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      Lung adenocarcinoma and squamous cell carcinoma difficult for immunohistochemical diagnosis can be distinguished by lipid profile

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          Abstract

          In patients with unresectable non-small cell lung cancer, histological diagnosis is frequently based on small biopsy specimens unsuitable for histological diagnosis when they are severely crushed and do not retain their morphology. Therefore, establishing a novel diagnostic method independent of tissue morphology or conventional immunohistochemistry (IHC) markers is required. We analyzed the lipid profiles of resected primary lung adenocarcinoma (ADC) and squamous cell carcinoma (SQCC) specimens using liquid chromatography-tandem mass spectrometry. The specimens of 26 ADC and 18 SQCC cases were evenly assigned to the discovery and validation cohorts. Non-target screening on the discovery cohort identified 96 and 13 lipid peaks abundant in ADC and SQCC, respectively. Among these 109 lipid peaks, six and six lipid peaks in ADC and SQCC showed reproducibility in target screening on the validation cohort. Finally, we selected three and four positive lipid markers for ADC and SQCC, demonstrating high discrimination abilities. In cases difficult to diagnose by IHC staining, [cardiolipin(18:2_18:2_18:2_18:2)-H] and [triglyceride(18:1_17:1_18:1) + NH4] + showed the excellent diagnostic ability for ADC (sensitivity: 1.00, specificity: 0.89, accuracy: 0.93) and SQCC (sensitivity: 0.89, specificity: 0.83, accuracy: 0.87), respectively. These novel candidate lipid markers may contribute to a more accurate diagnosis and subsequent treatment strategy for unresectable NSCLC.

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          The 2015 World Health Organization Classification of Lung Tumors: Impact of Genetic, Clinical and Radiologic Advances Since the 2004 Classification.

          The 2015 World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart has just been published with numerous important changes from the 2004 WHO classification. The most significant changes in this edition involve (1) use of immunohistochemistry throughout the classification, (2) a new emphasis on genetic studies, in particular, integration of molecular testing to help personalize treatment strategies for advanced lung cancer patients, (3) a new classification for small biopsies and cytology similar to that proposed in the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (4) a completely different approach to lung adenocarcinoma as proposed by the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (5) restricting the diagnosis of large cell carcinoma only to resected tumors that lack any clear morphologic or immunohistochemical differentiation with reclassification of the remaining former large cell carcinoma subtypes into different categories, (6) reclassifying squamous cell carcinomas into keratinizing, nonkeratinizing, and basaloid subtypes with the nonkeratinizing tumors requiring immunohistochemistry proof of squamous differentiation, (7) grouping of neuroendocrine tumors together in one category, (8) adding NUT carcinoma, (9) changing the term sclerosing hemangioma to sclerosing pneumocytoma, (10) changing the name hamartoma to "pulmonary hamartoma," (11) creating a group of PEComatous tumors that include (a) lymphangioleiomyomatosis, (b) PEComa, benign (with clear cell tumor as a variant) and
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            MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights

            Since its first release over a decade ago, the MetaboAnalyst web-based platform has become widely used for comprehensive metabolomics data analysis and interpretation. Here we introduce MetaboAnalyst version 5.0, aiming to narrow the gap from raw data to functional insights for global metabolomics based on high-resolution mass spectrometry (HRMS). Three modules have been developed to help achieve this goal, including: (i) a LC–MS Spectra Processing module which offers an easy-to-use pipeline that can perform automated parameter optimization and resumable analysis to significantly lower the barriers to LC-MS1 spectra processing; (ii) a Functional Analysis module which expands the previous MS Peaks to Pathways module to allow users to intuitively select any peak groups of interest and evaluate their enrichment of potential functions as defined by metabolic pathways and metabolite sets; (iii) a Functional Meta-Analysis module to combine multiple global metabolomics datasets obtained under complementary conditions or from similar studies to arrive at comprehensive functional insights. There are many other new functions including weighted joint-pathway analysis, data-driven network analysis, batch effect correction, merging technical replicates, improved compound name matching, etc. The web interface, graphics and underlying codebase have also been refactored to improve performance and user experience. At the end of an analysis session, users can now easily switch to other compatible modules for a more streamlined data analysis. MetaboAnalyst 5.0 is freely available at https://www.metaboanalyst.ca . Graphical Abstract From raw data to statistical and functional insights using MetaboAnalyst 5.0.
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              International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma.

