Subtype Of Non-small Cell Lung Cancer Research Articles

LncRNA SGMS1-AS1 regulates lung adenocarcinoma cell proliferation, migration, invasion, and EMT progression via miR-106a-5p/MYLI9 axis.

BackgroundLung cancer mainly includes non‐small cell lung cancer (NSCLC). Lung adenocarcinoma (LUAD) is the main subtype of NSCLC. Long non‐coding RNAs (LncRNAs) had been found to exert numerous functions on the progressions of cancers. MicroRNAs often exist as the target of LncRNAs to regulate a series of signaling pathways in human. We explored the effects and molecular mechanism of LncRNA SGMS1‐AS1 on the procedures of LUAD cells.MethodsThe ENCORI and GEPIA databases were used to analyze the differences in SGMS1, miR‐106a‐5p, and MYLIP between LUAD and normal tissue. Their expression levels were examined by RT‐PCR. CCK8, colony formation, migration, and invasion assay were conducted in LUAD cells which had silenced SGMS1‐AS1. To verify the relationship between SGMS1‐AS1, miR‐106a‐5p, and MYLIP, we overexpressed miR‐106a‐5p inhibitor or MYLIP in LUAD cells after decreasing SGMS1‐AS1 and repeated the above assays.ResultsSGMS1‐AS1 was downregulated in LUAD tissue as well as cells, which was related to good prognosis of patients with lung adenocarcinoma. Additionally, knockdown of SGMS1‐AS1 promoted proliferation, migration, invasion, and epithelial mesenchymal transition (EMT) progression of LUAD cells, which meant that SGMS1‐AS1 inhibited the progression of LUAD cells. Furthermore, miR‐106a‐5p was the direct target of SGMS1‐AS1 and transfecting miR‐106a‐5p inhibitor could reversed the impact induced by knockdown of SGMS1‐AS1. Subsequently, we found that MYLIP was the target of miR‐106a‐5p, which was negatively correlated with miR‐106a‐5p, but had high positive correlation with SGMS1‐AS1. Consistently, overexpression MYLIP partly eliminated the effects on A549 cells induced by silencing of SGMS1‐AS1.ConclusionLncRNA SGMS1‐AS1 inhibits the proliferation, invasion, migration and EMT progression of LUAD cells via targeting miR‐106a‐5p/MYLIP axis.

Identifying the histologic subtypes of non-small cell lung cancer with computed tomography imaging: a comparative study of capsule net, convolutional neural network, and radiomics.

Discriminating the subtypes of non-small cell lung cancer (NSCLC) based on computed tomography (CT) images is a challenging task for radiologists. Although several machine learning methods such as radiomics, and deep learning methods such as convolutional neural networks (CNNs) have been proposed to explore the problem, large sample sizes are required for effective training, and this may not be easily achieved in single-center datasets. In this study, an automated subtype recognition model with capsule net (CapsNet) was developed for the subtype discrimination of NSCLC. CapsNet utilizes an activity vector to record the relative spatial relationship of image elements that can subsequently better delineate the global image characteristics. CT images of 72 adenocarcinoma (AC) and 54 squamous cell carcinoma (SCC) patients were retrospectively collected from a single clinical center. The cancer region on the CT image was manually segmented for every subject by an experienced radiologist, and CapsNet, CNN, and four radiomics models were then used to construct the recognition model. The study demonstrated that CapsNet achieved the best discriminative performance (accuracy 81.3%, specificity 80.7%, sensitivity 82.2%) although its area under the curve was just marginally better than that of the optimal random forest (RF) based radiomics model. Not surprisingly, the performance of the CNN was only comparable to the other radiomics models. This study demonstrated that CapsNet is a viable potential framework for discriminating the subtypes of NSCLC, and its use could be extended to the recognition of other diseases especially in limited single-center datasets.

Effectiveness of pemetrexed-based chemotherapy and radiation therapy in RET-rearranged lung adenocarcinoma: a mono-institutional case series

