Lung Cancer Research Research Articles

Contribution of Next Sequencing Generation in Lung Cancer and Its Prognostic Implication

Lung cancer is one of the most commonly diagnosed cancers worldwide. It is the leading cause of cancer-related deaths in both men and women. In 2020, there were an estimated 2.2 million new cases of lung cancer and 1.8 million deaths due to the disease. Historically, lung cancer has been more common in men, but the gap has been closing. Smoking tobacco is the leading cause of lung cancer. Survival rates for lung cancer vary greatly depending on the stage at diagnosis and other factors. Overall, the prognosis for lung cancer is often poor, with a relatively low five-year survival rate compared to some other cancers. In this work we aim to show new paths in the diagnosis of lung cancer, through the study of several mutations and proteins, mostly detected by Next-generation sequencing (NGS) which has significantly transformed our understanding of cancer, by providing high-throughput and cost-effective methods for analyzing genomic information. In the context of lung cancer, NGS has played a crucial role in advancing our knowledge of the disease, improving diagnosis and treatment, and guiding personalized medicine approaches. key points highlighting the importance of next-generation sequencing in lung cancer: Comprehensive Genomic Profiling Identification of Driver Mutations Stratification of Patients Predicting Treatment Response Monitoring Disease Progression Clinical Trials and Drug Development Early Detection and Prognosis A large meta-analysis has been done, as well as a detailed study of 86 patients diagnosed with lung cancer in the ANALIZA laboratory. In this sense the most frequently implicated mutations in this tumor have been analyzed, ALK, ROS1 and EGFR, the positions they occupy in the genes, in addition to the programmed death ligand 1 (PD-L1), an immune control protein, which is expressed in activated immune cells and in tumor cells, and how its identification allows us to direct treatment in a more optimal way. In summary, next-generation sequencing has revolutionized the field of lung cancer research and clinical practice. By providing detailed insights into the genomic landscape of tumors, NGS facilitates personalized treatment approaches, early detection, and ongoing monitoring, ultimately leading to improved patient outcomes.

Advances in the Study of Tissue-resident Memory T Cells in Lung Cancer

Immune checkpoint inhibitors (ICIs) have been widely used in the treatment of lung cancer, but the benefit population is limited and there is a lack of effective predictive markers of efficacy. Tissue-resident memory T cells (TRM) reside in tissues and exert anti-tumor effects by expressing the integrins CD103, CD49a or C-type lectin CD69 and immune checkpoint receptors. TRM expressing programmed cell death 1 (PD-1) is enriched with transcriptional products associated with cytotoxicity and enhances T cell (antigen) receptor (TCR)-mediated cytotoxicity. TRM is a promising biomarker for predicting the efficacy and prognosis of immunotherapy in lung cancer patients. This review will describe the progress of TRM research in lung cancer. .

Lung Cancer Clinical Trials with a Seamless Phase II/III Design: Systematic Review

Current lung cancer clinical research focuses on biomarkers and personalized treatment strategies. Adaptive clinical trial designs have gained significant ground due to their increased flexibility, compared to the conventional model of drug development from phase I to phase IV trials. One such adaptive approach is the seamless phase II/III design, which has been used to reduce the total sample size and drug development time. In this context, an algorithmic systematic search was conducted in MEDLINE (PUBMED), SCOPUS, EMBASE and Cochrane Central Register of Controlled Trials until 31 June 2022 in order to identify lung cancer trials of systematic treatments that have employed the seamless phase II/III methodology and to describe their characteristics. The search strategy yielded a total of 1420 records that were screened through their title and abstract; 28 eligible trials were included in the systematic review. Based on the study endpoints, the most common subtype included phase II/III trials with inefficacy/futility analyses (61%; 17/28), followed by dose escalation phase II/III trials (18%; 5/28), one multi-arm multi stage trial and 5 trials with other design (18%). Most eligible trials were open-label (71%; 20/27), included patients with non-small cell lung cancer (82%; 23/28), evaluated targeted therapies and/or immunotherapies (82%; 23/28) and recruited patients with advanced disease (89.3%; 25/28). In conclusion, the seamless phase II/III design is a feasible and suitable approach in lung cancer research, with distinct design subcategories according to study endpoints.

Multigroup prediction in lung cancer patients and comparative controls using signature of volatile organic compounds in breath samples.

