Is histological confirmation necessary to avoid futile resections? Comparative of 4 university hospitals.

OBJECTIVES: There is no consensus in the literature on preoperative histological analysis for lung cancer. The objective of this study was to assess 4 diagnostic models used in different hospitals with differing practices regarding preoperative histological diagnosis and the consequences in terms of unnecessary surgery and futile major resection. METHODS: We carried out a retrospective observational study collected from 4 university hospitals in Spain over 3 years (January 2019 to December 2021). We included all patients with a confirmed diagnosis of primary lung cancer and any patients with suspected primary lung cancer who had undergone surgery. All patients underwent computed tomography and positron emission tomography/computed tomography scans. Each multidisciplinary committee was free to choose whether to perform flexible bronchoscopic or transthoracic lung biopsy. Decisions concerning whether to perform intraoperative sample analysis, the surgical approach and the type of resection were left to the surgical team. RESULTS: We included a total of 1642 patients. The use of flexible endoscopy and its diagnostic performance varied substantially between hospitals (range: 23.8-79.3% and 25-60.7%, respectively); and the same was observed for transthoracic biopsy and its performance (range: 16.9-82.3% and 64.6-97%, respectively). Regarding major resection surgery (lobectomy or more extensive resection), the lowest rate was observed in hospital C (1%) and the highest in hospital B (2.8%), with between-hospital differences not reaching significance (P = 0.173). CONCLUSIONS: The rate of histological sampling before lung cancer surgery still varies between hospitals. In spite of very diverse multidisciplinary management, the rate of futile lobectomy is not significantly higher in hospitals with lower rates of preoperative histological analysis.

Fusion of laser-induced breakdown spectroscopy technology and deep learning: a new method to identify malignant and benign lung tumors with high accuracy.

Precisely distinguishing between malignant and benign lung tumors is pivotal for suggesting therapeutic strategies and enhancing prognosis, yet this differentiation remains a daunting task. The growth rates, metastatic potentials, and prognoses of benign and malignant tumors differ significantly. Developing specialized treatment protocols tailored to various tumor types is essential for enhancing patient survival outcomes. Employing laser-induced breakdown spectroscopy (LIBS) in conjunction with a deep learning methodology, we attained a high-precision differential diagnosis of malignant and benign lung tumors. First, LIBS spectra of malignant tumors, benign tumors, and normal tissues were collected. The spectra were preprocessed and Z score normalized. Then, the intensities of the Mg II 279.6, Mg I 285.2, Ca II 393.4, Cu II 518.3, and Na I 589.6 nm lines were analyzed in the spectra of the three tissues. The analytical results show that the elemental lines have different contents in the three tissues and can be used as a basis for distinguishing between the three tissues. Finally, the RF-1D ResNet model was constructed by combining the feature importance assessment method of random forest (RF) and one-dimensional residual network (1D ResNet). The classification accuracy, precision, sensitivity, and specificity of the RF-1D ResNet model were 91.1%, 91.6%, 91.3%, and 91.3%, respectively. And the model demonstrates superior performance with an area under the curve (AUC) value of 0.99. The above results show that combining LIBS with deep learning is an effective way to diagnose malignant and benign tumors.

Recent Progress and Challenges in Clinical Translation of Nanomedicines in Diagnosis and Treatment of Lung Cancer.

Lung cancer is one of the leading causes of death across the world. There are numerous challenges in the early diagnosis and effective treatment of lung cancer, including developing multidrug resistance. However, the diagnosis of lung cancer could be minimally invasive or non-invasive. Nowadays, nanomedicines offer solutions to several emerging challenges in drug delivery research areas. It has the potential to enhance the therapeutic efficacy of biologically and chemically active agents at the site of action. This approach can also be employed in molecular and cellular imaging, precise and early detection, screening, and targeting drugs for lung cancer treatment. A proper understanding of the disease and timely diagnosis using strategically designed effective nanocarriers can be a promising approach to effectively managing cancer. The present review explores issues related to lung cancer chemotherapy and the promises and hurdles of newer approaches like nanomedicine. The article also summarizes the preclinical studies on diagnosis and treatment, pitfalls, and challenges in the clinical translation of nanomedicines for lung cancer therapy.