: Rearranged during Transfection gene (RET) fusions occur in 0.7–2% of non-small cell lung cancer (NSCLC) representing a novel target for oncogene addicted disease. Retrospective analyses showed remarkable response to the chemotherapic anti-folate drug Pemetrexed in patients affected by RET-fusion NSCLC, while immunotherapy does not assure remarkable efficacy. Nowadays, novel therapies are enriching the number of specific anti-RET strategies. The present mono-institutional case series reports significant responses to Pemetrexed, and radiation therapies performed on previously identified or oligo-progressing metastatic sites. Next Generation Sequencing conducted on histological tissue in two cases and on blood specimen in one case detected RET fusion in the clinical course after chemotherapy. As other oncogene addicted subtypes of NSCLC, such as EGFR mutated, ALK and ROS1 rearranged, radiation treatment of residual or oligo-progressing lesions appeared to prolong the clinical benefit from oncological treatments. Despite specific anti-RET treatments are under evaluation for RET-positive non squamous NSCLC, Pemetrexed assured optimal and durable clinical response. The addition of loco-regional treatment of residual or oligo-progressive disease prolonged the time to chemotherapy failure. The present manuscript aims at arising the hypothesis that loco-regional treatment could be considered for oligo-metastatic disease with consolidation extent and could allow beyond progression Pemetrexed-based therapy for oligo-progressive disease.

Novel imaging biomarkers predict progression-free survival in stage 3 NSCLC treated with chemoradiation and durvalumab.

3054 Background: The current management of stage III non-small cell lung cancer (NSCLC) is chemoradiation followed by durvalumab consolidation. There are no robust biomarkers that predict benefit from this regimen. We evaluated the utility of novel imaging biomarkers (radiomics) to distinguish patients with stage III NSCLC who will benefit from treatment from those likely to progress despite therapy. Methods: Patients with stage III NSCLC treated at our center with chemoradiation and durvalumab from July 2017 - July 2019 were identified. We collected patient clinical outcomes, subtype of NSCLC, and PD-L1 expression as well as pre-treatment CT images. Images were split into training and test sets. Lung tumors were contoured on 3D-Slicer software and 1542 radiomic features capturing both intra- and peritumoral texture patterns were extracted. The primary endpoint of this study was progression-free survival (PFS), and the secondary objective was difference in PFS within high PD-L1 (≥50%) and low PDL1 (<50%) groups. We used the least absolute shrinkage and selection operator (LASSO) Cox regression model to build the radiomic signature for PFS. A risk score was computed according to a linear combination of selected features and their corresponding coefficients. High- and low-risk groups were defined based on median radiomics risk score. Multivariable Cox regression analysis was performed to evaluate the effect of each factor on PFS. We performed Kaplan–Meier survival analysis and log-rank tests to assess prognostic ability of the features. Results: We identified 118 patients who fit our criteria with available CT images and randomly divided them into a training (n=59) and a test set (n=59). The radiomic risk score was calculated using a linear combination of the top six selected features with corresponding coefficients. In a multivariable analysis using clinicopathologic and radiomic signatures, the radiomics risk-score and PD-L1 expression were found to be significantly associated with PFS in training (risk-score: HR = 2.3, 95% CI: [1.46 – 3.63], P = 0.0003; PD-L1: HR = 0.31, 95% CI: [0.081 – 0.96], P = 0.038) and test sets (risk-score: HR= 2.56, 95% CI: [1.75 – 4], P = 8.7e-05; PD-L1: HR = 0.27, 95% CI: [0.048 – 0.58], P = 0.005). Kaplan-Meier analyses showed a significantly shorter PFS in the high-risk radiomics group versus the low-risk group (P < 0.0001). The radiomics risk scores were also predictive of significant differences in PFS within both the low (p=0.0005) and high (p=0.0007) PD-L1 groups. Conclusions: Radiomic biomarkers from pre-treatment CT images in stage III NSCLC patients were predictive of PFS to chemoradiation followed by durvalumab and could predict outcomes regardless of PD-L1 level. Pre-treatment radiomics may allow early prediction of benefit and expedite more aggressive treatment for high-risk patients. Additional validation of these imaging biomarkers is warranted.

Improving the Subtype Classification of Non-small Cell Lung Cancer by Elastic Deformation Based Machine Learning.

Non-invasive image-based machine learning models have been used to classify subtypes of non-small cell lung cancer (NSCLC). However, the classification performance is limited by the dataset size, because insufficient data cannot fully represent the characteristics of the tumor lesions. In this work, a data augmentation method named elastic deformation is proposed to artificially enlarge the image dataset of NSCLC patients with two subtypes (squamous cell carcinoma and large cell carcinoma) of 3158 images. Elastic deformation effectively expanded the dataset by generating new images, in which tumor lesions go through elastic shape transformation. To evaluate the proposed method, two classification models were trained on the original and augmented dataset, respectively. Using augmented dataset for training significantly increased classification metrics including area under the curve (AUC) values of receiver operating characteristics (ROC) curves, accuracy, sensitivity, specificity, and f1-score, thus improved the NSCLC subtype classification performance. These results suggest that elastic deformation could be an effective data augmentation method for NSCLC tumor lesion images, and building classification models with the help of elastic deformation has the potential to serve for clinical lung cancer diagnosis and treatment design.

