Targeted Gene Next-Generation Sequencing Panel in Patients with Advanced Lung Adenocarcinoma: Paving the Way for Clinical Implementation

Cancer patient management: Current use of next-generation sequencing in the EU TOP4

BACKGROUND

Next-generation sequencing (NGS) is recognised by a growing audience of medical professionals as a functional diagnostic tool in oncology. However, adoption in clinical routine proceeds haphazardly in Europe.

METHODS

A semi-structured interview survey was administered to 68 cancer care professionals in four EU countries between June-August and November-December 2021. Pre-screening questionnaires assessed sufficient NGS expertise, diverse geographical distribution, and professional roles.

RESULTS

Our findings provide a better understanding of current clinical, regulatory, and reimbursement practices for NGS in four EU countries.

CONCLUSIONS

Despite the impending European In-vitro Diagnostic Medical Devices Regulation (IVDR), tortuous national guidelines implementations and limping reimbursement policies are common traits across surveyed countries and produce disparity in access to advanced healthcare services amid regional distinctions.

POLICY SUMMARY

The evident information gap between involved parties and demand for consistent national guidelines could be filled by health economics analyses tailored to local specifics to provide factual leverage for a structured adoption of NGS testing.

Chinese expert consensus on the diagnosis and treatment of HER2-altered non-small cell lung cancer

Human epidermal growth factor receptor 2 (HER2) possesses tyrosine kinase activity and participates in cell growth, differentiation and migration, and survival. Its alterations, mainly including mutations, amplifications, and overexpression are associated with poor prognosis and are one of the major drivers in non-small cell lung cancer (NSCLC). Several clinical trials had been investigating on the treatments of HER2-altered NSCLC, including conventional chemotherapy, programmed death 1 (PD-1) inhibitors, tyrosine kinase inhibitors (TKIs) and antibody-drug conjugates (ADCs), however, the results were either disappointing or encouraging, but inconsistent. Trastuzumab deruxtecan (T-DXd) was recently approved by the Food and Drug Administration as the first targeted agent for treating HER2-mutant NSCLC. Effective screening of patients is the key to the clinical application of HER2-targeted agents such as TKIs and ADCs. Various testing methods are nowadays available, including polymerase chain reaction (PCR), next-generation sequencing (NGS), fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), etc. Each method has its pros and cons and should be reasonably assigned to appropriate patients for diagnosis and guiding treatment decisions. To help standardize the clinical workflow, our expert group reached a consensus on the clinical management of HER2-altered NSCLC, focusing on the diagnosis and treatment strategies.

Clinically actionable cancer somatic variants (CACSV): a tumor interpreted dataset for analytical workflows

BACKGROUND

The recent development and enormous application of parallel sequencing technology in oncology has produced immense amounts of cell-specific genetic information. However, publicly available cell-specific genetic variants are not explained by well-established guidelines. Additionally, cell-specific variants interpretation and classification has remained a challenging task and lacks standardization. The Association for Molecular Pathology (AMP), the American Society of Clinical Oncology (ASCO), and the College of American Pathologists (CAP) published the first consensus guidelines for cell-specific variants cataloging and clinical annotations.

METHODS

AMP-ASCO-CAP recommended sources and information were downloaded and used as follows: relative knowledge in oncology clinical practice guidelines; approved, investigative or preclinical drugs; supporting literature and each gene-tumor site correlation. All information was homogenized into a single knowledgebase. Finally, we incorporated the consensus recommendations into a new computational method.

RESULTS

A subset of cancer genetic variants was manually curated to benchmark our method and well-known computational algorithms. We applied the new method on freely available tumor-specific databases to produce a clinically actionable cancer somatic variants (CACSV) dataset in an easy-to-integrate format for most clinical analytical workflows. The research also showed the current challenges and limitations of using different classification systems or computational methods.

CONCLUSION

CACSV is a step toward cell-specific genetic variants standardized interpretation as it is readily adaptable by most clinical laboratory pipelines for somatic variants clinical annotations. CACSV is freely accessible at ( https://github.com/tsobahytm/CACSV/tree/main/dataset ).