DNA image cytometry of bronchial washing as a diagnostic adjunct to radial endobronchial ultrasound-guided sampling of peripheral lung lesions: A single center prospective study.

OBJECTIVE: The objective of this study is to study the adjunct role of combining DNA aneuploidy analysis with radial endobronchial ultrasound (R-EBUS)-guided sampling for diagnosis of peripheral lung lesions (PPLs). METHOD: A single-center prospective study was conducted in patients undergoing R-EBUS-guided sampling for PPLs. DNA image cytometry (DNA-ICM) was used to analyze DNA aneuploidy in bronchial washing from the bronchial segment of the PPL. Clinical information, R-EBUS data, pathology, DNA-ICM results, and follow-up data were analyzed. Sensitivity, specificity, and predictive values for R-EBUS-guided sampling, DNA-ICM, and the two methods combined were measured. Binary logistic regression was performed to determine influencing factors on diagnostic positivity rate. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff point for DNA-ICM. RESULTS: A total of 101 patients were enrolled. Sixty-four (63.4%) patients had confirmed malignant tumor, of whom 33 were confirmed by R-EBUS-guided sampling (biopsy and/or bronchial brush and wash cytology), and 31 by surgery or percutaneous lung biopsy. Thirty-seven patients were finally considered to have benign lesions, based on clinical information and 1-year follow-up. The sensitivity for malignant disease was 51.6% by R-EBUS, and specificity was 100%. DNA-ICM had a sensitivity of 67.2% and a specificity of 86.5%. When combining the two methods, sensitivity increased to 78.1% and specificity was 86.5%. Lesion size and whether the R-EBUS probe was located in the lesion were significantly associated with positivity rate of the combined methods. The optimal cutoff point for DNA-ICM was 5c for max DNA content, and 1 for aneuploid cell count (sensitivity 67.2%, specificity 86.5%, accuracy 63.4%). CONCLUSION: In malignant PPLs, DNA-ICM combined with R-EBUS-guided sampling can improve diagnostic positivity compared with either method alone.

Utility of needle biopsy in centrally located lung cancer for genome analysis: a retrospective cohort study.

BACKGROUND: It is essential to collect a sufficient amount of tumor tissue for successful next-generation sequencing (NGS) analysis. In this study, we investigated the clinical risk factors for avoiding re-biopsy for NGS analysis (re-genome biopsy) in cases where a sufficient amount of tumor tissue could not be collected by bronchoscopy. METHODS: We investigated the association between clinical factors and the risk of re-genome biopsy in patients who underwent transbronchial biopsy (TBB) or endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and required re-genome biopsy in cases enrolled in LC-SCRUM Asia, a prospective nationwide genome screening project in Japan. We also examined whether the frequency of re-genome biopsy decreased between the first and second halves of the enrolment period. RESULTS: Of the 572 eligible patients, 236 underwent TBB, and 134 underwent EBUS-TBNA. Twenty-four TBBs required re-genome biopsy, and multivariate analysis showed that the risk of re-genome biopsy was significantly increased in lesions where the tumor lesion was centrally located. In these cases, EBUS-TBNA should be utilized even if the lesion is a pulmonary lesion. However, it should be noted that even with EBUS-TBNA, lung field lesions are at a higher risk of re-canalization than mediastinal lymph node lesions. It was also found that even when tumor cells were detected in rapid on-site evaluation, a sufficient amount of tumor tissue was not always collected. CONCLUSIONS: For centrally located pulmonary mass lesions, EBUS-TBNA, rather than TBB, can be used to obtain tumor tissues that can be analyzed by NGS.

Liquid biopsy in non-small cell lung cancer: a meta-analysis of state-of-the-art and future perspectives.