ETV6-NTRK3 translocation-associated low-grade mucinous bronchial adenocarcinoma: A novel bronchial salivary gland-type non-small cell lung cancer subtype

IntroductionNTRK fusion genes have been found in several solid tumors, among which NSCLC and sarcoma. Novel NTRK translocation-related tumors are still being discovered. MethodsWe report a 49-year-old patient with a mass in the left lower lung lobe that was resected. This specimen was analyzed and sequenced using targeted DNA next generation sequencing (NGS) and anchored-multiplex-PCR (AMP) targeted RNA NGS. ResultsOn pathological evaluation, a peribronchial mucinous neoplasm with a unique morphology was found. RNA NGS analysis showed anETV6-NTRK3 translocation in a low-grade mucinous bronchial adenocarcinoma. ConclusionsThis entity represents a novel subtype of non-small cell lung cancer, which we would like to term ‘ETV6-NTRK3 translocation-associated low-grade mucinous bronchial adenocarcinoma’.

APOBEC3B deletion polymorphism and lung cancer risk in the southern Chinese population.

BackgroundApproximately 80–85% of lung cancer is the non-small cell lung cancer (NSCLC) subtype, which ranks as the leading cause of cancer deaths worldwide. APOBEC3B (A3B) was reported to be a key source of mutations in NSCLC. However, the role of the A3B deletion polymorphism in the etiology of NSCLC has not been well-documented.MethodsA case-control study with 317 NSCLC patients and 334 healthy controls was conducted to explore the association between the A3B deletion polymorphism and the risk of NSCLC. The unconditional logistic regression model was performed to calculate the odds ratio (OR) and the 95% confidence interval (CI), and the confounding factors were adjusted, including age, gender, and smoking status, to estimate the risk. An analysis of gene-environment interactions was performed using multifactor dimensionality reduction (MDR) software.ResultsWe found that the del/del genotype of A3B deletion significantly increased NSCLC risk. Compared with individuals carrying the ins/ins genotype of A3B deletion, individuals with the del/del genotype had a 2.36 times increased risk of developing NSCLC after adjusting for confounding factors (OR =2.71, 95% CI: 1.67–4.42, P<0.001). A 3-factor gene-environment (A3B deletion, gender, and smoking) interaction model was found for NSCLC (OR =4.407, 95% CI: 1.174–16.549, P=0.028).ConclusionsWe propose that the A3B deletion polymorphism can increase the risk of developing NSCLC, and their interactions with gender and smoking may contribute to the risk of NSCLC in the southern Chinese population.

Living with and beyond metastatic non-small cell lung cancer: the survivorship experience for people treated with immunotherapy or targeted therapy.

Immunotherapy (IT) and targeted therapy (TT) have improved survival for some patients with metastatic non-small cell lung cancer (NSCLC). Their lived experience is under-studied. We conducted a single centre, qualitative study to understand concerns and unmet needs amongst this novel survivor population. Eligible participants had metastatic NSCLC, aged >18, English-speaking and >6 months post initiation of IT/TT without progressive disease. Semi-structured interviews focused on physical, psychological, social and functional impacts of diagnosis, therapy and prognosis. Interviews were recorded and transcribed. Data were analysed via qualitative thematic analysis. Between May and December 2019, 20 participants were interviewed: median age 62 (range 34-83), 13 (65%) female; median time since diagnosis of metastatic NSCLC 27 months (range 10-108). Twelve out of 20 (60%) participants had a targetable mutation (EGFR/ALK/BRAF); 6 were receiving IT, 11 TT, 2 IT + chemotherapy and 1 IT + TT. Four main themes were identified: living long-term on IT and TT (chronic toxicities), psychological concerns (living with uncertainty, fear of cancer progression, scan-related anxiety), support with practical issues (finances, employment amidst prognostic uncertainty, challenges with trial participation) and wanting information pertinent to NSCLC subtype. Longer-term survivors of metastatic NSCLC experience significant physical, psychological and functional concerns and unmet needs. Results will inform a broader cross-sectional survey and resources to address the needs of this growing survivor group. A 'one-size-fits-all' approach to NSCLC survivorship is no longer appropriate. Survivors of metastatic NSCLC treated with novel therapies may benefit from specific information regarding long-term toxicities and psychological supports.

Experience and supportive care needs of metastatic lung cancer survivors living with uncertainty: a brief qualitative report.

