Integrating NGS-derived mutational profiling in the diagnosis of multiple lung adenocarcinomas

Next-Generation Sequencing vs. Clinical-Pathological Assessment in Diagnosis of Multiple Lung Cancers: A Systematic Review and Meta-Analysis

Accurately distinguishing between multiple primary lung cancers (MPLC) and intrapulmonary metastasis (IPM) is crucial for tailoring treatment strategies and improving patient outcomes. While molecular methods offer significant advantages over traditional clinical-pathological evaluations, they lack standardized diagnostic protocols and validated prognostic value. This study systematically compared the diagnostic and prognostic performance of molecular methods versus clinical-pathological evaluations in diagnosing multiple lung cancers (MLCs), specifically focusing on the impact of next-generation sequencing (NGS) parameters on diagnostic accuracy. A review of 41 studies encompassing 1266 patients revealed that two molecular methods, Mole1 (manually counting shared mutations) and Mole2 (bioinformatics-assisted clonal probability calculation), both demonstrated superior diagnostic accuracy and prognostic discrimination capabilities. Molecular assessment, particularly Mole1, effectively stratified prognosis for MPLC and IPM, leading to significantly improved disease-free survival (DFS: HR = 0.24, 95% CI: 0.15-0.39) and overall survival (OS: HR = 0.33, 95% CI: 0.18-0.58). Further analysis suggests that a minimal panel of 30-50 genes may be sufficient to effectively differentiate prognoses. Compared to Mole1, Mole2 demonstrated greater specificity and stability across various panels, achieving AUC values from 0.962 to 0.979. Clinical-pathological evaluations proved unreliable, not only failing to distinguish prognosis effectively but also exhibiting a potential misdiagnosis rate of 35.5% and 33.6% compared to the reference diagnosis. To improve both cost-effectiveness and diagnostic accuracy, bioinformatics-assisted molecular diagnostics should be integrated into multidisciplinary assessments, especially for high-risk cases where diagnostic errors are common.

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

Next-generation sequencing (NGS) offers a promising approach for differentiating multiple primary lung cancers (MPLC) from intrapulmonary metastasis (IPM), though panel selection and clonal interpretation remain challenging. Whole-exome sequencing (WES) data from 80 lung cancer samples were utilized to simulate MPLC and IPM, with various sequenced panels constructed through gene subsampling. Two clonal interpretation approaches primarily applied in clinical practice, MoleA (based on shared mutation comparison) and MoleB (based on probability calculation), were subsequently evaluated. ROC analysis highlighted MoleB's superior performance, especially with the NCCNplus panel (AUC = 0.950 ± 0.002) and pancancer MoleA (AUC = 0.792 ± 0.004). In two independent cohorts (WES cohort, N = 42 and non-WES cohort, N = 94), NGS-based methodologies effectively stratified disease-free survival, with NCCNplus MoleB further predicting prognosis. Phylogenetic analysis further revealed evolutionary distinctions between MPLC and IPM, establishing an optimized NGS-based framework for differentiating multiple lung cancers.

Chemotherapy combined with immunotherapy in a patient with multiple primary gastric and rectal cancers with good prognosis: A case report

RATIONALE

Multiple primary cancer is common in clinical practice, but its diagnosis process is complicated, and relevant genetic testing is required to assist in diagnosis when necessary. The formulation of treatment strategies for multiple primary cancer is a highly personalized process. In this article, we introduce a case of a patient with rectal cancer and gastric cancer who was diagnosed with multiple primary cancers, to investigate and explore the clinical application value of next-generation sequencing (NGS) testing in patients with multiple primary gastric and colorectal cancers.

PATIENT CONCERNS

A 74-year-old male patient had a mass at the anal verge.

DIAGNOSES

Endoscopy, imaging studies, and pathological examinations showed adenocarcinoma in both the rectal and gastric antral regions. Genetic testing confirmed the diagnosis of multiple primary cancer.

INTERVENTIONS

The patient received 8 cycles of neoadjuvant chemotherapy combined with immunotherapy and underwent laparoscopic radical resection for rectal cancer. Postoperative adjuvant chemotherapy (XELOX) supplemented with PD-1 immunotherapy, and Camrelizumab was continued.