              Adenocarcinoma is the most common histologic type of lung cancer. To address advances in oncology, molecular biology, pathology, radiology, and surgery of lung adenocarcinoma, an international multidisciplinary classification was sponsored by the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society. This new adenocarcinoma classification is needed to provide uniform terminology and diagnostic criteria, especially for bronchioloalveolar carcinoma (BAC), the overall approach to small nonresection cancer specimens, and for multidisciplinary strategic management of tissue for molecular and immunohistochemical studies. An international core panel of experts representing all three societies was formed with oncologists/pulmonologists, pathologists, radiologists, molecular biologists, and thoracic surgeons. A systematic review was performed under the guidance of the American Thoracic Society Documents Development and Implementation Committee. The search strategy identified 11,368 citations of which 312 articles met specified eligibility criteria and were retrieved for full text review. A series of meetings were held to discuss the development of the new classification, to develop the recommendations, and to write the current document. Recommendations for key questions were graded by strength and quality of the evidence according to the Grades of Recommendation, Assessment, Development, and Evaluation approach. The classification addresses both resection specimens, and small biopsies and cytology. The terms BAC and mixed subtype adenocarcinoma are no longer used. For resection specimens, new concepts are introduced such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) for small solitary adenocarcinomas with either pure lepidic growth (AIS) or predominant lepidic growth with ≤ 5 mm invasion (MIA) to define patients who, if they undergo complete resection, will have 100% or near 100% disease-specific survival, respectively. AIS and MIA are usually nonmucinous but rarely may be mucinous. Invasive adenocarcinomas are classified by predominant pattern after using comprehensive histologic subtyping with lepidic (formerly most mixed subtype tumors with nonmucinous BAC), acinar, papillary, and solid patterns; micropapillary is added as a new histologic subtype. Variants include invasive mucinous adenocarcinoma (formerly mucinous BAC), colloid, fetal, and enteric adenocarcinoma. This classification provides guidance for small biopsies and cytology specimens, as approximately 70% of lung cancers are diagnosed in such samples. Non-small cell lung carcinomas (NSCLCs), in patients with advanced-stage disease, are to be classified into more specific types such as adenocarcinoma or squamous cell carcinoma, whenever possible for several reasons: (1) adenocarcinoma or NSCLC not otherwise specified should be tested for epidermal growth factor receptor (EGFR) mutations as the presence of these mutations is predictive of responsiveness to EGFR tyrosine kinase inhibitors, (2) adenocarcinoma histology is a strong predictor for improved outcome with pemetrexed therapy compared with squamous cell carcinoma, and (3) potential life-threatening hemorrhage may occur in patients with squamous cell carcinoma who receive bevacizumab. If the tumor cannot be classified based on light microscopy alone, special studies such as immunohistochemistry and/or mucin stains should be applied to classify the tumor further. Use of the term NSCLC not otherwise specified should be minimized. This new classification strategy is based on a multidisciplinary approach to diagnosis of lung adenocarcinoma that incorporates clinical, molecular, radiologic, and surgical issues, but it is primarily based on histology. This classification is intended to support clinical practice, and research investigation and clinical trials. As EGFR mutation is a validated predictive marker for response and progression-free survival with EGFR tyrosine kinase inhibitors in advanced lung adenocarcinoma, we recommend that patients with advanced adenocarcinomas be tested for EGFR mutation. This has implications for strategic management of tissue, particularly for small biopsies and cytology samples, to maximize high-quality tissue available for molecular studies. Potential impact for tumor, node, and metastasis staging include adjustment of the size T factor according to only the invasive component (1) pathologically in invasive tumors with lepidic areas or (2) radiologically by measuring the solid component of part-solid nodules.
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                Author and article information

                Contributors
                kfunai@hama-med.ac.jp
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                26 July 2023
                26 July 2023
                2023
                : 13
                : 12092
                Affiliations
                [1 ]GRID grid.505613.4, ISNI 0000 0000 8937 6696, First Department of Surgery, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka 431-3192 Japan
                [2 ]GRID grid.505613.4, ISNI 0000 0000 8937 6696, Department of Cellular and Molecular Anatomy, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka 431-3192 Japan
                [3 ]GRID grid.505613.4, ISNI 0000 0000 8937 6696, Department of Tumor Pathology, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka 431-3192 Japan
                [4 ]GRID grid.505613.4, ISNI 0000 0000 8937 6696, Advanced Research Facilities and Services, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka 431-3192 Japan
                [5 ]Preppers Co. Ltd., 1-23-17 Kitashinagawa, Shinagawa Ward, Tokyo, 140-0001 Japan
                [6 ]MS-Solutions Co. Ltd., 2-18-13, Ogawanishimachi, Kodaira, Tokyo 187-0035 Japan
                [7 ]GRID grid.505613.4, ISNI 0000 0000 8937 6696, International Mass Imaging Center, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka 431-3192 Japan
                [8 ]Department of Systems Molecular Anatomy, Institute for Medical Photonics Research, Preeminent Medical Photonics Education and Research Center, 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka 431-3192 Japan
                Article
                37848
                10.1038/s41598-023-37848-w
                10372017
                37495609
                293cfb0a-e7e3-4309-a343-b5231375585b
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 March 2023
                : 28 June 2023
                Funding
                Funded by: the Japan agency for medical research and development
                Award ID: JP20gm0910004 / JP22ak0101179
                Award Recipient :
                Categories
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                © Springer Nature Limited 2023

                Uncategorized
                cancer,lung cancer,surgical oncology,mass spectrometry
                Uncategorized
                cancer, lung cancer, surgical oncology, mass spectrometry

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