Introduction: To date, tissue biopsy represents the gold standard for characterizing non-small-cell lung cancer (NSCLC), however, the complex architecture of the disease has introduced the need for new investigative approaches, such as liquid biopsy. Indeed, DNA analyzed in liquid biopsy is much more representative of tumour heterogeneity. Materials and methods: We performed a meta-analysis of 17 selected papers, to attest to the diagnostic performance of liquid biopsy in identifying EGFR mutations in NSCLC. Results: In the overall studies, we found a sensitivity of 0.59, specificity of 0.96 and diagnostic odds ratio of 24,69. Since we noticed a high heterogeneity among different papers, we also performed the meta-analysis in separate subsets of papers, divided by 1) stage of disease, 2) experimental design and 3) method of mutation detection. Liquid biopsy has the highest sensitivity/specificity in high-stage tumours, and prospective studies are more reliable than retrospective ones in terms of sensitivity and specificity, both NGS and PCR-based techniques can be used to detect tumour DNA in liquid biopsy. Discussion: Overall, liquid biopsy has the potential to help the management of NSCLC, but at present the non-homogeneous literature data, lack of optimal detection methods, together with relatively high costs make its applicability in routine diagnostics still challenging.

Lung Cancer Cell-Derived Exosome Detection Using Electrochemical Approach towards Early Cancer Screening.

Lung cancer is one of the deadliest cancers worldwide due to the inability of existing methods for early diagnosis. Tumor-derived exosomes are nano-scale vesicles released from tumor cells to the extracellular environment, and their investigation can be very useful in both biomarkers for early cancer screening and treatment assessment. This research detected the exosomes via an ultrasensitive electrochemical biosensor containing gold nano-islands (Au-NIs) structures. This way, a high surface-area-to-volume ratio of nanostructures was embellished on the FTO electrodes to increase the chance of immobilizing the CD-151 antibody. In this way, a layer of gold was first deposited on the electrode by physical vapor deposition (PVD), followed by thermal annealing to construct primary gold seeds on the surface of the electrode. Then, gold seeds were grown by electrochemical deposition through gold salt. The cell-derived exosomes were successfully immobilized on the FTO electrode through the CD-151 antibody, and cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) methods were used in this research. In the CV method, the change in the current passing through the working electrode is measured so that the connection of exosomes causes the current to decrease. In the EIS method, surface resistance changes were investigated so that the binding of exosomes increased the surface resistance. Various concentrations of exosomes in both cell culture and blood serum samples were measured to test the sensitivity of the biosensor, which makes our biosensor capable of detecting 20 exosomes per milliliter.

Combined Methylation of SHOX2 and RASSF1A Genes in Diagnosing Malignant Pleural Effusion.

BACKGROUND: It is a significant challenge to identify pleural effusion (PE) through differential diagnosis in clinical settings. The present study endeavors to devise a strategy to differentiate between malignant pleural effusion (MPE) and benign pleural effusion (BPE) by detecting gene methylation. METHODS: This study recruited 214 patients with PE, among which 104 patients were identified with MPE, while the remaining 110 patients were categorized as having BPE. The methylation levels of short stature homeobox 2 (SHOX2) and RAS association domain family 1, isoform A (RASSF1A) genes were analyzed through methylation-specific polymerase chain reaction (MS-PCR). RESULTS: The methylation status of either SHOX2 or RASSF1A genes was significantly elevated in MPE compared to BPE. The sensitivity and specificity of SHOX2 and RASSF1A methylation in diagnosing PE were 66.3% and 90.9%, respectively. The sensitivity of the combined methylation detection intended to diagnose pulmonary MPE was 73.5% and 52.8% in non-pulmonary MPE (p < 0.05), suggesting that combined detection of SHOX2 and RASSF1A methylation had high diagnostic value for lung cancer. In comparison to the results of cytology and DNA ploidy detection, methylation detection demonstrated a superior diagnostic efficiency in the diagnosis of lung cancer (p < 0.05). Additionally, the combined detection of SHOX2 and RASSF1A methylation was more potent in diagnosing BPE and MPE (p < 0.05), while compensating for the limitations of cytology and DNA ploidy detection. CONCLUSIONS: The detection of SHOX2 and RASSF1A methylation can effectively differentiate between BPE and MPE, especially in diagnosing pulmonary MPE.

