0.27-0.78; P = 0.004], respectively. The final model had an area under the receiver operating characteristic curve of 0.68 and was used to create a nomogram that gives a probability of fluorescence in vivo. CONCLUSIONS Primary tumours that are deeper from the pleural surface, especially in patients with a higher pack-years, are associated with a decreased likelihood of intraoperative localization. We identified a nomogram to predict the likelihood of tumour localization with IMI with pafolacianine.
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Affiliation(s)
- Patrick Bou-Samra
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Thoracic Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jonah Joffe
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics (DBEI), The University of Pennsylvania, Philadelphia, PA, USA
| | - Austin Chang
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Thoracic Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Emily Guo
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Thoracic Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Alix Segil
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Thoracic Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Feredun Azari
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Thoracic Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Gregory Kennedy
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Thoracic Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Azra Din
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Thoracic Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Wei-Ting Hwang
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics (DBEI), The University of Pennsylvania, Philadelphia, PA, USA
| | - Sunil Singhal
- University of Pennsylvania, Perlman School of Medicine, Department of Surgery, Philadelphia, PA, USA
- Abramson Cancer Center, Department Of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
- Department of Thoracic Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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