Early detection of lung cancer is a crucial factor for increasing its survival rates among the detected patients. The presence of carbonyl volatile organic compounds (VOCs) in exhaled breath can play a vital role in early detection of lung cancer. Identifying these VOC markers in breath samples through innovative statistical and machine learning techniques is an important task in lung cancer research. Therefore, we proposed an experimental approach for generation of VOC molecular concentration data using unique silicon microreactor technology and further identification and characterization of key relevant VOCs important for lung cancer detection through statistical and machine learning algorithms. We reported several informative VOCs and tested their effectiveness in multi-group classification of patients. Our analytical results indicated that seven key VOCs, including C4H8O2, C13H22O, C11H22O, C2H4O2, C7H14O, C6H12O, and C5H8O, are sufficient to detect the lung cancer patients with higher mean classification accuracy (92%) and lower standard error (0.03) compared to other combinations. In other words, the molecular concentrations of these VOCs in exhaled breath samples were able to discriminate the patients with lung cancer (n = 156) from the healthy smoker and nonsmoker controls (n = 193) and patients with benign pulmonary nodules (n = 65). The quantification of carbonyl VOC profiles from breath samples and identification of crucial VOCs through our experimental approach paves the way forward for non-invasive lung cancer detection. Further, our experimental and analytical approach of VOC quantitative analysis in breath samples may be extended to other diseases, including COVID-19 detection.

Chlorotoxin and Lung Cancer: A Targeting Perspective for Drug Delivery.

In the generational evolution of nano-based drug delivery carriers, active targeting has been a major milestone for improved and selective drug accumulation in tissues and cell types beyond the existing passive targeting capabilities. Among the various active targeting moieties, chlorotoxin, a peptide extracted from scorpions, demonstrated promising tumor cell accumulation and selection. With lung cancer being among the leading diagnoses of cancer-related deaths in both men and women, novel therapeutic methodologies utilizing nanotechnology for drug delivery emerged. Given chlorotoxin's promising biological activity, we explore its potential against lung cancer and its utilization for active targeting against this cancer's tumor cells. Our analysis indicates that despite the extensive chlorotoxin's research against glioblastoma, lung cancer research with the molecule has been limited, despite some promising early results.

Current status of immunotherapy for non-small cell lung cancer.

Nowadays, lung cancer is still the deadliest oncological disease in the world. Among them, non-small cell lung cancer (NSCLC) accounts for 80%∼85% of all lung cancers, and its 5-year survival rate is less than 15%, making the situation critical. In the past decades, despite some clinical advances in conventional treatments, the overall survival rate of NSCLC is still not optimistic due to its unique physiological conditions and the frequent occurrence of tumor escape. In recent years, immunotherapy has become a new hot spot in lung cancer research, including antibody therapy and cell therapy, which have been developed and utilized one after another, especially immune checkpoint inhibitor (ICI). These approaches have effectively improved the overall survival rate and objective response rate of NSCLC patients by enhancing the immune capacity of the body and targeting tumor cells more effectively, which is more specific and less toxic compared with conventional chemotherapy, and providing more strategies for NSCLC treatment. In this paper, we reviewed the relevant targets, clinical progress and adverse reaction in monoclonal antibodies, antibody-drug conjugates, ICI, bispecific antibodies, T-cell receptor engineered T cell therapy (TCR-T), Chimeric antigen receptor T-cell immunotherapy (CAR-T), and also report on their combination therapy from the immune-related background to provide better NSCLC treatment and prospective.

Inferring Cell-type-specific Genes of Lung Cancer Based on Deep Learning.

Lung cancer is cancer with the highest incidence in the world, and there is obvious heterogeneity within its tumor. The emergence of single-cell sequencing technology allows researchers to obtain cell-type-specific expression genes at the single-cell level, thereby obtaining information regarding the cell status and subpopulation distribution, as well as the communication behavior between cells. Many researchers have applied this technology to lung cancer research, but due to the shortcomings of insufficient sequencing depth, only a small part of the gene expression can be detected. Researchers can only roughly compare whether a few thousand genes are significant in different cell types. To fully explore the expression of all genes in different cell types, we propose a method to predict cell-type-specific genes. This method infers cell-type-specific genes based on the expression levels of genes in different tissues and cells and gene interactions. At present, biological experiments have discovered a large number of cell-type-specific genes, providing a large number of available samples for the application of deep learning methods. Therefore, we fused Graph Convolutional Network (GCN) with Convolutional Neural Network( CNN) to build, model, and inferred cell-type-specific genes of lung cancer in 8 cell types. This method further analyzes and processes single-cell data and provides a new basis for research on heterogeneity in lung cancer tumor, microenvironment, invasion and metastasis, treatment response, drug resistance, etc.