Consensus for HER2 alterations testing in non-small-cell lung cancer

Human epidermal growth factor receptor 2 (HER2) is a transmembrane glycoprotein receptor with intracellular tyrosine kinase activity. Its alterations, including mutation, amplification and overexpression, could result in oncogenic potential and have been detected in many cancers such as non-small-cell lung cancer (NSCLC). Such alterations are, in general, considered markers of poor prognosis. Anti-HER2 antibody-drug conjugates, e.g. trastuzumab deruxtecan (T-DXd, DS-8201) and disitamab vedotin (RC48), were recently approved for HER2-positive breast and gastric cancers. Meanwhile, several HER2-targeted drugs, such as T-DXd, neratinib, afatinib, poziotinib and pyrotinib, have been evaluated in patients with advanced NSCLC, with several of them demonstrating clinical benefit. Therefore, identifying HER2 alterations is pivotal for NSCLC patients to benefit from these targeted therapies. Recent guidelines on HER2 testing were developed for breast and gastric cancer, however, and have not been fully established for NSCLC. The expert group here reached a consensus on HER2 alteration testing in NSCLC with the focus on clinicopathologic characteristics, therapies, detection methods and diagnostic criteria for HER2-altered NSCLC patients. We hope this consensus could improve the clinical management of NSCLC patients with HER2 alterations.

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Human epidermal growth factor receptor 2 (HER2) alterations lead to poor prognosis in non-small-cell lung cancer (NSCLC).

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Identifying HER2 alterations is pivotal to guide the anti-HER2-targeted therapies in NSCLC.

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The requirements for HER2 mutation, amplification or expression testing are distinct in NSCLC.

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This consensus fills the gap in the criteria for HER2 alteration testing in NSCLC.

OUP accepted manuscript

Purpose

Lung cancer relapse may be associated with the presence of a small population of cancer stem cells (CSCs) with unlimited proliferative potential. Our study assessed the relationship between CSCs and the relapse rate in patients harboring adenocarcinoma (ADL) and squamous cell carcinoma of the lung (SCCL).

Experimental design

This is an observational prospective cohort study (NCT04634630) assessing the influence of CSC frequency on relapse rate after major lung resection in 35 patients harboring early (I-II) (n = 21) and locally advanced (IIIA) (n = 14) ADL and SCCL. There was a 2-year enrollment period followed by a 1-year follow-up period. Surgical tumor specimens were processed, and CSCs were quantified by cytofluorimetric analysis.

Results

Cancer stem cells were expressed in all patients with a median of 3.1% of the primary cell culture. Primary analysis showed no influence of CSC frequency on the risk of relapse (hazard ratio [HR] = 1.05, 95% confidence interval [CI] = 0.85-1.30). At secondary analysis, patients with locally advanced disease with higher CSC frequency had an increased risk of relapse (HR = 1.26, 95% CI = 1.14-1.39), whereas this was not observed in early-stage patients (HR = 0.90, 95% CI = 0.65-1.25).

Conclusion

No association was found between CSC and relapse rates after major lung resection in patients harboring ACL and SCCL. However, in locally advanced-stage patients, a positive correlation was observed between CSC frequency and risk of relapse. These results indicate a need for further molecular investigations into the prognostic role of CSCs at different lung cancer stages.

Clinical Trial Registration

NCT04634630.

Cell-Free DNA and Clinical Characteristics in Patients with Small Intestinal or Pancreatic Neuroendocrine Tumors

INTRODUCTION

Neuroendocrine tumors (NETs) are rare and characterized by a heterogeneous clinical course and an unmet need for better prognostic markers. Plasma cell-free DNA (cfDNA) has prognostic value in other malignancies but is not previously investigated in NETs. We studied cfDNA levels in patients with mainly low-grade small intestinal NET -(siNET) or pancreatic NET (pNET) and evaluated the prognostic potential of cfDNA.

MATERIALS AND METHODS

We included 70 NET patients, siNET (n = 50) and pNET (n = 20). Plasma cfDNA levels were determined by droplet digital PCR for the beta-2-microglobulin gene every 6 months during a period of 3 years, including in a subgroup of 19 patients during peptide receptor radionuclide therapy (PRRT) therapy.

RESULTS

cfDNA levels were higher in both siNET and pNET compared to a previously established healthy cohort (p < 0.0001). -cfDNA levels did not predict overall survival (crude hazard ratio [HR] 0.95 [0.57-1.58], p = 0.837, adjusted for smoking status HR 0.77 [0.51-1.17], p = 0.22). The impact of cfDNA level on progression-free survival showed different trends in siNET and pNET. There was no effect of PRRT treatment on cfDNA levels and no difference in cfDNA levels between patients with and without progressive disease after PRRT (ANOVA p = 0.66). cfDNA levels were significantly higher in never-smokers and previous smokers than in current smokers (p = 0.029).