Conducting polymer composite-based biosensing materials for the diagnosis of lung cancer: A review.

The development of a simple and fast cancer detection method is crucial since early diagnosis is a key factor in increasing survival rates for lung cancer patients. Among several diagnosis methods, the electrochemical sensor is the most promising one due to its outstanding performance, portability, real-time analysis, robustness, amenability, and cost-effectiveness. Conducting polymer (CP) composites have been frequently used to fabricate a robust sensor device, owing to their excellent physical and electrochemical properties as well as biocompatibility with nontoxic effects on the biological system. This review brings up a brief overview of the importance of electrochemical biosensors for the early detection of lung cancer, with a detailed discussion on the design and development of CP composite materials for biosensor applications. The review covers the electrochemical sensing of numerous lung cancer markers employing composite electrodes based on the conducting polyterthiophene, poly(3,4-ethylenedioxythiophene), polyaniline, polypyrrole, molecularly imprinted polymers, and others. In addition, a hybrid of the electrochemical biosensors and other techniques was highlighted. The outlook was also briefly discussed for the development of CP composite-based electrochemical biosensors for POC diagnostic devices.

Accurate and Convenient Lung Cancer Diagnosis through Detection of Extracellular Vesicle Membrane Proteins via Förster Resonance Energy Transfer.

Tumor-derived extracellular vesicles (EVs) are promising to monitor early stage cancer. Unfortunately, isolating and analyzing EVs from a patient's liquid biopsy are challenging. For this, we devised an EV membrane proteins detection system (EV-MPDS) based on Förster resonance energy transfer (FRET) signals between aptamer quantum dots and AIEgen dye, which eliminated the EV extraction and purification to conveniently diagnose lung cancer. In a cohort of 80 clinical samples, this system showed enhanced accuracy (100% versus 65%) and sensitivity (100% versus 55%) in cancer diagnosis as compared to the ELISA detection method. Improved accuracy of early screening (from 96.4% to 100%) was achieved by comprehensively profiling five biomarkers using a machine learning analysis system. FRET-based tumor EV-MPDS is thus an isolation-free, low-volume (1 µL), and highly accurate approach, providing the potential to aid lung cancer diagnosis and early screening.

Molecular modeling and simulation of transition metal-doped molybdenum disulfide biomarkers in exhaled gases for early detection of lung cancer.

BACKGROUND: The presence of volatile organic compounds (VOCs) in the exhaled breath of lung cancer patients is the only available source for detecting the disease at its initial stage. Exhaled breath analysis depends purely on the performance of the biosensors. The interaction between VOCs and pristine MoS2 is repulsive in nature. Therefore, modifying MoS2 via surficial adsorption of the transition metal nickel is of prime importance. The surficial interaction of six VOCs with Ni-doped MoS2 led to substantial variations in the structural and optoelectronic properties compared to those of the pristine monolayer. The remarkable improvement in the conductivity, thermostability, good sensing response, and recovery time of the sensor exposed to six VOCs revealed that a Ni-doped MoS2 exhibits impressive properties for the detection of exhaled gases. Different temperatures have a significant impact on the recovery time. Humidity has no effect on the detection of exhaled gases upon exposure to VOCs. The obtained results may encourage the use of exhaled breath sensors by experimentalists and oncologists to enable potential advancements in lung cancer detection. METHODS: The surface adsorption of transition metal and its interaction with volatile organic compounds on a MoS2 surface was studied by using Spanish Initiative for Electronic Simulations with Thousands of Atoms (SIESTA). The pseudopotentials used in the SIESTA calculations are norm-conserving in their fully nonlocal forms. The atomic orbitals with finite support were used as a basis set, allowing unlimited multiple-zeta and angular momenta, polarization, and off-site orbitals. These basis sets are the key for calculating the Hamiltonian and overlap matrices in O(N) operations. The present hybrid density functional theory (DFT) is a combination of PW92 and RPBE methods. Additionally, the DFT+U approach was employed to accurately ascertain the coulombic repulsion in the transition elements.