Molecularly targeted therapies have revolutionized non-small cell lung cancer (NSCLC) treatment. Many patients with metastatic NSCLC receiving targeted therapy may live several years with incurable cancer. We sought to describe how these metastatic cancer survivors and their caregivers experience uncertainty about the future and identify their unmet supportive care needs. We conducted semi-structured interviews with patients with metastatic NSCLC receiving targeted therapy (n = 39) and their caregivers (n = 16). We used a framework approach to code and analyze the qualitative data. Metastatic lung cancer survivors described awareness of their mortality and the possibility that their cancer could progress at any time. Though some found ways to cope, many felt inadequately supported to manage their distress, especially since they were "doing fine medically." Survivors struggled with decisions about working and managing their finances given their uncertain life expectancy and sought trustworthy lung cancer information in plain language. They wished to compare experiences with other patients with their molecular subtype of NSCLC. Participants desired comprehensive cancer care that includes psychosocial support, preparation for the future, and ways to promote their own health, such as through lifestyle changes. Patients with metastatic NSCLC receiving targeted therapy and their caregivers experience distress related to living with uncertainty and desire more coping support, connection with peers, information, and healthy lifestyle guidance. Patients living with treatable yet incurable cancer and their caregivers are a growing population of cancer survivors. Recognition of their unmet needs may inform the development of tailored support services to help them live well with cancer.

High discrepancy in thrombotic events in non-small cell lung cancer patients with different genomic alterations.

BackgroundAcute complications, such as venous thromboembolism (VTE), are common in patients with advanced severe lung cancers. However, current VTE risk scores cannot adequately identify high-risk patients with non-small cell lung cancer (NSCLC). The study proposed to elucidated the incidence of thromboembolism (TE) in patients with different oncogenic aberrations and the impact of these aberrations on the efficacy of targeted therapy in patients with NSCLC.MethodsA systemic review was conducted in Web of Science, PubMed, Embase and the Cochrane Library to evaluate the incidence of TE in different molecular subtypes of NSCLC. Data from patients diagnosed of advanced NSCLC who harboring anaplastic lymphoma kinase (ALK) or ROS proto-oncogene 1 receptor tyrosine kinase (ROS1) rearrangements since 2016 to 2019 were also retrospectively collected. A meta-analysis with random-effects model, sensitivity analysis and publication bias were performed. The principal summary measure was incidence of thrombotic events in NSCLC patients. And the efficacy of tyrosine kinase inhibitor (TKI) therapy was compared between the two subgroups.ResultsA total of 5,767 cases from 20 studies were included in the analysis of the incidence of thrombosis in patients with different oncogenic alterations. The pooled analysis showed a higher risk of thrombosis in ROS1-fusion types (41%, 95% CI: 35–47%) and ALK-fusion types (30%, 95% CI: 24–37%) than in EGFR-mutation (12%, 95% CI: 8–17%), KRAS-mutation (25%, 95% CI: 13–50%), and wild-type (14%, 95% CI: 10–20%) cases. A high prevalence of thrombosis (ALK: 24.4%; ROS1: 32.6%) was observed in the Shanghai Pulmonary Hospital (SPH) cohort of 224 patients with ALK or ROS1 fusion. Furthermore, patients with embolism had significantly shorter progression-free survival (PFS) after TKI therapy than those without embolism, both in the ALK+ cohort (5.6 vs. 12.9 months, P<0.0001) and in the ROS1+ cohort (9.6 vs. 17.6 months, P=0.0481).ConclusionsNSCLC patients with ALK/ROS1 rearrangements are more likely to develop thrombosis than patients with other oncogenic alterations. Thrombosis may also be associated with an inferior response and PFS after TKI therapy.

P59.07 Molecular Profiling of Human Non-Small Cell Lung Cancer by Single-Cell RNA-Seq