DISCUSSION/CONCLUSION

cfDNA levels are higher in NET patients than in healthy controls; however, there was no association with prognosis, and cfDNA levels were unaffected by PRRT. Our observations suggest that cfDNA levels are not associated with the disease course in low-grade NET in contrast to other malignancies.

The value of cell-free circulating tumour DNA profiling in advanced non-small cell lung cancer (NSCLC) management

Liquid biopsy (LB) has boosted a remarkable change in the management of cancer patients by contributing to tumour genomic profiling. Plasma circulating cell-free tumour DNA (ctDNA) is the most widely searched tumour-related element for clinical application. Specifically, for patients with lung cancer, LB has revealed valuable to detect the diversity of targetable genomic alterations and to detect and monitor the emergence of resistance mechanisms. Furthermore, its non-invasive nature helps to overcome the difficulty in obtaining tissue samples, offering a comprehensive view about tumour diversity. However, the use of the LB to support diagnostic and therapeutic decisions still needs further clarification. In this sense, this review aims to provide a critical view of the clinical importance of plasma ctDNA analysis, the most widely applied LB, and its limitations while anticipating concepts that will intersect the present and future of LB in non-small cell lung cancer patients.

Graphical Abstract

Diagnostic and economic value of biomarker testing for targetable mutations in non-small-cell lung cancer: a literature review

We aimed to assess the diagnostic and economic value of next-generation sequencing (NGS) versus single-gene testing, and of liquid biopsy (LBx) versus tissue biopsy (TBx) in non-small-cell lung cancer biomarker testing through literature review. Embase and MEDLINE were searched to identify relevant studies (n = 43) from 2015 to 2020 in adults with advanced non-small-cell lung cancer. For NGS versus single-gene testing, concordance was 70-99% and sensitivity was 86-100%. For LBx versus TBx, specificity was 43-100% and sensitivity was ≥60%. Turnaround times were longer for NGS versus single-gene testing (but not vs sequential testing) and faster for LBx versus TBx. NGS was cost-effective, and LBx reduced US per-patient costs. NGS versus single-gene testing and LBx versus TBx were concordant. NGS and LBx may be cost-effective for initial screening.

How clinically useful is comprehensive genomic profiling for patients with non-small cell lung cancer? A systematic review

Given the lack of a gold standard, the clinical usefulness of Comprehensive Genomic Profiling (CGP) has not been established. This systematic review aimed to evaluate evidence about the clinical benefit of CGP for patients with Non-small cell lung carcinoma (NSCLC). All controlled studies that evaluated the ability of CGP to detect actionable targets (ATs) reported increases in the number of samples with ATs. The frequency of ATs detected in uncontrolled case series ranged from 0.7 % for RET mutations to 45 % for EGFR mutations. The studies that evaluated therapies targeted to EGFR, ALK, ROS-1, MET, and RET mutations documented significant improvement in clinical outcomes. This review suggests that CGP tests may be clinically helpful for treating patients with NSCLC. Although current evidence is associated with a high risk of bias, the significant impact of NSCLC on individuals and society may justify the routine use of CGP testing for this disease.

Multi-Gene Testing Overview with a Clinical Perspective in Metastatic Triple-Negative Breast Cancer

Next-generation sequencing (NGS) is the technology of choice for the routine screening of tumor samples in clinical practice. In this setting, the targeted sequencing of a restricted number of clinically relevant genes represents the most practical option when looking for genetic variants associated with cancer, as well as for the choice of targeted treatments. In this review, we analyze available NGS platforms and clinical applications of multi-gene testing in breast cancer, with a focus on metastatic triple-negative breast cancer (mTNBC). We make an overview of the clinical utility of multi-gene testing in mTNBC, and then, as immunotherapy is emerging as a possible targeted therapy for mTNBC, we also briefly report on the results of the latest clinical trials involving immune checkpoint inhibitors (ICIs) and TNBC, where NGS could play a role for the potential predictive utility of homologous recombination repair deficiency (HRD) and tumor mutational burden (TMB).

Clinical Application of Next-Generation Sequencing of Plasma Cell-Free DNA for Genotyping Untreated Advanced Non-Small Cell Lung Cancer

Simple Summary

Plasma ctDNA is a material source for molecular analysis particularly useful when tissue is not available or sufficient. NGS-based plasma genotyping should be integrated into the clinical workup of newly diagnosed advanced NSCLC.