OUTCOMES

Gastric lesions continued to regress and eventually disappeared completely at the end of adjuvant therapy.

LESSONS

According to the results of NGS testing, the multiple primary cancers' patient received personalized treatment and ultimately achieved clinical complete remission. This case highlights the critical role of genetic testing in accurately identifying multiple primary cancer and the value of personalized guidance for patient treatment using NGS in clinical practice.

Multiple primary lung cancer: Updates and perspectives

Management of multiple primary lung cancer (MPLC) remains challenging, partly due to its increasing incidence, especially with the significant rise in cases of multiple lung nodules caused by low-dose computed tomography screening. Moreover, the indefinite pathogenesis, diagnostic criteria, and treatment selection add to the complexity. In recent years, there have been continuous efforts to dissect the molecular characteristics of MPLC and explore new diagnostic approaches as well as treatment modalities, which will be reviewed here, with a focus on newly emerging evidence and future perspectives, hope to provide new insights into the management of MPLC and serve as inspiration for future research related to MPLC.

Classification of multiple primary lung cancer in patients with multifocal lung cancer: assessment of a machine learning approach using multidimensional genomic data

Background

Multiple primary lung cancer (MPLC) is an increasingly well-known clinical phenomenon. However, its molecular characterizations are poorly understood, and still lacks of effective method to distinguish it from intrapulmonary metastasis (IM). Herein, we propose an identification model based on molecular multidimensional analysis in order to accurately optimize treatment.

Methods

A total of 112 Chinese lung cancers harboring at least two tumors (n = 270) were enrolled. We retrospectively selected 74 patients with 121 tumor pairs and randomly divided the tumor pairs into a training cohort and a test cohort in a 7:3 ratio. A novel model was established in training cohort, optimized for MPLC identification using comprehensive genomic profiling analyzed by a broad panel with 808 cancer-related genes, and evaluated in the test cohort and a prospective validation cohort of 38 patients with 112 tumors.

Results

We found differences in molecular characterizations between the two diseases and rigorously selected the characterizations to build an identification model. We evaluated the performance of the classifier using the test cohort data and observed an 89.5% percent agreement (PA) for MPLC and a 100.0% percent agreement for IM. The model showed an excellent area under the curve (AUC) of 0.947 and a 91.3% overall accuracy. Similarly, the assay achieved a considerable performance in the independent validation set with an AUC of 0.938 and an MPLC predictive value of 100%. More importantly, the MPLC predictive value of the classification achieved 100% in both the test set and validation cohort. Compared to our previous mutation-based method, the classifier showed better κ consistencies with clinical classification among all 112 patients (0.84 vs. 0.65, p <.01).

Conclusion

These data provide novel evidence of MPLC-specific genomic characteristics and demonstrate that our one-step molecular classifier can accurately classify multifocal lung tumors as MPLC or IM, which suggested that broad panel NGS may be a useful tool for assisting with differential diagnoses.

Case report: Targeted sequencing facilitates the diagnosis and management of rare multifocal pure ground-glass opacities with intrapulmonary metastasis

Introduction

Treatments for multiple ground-glass opacities (GGOs) for which the detection rate is increasing are still controversial. Next-generation sequencing (NGS) may provide additional key evidence for differential diagnosis or optimal therapeutic schedules.

Case presentation

We first reported a rare case in which more than 100 bilateral pulmonary GGOs (91.7% of the GGOs were pure GGOs) were diagnosed as both multiple primary lung cancer and intrapulmonary metastasis. We performed NGS with an 808-gene panel to assess both somatic and germline alterations in tissues and plasma. The patient (male) underwent three successive surgeries and received osimertinib adjuvant therapy due to signs of metastasis and multiple EGFR-mutated tumors. The patient had multiple pure GGOs, and eight tumors of four pathological subtypes were evaluated for the clonal relationship. Metastasis, including pure GGOs and atypical adenomatous hyperplasia, was found between two pairs of tumors. Circulating tumor DNA (ctDNA) monitoring of disease status may impact clinical decision-making.

Conclusions

Surgery combined with targeted therapies remains a reasonable alternative strategy for treating patients with multifocal GGOs, and NGS is valuable for facilitating diagnostic workup and adjuvant therapy with targeted drugs through tissue and disease monitoring via ctDNA.