Lung Cancer in the Non-smoker: A Patient View Focused on the Hopes and Challenges Facing the Non-smoker Population

A patient view paper focused on hopes and challenges facing the never smoker lung cancer population – from lived experience, unexpected diagnosis, treatment and subsequent immersion in lung cancer research and patient advocacy over many years, citing examples, references and events organised to explore the subject by UK research institutions. Material/methodsBased on lived experience, invited patient perspective conference presentations including National Cancer Research Institute (NCRI) never smoker lung cancer research strategy event opening presentation and subsequent article, includes references to relevant papers/findings and points raised during research events/group discussions, alongside personal experiences and beliefs. ResultsDiscussions with clinicians, events, surveys, meetings and virtual discussions all revealed a dearth of evidence available to identify the best way to deal with this patient cohort at almost every aspect of their experience – from missed/late diagnosis, to screening potential (non-existent), mutation driven treatments (what about those ineligible?), and psychosocial/psychological aspects given their different life stage from older traditional lung cancer patients. ConclusionMore effort and focus are needed to better understand what is driving these cases, how best to detect them sooner and respond/refer to treatments as well as developing screening methods alongside increased public and healthcare professional awareness raising and tools to support clinicians in earlier detection.

Medical Data Analysis of CYP1B1 Gene Polymorphism and Clinical Prognosis of Minimally Invasive Surgery for Lung Cancer.

To address the issue of genetic mutations in medical records, clinical studies on minimally invasive surgery for breast cancer have been proposed. The CYP1B1 gene is mainly a single-nucleotide mutation, which affects the enzymatic reaction related to carcinogens and causes the susceptibility differences of different individuals. First, the survival rate and other factors influencing the estimation of 120 leukemia patients were examined with the help of various medical records by establishing an organization for auxiliary diagnosis of lung cancer based on expertise. Secondly, through the treatment of 120 leukemia patients after minor surgery, the average life expectancy of 120 patients was 19 months, the one-year survival rate was 74.61%, and the two-year survival rate was 32.70%. Currently, there are more than 160 cases of CYP1B1 discovered. In recent years, people have gradually entered into in-depth research on the correlation between genes and lung cancer, which is of great significance to the treatment and research of lung cancer. An analysis showed patients' age, stage, whether they would work, whether radiation therapy and antibiotics were offered, and so on. s has a direct impact on patient survival, and many tests have shown that the patient's age, stage, whether it will work, and whether fire radiation and drug therapy are provided are important interventions for patients with anemia. Finally, in patients with leukemia, especially during the restricted period, combined treatment with a physician, radiologist, and surgeon should be initiated as soon as possible. For a wide range of disease, depending on the use of chemotherapy, local metastasis with antibiotics can improve the disease. After success, it is more beneficial to choose second-line treatment.

Phosphoproteomics of extracellular vesicles integrated with multiomics analysis reveals novel kinase networks for lung cancer.

Phosphorylation regulates the functions of proteins and aberrant phosphorylation often leads to a variety of diseases, including cancers. Extracellular vesicles (EVs) are important messengers in the microenvironment and their proteome contributes to cancer genesis and metastasis, while the kinases that driving EVs proteins' phosphorylation are less known. Clinical tissue samples from 13 patients with non-small-cell lung cancer (NSCLC) were utilized to isolate cancer EVs and adjacent normal EVs. Through quantitative phosphoproteomics analysis, 2473 phosphorylation sites on 1567 proteins were successfully identified and quantified. Accordingly, 152 kinases were identified, and 25 of them were differentially expressed. Based on Tied Diffusion through Interacting Events (TieDIE) algorithm, we integrated genomic and transcriptomic data sets of NSCLC from TCGA with our phosphoproteome data set to construct signaling networks. Through database integration and multiomics enrichment analysis, a compact network of 234 nodes with 1599 edges was constructed, which consisted of 34 transcription factors, 33 kinases, 63 aberrant genes, and 172 linking proteins. Rarely studied phosphorylation sites were specifically enriched. Key phosphoproteins of network nodes were validated in patients' EVs, including MAPK6S189 , IKBKES172 , SRCY530 , CDK7S164 , and CDK1T14 . These networks depict intrinsic signal-regulation derived from EVs' phosphoproteins, providing a comprehensive and pathway-based strategy for in-depth lung cancer research.