Promising Mass-Productive 4-Inch Commercial SERS Sensor with Particle in Micro-Nano Porous Ag/Si/Ag Structure Using in Auxiliary Diagnosis of Early Lung Cancer.

The construction of commercial surface enhanced Raman scattering (SERS) sensors suitable for clinical applications is a pending problem, which is heavily limited by the low production of high-performance SERS bases, because they usually require fine or complicated micro/nano structures. To solve this issue, herein, a promising mass-productive 4-inch ultrasensitive SERS substrate available for early lung cancer diagnosis is proposed, which is designed with a special architecture of particle in micro-nano porous structure. Benefitting from the effective cascaded electric field coupling inside the particle-in-cavity structure and efficient Knudsen diffusion of molecules within the nanohole, the substrate exhibits remarkable SERS performance for gaseous malignancy biomarker, with the limit of detection is 0.1 ppb and the average relative standard deviation value at different scales (from cm2 to µm2 ) is ≈16.5%. In practical application, this large-sized sensor can be further divided into small ones (1 × 1 cm2 ), and more than 65 chips will be obtained from just one 4-inch wafer, greatly increasing the output of commercial SERS sensor. Further, a medical breath bag composed of this small chip is designed and studied in detail here, which suggested high-specificity recognition for lung cancer biomarker in mixed mimetic exhalation tests.

Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective.

Lung cancer is one of the malignant tumors with the highest incidence and mortality in the world. The overall five-year survival rate of lung cancer is relatively lower than many leading cancers. Early diagnosis and prognosis of lung cancer are essential to improve the patient's survival rate. With artificial intelligence (AI) approaches widely applied in lung cancer, early diagnosis and prediction have achieved excellent performance in recent years. This review summarizes various types of AI algorithm applications in lung cancer, including natural language processing (NLP), machine learning and deep learning, and reinforcement learning. In addition, we provides evidence regarding the application of AI in lung cancer diagnostic and clinical prognosis. This review aims to elucidate the value of AI in lung cancer diagnosis and prognosis as the novel screening decision-making for the precise treatment of lung cancer patients.

Multiarray Biosensor for Diagnosing Lung Cancer Based on Gap Plasmonic Color Films.

Adaptable and sensitive materials are essential for the development of advanced sensor systems such as bio and chemical sensors. Biomaterials can be used to develop multifunctional biosensor applications using genetic engineering. In particular, a plasmonic sensor system using a coupled film nanostructure with tunable gap sizes is a potential candidate in optical sensors because of its simple fabrication, stability, extensive tuning range, and sensitivity to small changes. Although this system has shown a good ability to eliminate humidity as an interferant, its performance in real-world environments is limited by low selectivity. To overcome these issues, we demonstrated the rapid response of gap plasmonic color sensors by utilizing metal nanostructures combined with genetically engineered M13 bacteriophages to detect volatile organic compounds (VOCs) and diagnose lung cancer from breath samples. The M13 bacteriophage was chosen as a recognition element because the structural protein capsid can readily be modified to target the desired analyte. Consequently, the VOCs from various functional groups were distinguished by using a multiarray biosensor based on a gap plasmonic color film observed by hierarchical cluster analysis. Furthermore, the lung cancer breath samples collected from 70 healthy participants and 50 lung cancer patients were successfully classified with a high rate of over 89% through supporting machine learning analysis.

Research progress regarding long-chain non-coding RNA in lung cancer: a narrative review.

