Precise diagnosis and prognosis assessment of malignant lung nodules: a narrative review

Introduction

Pulmonary nodules (PNs) are mainly peripheral solitary or multiple small (≤3 cm in diameter) focal radiographic opacities, which are surrounded by lung parenchyma (1). With the widespread application of low-dose computed tomography (LDCT) in daily clinical practice, the number of solitary nodules detected has significantly increased (2-4).

Malignant lung nodules account for only 5% of all lung nodules, and their management differs significantly from that of benign lung nodules (5-7). Beyond the diagnosis of malignant PNs, there is heterogeneity in prognosis, and standard care may lead to undertreatment in high-risk patients and transitional treatment in low-risk patients with malignant lung nodules. Therefore, accurately distinguishing between benign and malignant PNs, as well as precise risk stratification of malignant PNs, is a critical clinical problem that must be solved urgently.

This review focused on the current progress in the precise diagnosis of malignant PNs in primary lung cancer, to improve clinical decision-making, especially regarding early diagnostics. We also estimated the potential prognosis for patients with malignant diagnoses (Figure 1). This strategy will assist with identification of individuals who might benefit from postoperative multimodal therapy. We present this article in accordance with the Narrative Review reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1058/rc).

Figure 1 Central image. The figure on the left illustrates the diagnostic approaches for malignant lung nodules; the figure on the right depicts the methods employed for prognosis assessment of malignant lung nodules. CT, computed tomography; PET, positron emission tomography; CTC, circulating tumor cell; ctDNA, circulating tumor DNA; PD-1, programmed cell death 1; PD-L1, programmed death ligand 1; TIL, tumor infiltrating lymphocyte.

Methods

Primarily, a literature search was conducted in the databases of PubMed and Web of Science for research related to the diagnosis and prognosis of PNs, without setting any restrictions on publication year or study design; the search strategy is shown in Table 1.

Identification of benign and malignant lung nodules

Classical clinicopathological factors

Classical clinicopathological factors play an important role in distinguishing between benign and malignant nodules. Older adults with PNs have a higher probability of being diagnosed with malignancy, whereas lung cancer is still relatively rare in individuals younger than 35 years and is unusual before the age of 40 years. For each additional decade of life, lung cancer incidence increases steadily (4). Smoking is the main risk factor for lung cancer, with smokers being 10–35 times more likely to have lung cancer than non-smokers, and secondhand smoke is also considered a risk factor (8). Quitting smoking after diagnosis can improve the overall survival (OS) rate and progression-free survival (PFS) time of smokers with early-stage lung cancer (9). The proportion of nonmalignant and malignant causes of death has been shown to be significantly higher in patients with primary resection of stage I non-small cell lung cancer (NSCLC) who smoked for more than 30 years. In addition, the progression of malignant tumors in patients with a smoking history of ≥30 pack-years is higher than that in patients with a history of less than 30 pack-years (10). Therefore, the biological malignancy of the primary lesions and the decrease of airway immune function may be the reasons for the high recurrence rate and poor prognosis of heavy smokers. A study showed that emphysema was an independent risk factor for lung cancer (11). Analysis of the prevalence of lung cancer and emphysema in the National Lung Screening Trial (NLST) showed that the incidence of cancer in patients with emphysema was higher than that in patients without emphysema (25 cancer patients per 1,000 screened emphysema patients vs. 7.5 cancer patients per 1,000 non-emphysema patients screened) (12). The risk of a malignant tumor in patients with pulmonary fibrosis is 4.2 times higher than that in those with emphysema alone, especially idiopathic pulmonary fibrosis, which is also an independent risk factor (13). In addition, chronic obstructive pulmonary disease, exposure to occupational carcinogens (asbestos, cadmium, arsenic, chromium, radon, silica, and kerosene fumes), previous cancer history, and family history of lung cancer also increase the probability of a PN being malignant (14-18).

Radiomics

Radiographic features based on computed tomography (CT) images make a significant contribution to differentiating benign and malignant PNs. The general radiological characteristics in CT imaging of malignant nodules include solid component, margin (clear, blurred), lobulation, speculation, bubble lucency, honeycomb sign, changes in the vessels and pleural indentation signs, and bronchial aeration signs (19,20). The solid component of ground-glass nodules (GGNs) is a critical determinant in predicting their malignancy (21-23). A single-institution study with a follow-up period of 15 years revealed that pure GGNs without solid components are predominantly histologically classified as preinvasive subtypes. In contrast, nodules with a consolidation-to-tumor ratio exceeding 25% are primarily characterized histologically as invasive adenocarcinomas (24). In a prospective multi-institutional cohort study, solid components greater than 2 mm on mediastinal windows were found to be highly indicative of invasive adenocarcinoma (25).