Sensor Technology for Opening New Pathways in Diagnosis and Therapeutics of Breast, Lung, Colorectal and Prostate Cancer

This study analyzes the interaction between sensor research and technology and different types of cancer (breast, lung, colorectal, and prostate) with the goal of detecting new directions for improving diagnosis and therapeutics in medicine. This study develops an approach to computational scientometrics based on data from the Web of Science from the 1991 to 2021 period. The results of this analysis show the vital role of biosensors and electrochemical biosensors applied in breast cancer, lung cancer, and prostate cancer research. Instead, scientific research of optical sensors is developing main technological trajectories in breast, prostate, and colorectal cancer for improving diagnostics. Finally, oxygen sensor research has a main technological development in breast and lung cancer for new applications in breath analysis directed to treatment processes. Preliminary results presented here clearly illustrate the evolutionary paths of sensor research and technologies that have great potential for developing incremental and radical innovations in cancer diagnosis and therapies. These conclusions are, of course, tentative. There is a need for much more detailed research based on other aspects and factors for detecting stable technological trajectories that can foster the technology transfer of new sensor in cancer research for improving diagnosis and therapeutics, reducing, whenever possible, world-wide mortality of cancer in society.JEL Classification: I10, O30, O31, O32; O33. Doi: 10.28991/HIJ-2022-03-03-010 Full Text: PDF

Recent advances in the electrochemical sensing of lung cancer biomarkers

In the current scenario, about 25% of all cancer deaths reported globally are related to lung cancer. Despite the development of different diagnosing techniques, including X-ray, magnetic resonance imaging, biopsy, etc., there is still a significant challenge in dealing with lung cancer mortality and morbidity. Therefore, the early diagnosis and treatment of lung cancer is essential and holds a considerable place in lung cancer research. Biomarkers, an indicator, are overexpressed in the malignant tissues and are found in the body fluids. The existence of these biomolecules beyond the cut-off level can be used as an indicator for sensing tumour markers in the diagnosis, prognosis, and clinical management of lung cancer. Hence, fast and precise detection of biomarkers is helpful in the early detection of cancer. Moreover, the redox materials used for sensing biomarkers play a critical role in the sensitivity of electroanalytical devices. Therefore, we critically review the early diagnosis of lung cancer using an electrochemical biosensor. First, the importance of biomarkers and their application in determining various stages are discussed. A detailed section is devoted to recent electrochemical electrode materials, including graphene (Gr), carbon nanotube (CNT), and metal-based nanomaterials. Finally, the limitations and future prospects of electrochemical sensors are elaborated.

Measuring the margin distance in pulmonary wedge resection.

Margin distance contributes to survival and recurrence during wedge resections for early-stage non-small cell lung cancer. The Initiative for Early Lung Cancer Research on Treatment sought to standardize a surgeon-measured margin intraoperatively. Lung cancer patients who underwent wedge resection were reviewed. Margins were measured by the surgeon twice as per a standardized protocol. Intraobserver variability as well as surgeon-pathologist variability were compared. Forty-five patients underwent wedge resection. Same-surgeon measurement analysis indicated good reliability with a small mean difference and narrow limit of agreement for the two measures. The median surgeon-measured margin was 18.0 mm, median pathologist-measured margin was 16.0 mm and the median difference between the surgeon-pathologist margin was -1.0 mm, ranging from -18.0 to 12.0 mm. Bland-Altman analysis for margin measurements demonstrated a mean difference of 0.65 mm. The limit of agreement for the two approaches were wide, with the difference lying between -16.25 and 14.96 mm. A novel protocol of surgeon-measured margin was evaluated and compared with pathologist-measured margin. High intraobserver agreement for repeat surgeon measurements yet low-to-moderate correlation or directionality between surgeon and pathologic measurements were found. A standardized protocol may reduce variability in pathologic assessment. These findings have critical implications considering the impact of margin distance on outcomes.

Lung Cancer Organoids: The Rough Path to Personalized Medicine.