Abstract

Background: Analysis of circulating tumor DNA (ctDNA) has remarkable potential as a non-invasive lung cancer molecular diagnostic method. This prospective study addressed the clinical value of a targeted-gene amplicon-based plasma next-generation sequencing (NGS) assay to detect actionable mutations in ctDNA in patients with newly diagnosed advanced lung adenocarcinoma. Methods: ctDNA test performance and concordance with tissue NGS were determined, and the correlation between ctDNA findings, clinical features, and clinical outcomes was evaluated in 115 patients with paired plasma and tissue samples. Results: Targeted-gene NGS-based ctDNA and NGS-based tissue analysis detected 54 and 63 genomic alterations, respectively; 11 patients presented co-mutations, totalizing 66 hotspot mutations detected, 51 on both tissue and plasma, 12 exclusively on tissue, and 3 exclusively on plasma. NGS-based ctDNA revealed a diagnostic performance with 81.0% sensitivity, 95.3% specificity, 94.4% PPV, 83.6% NPV, test accuracy of 88.2%, and Cohen’s Kappa 0.764. PFS and OS assessed by both assays did not significantly differ. Detection of ctDNA alterations was statistically associated with metastatic disease (p = 0.013), extra-thoracic metastasis (p = 0.004) and the number of organs involved (p = 0.010). Conclusions: This study highlights the potential use of ctDNA for mutation detection in newly diagnosed NSCLC patients due to its high accuracy and correlation with clinical outcomes.

Integrated Analysis of Whole Genome and Epigenome Data Using Machine Learning Technology: Toward the Establishment of Precision Oncology

With the completion of the International Human Genome Project, we have entered what is known as the post-genome era, and efforts to apply genomic information to medicine have become more active. In particular, with the announcement of the Precision Medicine Initiative by U.S. President Barack Obama in his State of the Union address at the beginning of 2015, "precision medicine," which aims to divide patients and potential patients into subgroups with respect to disease susceptibility, has become the focus of worldwide attention. The field of oncology is also actively adopting the precision oncology approach, which is based on molecular profiling, such as genomic information, to select the appropriate treatment. However, the current precision oncology is dominated by a method called targeted-gene panel (TGP), which uses next-generation sequencing (NGS) to analyze a limited number of specific cancer-related genes and suggest optimal treatments, but this method causes the problem that the number of patients who benefit from it is limited. In order to steadily develop precision oncology, it is necessary to integrate and analyze more detailed omics data, such as whole genome data and epigenome data. On the other hand, with the advancement of analysis technologies such as NGS, the amount of data obtained by omics analysis has become enormous, and artificial intelligence (AI) technologies, mainly machine learning (ML) technologies, are being actively used to make more efficient and accurate predictions. In this review, we will focus on whole genome sequencing (WGS) analysis and epigenome analysis, introduce the latest results of omics analysis using ML technologies for the development of precision oncology, and discuss the future prospects.

Simultaneous Identification of EGFR,KRAS,ERBB2, and TP53 Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics

Simple Summary

Multiple genetic mutations are associated with the outcomes of patients with non-small cell lung cancer (NSCLC) after using tyrosine kinase inhibitor, but the cost for detecting multiple genetic mutations is high. Few studies have investigated whether multiple genetic mutations can be simultaneously detected based on image features in patients with NSCLC. We developed a machine learning-derived radiomics approach that can simultaneously discriminate the presence of EGFR, KRAS, ERBB2, and TP53 mutations on CT images in patients with NSCLC. These findings suggest that machine learning-derived radiomics may become a noninvasive and low-cost method to screen for multiple genetic mutations in patients with NSCLC before using next-generation sequencing tests, which can help to improve individualized targeted therapies.

