Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma
(1) Background: Oesophageal cancers are often late-presenting and have a poor 5-year survival rate. The standard treatment of oesophageal adenocarcinomas involves neoadjuvant chemotherapy with or without radiotherapy followed by surgery. However, less than one third of patients respond to neoadjuvan...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Cancers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-6694/14/4/996 |
| _version_ | 1797482110955552768 |
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| author | William Jiang Jelske M. de Jong Richard van Hillegersberg Matthew Read |
| author_facet | William Jiang Jelske M. de Jong Richard van Hillegersberg Matthew Read |
| author_sort | William Jiang |
| collection | DOAJ |
| description | (1) Background: Oesophageal cancers are often late-presenting and have a poor 5-year survival rate. The standard treatment of oesophageal adenocarcinomas involves neoadjuvant chemotherapy with or without radiotherapy followed by surgery. However, less than one third of patients respond to neoadjuvant therapy, thereby unnecessarily exposing patients to toxicity and deconditioning. Hence, there is an urgent need for biomarkers to predict response to neoadjuvant therapy. This review explores the current biomarker landscape. (2) Methods: MEDLINE, EMBASE and ClinicalTrial databases were searched with key words relating to “predictive biomarker”, “neoadjuvant therapy” and “oesophageal adenocarcinoma” and screened as per the inclusion and exclusion criteria. All peer-reviewed full-text articles and conference abstracts were included. (3) Results: The search yielded 548 results of which 71 full-texts, conference abstracts and clinical trials were eligible for review. A total of 242 duplicates were removed, 191 articles were screened out, and 44 articles were excluded. (4) Discussion: Biomarkers were discussed in seven categories including imaging, epigenetic, genetic, protein, immunologic, blood and serum-based with remaining studies grouped in a miscellaneous category. (5) Conclusion: Although promising markers and novel methods have emerged, current biomarkers lack sufficient evidence to support clinical application. Novel approaches have been recommended to assess predictive potential more efficiently. |
| first_indexed | 2024-03-09T22:24:37Z |
| format | Article |
| id | doaj.art-eedd7a5efb314b78a881a7a7039f2fb6 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-09T22:24:37Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-eedd7a5efb314b78a881a7a7039f2fb62023-11-23T19:09:45ZengMDPI AGCancers2072-66942022-02-0114499610.3390/cancers14040996Predicting Response to Neoadjuvant Therapy in Oesophageal AdenocarcinomaWilliam Jiang0Jelske M. de Jong1Richard van Hillegersberg2Matthew Read3Upper Gastrointestinal Surgery Department, St Vincent’s Hospital Melbourne, 41 Victoria Parade, Fitzroy, VIC 3065, AustraliaGastrointestinal Oncology Department, The University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The NetherlandsGastrointestinal Oncology Department, The University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The NetherlandsUpper Gastrointestinal Surgery Department, St Vincent’s Hospital Melbourne, 41 Victoria Parade, Fitzroy, VIC 3065, Australia(1) Background: Oesophageal cancers are often late-presenting and have a poor 5-year survival rate. The standard treatment of oesophageal adenocarcinomas involves neoadjuvant chemotherapy with or without radiotherapy followed by surgery. However, less than one third of patients respond to neoadjuvant therapy, thereby unnecessarily exposing patients to toxicity and deconditioning. Hence, there is an urgent need for biomarkers to predict response to neoadjuvant therapy. This review explores the current biomarker landscape. (2) Methods: MEDLINE, EMBASE and ClinicalTrial databases were searched with key words relating to “predictive biomarker”, “neoadjuvant therapy” and “oesophageal adenocarcinoma” and screened as per the inclusion and exclusion criteria. All peer-reviewed full-text articles and conference abstracts were included. (3) Results: The search yielded 548 results of which 71 full-texts, conference abstracts and clinical trials were eligible for review. A total of 242 duplicates were removed, 191 articles were screened out, and 44 articles were excluded. (4) Discussion: Biomarkers were discussed in seven categories including imaging, epigenetic, genetic, protein, immunologic, blood and serum-based with remaining studies grouped in a miscellaneous category. (5) Conclusion: Although promising markers and novel methods have emerged, current biomarkers lack sufficient evidence to support clinical application. Novel approaches have been recommended to assess predictive potential more efficiently.https://www.mdpi.com/2072-6694/14/4/996oesophageal adenocarcinomagastroesophageal adenocarcinomaoesophageal cancerpredictive biomarkerimaging markerpredict response |
| spellingShingle | William Jiang Jelske M. de Jong Richard van Hillegersberg Matthew Read Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma Cancers oesophageal adenocarcinoma gastroesophageal adenocarcinoma oesophageal cancer predictive biomarker imaging marker predict response |
| title | Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma |
| title_full | Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma |
| title_fullStr | Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma |
| title_full_unstemmed | Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma |
| title_short | Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma |
| title_sort | predicting response to neoadjuvant therapy in oesophageal adenocarcinoma |
| topic | oesophageal adenocarcinoma gastroesophageal adenocarcinoma oesophageal cancer predictive biomarker imaging marker predict response |
| url | https://www.mdpi.com/2072-6694/14/4/996 |
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