Simple SummaryLung cancer is very difficult to cure, especially when it has spread to other parts of the body. One of the main reasons that delay the identification of effective therapies is the complexity of lung cancer cells, which can be very different among individual patients. Organoids are small aggregates of tumor cells that are generated from lung tumors and used in cancer research laboratories to study the features of tumor cells. Organoids have unique properties, as they reproduce many characteristics of the tumor derived from each specific patient. Due to their capacity to reproduce individual tumor features in the laboratory setting, organoids are an excellent system to study lung cancer and to identify functional therapies. This review summarizes the challenges encountered by researchers in the field of lung cancer organoids and describes how the advances in organoid technology may allow the future development of individualized therapies for lung cancer patients.Lung cancer is the leading cause of cancer death worldwide. Despite significant advances in research and therapy, a dismal 5-year survival rate of only 10–20% urges the development of reliable preclinical models and effective therapeutic tools. Lung cancer is characterized by a high degree of heterogeneity in its histology, a genomic landscape, and response to therapies that has been traditionally difficult to reproduce in preclinical models. However, the advent of three-dimensional culture technologies has opened new perspectives to recapitulate in vitro individualized tumor features and to anticipate treatment efficacy. The generation of lung cancer organoids (LCOs) has encountered greater challenges as compared to organoids derived from other tumors. In the last two years, many efforts have been dedicated to optimizing LCO-based platforms, resulting in improved rates of LCO production, purity, culture timing, and long-term expansion. However, due to the complexity of lung cancer, further advances are required in order to meet clinical needs. Here, we discuss the evolution of LCO technology and the use of LCOs in basic and translational lung cancer research. Although the field of LCOs is still in its infancy, its prospective development will likely lead to new strategies for drug testing and biomarker identification, thus allowing a more personalized therapeutic approach for lung cancer patients.

Comparison of lung cancer aggressiveness in patients who never smoked compared to those who smoked

ObjectivesTo determine whether radiographic measures of tumor aggressiveness differ by smoking status. Materials and MethodsAll patients diagnosed with non-small-cell lung cancer(NSCLC) ≤ 30 mm in maximum diameter, without clinical evidence of metastasis who had both pre-treatment PET scans and two CT scans at least 90 days apart in a prospective cohort, the Initiative for Early Lung Cancer Research on Treatment(IELCART) at Mount Sinai between 2016 and 2020 were identified. Comparison of two measures of tumor aggressiveness, positron emission tomography(PET) SUVmax and tumor volume doubling time(VDT) by smoking status was performed. ResultsOf 417 patients identified, 158 patients had pre-treatment PET scans and at least two CT scans available. The two measures of tumor aggressiveness, SUVmax and VDT values were significantly different between patients who had never smoked and those who smoked: patients who never smoked had lower median SUVmax[2.5(IQR: 1.1–4.8) vs. 4.2(IQR:2.1–9.2),p = 0.002] and longer median VDT[(372.6 days vs. 225.6 days,p = 0.001)] compared to those who smoked. Using multivariable analyses, when adjusting for age and sex alone, SUVmax(p = 0.004) and VDT(p = 0.0001) remained significantly different by smoking status. The final multivariable analysis, adjusted for all three co-variates(sex, age and tumor histology) showed no significant difference in SUVmax and VDT by smoking status [SUVmax(p = 0.25) and VDT(p = 0.06)]. ConclusionSmoking history does not influence VDT or PET SUVmax measures of lung cancer aggressiveness.

Patient-Derived Lung Tumoroids-An Emerging Technology in Drug Development and Precision Medicine.

Synthetic 3D multicellular systems derived from patient tumors, or tumoroids, have been developed to complete the cancer research arsenal and overcome the limits of current preclinical models. They aim to represent the molecular and structural heterogeneity of the tumor micro-environment, and its complex network of interactions, with greater accuracy. They are more predictive of clinical outcomes, of adverse events, and of resistance mechanisms. Thus, they increase the success rate of drug development, and help clinicians in their decision-making process. Lung cancer remains amongst the deadliest of diseases, and still requires intensive research. In this review, we analyze the merits and drawbacks of the current preclinical models used in lung cancer research, and the position of tumoroids. The introduction of immune cells and healthy regulatory cells in autologous tumoroid models has enabled their application to most recent therapeutic concepts. The possibility of deriving tumoroids from primary tumors within reasonable time has opened a direct approach to patient-specific features, supporting their future role in precision medicine.