Abstract

Purpose: To develop a machine learning-derived radiomics approach to simultaneously discriminate epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene (KRAS), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and tumor protein 53 (TP53) genetic mutations in patients with non-small cell lung cancer (NSCLC). Methods: This study included consecutive patients from April 2018 to June 2020 who had histologically confirmed NSCLC, and underwent pre-surgical contrast-enhanced CT and post-surgical next-generation sequencing (NGS) tests to determine the presence of EGFR, KRAS, ERBB2, and TP53 mutations. A dedicated radiomics analysis package extracted 1672 radiomic features in three dimensions. Discriminative models were established using the least absolute shrinkage and selection operator to determine the presence of EGFR, KRAS, ERBB2, and TP53 mutations, based on radiomic features and relevant clinical factors. Results: In 134 patients (63.6 ± 8.9 years), the 20 most relevant radiomic features (13 for KRAS) to mutations were selected to construct models. The areas under the curve (AUCs) of the combined model (radiomic features and relevant clinical factors) for discriminating EGFR, KRAS, ERBB2, and TP53 mutations were 0.78 (95% CI: 0.70–0.86), 0.81 (0.69–0.93), 0.87 (0.78–0.95), and 0.84 (0.78–0.91), respectively. In particular, the specificity to exclude EGFR mutations was 0.96 (0.87–0.99). The sensitivity to determine KRAS, ERBB2, and TP53 mutations ranged from 0.82 (0.69–90) to 0.92 (0.62–0.99). Conclusions: Machine learning-derived 3D radiomics can simultaneously discriminate the presence of EGFR, KRAS, ERBB2, and TP53 mutations in patients with NSCLC. This noninvasive and low-cost approach may be helpful in screening patients before invasive sampling and NGS testing.

Dealing with NSCLC EGFR mutation testing and treatment: A comprehensive review with an Italian real-world perspective

Since their discovery, relevant efforts have been made to optimize the detection approaches to EGFR mutations as well as the clinical management of EGFR-mutated NSCLC. The recent shift from single gene testing to novel comprehensive detection platforms along with the development of new generation tyrosine kinase inhibitors, targeting both common and uncommon EGFR-mutations, is leading to a progressive increase in the number of patients who may benefit from targeted approaches, with subsequent impact on their long-term survival and quality of life. However, a prompt and adequate implementation of the most recent diagnostic and treatment advances in the routine practice often remains critical to be specifically addressed. In this review we provide a complete and updated overview of the different detection platforms and therapeutic options currently available for the clinical management of advanced EGFR-positive NSCLC, summarizing scientific evidence and describing molecular testing as well as treatment practice in the real-word scenario.

A multidisciplinary approach for the differential diagnosis between multiple primary lung adenocarcinomas and intrapulmonary metastases

PURPOSE

The distinction between multiple primary lung cancers (MPLCs) and intrapulmonary metastases has a significant impact on tumor staging and therapeutic choices. Several criteria have been proposed to solve this diagnostic issue, but a definitive consensus is still missing. We tested the efficacy of a combined clinical, histopathological and molecular ("real world") approach for the correct classification of multiple lung tumors in a selected cohort of patients.

METHODS

24 multiple lung tumors with a diagnosis of adenocarcinoma from 10 patients were retrospectively reviewed. Radiological, pathological and clinical information, including follow-up, were integrated with molecular profiling via a routine multigene panel sequencing.

RESULTS

Comprehensive histologic assessment revealed readily distinguishable histologic patterns between multiple tumors suggesting unrelated lesions in 7 cases, in agreement with clinical, radiological and molecular data, thus leading to final diagnosis of MPLCs. In the remaining 3 cases, the differential diagnosis between MPLCs and intrapulmonary metastases was challenging, since the histologic features of the lesions were similar or identical. The final interpretation (2 MPLCs and 1 most likely intrapulmonary metastases) was reached thanks to the integration of all available data, and was confirmed by follow-up.

CONCLUSIONS

A multidisciplinary approach including a routinely affordable multigene panel sequencing is a useful tool to discriminate MPLCs from intrapulmonary metastases in multiple lung nodules sharing the adenocarcinoma histotype.

How the COVID-19 Pandemic Impacted Oncological Molecular Diagnosis: A Picture from a National Reference Center for Molecular Pathology

Introduction

The Portuguese healthcare system had to adapt at short notice to the COVID-19 pandemic. We implemented workflow changes to our molecular pathology laboratory, a national reference center, to maximize safety and productivity. We assess the impact this situation had on our caseload and what conclusions can be drawn about the wider impact of the pandemic in oncological therapy in Portugal. Material and Methods. We reviewed our database for all oncological molecular tests requested between March and April of 2019 and 2020. For each case, we recorded age, sex, region of the country, requesting institution, sample type, testing method, and turnaround time (TAT). A comparison between years was made.

Results

The total number of tests decreased from 421 in 2019 to 319 in 2020 (p = 0.0027). The greatest reduction was in clinical trial-related cases. Routine cases were similar between years (267 vs. 256). TAT was higher in 2019 (mean 15 days vs. 12.3 days; p = 0.0003). Medium- to large-sized public hospitals in the north of the country were mostly responsible for the reduction in cases (p = 0.0153).

