Diagnosis and treatment of lung cancer: A molecular perspective

Abstract

This editorial comments on the review by Da Silva et al, published in the World Journal of Clinical Oncology which focuses on the molecular perspectives of lung cancer. With the rapid development of molecular technology, new diagnostic methods are constantly emerging, including liquid biopsy, the identification of gene mutations, and the monitoring biomarkers, thus providing precise information with which to identify the occurrence and development of lung cancer. Biomarkers, such as circulating tumor cells, circulating tumor DNA, and circulating RNA can provide helpful information for clinical application. Common types of genetic mutations and immune checkpoints include epidermal growth factor receptor, anaplastic lymphoma kinase, c-ROS proto-oncogene 1, programmed death-1 and cytotoxic T-lymphocyte-associated protein. According to specific biomarkers, targeted therapy and immunotherapy can improve survival outcomes based on the types of gene mutation and immune checkpoints. The application of molecular approaches can facilitate our ability to control the progression of disease and select appropriate therapeutic strategies for patients with lung cancer.

Key Words: Lung cancer; Molecular; Oncogenic mutations; Biomarkers; Liquid biopsy; Targeted therapy; Immunotherapy

Core Tip: The development of molecular biology techniques, including liquid biopsy techniques, the identification of gene mutations, and the application of immune checkpoint inhibitors can contribute to early and accurate diagnosis and personalized treatment strategies for lung cancer.

INTRODUCTION

Lung cancer remains the leading global cause of death by cancer[1] and contributes significantly to the global disease burden[2], accounting for 1 in 8 cancer diagnoses and 1 in 5 deaths worldwide. Lung cancer can be categorized into non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLC accounts for 80%–85% of all lung cancers, including adenocarcinoma, squamous lung cancer, large cell carcinoma, and adenosquamous carcinoma[3]. Traditional diagnostic methodology includes radiographic screening, sputum examination, bronchoscopy and lung tissue biopsy. Although radiographic screening is non-invasive, this screening method is associated with low levels of accuracy and sensitivity[4]. The examination of sputum is also associated with low sensitivity and is generally used only as an auxiliary form of diagnosis[5]. Bronchoscopy exhibits only limited specificity for distinguishing adenocarcinoma[6]. Furthermore, bronchoscopy and lung tissue biopsy are both invasive diagnostic tools. Surgical intervention, chemotherapy, and radiotherapy constitute the cornerstone of conventional therapeutics. However, radiotherapy and chemotherapy, as primary interventions for inoperable cancer, are associated with significant adverse effects, including bone marrow suppression and drug resistance, thus resulting in a low survival rate[7].

Consequently, improving the diagnostic efficacy and developing precision therapy for lung cancer remains a major challenge. With the ongoing development of sequencing and multi-omics analysis technologies, molecular biomarkers are frequently being identified and utilized in oncology[8,9]. Da Silva et al[10] reviewed the molecular perspectives of clinical oncology treatment and highlighted the importance of precision medicine by compiling data relating to molecular biomarkers and approaches. NSCLC has successfully adopted and utilized the concept of precision medicine by using molecular biomarkers to reflect tumor status and establish individualized therapy[9]. The editorial focuses on the current applications of emerging molecular technologies, as well as limitations and future prospects.

APPLICATIONS OF MOLECULAR TECHNIQUES

Accurate diagnosis is crucial if we are to delay the progression of disease and provide appropriate treatments for lung cancer during the initial stage. Histopathological biopsy is the definitive standard for diagnosing lung cancer. However, the invasive manner of this technique and associated constraints in facilitating early detection necessitate the identification and exploration of novel diagnostic modalities thereby enabling prompt therapeutic intervention[3]. Biomarkers occupy a critical position in identifying indeterminate pulmonary nodules found during traditional diagnosis and refining the clinical risk of lung cancer[11,12]. Detecting specific molecular biomarkers can minimize harm and cost without increasing the number of cancer deaths, such as carcinoembryonic antigen (CEA), complement fragments, circulating tumor DNA (ctDNA), circulating cell-free DNA (cfDNA) and blood protein profiling[11] (Figure 1).