Comparison of the somatic mutations between circulating tumor DNA and tissue DNA in Chinese patients with non-small cell lung cancer

Non-invasive liquid biopsies of circulating tumor DNA (ctDNA) is a rapidly growing field in the research of non-small cell lung cancer (NSCLC). In this study, factors affecting the concordance of mutations in paired plasma and tissue and the detection rate of ctDNA in real-world Chinese patients with NSCLC were identified. Peripheral blood and paired formalin-fixed paraffin-embedded tumor tissue samples from 125 NSCLC patients were collected and analyzed by sequencing 15 genes. Serological biomarkers were tested by immunoassay. The overall concordance between tumor and plasma samples and the detection rate of somatic mutations in ctDNA was 69.2% and 78.4%, respectively. The concordance and detection rate raised with clinical stage were stage I: 14.3%, 14.3%; stage II: 53.3%, 60.0%; stage III: 71.4%, 78.1%; stage IV: 74.1%, 85.2%. With increased tumor diameter, the concordance and detection rate raised from 33.33% to 71.64% and 33.33% to 80.8%, respectively. For patients with partial response, stable disease, progressive disease, and who were treatment-naïve, the concordance and detection rates were 0.0%, 62.7%, 75.2, 73.6%, and 16.7%, 61.9%, 83.3%, 86.5%, respectively. Serological markers: CEA, CA125, NSE, and CYFRA21-1 were significantly higher for patients with detectable somatic alterations in ctDNA than in those who were ctDNA negative (17.08 ng/mL vs. 3.95 ng/mL, 21.63 U/mL vs. 18.27 U/mL, 17.68 U/mL vs. 14.14 U/mL, and 6.55 U/mL vs. 3.81 U/mL, respectively). Advanced-stage, treatment naïve or poor therapy outcome, and large tumor size were associated with a high concordance and detection rate. Patients with detectable mutations in ctDNA had a higher level of carcinoembryonic antigen, CA125, NSE, and CYFRA21-1.

Cáncer de pulmón, tendencias desde la perspectiva del cuidado

Objective: identify trends in lung cancer research over the past five years from a nursing care perspective. Method: bibliometric and exploratory review based on the web of science database. The descriptors, lung neoplasm and nursing care were used with application of filters, obtaining a total of 62 articles published between the years 2017-2021. The bibliometric analysis was performed using bibliometrix with the total number of documents obtained; 30 articles describing the main thematic trends identified in the conceptual structure were used for the exploratory analysis. Results: bibliometric indicators show an average publication rate of 12 articles per year, with a predominance of publications with a quantitative approach (66.7 %) and a low level of evidence (56.7 %). The highest number of articles published per source and author was 4. The exploratory results show five relevant topics related to: lung cancer diagnosis, symptoms, palliative care, quality of life and advanced nursing practice. Conclusion: it is possible to identify publications that emphasize the aforementioned topics, with a low level of evidence and with few interventions carried out by nurses. The studies focus on symptom control and end-of-life care.

Uniting Latin America Through Research: How Regional Research Can Strengthen Local Policies, Networking, and Outcomes for Patients With Lung Cancer.

Lung cancer represents a considerable global health threat, leading the list in terms of cancer-related deaths worldwide. An important proportion of lung cancer cases occur within Latin America, and current projections show that over the next decade, the number of deaths due to lung cancer will double in the region, underscoring the need to implement evidence-based interventions to improve outcomes. Several challenges have limited the progress in lung cancer research in Latin America for many years, though recently the surge of multidisciplinary, transnational, and transcultural research groups have overcome many of these limitations. The increase in region-specific knowledge has improved cancer care in the area, providing clinicians with a specific demographic and molecular profile for Hispanic patients with lung cancer; as a result, the implementation of precision oncology has benefited from a profound knowledge of the patient profile. Nonetheless, there are still challenges to improve research in Latin America, including stabilizing funding sources to continue independent research, supporting mentoring programs and an early immersion in clinical research for early career fellows, and overcoming barriers for publishing.

Programmed Cell Death Protein 1/Programmed Cell Death Protein Ligand 1 Immunosuppressants in Advanced Non-Small Cell Lung Cancer Research Progress in Treatment.

PD-1/PD-L1 play key roles in tumor immune escape and the formation of the tumor microenvironment, and are closely related to the generation and development of tumors. Blocking the PD-1/PD-L1 pathway can reshape the tumor microenvironment or block the formation of the tumor microenvironment and enhance endogenous antitumor immune response. Clinical trials show that the treatment of non-small cell lung cancer (NSCLC) with PD-1/PD-L1 inhibitors has significant advantages. The review briefly describes these basic principles of the PD-1/PD-L1 pathway and action mechanism in the treatment of NSCLC. A summary of global PD-1/PD-L1 clinical trials and five PD-1/PD-L1 inhibitors approved by FDA, EMA and NMPA for advanced NSCLC were analyzed.