Nodule size is correlated with the risk of malignancy (26). Gierada et al. reported that 598 PNs were diagnosed as lung cancer in the 3-year NLST screening program, of which 70.5% of nodules were larger than 2 cm in diameter and only 15% were less than 1 cm in diameter (27). Recent studies have reported that the malignant tumor probability is 1% for nodules with a diameter less than 6 mm, 1–2% for nodules 6–8 mm in diameter, and over 3% for nodules larger than 8 mm in diameter (26). Part-solid lung nodules are managed according to the size of the solid components. The larger the solid components, the higher the risk of malignancy. When the ground-glass PNs persist for more than 3 months and the diameter is more than 10 mm, the probability of malignancy is 10–50% (28).

Positron emission tomography-computed tomography (PET-CT) imaging is widely used as a noninvasive test to evaluate lung nodules suspicious for cancer. The level of fluorodeoxyglucose (FDG) uptake could also be used to predict patient survival, and FDG uptake is mainly measured according to the maximum standardized uptake value (SUV). A higher maximum SUV (SUVmax) is associated with a higher metabolic rate and a higher degree of malignancy (29). A pooled analysis of 1,330 patients demonstrated that integrated PET/CT imaging provided a sensitivity of 98.7% and a specificity of 58.2% (30). Kim et al. reported that PET-CT performed well in distinguishing benign from malignant for solitary PNs, with a sensitivity of 97% and specificity of 85% (31). Lung magnetic resonance imaging (MRI) is an emerging modality in the early detection of lung cancer, but the major setback of lung MRI in comparison with CT is the detection of subcentimeter nodules (32).

Diagnostic models combined with multiple imaging features can significantly improve accuracy and sensitivity. The Mayo Clinic Model is a well-recognized predictive model that comprises clinicodemographic data of age, cigarette smoking status, and history of extra-thoracic malignant neoplasm and chest radiological data of diameter, location, and edge characteristics (e.g., lobulation, speculation, and shagginess). The model has strong distinguishing ability [area under the curve (AUC) was 0.833 in the developmental data set and 0.801 in the validation data set]. The VA, Brock, and Herder models have been established based on the Mayo Clinic Model (33-36). Al-Ameri et al. verified four such models in a population of patients with lung nodules in the UK, and the Mayo and Brock models had good accuracy in finding the possibility of malignancy nodules on CT scans (37). Among patients who received FDG PET-CT for nodule evaluation, the model that incorporated FDG avidity described by Herder et al. had the highest accuracy (36,37). Risk models use the growing amount of diagnostic information to create more accurate risk assessment of malignancy tumors (38-40). Soardi et al. developed the Bayesian Inference Malignancy Calculator (BIMC) model, including age, smoking, personal history of cancer, nodule diameter, edges and location, volume doubling time, minimum lesion density, contraction-enhanced CT enhancement and FDG uptake; the AUC of the BIMC model was 0.893 in an internal validation (41).

Deep learning (DL) has been proposed as a promising tool for the classification of malignant nodules (42-44). Ardila et al. used a DL algorithm to predict the malignant probability of lung nodules using current and previous CT volumes, and the result showed excellent performance (AUC of 94.4%) in 6,716 NLST cases (45). DL was shown to be useful in CT scans from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), with an accuracy of 97.6% (46). Heuvelmans et al. retrospectively validated the Lung Cancer Prediction Conditional Neural Network, which showed excellent performance in the identification of benign lung nodules; the overall AUC was 94.5% (47).

Solid biopsy

The relationship between imaging characteristics and the nature of PNs is not always straightforward; the same type of PNs may present with varying imaging features, whereas different nodules can exhibit similar imaging appearances. Consequently, a broader range of methods is employed to assess the nature of PNs. In recent years, the integration of advanced imaging techniques with biopsy methods has significantly enhanced the role of lung biopsy in the qualitative diagnosis of PNs.

