{"title":"非小细胞肺癌（NSCLC）诊断范式的转变：从单一基因测试到综合基因组分析。","authors":"Ushna Zameer, Wajiha Shaikh, Abdul Moiz Khan","doi":"10.1177/11769351241243243","DOIUrl":null,"url":null,"abstract":"<p><p>Lung cancer imposes a burden on the health care system worldwide affecting 2 million people and causing 1.8 million deaths in 2021.More than 85% of all lung cancer cases are reported under Non-small-cell lung cancer (NSCLC). It is critical to discover gene alterations to treat non-small cell lung cancer successfully. The CAP/IASLC/AMP recommendations supported use of polymerase chain reaction (PCR) and fluorescent in situ hybridization (FISH) <i>EGFR</i> (epidermal growth factor receptor) mutations and <i>ALK</i> (Anaplastic lymphoma kinase) rearrangements, respectively. A study presented in the annual meeting of the American Society of Clinical Oncology (ASCO) in Chicago emphasized the need for comprehensive genomic profiling (CGP) before single gene tests (SGTs) since it demonstrated that SGT can result in the depletion of precious biopsy samples. As a result, the efficacy of thorough genetic Profiling (CGP) is reduced, preventing patients from receiving valuable genetic information about their tumors.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10998481/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Paradigm Shift in Non-Small-Cell Lung Cancer (NSCLC) Diagnostics: From Single Gene Tests to Comprehensive Genomic Profiling.\",\"authors\":\"Ushna Zameer, Wajiha Shaikh, Abdul Moiz Khan\",\"doi\":\"10.1177/11769351241243243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Lung cancer imposes a burden on the health care system worldwide affecting 2 million people and causing 1.8 million deaths in 2021.More than 85% of all lung cancer cases are reported under Non-small-cell lung cancer (NSCLC). It is critical to discover gene alterations to treat non-small cell lung cancer successfully. The CAP/IASLC/AMP recommendations supported use of polymerase chain reaction (PCR) and fluorescent in situ hybridization (FISH) <i>EGFR</i> (epidermal growth factor receptor) mutations and <i>ALK</i> (Anaplastic lymphoma kinase) rearrangements, respectively. A study presented in the annual meeting of the American Society of Clinical Oncology (ASCO) in Chicago emphasized the need for comprehensive genomic profiling (CGP) before single gene tests (SGTs) since it demonstrated that SGT can result in the depletion of precious biopsy samples. As a result, the efficacy of thorough genetic Profiling (CGP) is reduced, preventing patients from receiving valuable genetic information about their tumors.</p>\",\"PeriodicalId\":35418,\"journal\":{\"name\":\"Cancer Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10998481/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/11769351241243243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11769351241243243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
A Paradigm Shift in Non-Small-Cell Lung Cancer (NSCLC) Diagnostics: From Single Gene Tests to Comprehensive Genomic Profiling.
Lung cancer imposes a burden on the health care system worldwide affecting 2 million people and causing 1.8 million deaths in 2021.More than 85% of all lung cancer cases are reported under Non-small-cell lung cancer (NSCLC). It is critical to discover gene alterations to treat non-small cell lung cancer successfully. The CAP/IASLC/AMP recommendations supported use of polymerase chain reaction (PCR) and fluorescent in situ hybridization (FISH) EGFR (epidermal growth factor receptor) mutations and ALK (Anaplastic lymphoma kinase) rearrangements, respectively. A study presented in the annual meeting of the American Society of Clinical Oncology (ASCO) in Chicago emphasized the need for comprehensive genomic profiling (CGP) before single gene tests (SGTs) since it demonstrated that SGT can result in the depletion of precious biopsy samples. As a result, the efficacy of thorough genetic Profiling (CGP) is reduced, preventing patients from receiving valuable genetic information about their tumors.
期刊介绍：
The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.
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