Fig. 7: Recommended procedure for discriminating MLCs. | npj Precision Oncology

Fig. 7: Recommended procedure for discriminating MLCs.

From: Optimizing the NGS-based discrimination of multiple lung cancers from the perspective of evolution

Fig. 7

The gray boxes stand for the diagnostic steps before discriminating MLCs. The pink boxes display the clinicopathological evaluation and possible biopsy. The blue boxes describe the molecular assessment. The discrimination of MLCs starts with clinical evaluation. If preoperative biopsy of multiple foci is possible, it may allow the identification based on molecular features. Resected tumors are routinely subjected to pathological evaluation, which can unambiguously diagnose some typical cases with CHA. Molecular evaluation is recommended to be carried out together with pathology for all cases to reduce misdiagnosis. If the case is pathologically equivocal or lacking experienced pathologists, molecular evaluation should be preferentially performed. Bioinformatic interpretation of detected mutations is advised to quantify the clonal relatedness. On this premise, NGS with the NCCNplus panel (9 drivers recommended by the NCCN [EGFR, KRAS, ALK, BRAF, ERBB2, MET, RET, ROS1, PIK3CA] plus TP53) is recommended as the first choice, followed by WES as the second choice, and NGS with panels modified for MLCs as the third choice. With limited access to bioinformatic analysis, NGS using pancancer panels is recommended. If no mutation has been detected by limited sequencing, WES should be applied to eliminate inconclusiveness. Techniques based on other marker, such as variations in chromosomes or RNAs need further verification but could be carried out simultaneously with the former methods for research purposes. MLCs multiple lung cancers, MPLC multiple primary lung cancers, IPM intrapulmonary metastasis, NGS next-generation sequencing, WES whole-exome sequencing, ACCP American College of Chest Physicians, IASLC International Association for the Study of Lung Cancer, NCCN National Comprehensive Cancer Network.

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