Percutaneous lung biopsy involves the precise localization of nodules using CT or ultrasound imaging, measuring the size of the lesion, the distance from the skin, and the angle of needle insertion. A needle with a diameter of approximately 14 mm is then carefully guided into the lesion, allowing for accurate sampling of pathological tissue. This technique boasts several advantages, including high accuracy, minimal invasiveness, and rapid recovery, as it enables direct sampling from the lesion site, thereby avoiding more invasive diagnostic methods such as thoracotomy. However, it is important to note that this procedure carries some risk of complications, including bleeding and pneumothorax.

In addition to percutaneous lung biopsy, endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) can also assist in determining the benign or malignant nature of PNs. EBUS-TBNA allows for real-time ultrasound-guided biopsy of mediastinal lesions and lymph nodes outside the large airways, making it an efficient and minimally invasive diagnostic tool. This technique is characterized by high diagnostic accuracy and a low incidence of complications, leading to its widespread application in the diagnosis and staging of lung cancer (48,49). Compared to CT-guided percutaneous lung biopsy, which is also a minimally invasive sampling method, EBUS-TBNA offers distinct advantages in tumor staging and facilitates repeated sampling with fewer complications (50).

Liquid biopsy

Liquid biopsy can be utilized for the diagnosis and treatment of various cancers, including lung cancer, breast cancer, and prostate cancer, enabling non-invasive real-time monitoring of disease progression. The most promising applications of liquid biopsy are screening and early diagnosis, which helps to improve the survival rate and reduce the disease burden. Currently, liquid biopsies mainly include measurements of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes, and autoantibodies (AABs) (51,52).

CTCs are cancer cells that circulate in the blood after naturally shedding from original or metastatic tumors. As an important biomarker of liquid biopsy, CTCs have good application prospects in the diagnosis, prognostic prediction, and monitoring of lung cancer (52,53). The enrichment techniques of CTC include immunomagnetic positive/negative enrichment, microfluidic immunocapture, and membrane filtration (54). In recent years, there has been a great improvement in the diagnosis of benign and malignant PNs using CTC. CTCs captured by folic acid receptors and CTC measurement using the ScreenCell Cyto filtration system (ScreenCell, Paris, France) are highly effective for lung cancer diagnosis, with sensitivities of 85.05% and 70.1%, respectively (55,56). CTC isolation using the CellCollector (GILUPI, Potsdam, Germany) in vivo detection method may also be effective for distinguishing between benign and malignant nodules (56). Furthermore, the size of PNs is correlated with the quantity of CTCs. Research has indicated that larger tumors tend to shed more tumor cells into the bloodstream. Specifically, PNs with greater diameter and volume are more likely to yield detectable levels of CTCs in the blood (57).

ctDNA is a small nucleic acid released by apoptotic or necrotic tumor cells. It represents tumor cell genes encoded by circulating free DNA (cfDNA) and serves as a valuable indicator of epigenetic alterations. Plasma has been reported to be a good source of ctDNA (58). However, the main limitation of ctDNA is its relatively low sensitivity when tumor volume or burden is minimal. However, as PNs increase in size and tumor stage advances, the sensitivity of ctDNA detection improves significantly: 45% for stage I, 72% for stage II, 75% for stage III, and 83% for stage IV tumors (59,60). To overcome the limitation of sensitivity of more standard methods, some studies have applied personalized cancer profiling by deep sequencing, tagged AMplicon deep sequencing, Safe-sequencing, and Duplex sequencing for the early diagnosis of lung cancer, but this still resulted in low sensitivity (50%) (61). However, integrated digital error suppression has improved the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq). Moreover, methylated promoter detection in the plasma has been shown to be more accurate in the diagnosis of early-stage lung cancer (62-65). Liang et al. combined ctDNA and DNA methylation to distinguish between lung cancer and benign nodules, and the sensitivity in stage IA was 75% (66). Ooki et al. used methylation-specific polymerase chain reaction (PCR) to detect six genes selected in The Cancer Genome Atlas (TCGA) dataset and showed that the sensitivity is 72.1% in stage IA adenocarcinoma (67). Hulbert et al. also detected another six genes identified from TCGA dataset, the results showed that the sensitivity was 65–76% and the specificity was 74–84% (68).