Lung cancer is one of the malignant tumors with the highest morbidity and mortality worldwide. As the lung is a complex organ composed of more than 40 different types of cells, which contribute to the heterogeneity of lung cancers at tumor initiation, it is important to separate different cell types to profile their characteristics. In this study, we aim to comprehensively analyze the molecular heterogeneity of non-small-cell lung cancer (NSCLC). We performed single-cell RNA-seq analyses on 7,364 individual cells from tumor tissues and matched normal tissues from 19 primary lung cancer patients and 1 pulmonary chondroid hamartoma patient. We identified a significant proportion of cancer cells simultaneously expressing classical marker genes for two or three histologic subtypes of NSCLC—adenocarcinoma (ADC), squamous cell carcinoma (SCC), and large cell neuroendocrine carcinoma (LCNEC) in the same individual cell; this was verified by coimmunostaining and RNA in situ hybridization. These data suggest that mixed-lineage tumor cells are highly plastic with mixed features of different types of NSCLC. Both copy number variation (CNV) patterns and mitochondrial mutations clearly showed that the mixed-lineage and single-lineage tumor cells from the same patient had common tumor ancestors rather than different origins. Moreover, we revealed that patients with high mixed-lineage features of different cancer subtypes had worse survival than patients with low mixed-lineage features, indicating that mixed-lineage tumor features were associated with poorer prognosis. Based on the pseudotime trajectory of gene expression dynamics from normal epithelial cells to cancer cells, a cancer-specific gene set has been identified, which includes AKR1B1 and RAMP1. Knockdown experiments verified that both AKR1B1 and RAMP1 were necessary for tumor growth, suggesting that they can serve as candidate targets for tumor therapy. Our work provides novel insights into the heterogeneity of NSCLC and offers clues for the more refined classification, diagnosis and treatment of each subtype.

P11.03 Importance of Capturing the Patient Experience of Overall Symptoms and HRQoL Impact in Patients With ALK+ NSCLC

Non–small cell lung cancer (NSCLC) with the anaplastic lymphoma kinase-positive (ALK+) mutation is a rare subtype of NSCLC. Available treatments include several ALK inhibitor therapies (eg, crizotinib, alectinib, ceritinib, and brigatinib) with some showing health-related quality of life (HRQoL) benefits. HRQoL, including disease- and treatment-related symptoms and impacts, is a significant factor when making treatment decisions. However, qualitative research on HRQoL among ALK+ patients is limited. The aim of this study was to better understand the overall symptom experience and HRQoL impact from the perspective of ALK+ NSCLC patients. Interviews with expert oncologists were conducted to provide the clinical perspective and guide patient interviews. Following approval by an independent review board, semi-structured qualitative interviews were conducted with NSCLC patients with epidermal growth factor receptor or ALK mutations who had been symptomatic in the past month. During interviews, patients described their symptoms and the related HRQoL impact. Six oncologists were interviewed, identifying NSCLC symptoms, particularly: shortness of breath (100%), fatigue (100%), cough (83%), pain (67%), and hemoptysis (67%). The most common impacts were anxiety (50%), depression (50%), and confusion/bewilderment surrounding the diagnosis (50%), as most patients were never smokers and younger. A total of 36 NSCLC patients were interviewed, including 8 ALK+ patients (median age 48.5 years [28–53]; 50% female, median disease duration 2.8 years [0–7]). All ALK+ patients had received radiation, 87.5% had received chemotherapy, and 62.5% had received targeted therapy. The most commonly reported symptoms from ALK+ patients were shortness of breath (100%), phlegm/congestion (100%), pain (87.5%), feeling tired/fatigue (87.5%), weight loss (75%), cough, coughing blood, appetite loss, constipation, and diarrhea (all 62.5%). Patients described experiencing negative impacts on daily activities (87.5%), including household chores and the ability to do hobbies. Additionally, impacts on social, emotional (both 62.5%), and physical functioning (50%) were also commonly reported. The patient experience with the core symptoms of lung cancer (dyspnea, cough, and pain) among ALK+ NSCLC patients was similar across our sample, irrespective of mutation. This qualitative research also confirmed the selection of patient-reported outcome instruments to assess core concepts that best capture the patient experience of ALK+ patients in a clinical trial setting, including a recent clinical trial of brigatinib versus crizotinib in ALK+ NSCLC. In this clinical trial, patients on brigatinib showed significant HRQoL benefits compared with crizotinib in the most common symptoms or impacts reported in the current qualitative study, including fatigue, nausea and vomiting, appetite loss, constipation, as well as emotional, social functioning, and global health status/QoL. Incorporation of the patient voice through direct patient engagement provided valuable in-depth insight about patient experience in ALK+ NSCLC. This qualitative research provided insights into the unmet needs and patient goals for treatment, which may then be measured in a clinical trial to demonstrate treatment benefit from the patient perspective. It is important to measure what matters most to patients to improve treatment decision-making.

Hiltonol Cocktail Kills Lung Cancer Cells by Activating Cancer-Suppressors, PKR/OAS, and Restraining the Tumor Microenvironment.