Background and Objective: Lung cancer is the main cause of cancer-related death worldwide, and its incidence rate is high. Traditional methods of lung cancer screening, such as those based on X-ray, low-dose computed tomography (LDCT), positron emission computed tomography (PET/CT), electronic bronchoscopy, and serum tumor markers were not satisfied with the urgent need in improving the patient survival rate. Thus, biomarkers for early diagnosis and prognosis of lung cancer are extremely needed. Studies have identified a variety of long-chain non-coding RNAs (lncRNAs) that are expressed at abnormal levels in patients with lung cancer which was believed as a potential biomarker for the diagnosis and prognostic evaluation of lung cancer. This review aims to discuss the role of lncRNAs in non-small cell lung cancer (NSCLC), so as to provide insights into the prognosis of lung cancer. Methods: We searched PubMed database of the related scientific researches with outcomes from 09/16/2011 to 05/02/2022 focusing on lncRNA application in lung cancer via searching terms of "lncRNA AND lung cancer", "lncRNA AND non-small cell lung cancer", "lncRNA AND drug resistance", "lncRNA AND radio sensitivity". Published articles written in English available to readers were considered. Key Content and Findings: We summarized significantly differentially-expressed lncRNAs in lung cancer tissues compared with healthy individuals and normal tissues which would become potential biomarkers for lung cancer diagnosis and therapeutic target as a non-invasive detection method. Conclusions: LncRNAs might be valuable potential diagnostic biomarkers of lung cancer progression.

Blood protein biomarkers in lung cancer.

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

Racial difference in BMI and lung cancer diagnosis: analysis of the National Lung Screening Trial.

BACKGROUND: The inverse relationship between BMI and lung cancer diagnosis is well defined. However, few studies have examined the racial differences in these relationships. The purpose of this paper is to explore the relationships amongst race, BMI, and lung cancer diagnosis using the National Lung Screening Trial (NLST) data. METHODS: Multivariate regression analysis was used to analyze the BMI, race, and lung cancer diagnosis relationships. RESULTS: Among 53,452 participants in the NLST cohort, 3.9% were diagnosed with lung cancer, 43% were overweight, and 28% were obese. BMI was inversely related to lung cancer diagnosis among Whites: those overweight (aOR = .83, 95%CI = .75-.93), obese (aOR = .64, 95%CI = .56-.73) were less likely to develop lung cancer, compared to those with normal weight. These relationships were not found among African-Americans. CONCLUSION: Our findings indicate that the inverse relationship of BMI and lung cancer risk among Whites is consistent, whereas this relationship is not significant for African-Americans. In consideration of higher lung cancer incidence among African Americans, we need to explore other unknown mechanisms explaining this racial difference.

Handling and standardization of EBUS needle aspiration in NSCLC patients: The value of the cell block, a monoinstitutional experience.

BACKGROUND: Lung cancer is the main cause of cancer-related death worldwide, and 85% of all lung tumors are non-small cell lung cancers (NSCLC). More than 60% of all lung tumors are diagnosed at an advanced stage, leading to poor prognosis. Given the growing demand for NSCLC profiling for selection of the most appropriate therapy, the acquisition of adequate tumor samples has become increasingly crucial, mostly in advanced NSCLC patients due to old age and/or comorbidities. Being a mini-invasive sampling technique, endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) represents a valuable alternative to traditional transthoracic or surgical sampling in these patients, and perfoming cell block (CB) could be crucial to maximize the potential biological information. The aim of this study is to describe a monoinstitutional interprofessional experience in handling EBUS-TBNA and CB in 464 patients. METHODS: We retrospectively collected all the consecutive CBs obtained from EBUS TBNA performed between 2014 and 2021 on the lung lesions or mediastinal lymph nodes. All the CBs were handled in a standardized method. RESULTS: A total of 95.5% (448/464 samples) of adequacy for site and 92.6% (430/464) of adequacy for diagnosis were observed. Moreover, in the adenocarcinoma histotype, ALK, ROS1 and tumor proportion score (TPS) PD-L1 assessment by IHC was possible in 96% (140/146) of cases, and molecular profile was obtained in 93.8% (137/146) of cases. In the squamous cell carcinoma histotype, TPS PD-L1 assessment was possible in 81% (13/16) of cases. All four CB results obtained from carcinoma NOS were adequate for ALK, ROS1 and PD-L1 assessment and molecular profiling. All 39 metastatic samples from extra-pulmonary primary were adequate for immunohistochemical characterization and molecular profiling. Finally, reporting of the tumor sample adequacy to the clinicians took a median time of about 30 h (range: 24-80 h). CONCLUSION: Careful cytological smear management together with the handling and standardization of CB obtained from EBUS-TBNA could represent an effective method to increase the adequacy of the tumor specimen for both diagnosis and molecular profile.