Exosomes are 30–100 nm extracellular vesicles which are composed of nucleotides and proteins secreted by most cell types and abundantly present in body fluids (69). Exosomes are considered the most potential biomarkers for diagnosing early lung cancer. Jin et al. found that exosomal microRNA (miRNA) profiles in plasma could identify stage I NSCLC, with a sensitivity of 80.253%, specificity of 92.3%, and an AUC of 0.899 (70). They also found four adenocarcinoma-specific exosomal miRNAs (miR-181-5p, miR30a-3p, miR-30e-3p, and miR-361-5p) and three squamous cell carcinoma (SCC)-specific exosome miRNAs (miR-10b-5p, miR-15b-5p, and miR320b) with promising diagnostic power to distinguish adenocarcinoma from SCC (AUC values of adenocarcinomas and SCC were 0.936 and 0.911, respectively) (70). A systematic meta-analysis revealed that miRNAs still play an important role in the diagnostic of early-stage lung cancer, with a sensitivity and specificity of 80% and 81%, respectively (71). Bianchi et al. studied the potential role of circulating miRNAs in the serum of high-risk individuals, and a panel of 34-miRNAs (miR-test) showed that the diagnostic accuracy was 80% in asymptomatic high-risk patients with early-stage NSCLC (72). Li et al. proposed that exo-growth arrest-specific transcript 5 could be used to identify patients with stage I NSCLC, with an AUC value of 0.822 (73).

AABs are produced by the abnormal exposure or presentation of tumor-associated antigens to promote autoimmune reactions. The relevant antigen produced during tumorigenesis is recognized by the immune system, which in turn produces tumor-related AABs that can be used as tumor markers to assist in the diagnosis of lung cancer (74,75). Measurement of AABs in serum can be a less invasive, long-term, and stable strategy for the early detection of lung cancer (76). Lastwika et al. reported that four AABs (FCGR2A, EPB41L3, LINGO1, and S100A7L2) were detected using high-density protein arrays, with an AUC of 0.78 in indeterminate PNs (77). Wang et al. found that seven AAB (7-AAB) panel tests had significantly higher predictive capability for malignant nodules than radiological modalities. The test had 90.2% sensitivity and 92.7% positive predictive value (PPV) (78). AABs are more effective when combined with traditional methods. Ling et al. found that the 7-AAB panel combined with the Mayo model were more reliable in early detection of lung cancer than the 7-AAB panel alone or the Mayo alone, with a sensitivity of 93.5% (79). Leidinger et al. reported that an AAB spectrum, consisting of 1,827 integer intensity values ranging from 0 to 255, could distinguish between patients from controls without any lung disease, with a specificity of 97.6%, sensitivity of 75.9%, and an accuracy of 92.9% in stage IA/IB tumors (80).

Combined diagnosis

The combination of classical diagnostic techniques and liquid biopsy can greatly improve the sensitivity and accuracy of distinguishing benign nodules from malignant nodules (81,82). Yang et al. developed a patient risk model and a nodule risk model based on clinical information, risk factors, and LDCT that exhibited high efficacy in classification. The AUC was 0.704 in the training dataset and 0.719 in the validation dataset. For the nodule risk model, the AUC of the training dataset was 0.915, and that of the validation dataset was 0.584 (83). The combination of AABs with CT could improve diagnostic performance, with high specificity (>92%) and PPV (>70%) (84). Lin et al. showed that the combination of plasma biomarkers and radiological features could more accurately identify lung cancer, with a sensitivity and specificity of 89.9% and 90.9%, respectively (85). Xi et al. established a prediction model for early-stage NSCLC by 3 miRNAs (miRNA-146a, -200b, and -7) and CT features (pleural indentation and speculation); the model had 92.9% sensitivity and 83.3% specificity in the training set (86).

Recent advancements in the diagnostic methods for PNs have been notable. However, multiple studies indicate that only 10–25% of pure GGNs exhibit enlargement or progression upon follow-up. Additionally, just 40% of part-solid nodules show an increase in size or solid component during monitoring (87,88). These findings suggest that not all PNs necessitate intervention or surgical treatment. Current guidelines recommend surgical intervention under specific criteria: (I) persistent pure GGNs with a diameter of ≥15 mm, solid nodules with a diameter of ≥8 mm, or persistent part-solid nodules with a solid component of ≥5 mm that are highly suspected of malignancy; and (II) stability or growth after dynamic follow-up, defined as an increase of ≥2 mm in the maximum diameter of the nodule or the maximum diameter of the solid component (26).