NSCLC (non-small cell lung cancer) is a leading cause of cancer-related deaths worldwide. Clinical trials showed that Hiltonol, a stable dsRNA representing an advanced form of polyI:C (polyinosinic-polycytidilic acid), is an adjuvant cancer-immunomodulator. However, its mechanisms of action and effect on lung cancer have not been explored pre-clinically. Here, we examined, for the first time, how a novel Hiltonol cocktail kills NSCLC cells. By retrospective analysis of NSCLC patient tissues obtained from the tumor biobank; pre-clinical studies with Hiltonol alone or Hiltonol+++ cocktail [Hiltonol+anti-IL6+AG490 (JAK2 inhibitor)+Stattic (STAT3 inhibitor)]; cytokine analysis; gene knockdown and gain/loss-of-function studies, we uncovered the mechanisms of action of Hiltonol+++. We demonstrated that Hiltonol+++ kills the cancer cells and suppresses the metastatic potential of NSCLC through: (i) upregulation of pro-apoptotic Caspase-9 and Caspase-3, (ii) induction of cytosolic cytochrome c, (iii) modulation of pro-inflammatory cytokines (GRO, MCP-1, IL-8, and IL-6) and anticancer IL-24 in NSCLC subtypes, and (iv) upregulation of tumor suppressors, PKR (protein kinase R) and OAS (2′5′ oligoadenylate synthetase). In silico analysis showed that Lys296 of PKR and Lys66 of OAS interact with Hiltonol. These Lys residues are purportedly involved in the catalytic/signaling activity of the tumor suppressors. Furthermore, knockdown of PKR/OAS abrogated the anticancer action of Hiltonol, provoking survival of cancer cells. Ex vivo analysis of NSCLC patient tissues corroborated that loss of PKR and OAS is associated with cancer advancement. Altogether, our findings unraveled the significance of studying tumor biobank tissues, which suggests PKR and OAS as precision oncological suppressor candidates to be targeted by this novel Hiltonol+++ cocktail which represents a prospective drug for development into a potent and tailored therapy for NSCLC subtypes.

Use of four genes in exosomes as biomarkers for the identification of lung adenocarcinoma and lung squamous cell carcinoma.

The determination of biomarkers in the blood specific for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is crucial for the selection of effective treatment strategies and the prediction of prognosis. The purpose of the present study was to analyze the differentially expressed genes (DEGs) in LUSC and LUAD from The Cancer Genome Atlas (TCGA) database. In order to identify the potential biomarkers for non-small cell lung cancer (NSCLC) for clinical diagnosis, bioinformatics was used to analyze the DEGs of two subtypes of NSCLC, LUAD and LUSC. Exosomes were isolated from the serum of patients with LUAD or LUSC and identified using transmission electron microscopy, nanoparticle tracking analysis and western blot analysis. A total of four differential exosomal mRNAs were selected for validation with serum samples from 70 patients with NSCLC via reverse transcription-quantitative polymerase chain reaction. Receiver operating characteristic curves were established to evaluate the clinical diagnostic value of four DEGs for patients with LUAD and LUSC. The analysis based on TCGA data revealed the DEGs in LUSC and LUAD: A total of 1,619 genes were differentially expressed in patients with LUSC and LUAD. DEGs analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that inflammation-related signaling pathways, such as complement pathways, and multiple autoimmune diseases, such as systemic lupus erythematosus and asthma were mainly enriched in LUAD. The cell cycle, Hippo signaling pathway, Rap1 signaling pathway and Wnt signaling pathway were the main signaling pathways enriched in LUSC. The combination of tumor protein P63 (TP63), keratin 5 (KRT5), CEA cell adhesion molecule 6 (CEACAM6) and surfactant protein B (SFTPB) improved the specificity and sensitivity in the diagnosis of different lung cancer subtypes. Exosomal TP63, KRT5, CEACAM6 and SFTPB mRNAs can thus be used as biomarkers to differentiate between LUSC and LUAD, and may provide a novel strategy for their differential diagnosis and treatment.

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification.

Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs. Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λHU), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT40keV), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements. Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λHU, and CT40keV performed better in the VP (NICVP, λVPHU, and CTVP40keV) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NICVP, λVPHU, and CTVP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NICAP (AUC =0.89) were greater than other parameters. NICAP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility. Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

Machine Learning for Histologic Subtype Classification of Non-Small Cell Lung Cancer: A Retrospective Multicenter Radiomics Study.