Figure 1 The application of molecular methodologies in lung cancer. CTCs: Circulating tumor cells; CEA: Carcinoembryonic antigen; ctDNA: Circulating tumor DNA; cRNA: Circulating RNA; PD-1/PD-L1: Programmed death-1 and its ligand; EGFR: Epidermal growth factor receptor; ALK: Anaplastic lymphoma kinase; ROS1: C-ROS proto-oncogene 1; CTLA-4: Cytotoxic T-lymphocyte-associated protein.

CEA is one of the genetic cancer antigens found in the serum that is strongly associated with the progression of lung cancer[13]. The detection of CEA allows us to monitor the incidence of lung cancer and assess therapy efficacy[14]. The expression of CEA, cytokeratin19 fragment (CYFRA21-1) and neuron-specific enolase can provide useful information and facilitate treatment options. A previous meta-analysis reported that CEA levels could predict EGFR mutations in patients with NSCLC[15]. Furthermore, CEA is known to contribute to the regulation of fatty acid metabolism in NSCLC, along with induced tumor cell proliferation and migration[16]. Although CEA serves as a biomarker for various malignancies, its specificity for lung cancer is unsatisfactory, thus limiting its clinical utility[17]. Furthermore, the levels of CEA are low in vivo and susceptible to other biomarkers like cfDNA[17]. Thus, it is essential to enhance the detection limit and sensitivity of the equipment used to detect biomarkers.

Liquid biopsy, a non-traumatic diagnostic tool, is easier to acquire from a patient than a biopsy of lung tissue and can reflect the state of the tumor microenvironment in real-time. In addition, liquid biopsy allows for the dynamic monitoring of the response to treatment in patients with NSCLC. Liquid biopsy is predominantly used to analyze circulating tumor cells (CTCs), ctDNA, exosomes, and circulating RNA (cRNA)[18]. In addition, new technologies, such as next-generation sequencing (NGS) can enable the identification of diverse predictive biomarkers and the detection of oncogenic molecular targets with elevated levels of sensitivity and specificity[19]. NGS is more sensitive and specific than immunohistochemistry for the analysis of gene fusion mutations, which was particularly accurate for predicting the clinical benefit of crizotinib[20]. The testing of CTCs plays a pivotal role in the early recognition of lung cancer and can reflect tumor heterogeneity, a significant detail that are often overlooked by traditional biopsy methods[21,22]. The gene expression and mutation profile of CTCs can reflect the composition of primary and metastatic tumors, which can effectively distinguish between benign and malignant nodules[23]. The continuous monitoring of CTC concentrations and gene mutations can help us to assess the efficacy of treatment. ctDNA obtained from liquid biopsy can reflect the genomic profile and identify patients who might benefit from a particular form of targeted therapy[24,25]. Furthermore, the levels of ctDNA are known to be strongly correlated with tumor burden in patients and indicate a response to treatment earlier than conventional imaging modalities[23]. The sensitivity of ctDNA testing was found to be 82% for the detection of stage IV NSCLC while the specificity of ctDNA was 99.8% for the detection of gene mutations, thus highlighting the significant potential of ctDNA as a non-invasive diagnostic tool, although the screening of healthy individuals may result in false positives[26]. The specificities of CTCs, ctDNA and cRNA are notably higher than that of CEA (Table 1)[27-33]. Due to the heterogeneity of tumors, a single liquid biopsy may not fully reflect the genetic status, location and complexity of a given tumor.

Table 1 Comparison of diagnostic biomarkers.