Prognosis evaluation of malignant lung nodules

Approximately 4% of PNs are malignant, and most malignant PNs (peripheral) are relatively in the early stage of disease (stage I or stage IA) (28). The Lung Cancer Study Group (LCSG) trial established that lobectomy with systematic lymph node dissection or lymphatic sampling without adjuvant therapy is the standard treatment for stage IA lung cancer (89). However, the prognosis of stage IA lung cancer is heterogenous. Some high-risk patients have poor biological performance, a high risk of recurrence and metastasis, and poor prognosis and may thus require active clinical intervention. Some low-risk individuals have indolent biological characteristics, excellent prognosis, and low risk of metastasis and recurrence, and radical surgical treatment may not be required. Downgrading surgical resection and the intensity of clinical treatment will not decrease prognosis. Therefore, an accurate evaluation of the prognosis of stage IA lung cancer is key to risk stratification and precision medicine.

Demographic and clinical prognostication

Clinicodemographic features, including sex, age, smoking history, economic status, and systemic immune status, are all significant independent risk prognostic factors for early lung cancer. The JCOG0201 study showed that age >65 years was a potential risk factor for recurrence-free survival (RFS) in stage IA NSCLC (90). Smoking pack-years is also an important clinical prognostic factor to evaluate the overall long-term survival of patients with stage I primary resection of NSCLC (91). The risk of cancer development and mortality has been shown to be significantly lower in patients who stop smoking than in those who continue to smoke (92,93). Ou et al. reported that old age, male gender, non-surgical treatment, and poor histological grade were associated with an increased mortality risk. Meanwhile, bronchioloalveolar carcinoma and Asian race were associated with a reduced risk of death from stage I NSCLC (94). Lower socioeconomic status, racial and ethnic disparities are also prognostic factors in patients with early-stage lung cancer. The indexes of systemic immunity and inflammation reflect the state of autoimmune function and are related to the occurrence, proliferation, angiogenesis, and metastasis of tumors, which are of great significance to the prognosis of stage I NSCLC (95,96). Takahashi et al. showed that a high preoperative neutrophil-to-lymphocyte ratio (NLR) was an important predictor of poor prognosis, which was related to more frequent distant metastases in patients with completely resected stage I NSCLC (97). Platelets play important roles in blood clotting, fibrinolysis, inflammatory responses, and neoplasia, and also significantly impact the growth, survival, and metastasis of tumor cells. A meta-analysis showed that high NLR, high platelet/lymphocyte ratio, and low lymphocyte/monocyte ratio were significant predictors of poor prognosis (98,99).

Tumor-related factors

Nodule characteristics, such as size, density, and pathological subtypes, influence prognosis. Tumor size is an important indicator of prognosis in patients with early-stage lung cancer. Koike et al. retrospectively evaluated 3,315 patients with stage I disease who underwent complete surgical resection and found that tumor size was an independent prognostic factor for postoperative survival (100). A study including 255 patients with stage IA NSCLC who underwent surgical resection showed that solid tumor volume was an independent influencing factor of disease-free survival (DFS), and the evaluation of tumor volume was more accurate than cross-sectional measurements (101). Tumor size has a marked impact on lymph node metastasis; the larger the tumor diameter, the higher the probability of lymph node metastasis (102,103). A meta-analysis showed that tegafur-uracil is associated with significantly better survival than surgery alone in patients with stage IA (T>2, ≤3 cm) NSCLC (104). Sensitivity to chemotherapy increased as the tumor size increased (105). Rami-porta et al. found that tumor size ranging from 1 cm to 5 cm is associated with prognosis, with each centimeter increase being associated with a significantly different prognosis (106). Therefore, according to the primary tumor size, the 8^th edition of the tumor-node-metastasis (TNM) staging system of lung cancer was subdivided into T1a (≤1 cm), T1b (>1, ≤2 cm), and T1c (>2, ≤3 cm).