Watch the Mime Carefully! A Refractory Interstitial Lung Disease.

Epithelioid hemangioendothelioma (EHE) is a rare neoplasm of a vascular origin which can arise in different locations such as the lungs, liver, soft tissue, and rarely, in the bones. In the lungs, pulmonary hemangioendothelioma (PEH) shows a variable clinical behavior, displaying a range from either an asymptomatic course to a highly aggressive progression with metastases. Based on radiological features, PEH differential diagnosis mainly includes primary or metastatic lymphangitic carcinomatosis, granulomatous infections, and diffuse interstitial lung diseases where ground glass pattern predominates. In this case, a transbronchial biopsy and subsequent histological and immunohistochemical analysis allowed for the attribution of the scenario to a pulmonary epithelioid hemangioendothelioma. Clinicians should always consider bronchoscopy as a useful and effective tool to better investigate indeterminate and questionable clinical pictures, sparing patients the morbidity and mortality associated with more invasive techniques such as surgical or thoracoscopic biopsy.

Analysis of the lncRNA-miRNA-mRNA Network Reveals a Potential Regulatory Mechanism of EGFR-TKI Resistance in NSCLC.

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are widely used for patients with EGFR-mutated lung cancer. Despite its initial therapeutic efficacy, most patients eventually develop drug resistance, which leads to a poor prognosis in lung cancer patients. Previous investigations have proved that non-coding RNAs including long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs) contribute to drug resistance by various biological functions, whereas how they regulate EGFR-TKI resistance remains unclear. In this study, we examined gene expression using the microarray technology on gefitinib-resistant NSCLC cells to obtain differentially expressed (DE) lncRNAs and mRNAs. A total of 45 DE-lncRNAs associated with overall survival and 1799 target DE-mRNAs were employed to construct a core lncRNA-miRNA-mRNA network to illustrate underlying molecular mechanisms of how EGFR-TKI resistance occurs in NSCLC. We found that target DE-mRNAs were mainly enriched in pathways involved in EGFR-TKI resistance, especially the target DE-mRNAs regulated by LINC01128 were significantly enriched in the PI3K/Akt signaling pathway, where the synergy of these target DE-mRNAs may play a key role in EGFR-TKI resistance. In addition, downregulated LINC01128, acting as a specific miRNA sponge, decreases PTEN via sponging miR-25-3p. Furthermore, signaling reactions caused by the downregulation of PTEN would activate the PI3K/Akt signaling pathway, which may lead to EGFR-TKI resistance. In addition, a survival analysis indicated the low expression of LINC01128, and PTEN is closely related to poor prognosis in lung adenocarcinoma (LUAD). Therefore, the LINC01128/miR-25-3p/PTEN axis may promote EGFR-TKI resistance via the PI3K/Akt signaling pathway, which provides new insights into the underlying molecular mechanisms of drug resistance to EGFR-TKIs in NSCLC. In addition, our study sheds light on developing novel therapeutic approaches to overcome EGFR-TKI resistance in NSCLC.