BackgroundHistologic phenotype identification of Non-Small Cell Lung Cancer (NSCLC) is essential for treatment planning and prognostic prediction. The prediction model based on radiomics analysis has the potential to quantify tumor phenotypic characteristics non-invasively. However, most existing studies focus on relatively small datasets, which limits the performance and potential clinical applicability of their constructed models.MethodsTo fully explore the impact of different datasets on radiomics studies related to the classification of histological subtypes of NSCLC, we retrospectively collected three datasets from multi-centers and then performed extensive analysis. Each of the three datasets was used as the training dataset separately to build a model and was validated on the remaining two datasets. A model was then developed by merging all the datasets into a large dataset, which was randomly split into a training dataset and a testing dataset. For each model, a total of 788 radiomic features were extracted from the segmented tumor volumes. Then three widely used features selection methods, including minimum Redundancy Maximum Relevance Feature Selection (mRMR), Sequential Forward Selection (SFS), and Least Absolute Shrinkage and Selection Operator (LASSO) were used to select the most important features. Finally, three classification methods, including Logistics Regression (LR), Support Vector Machines (SVM), and Random Forest (RF) were independently evaluated on the selected features to investigate the prediction ability of the radiomics models.ResultsWhen using a single dataset for modeling, the results on the testing set were poor, with AUC values ranging from 0.54 to 0.64. When the merged dataset was used for modeling, the average AUC value in the testing set was 0.78, showing relatively good predictive performance.ConclusionsModels based on radiomics analysis have the potential to classify NSCLC subtypes, but their generalization capabilities should be carefully considered.

LncRNA CBR3-AS1 potentiates Wnt/\u03b2-catenin signaling to regulate lung adenocarcinoma cells proliferation, migration and invasion

BackgroundLong non-coding RNAs (lncRNAs) are pervasively transcribed in genome and emerging as a new player in tumorigenesis due to their functions in transcriptional, posttranscriptional and epigenetic mechanisms of gene regulation. As the most frequent malignancy and the foremost source of cancer mortality, lung cancer is a heterogeneous disorder. The most common type of lung cancer is Non-small cell lung cancer (NSCLC), occupying 85% of the total cases, and the main subtypes of NSCLC include lung adenocarcinoma (LAD), large cell carcinoma (LCC), and lung squamous cell carcinoma (LSCC). Recently, numerous lncRNAs have been reported to be strongly linked to NSCLC. In the present study, we found that a new lncRNA CBR3-AS1 is highly expressed in lung cancer. In addition, we also examined the expression of lncRNA CBR3-AS1 in 60 of LADs, 40 of LCCs and 40 of LSCCs patient samples, finding that CBR3-AS1 was specificity highly expressed in LAD cancer tissues. Mechanically, we discovered that CBR3-AS1 could regulate the proliferation, migration and invasion of LAD cells through targeting Wnt/β-catenin signaling.MethodsReal-time PCR, RNA-pulldown, RIP, western blotting, lentivirus transfection, luciferase reporter assays, cell proliferation assays, colony formation assays, wound healing scratch assays and transwell assays were employed to examine the relationship between lncRNA CBR3-AS1 and its regulation of Wnt/β-catenin signaling in LAD cells.ResultsLncRNA CBR3-AS1 is highly-expressed in LAD and cell lines. LncRNA CBR3-AS1 shows physical association with β-catenin. CBR3-AS1 could facilitate Wnt/β-catenin signaling activation thought promoting nuclear localization of β-catenin. CBR3-AS1 promotes LAD cell proliferation, migration and invasion by targeting Wnt/β-catenin signaling.ConclusionIt can be found that a new functional lncRNA CBR3-AS1 could promote nuclear localization of β-catenin so as to facilitate Wnt/β-catenin signaling activation and regulate the proliferation, migration and invasion of LAD cells.

Molecular characteristics of primary pulmonary lymphoepithelioma-like carcinoma based on integrated genomic analyses

Primary pulmonary lymphoepithelioma-like carcinoma (pLELC) is a rare non-small cell lung cancer (NSCLC) subtype. Clinical features have been described in our previous report, but molecular characteristics remain unclear. Herein, pLELC genomic features were explored. Among 41,574 lung cancers, 128 pLELCs and 162 non-pLELC NSCLCs were enrolled. Programmed cell death ligand 1 (PD-L1) and protein 53 (p53) expression was detected in 47 surgically resected pLELC samples by immunohistochemical assays. Multiomics genomic analyses, including whole-genome sequencing (WGS), RNA whole-transcriptome sequencing (RNA-seq), and Epstein-Barr virus (EBV) integration analyses, were performed on eight frozen pLELC tissues and compared with 50 lung adenocarcinomas (LUADs) and 50 lung squamous cell carcinomas (LUSCs) from The Cancer Genome Atlas (TCGA) and another 26 EBV-positive nasopharynx cancers (EBV+-NPCs). Progression-free survival (PFS) and overall survival (OS) of pLELC patients were better than those of non-pLELC patients. High PD-L1 or p53 expression was associated with extended disease-free survival (DFS). pLELC had 14 frequently mutated genes (FMGs). Somatically mutated genes and enrichment of genetic lesions were found, which differed from observations in LUAD, LUSC, and EBV+-nasopharyngeal carcinoma (NPC). Three tumor-associated genes, zinc finger and BTB domain-containing 16 (ZBTB16), peroxisome proliferator activated receptor gamma (PPARG), and transforming growth factor beta receptor 2 (TGFBR2), were downregulated with copy number variation (CNV) loss. EBV was prone to integrating into intergenic and intronic regions with two upregulated miR-BamH1-A rightward transcripts (BARTs), BART5-3P and BART20-3P. Our findings reveal that pLELC has a distinct genomic signature. Three tumor-associated genes with CNV loss and two miR-BARTs might be involved in pLELC tumorigenesis.