Nodule density is also crucial for prognosis. PNs are often divided into three categories: pure solid nodules, pure GGNs, and partially solid nodules (PSNs) (107). The risk of prognosis in solid nodules is significantly higher than that in PSNs and pure GGNs. Meanwhile, pure GGNs have an excellent prognosis (108). Ye et al. retrospectively evaluated 1,212 patients with stage IA lung adenocarcinoma (LUAD) and divided them into the GGN, PSN, and pure solid nodule groups. The 5-year NSCLC-related RFS rates were 99.43%, 91.74%, and 58.08% (P<0.0001), and the 5-year NSCLC-related OS were 100%, 98.13%, and 80.27% (P<0.0001), respectively (109). Consolidation tumor ratio (CTR) was also reported to be a significant prognostic factor in early-stage NSCLC (108,110). Matsunaga et al. demonstrated that the prevalence of lymph node metastasis increased significantly with increasing CTR, and CTR was an independent prognostic factor for DFS (111). Yip et al. found that both DFS and OS were higher for category PSNs <80% than for category PSNs ≥80% (112). Therefore, in the International Association for Lung Cancer TNM staging system 8^th edition suggested that clinical T staging should be based on the solid tumor size rather than on the whole size of these lesions. However, PSNs with ground-glass components are a special type of tumor. Hattori et al. evaluated 1,181 surgical resection clinical N0 M0 NSCLC patients and found that maximum tumor size and CTR were not correlated with poor OS in partial solid lung cancer on imaging (113). Therefore, the estimation of prognosis for early-stage NSCLC based on solid components remains controversial.

The combination of tumor size and nodule density is an important factor for prognostic estimation. In a prospective multi-institution study (JCOG0201), the 10-year RFS of ground-glass opacities (GGOs) patients with CTR ≤0.25 and tumor length ≤2 cm was 94.1% (114). Lesions typically showing pure GGN measuring ≤3 cm are classified as Tis and part-solid nodules with a solid component measuring ≤0.5 cm as T1mi. These patients have a 100% or near 100% DFS if the lesion is completely resected (115). The JCOG0804 trial also confirmed that patients with stage IA LUAD with T ≤2 cm and CTR ≤0.25 could benefit from sublobular treatment (mainly wedge-shaped) (116). The JCOG0802 trial showed that segment resection was better for stage IA LUAD with T ≤2 cm and CTR >0.5, ≤1 (117). Based on these results, localized resection can achieve an OS equivalent to or even more beneficial than standard lobectomy in patients with tumor size ≤2 cm, especially those with predominant GGO LUAD, with RFS, and the surgical method can be directly determined based on imaging features.

Furthermore, histological subtype significantly affects the prognosis of stage IA lung cancer. Micropapillary- and solid-predominant adenocarcinomas have a significantly higher risk of recurrence than other types (118-120). Tumor spread through air spaces (STAS) of tumor cells is closely related to the prognosis of stage I NSCLC patients, and STAS is an important risk factor for recurrence after limited resection in early-stage lung cancer (121,122). In addition, lymph vascular invasion, vessel invasion, and poor tumor differentiation are risk factors for recurrence and poor prognosis in stage IA NSCLC (123-126). Studies have reported that lepidic-predominant LUAD has favorable prognosis. Meanwhile, patients with micropapillary or solid components are correlated with lymph node metastasis, and adjuvant chemotherapy may be beneficial in micropapillary patients with stage IA (127-129). Hence, due to the requirement of the main features of lepidic growth and the lack of vascular, pleural, or air space invasion to classify a tumor as minimally invasive adenocarcinoma, it is possible that a tumor measuring ≤5 mm would be categorized as invasive adenocarcinoma and therefore be T1a, but not T1mi. Visceral pleural invasion was classified as T2 in the 8th edition of the TNM staging.

