Literature DB >> 31714259

Beyond tissue biopsy: a diagnostic framework to address tumor heterogeneity in lung cancer.

Wieland Voigt1, Christian Manegold2, Lothar Pilz2, Yi-Long Wu3, Leonard Müllauer4, Robert Pirker5, Martin Filipits6, Jacek Niklinski7, Lubos Petruzelka8, Helmut Prosch9.   

Abstract

PURPOSE OF REVIEW: The objective of this review is to discuss the strength and limitations of tissue and liquid biopsy and functional imaging to capture spatial and temporal tumor heterogeneity either alone or as part of a diagnostic framework in non-small cell lung cancer (NSCLC). RECENT
FINDINGS: NSCLC displays genetic and phenotypic heterogeneity - a detailed knowledge of which is crucial to personalize treatment. Tissue biopsy often lacks spatial and temporal resolution. Thus, NSCLC needs to be characterized by complementary diagnostic methods to resolve heterogeneity. Liquid biopsy offers detection of tumor biomarkers and for example, the classification and monitoring of EGFR mutations in NSCLC. It allows repeated sampling, and therefore, appears promising to address temporal aspects of tumor heterogeneity. Functional imaging methods and emerging image analytic tools, such as radiomics capture temporal and spatial heterogeneity. Further standardization of radiomics is required to allow introduction into clinical routine.
SUMMARY: To augment the potential of precision therapy, improved diagnostic characterization of tumors is pivotal. We suggest a comprehensive diagnostic framework combining tissue and liquid biopsy and functional imaging to address the known aspects of spatial and temporal tumor heterogeneity on the example of NSCLC. We envision how this framework might be implemented in clinical practice.

Entities:  

Mesh:

Year:  2020        PMID: 31714259     DOI: 10.1097/CCO.0000000000000598

Source DB:  PubMed          Journal:  Curr Opin Oncol        ISSN: 1040-8746            Impact factor:   3.645


  6 in total

1.  Assessing dynamic metabolic heterogeneity in non-small cell lung cancer patients via ultra-high sensitivity total-body [18F]FDG PET/CT imaging: quantitative analysis of [18F]FDG uptake in primary tumors and metastatic lymph nodes.

Authors:  DaQuan Wang; Xu Zhang; Bo Qiu; SongRan Liu; Hui Liu; ChaoJie Zheng; Jia Fu; YiWen Mo; NaiBin Chen; Rui Zhou; Chu Chu; FangJie Liu; JinYu Guo; Yin Zhou; Yun Zhou; Wei Fan; Hui Liu
Journal:  Eur J Nucl Med Mol Imaging       Date:  2022-07-11       Impact factor: 10.057

2.  Development of a Radiomics Prediction Model for Histological Type Diagnosis in Solitary Pulmonary Nodules: The Combination of CT and FDG PET.

Authors:  Mengmeng Yan; Weidong Wang
Journal:  Front Oncol       Date:  2020-09-15       Impact factor: 6.244

3.  Accuracy of next-generation sequencing for molecular profiling of small specimen of lung cancer: a prospective pilot study of side-by-side comparison.

Authors:  Xiaosong Ben; Dan Tian; Weitao Zhuang; Rixin Chen; Sichao Wang; Zihao Zhou; Cheng Deng; Ruiqing Shi; Songlin Liu; Dongkun Zhang; Jiming Tang; Liang Xie; Haiyu Zhou; Zhou Zhang; Min Li; Xuanye Zhang; Guibin Qiao
Journal:  Diagn Pathol       Date:  2022-10-12       Impact factor: 3.196

Review 4.  Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective.

Authors:  Teresa W-M Fan; Richard M Higashi; Yelena Chernayavskaya; Andrew N Lane
Journal:  Metabolites       Date:  2020-06-15

5.  A Non-invasive Method to Diagnose Lung Adenocarcinoma.

Authors:  Mengmeng Yan; Weidong Wang
Journal:  Front Oncol       Date:  2020-04-29       Impact factor: 6.244

6.  Unveiling mutational dynamics in non-small cell lung cancer patients by quantitative EGFR profiling in vesicular RNA.

Authors:  Luigi Pasini; Michela Notarangelo; Alessandro Vagheggini; Marco Angelo Burgio; Lucio Crinò; Elisa Chiadini; Andrea Iamurri Prochowski; Angelo Delmonte; Paola Ulivi; Vito Giuseppe D'Agostino
Journal:  Mol Oncol       Date:  2021-05-20       Impact factor: 6.603

  6 in total

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