Molecular characterization of lung carcinomas: A study on diagnostic, predictive, and prognostic markers using immunohistochemical analysis at a Tertiary Care Center in Uttarakhand, India.

INTRODUCTION:Focused studies in different geographic regions would delineate the underlying biological differences and molecular alterations in non-small cell lung cancer (NSCLC) worldwide. Previous studies in literature have documented limited characterization by studying a minimal number of biological markers. This study was done to evaluate expression of multiple immunomarkers including diagnostic, prognostic, and predictive markers in NSCLC for its characterization.MATERIALS AND METHODS:This was an observational study conducted on 60 consecutive cases of NSCLC. Immunomarkers comprising of p63, p40, TTF-1, napsin A, B-Raf, c-Met, phospho-AKT (P-AKT), PTEN, anaplastic lymphoma kinase (ALK), epidermal growth factor receptor (EGFR) and K-Ras, synaptophysin, chromogranin and pan-cytokeratin were evaluated on paraffin-embedded tissue sections of NSCLC.RESULTS:Age of patients with NSCLC in our study ranged from 35 to 90 years, and 93.3% of them were chronic smokers. 93.3% of cases presented in late stages (Stages III and IV) and 78% of cases were squamous cell carcinoma (SCC). EGFR positivity was noted in 83.3% of cases. ALK was positive in one case while C-Met and PTEN immunopositivity was noted in only two cases. Ten cases showed positivity for K-Ras and 90% of these were SCC. Ten cases were positive for B-Raf and 80% of these were SCC. 30% of cases showed immunopositivity for P-AKT. None of the molecular markers was found to have statistically significant correlation with clinicopathological parameters.CONCLUSION:SCC is the predominant histological subtype of NSCLC in the region of Uttarakhand, India, with a high proportion of cases harboring EGFR mutation. Variable expression of K-Ras, P-AKT, ALK 1, and PTEN in NSCLC signifies that molecular profile of every case is individualistic and independent. We attribute this to ethnicity, influence of implicated substance or metabolite in tobacco, and variable mutations incurred in tumor cells over a period of time.

Roles of Lipid Profiles in Human Non-Small Cell Lung Cancer.

Aims: This review aims to identify lipid biomarkers of non-small cell lung cancer (NSCLC) in human tissue samples and discuss the roles of lipids in tissue molecular identification, the discovery of potential biomarkers, and surgical margin assessment. Methods: A review of the literature focused on lipid-related research using mass spectrometry (MS) techniques in human NSCLC tissues from January 1, 2015, to November 20, 2020, was conducted. The quality of included studies was assessed using the QUADAS-2 tool. Results: Twelve studies met the inclusion criteria and were included in the review. The risk of bias was unclear in the majority of the studies. The contents of lipids including fatty acids, phosphatidyl choline, phosphatidyl ethanolamine, phosphatidyl inositol, cardiolipin, phosphatidyl serine, phosphatidyl glycerol, ceramide, lysophosphatidylethanolamine, lysophosphatidylcholine, and lysophosphatidylglycerol differed significantly between cancer and healthy tissues. The sensitivity or specificity of the discrimination model was reported in 8 studies, and the sensitivity and specificity varied among the reported methods. The lipid profiles differed between adenocarcinoma and squamous cell carcinoma NSCLC subtypes. Conclusion: In preclinical studies, MS analysis and multiple discrimination models can be combined to distinguish NSCLC tissues from healthy tissues based on lipid profiles, which provides a new opportunity to evaluate the surgical margin and cancer subtype intraoperatively. Future studies should provide guidance for selecting patients and discrimination models to develop an improved method for clinical application.