Molecular biomarkers

Molecular biomarkers also play an important role in prognosis evaluation in early-stage lung cancer. Izar et al. showed that completely resected stage I epidermal growth factor receptor (EGFR) mutation-positive NSCLC was associated with a significantly lower recurrence rate and longer 5-year DFS and OS than was wild-type EGFR (130). KRAS status is an independent prognostic risk factor; patients with mutations have significantly worse DFS and OS than do patients with KRAS-wild type (131). The positive expression of human epidermal growth factor receptor 2 (HER2) also indicates worse 5-year OS in stage I disease (132). Overexpression of vascular endothelial growth factor is related to poor survival in early-stage NSCLC patients (133). P53 mutations are potential markers of poor prognosis in stage I LUAD patients. Graziano et al. reported that P53 mutations are prevalent in 47% of patients with stage IB NSCLC, and a significant correlation between shorter DFS and OS was observed in the patients with P53 protein expression (134,135). Herbst et al. found that a lower matrix metalloproteinase (MMP)-to-E-cadherin ratio (≤2) was significantly associated with longer OS and lower disease recurrence rates (136). D’Amico et al. found that C-erbb-2 expression is a significant risk factor for tumor recurrence in stage I lung cancer (137). Ruffini et al. retrospectively evaluated 1,290 patients who underwent surgery for primary lung tumor and found that tumor-infiltrating lymphocyte levels were correlated with improved the survival rate of SCCs, especially in early-stage disease (138). The combination of multiple biomarkers will more accurately predict prognosis. Sandoval et al. found that the hypermethylation of five genes (HIST1H4F, PCDHGB6, NPBWR1, ALX1, and HOXA9) was related to shorter RFS and affected the outcome of stage I NSCLC. A signature based on the number of hypermethylated events was used to distinguish between high-risk and low-risk NSCLC patients in stage I (139). A study that investigated 956 patients with stage I LUAD showed that immune markers (FoxP3, FoxP3/CD3, IL-7R, and IL-12Rβ2) were independently associated with recurrence. A meta-analysis suggested that positive programmed death-ligand 1 (PD-L1) expression was related to prominently shorter DFS and significantly worse OS (140). A meta-analysis indicated that PD-L1 expression was related to markedly shorter DFS and significantly worse OS (141).

Perspective

As the prevalence of PNs has significantly increased, it is particularly important to differentially diagnose benign and malignant PNs using minimally invasive or non-invasive methods to avoid overdiagnosis. Liquid biopsy has become an important research topic and a direction for future research in the early diagnosis of lung cancer in recent years. However, liquid biopsy currently does not have clear thresholds and standard operating protocols, and, unlike CT, it cannot assess tumor staging. Despite the great potential of the existing methodologies, there is no single molecular biomarker of lung cancer for routine clinical practice. Further studies are required.

First, biomarkers combined with imaging features may be more effective in the diagnosis of lung cancer, and the criteria for distinguishing benign and malignant nodules should be improved. Minimal residual disease (MRD) monitoring is a promising strategy, and preoperative ctDNA testing to determine patient prognosis has good potential. Second, patients with nodule diameter ≤2 cm, pure adenocarcinoma in situ (AIS) histology, GGO attenuation in >50% of the diameter on CT, or volume doubling time >400 days may be considered for sublobar resection. Meanwhile, non-surgical patients with early-stage NSCLC should be considered for conventional or stereotactic radiotherapy. For patients with early-stage lung cancer with slow-growing disease or those who are not candidates for surgery, noninvasive ablative therapies are necessary. The genomic differences between fast- and slow-growing diseases need to be clarified. The molecular events that mediate disease progression require further investigation.

Studies have suggested that adjuvant targeted therapies could improve PFS in early-stage NSCLC but may not convert to improved OS. The possible reason for the improvement in PFS but not in OS could be a result of tyrosine kinase inhibitors not being able to completely eliminant micrometastatic disease. Neoadjuvant chemotherapy has potential advantages, including improved tolerability, possible staging reduction, and earlier treatment of micrometastases in early-stage NSCLC. In parallel, immune checkpoint therapy has become an indispensable treatment, especially for patients who lack actionable oncogenic drivers. Despite future challenges, the discovery and application of new biomarkers will promote the development of precision medicine and improvement of outcomes in patients with early-stage NSCLC.

This review summarizes the research progress in the clinical management of malignant PNs, but it did not investigate the clinical application and prevalence of various research advances, as a comprehensive investigation of clinical application is not readily feasible.

Conclusions

Clinicopathological features and imaging characteristics play an important role in the diagnosis and prognosis assessment of early lung cancer, but liquid biopsy and artificial intelligence are also promising owing to their convenience and accuracy.

Acknowledgments

We thank Jianfei Zhu and Wenchen Wang for critically editing the manuscript.

Funding: This study was funded by the National Natural Science Foundation of China (82002421), Youth Talent Lifting Program of Shaanxi Association for Science and Technology (20230311), Key research and development plan of Shaanxi Province (2023-YBSF-318), Health Care Special Research Project of Military Logistics Research Program (23BJZ23, 19BJZ20), Key Projects in Military Logistics (BKJ21J009).

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1058/rc

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