Types	Function	Specificity	Efficacy assessment
CTCs[27-29]	CTCs can identify all types of tumor cells and can be detected at early stages of lung cancer	High specificity	The number of CTCs is highly consistent with the therapy efficacy
ctDNA[26,30]	ctDNA serves as an independent molecular marker for NSCLC and allows for the optimization of clinical staging in the early to middle stages and monitor early metastasis	High specificity	ctDNA indicates the patient's response to treatment earlier than imaging examinations
CEA[15,16,31]	CEA is expressed at high levels in NSCLC and increases with the progression of clinical staging	Broad-spectrum but low specificity	Effective treatment can restore serum CEA concentration to baseline levels
cRNA[32,33]	An indicator of tumor proliferation and migration	High specificity	Up-regulation of cRNA is related to poor prognosis

CTCs: Circulating tumor cells; ctDNA: circulating tumor DNA; CEA: Carcinoembryonic antigen; cRNA: circulating RNA.

Simultaneously, molecular biology techniques have advanced our ability to treat cancer. Currently, the different subtypes of NSCLC can be identified by specific molecular characteristics based on a series of oncogenic mutations, which can also contribute to the development of targeted therapy[34]. Epidermal growth factor receptor (EGFR) mutations, including point mutations, deletions and insertions, is a common oncogenic driver event in patients with NSCLC[35]. The detection of EGFR alterations has been generally recommended for NSCLC patients in order to increase our understanding of the specific pathological features[3,36]. Tyrosine kinase inhibitors (TKIs) have been long regarded as the primary treatment for NSCLC patients with EGFR mutations[34]. These targeted therapies have been successfully used for the treatment of lung cancer by improving survival outcomes and reducing mortality[37]. Gefitinib is a first generation of EGFR-TKIs that can prolong survival when combined with chemotherapy[38]. For EGFR T790M-resistant mutations, third-generation TKIs, such as Osimertinib, can further improve progression-free survival (PFS) and intracerebral remission rate in patients with intracerebral metastasis[38,39]. In addition, anaplastic lymphoma kinase (ALK) and c-ROS proto-oncogene 1 (ROS1) had emerged as novel driver genes and are receiving significant attention with regards to the treatment of NSCLC. ALK and ROS1 proteins are known to be involved in the activation of cell proliferation signaling pathways; mutations of the genes encoding these proteins can potentially culminate in oncogenic transformation[40,41]. Targeted therapies for ALK and ROS1 rearrangements can improve PFS. Crizotinib is a TKI that targets ALK and ROS1 rearrangements and has been approved as a first-line treatment to improve the overall survival (OS) of patients with NSCLC and positivity for both ALK and ROS1[19]. Based on these multiple molecules, oncogene-centric paradigms have been established for the genesis and development of NSCLC[42], as evidenced by the extensive application and robust activity of corresponding targeted therapy in the clinic (Table 2).

Table 2 Comparison of therapeutic biomarkers.

Types	Clinical relevance	Associated therapeutic strategies	Drugs
EGFR[43]	Lung adenocarcinoma has a substantially greater rate of EGFR mutation than lung squamous cell carcinoma	First-line treatment drugs for NSCLC patients with EGFR sensitive gene mutations	Osimertinib, Almonertinib, Furmonertinib, Befotertinib, Gefitinib
ALK[44]	ALK positive NSCLC patients are usually young, non-smoking, and EGFR non mutated lung adenocarcinoma populations	For advanced NSCLC patients accompanied by ALK gene fusion	Crizotinib, Alectinib, Ensartinib
ROS1[45]	ROS1-positive lung cancer is commonly found in young, non-smoking, or lightly smoking lung adenocarcinoma patients	For ROS1 positive NSCLC patients	Crizotinib, Entrectinib, Lorlatinib, Cabozantinib
PD-1/ PD-L1[46]	PD-1/PD-L1 inhibits T cell function via the TCR receptor signaling pathway, leading to immune escape in tumors	For driver gene negative advanced NSCLC patients	Nivolumab, Pembrolizumab, Camrelizumab, Tislelizumab, Sintilimab, Durvalumab, Atezolizumab
CLTA-4[47,48]	CLTA-4 facilitates tumor immune evasion	For advanced and metastatic NSCLC patients	Ipilimumab, Tremelimumab, Cadornilimab

EGFR: Epidermal growth factor receptor; ALK: Anaplastic lymphoma kinase; ROS1: C-ROS proto-oncogene 1; PD-1/PD-L1: Programmed death-1 and its ligand; TCR: T cell receptor; CTLA-4: Cytotoxic T-lymphocyte-associated protein.