Conclusions

Case reduction was observed at hospitals that have mostly been involved in the treatment of COVID-19 and in the north of the country, the region worst-hit by the pandemic. Similar to other studies, our TAT decreased, even with a similar number of routine cases. Thus, we conclude that it is possible to successfully adapt the workflow of a molecular pathology laboratory to new safety standards without losing efficiency.

Artificial intelligence (AI) and big data in cancer and precision oncology

Artificial intelligence (AI) and machine learning have significantly influenced many facets of the healthcare sector. Advancement in technology has paved the way for analysis of big datasets in a cost- and time-effective manner. Clinical oncology and research are reaping the benefits of AI. The burden of cancer is a global phenomenon. Efforts to reduce mortality rates requires early diagnosis for effective therapeutic interventions. However, metastatic and recurrent cancers evolve and acquire drug resistance. It is imperative to detect novel biomarkers that induce drug resistance and identify therapeutic targets to enhance treatment regimes. The introduction of the next generation sequencing (NGS) platforms address these demands, has revolutionised the future of precision oncology. NGS offers several clinical applications that are important for risk predictor, early detection of disease, diagnosis by sequencing and medical imaging, accurate prognosis, biomarker identification and identification of therapeutic targets for novel drug discovery. NGS generates large datasets that demand specialised bioinformatics resources to analyse the data that is relevant and clinically significant. Through these applications of AI, cancer diagnostics and prognostic prediction are enhanced with NGS and medical imaging that delivers high resolution images. Regardless of the improvements in technology, AI has some challenges and limitations, and the clinical application of NGS remains to be validated. By continuing to enhance the progression of innovation and technology, the future of AI and precision oncology show great promise.

Identifying CpG methylation signature as a promising biomarker for recurrence and immunotherapy in non-small-cell lung carcinoma

Epigenetic alterations are crucial to oncogenesis and regulation of gene expression in non-small-cell lung carcinoma (NSCLC). DNA methylation (DNAm) biomarkers may provide molecular-level prediction of relapse risk in cancer. Identification of optimal treatment is warranted for improving clinical management of NSCLC patients. Using machine learning algorithm we identified 4 recurrence predictive CpG methylation markers (cg00253681/ART4, cg00111503/KCNK9, cg02715629/FAM83A, cg03282991/C6orf10) and constructed a risk score model that potently predicted recurrence-free survival and prognosis for patients with NSCLC (P = 0.0002). Integrating genomic, transcriptomic, proteomic and clinical data, the DNAm-based risk score was observed to significantly associate with clinical stage, cell proliferation markers, somatic alterations, tumor mutation burden (TMB) as well as DNA damage response (DDR) genes, and potentially predict the efficacy of immunotherapy. In general, our identified DNAm signature shows a significant correlation to TMB and DDR pathways, and serves as an effective biomarker for predicting NSCLC recurrence and response to immunotherapy. These findings demonstrate the utility of 4-DNAm-marker panel in the prognosis, treatment decision-making and evaluation of therapeutic responses for NSCLC.

Genetic Markers in Lung Cancer Diagnosis: A Review

Lung cancer is the most often diagnosed cancer in the world and the most frequent cause of cancer death. The prognosis for lung cancer is relatively poor and 75% of patients are diagnosed at its advanced stage. The currently used diagnostic tools are not sensitive enough and do not enable diagnosis at the early stage of the disease. Therefore, searching for new methods of early and accurate diagnosis of lung cancer is crucial for its effective treatment. Lung cancer is the result of multistage carcinogenesis with gradually increasing genetic and epigenetic changes. Screening for the characteristic genetic markers could enable the diagnosis of lung cancer at its early stage. The aim of this review was the summarization of both the preclinical and clinical approaches in the genetic diagnostics of lung cancer. The advancement of molecular strategies and analytic platforms makes it possible to analyze the genome changes leading to cancer development-i.e., the potential biomarkers of lung cancer. In the reviewed studies, the diagnostic values of microsatellite changes, DNA hypermethylation, and p53 and KRAS gene mutations, as well as microRNAs expression, have been analyzed as potential genetic markers. It seems that microRNAs and their expression profiles have the greatest diagnostic potential value in lung cancer diagnosis, but their quantification requires standardization.