Immune checkpoint inhibitors have proven to be more effective than conventional chemotherapy[49], including programmed death-1 (PD-1), programmed death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated protein (CTLA-4). Both PD-1 and PD-L1 are known to be expressed at high levels in tumor cells and can exert negative effects on the immune system, particularly in terms of T cells[50,51]. The activation of PD-1 and PD-L1 can reduce the immune response of T cells and mediate the immune escape of tumor cells. Furthermore, the blockade of PD-1 and PD-L1 represents the most effective immunotherapeutic approach for NSCLC[52] and works by reversing the immunosuppressive status of the tumor microenvironment, thereby inhibiting tumor growth and eliminating tumor cells[49,51]. Pembrolizumab, a humanized antibody against PD-1, has been shown to exert significant anti-tumor activity in patients with advanced NSCLC, especially for tumor cells with high expression levels of PD-1[52,53]. The combination of pembrolizumab and chemotherapy as a first-line treatment significantly improved PFS and OS in NSCLC patients when compared to chemotherapy alone[54,55]. Despite the significant potential of PD-1 and PD-L1 inhibitors, their efficacy is constrained in tumor cells lacking inflammation, thus leading to a diminished response[56]. Furthermore, due to drug resistance, efficacy can be reduced even further. Appropriate combination therapy can enhance the antigen presenting functionality of T cells and reduce immunosuppressive resistance[57]. CTLA-4, an immunosuppressive molecule that is predominantly expressed in T cells, is a significant ‘hot-target’ for tumor-targeted immunotherapy and can facilitate tumor immune evasion by inhibiting the activation and proliferation of T cells[58]. Notably, the blockade of CTLA-4 remains controversial due to limited efficacy and high toxicity, although a corresponding CTLA-4 antibody (ipilimumab) has been used in the clinic[59].

FUTURE AND CHALLENGES

The crux of precision medicine in lung cancer lies in the effective amalgamation of multi-omics data with artificial intelligence (AI) to identify specific molecular characteristics of tumors, thereby enhancing diagnostic precision and tailoring therapeutic strategies. Future studies should concentrate on harnessing and dissecting a multi-omics dataset, which will encompass a spectrum of biological insights, ranging from genomics to proteomics and metabolomics[60]. The incorporation of AI technology could significantly enhance early detection, pathological diagnosis, and classification, as well as facilitate prognostic evaluation and a more profound comprehension of the underlying molecular mechanisms[61]. However, multi-source, complex, and unstandardized datasets pose significant challenges to the establishment and application of AI models[61]. Therefore, a critical area for future investigation involves the effective integration of multi-omics approaches with AI technologies to enhance diagnostic accuracy and precision medicine.

CONCLUSION

Owing to our increasing comprehension of the molecular features of lung cancer, we are making significant progress regards to the diagnosis, molecular targeted therapy, and immunotherapy of this disease. The detection of biomarkers has become vital for the diagnosis of lung cancer and the development of personalized clinical management strategies. Furthermore, liquid biopsy will gradually be integrated with multi-omics information, AI and machine learning algorithms to facilitate the selection of targeted therapies for patients and allow for the dynamic surveillance of tumor progression. Concurrently, the establishment of standardized operating protocols are paramount if we are to enhance the precision and reliability of outcomes arising from liquid biopsy. Based on the complexity of medical conditions, further investigation is required for the development of precision oncology.