Amyloid-beta pathology-induced nanoscale synaptic disruption:the case of the GABA_B-GIRK assembly

Alzheimer's disease (AD) is characterized by an imbalance between excitatory and inhibitory brain networks,leading to aberrant homeostatic synaptic plasticity.AD has progressively been recognized as syna ptopathy and syna ptic dysfunction has been identified as a key component of its pathogenesis (Schirinzi et al.,2020).Syna ptic dysfunction is believed to precede synapse loss,a primary biological correlate of cognitive decline in AD,inevita bly associated with neuronal death.

NLRP3-mediated autophagy dysfunction links gut microbiota dysbiosis to tau pathology in chronic sleep deprivation

Emerging evidence indicates that sleep deprivation(SD)can lead to Alzheimer’s disease(AD)-related pathological changes and cognitive decline.However,the underlying mechanisms remain obscure.In the present study,we identified the existence of a microbiota-gut-brain axis in cognitive deficits resulting from chronic SD and revealed a potential pathway by which gut microbiota affects cognitive functioning in chronic SD.Our findings demonstrated that chronic SD in mice not only led to cognitive decline but also induced gut microbiota dysbiosis,elevated NLRP3 inflammasome expression,GSK-3βactivation,autophagy dysfunction,and tau hyperphosphorylation in the hippocampus.Colonization with the“SD microbiota”replicated the pathological and behavioral abnormalities observed in chronic sleep-deprived mice.Remarkably,both the deletion of NLRP3 in NLRP3-/-mice and specific knockdown of NLRP3 in the hippocampus restored autophagic flux,suppressed tau hyperphosphorylation,and ameliorated cognitive deficits induced by chronic SD,while GSK-3βactivity was not regulated by the NLRP3 inflammasome in chronic SD.Notably,deletion of NLRP3 reversed NLRP3 inflammasome activation,autophagy deficits,and tau hyperphosphorylation induced by GSK-3βactivation in primary hippocampal neurons,suggesting that GSK-3β,as a regulator of NLRP3-mediated autophagy dysfunction,plays a significant role in promoting tau hyperphosphorylation.Thus,gut microbiota dysbiosis was identified as a contributor to chronic SD-induced tau pathology via NLRP3-mediated autophagy dysfunction,ultimately leading to cognitive deficits.Overall,these findings highlight GSK-3βas a regulator of NLRP3-mediated autophagy dysfunction,playing a critical role in promoting tau hyperphosphorylation.

The Use of CT Perfusion to Determine Microvessel Density in Lung Cancer: Comparison with FDG-PET and Pathology

Objective： To investigate the validity of CT perfusion in assessing angiogenic activity of lung cancer. Methods： Fifty-six patients with lung cancer scheduled for elective surgical resection received 16-slice helical CT perfusion imaging. Time-density curve （TDC）, blood flow （BF）, blood volume （BV）, mean transmit time （MTT） and permeability surface area product （PS） were calculated. 18F-deoxyglucose-positron emission tomography （FGD-PET） was carried out in 14 out of the 56 patients to calculate standardized uptake values （SUVs）. Tumor microvessel density （MVD） was examined using CD34 immunohistochemical staining of the resected tumor tissue. Pearson’s correlation analysis was used to evaluate potential correlation between CT perfusion parameters and MVD or SUV. Results： Average time to peak height （TPH） of the TDCs （including two types of TDC） was 24.38±5.69 seconds. Average BF, BV, MTT and PS were 93.42±53.45 ml/100g/min,93.42±53.45 ml/100g,6.83±4.51 s and 31.92±18.73 ml/100g/min, respectively. Average MVD was 62.04±29.06/HPF. The mean SUV was 6.33±3.26. BF was positively correlated with MVD （r=0.620,P0.01） and SUV （r=0.891, P0.01）. PS was also positively correlated with SUV （r=0.720, P0.05）. A positive correlation was also observed between tumor MVD and SUV （r=0.915, P0.01）. Conclusions： CT perfusion imaging is a reliable tool to evaluate the tumor neovascularity of lung cancer.

Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts

Odontogenic keratocyst(OKC)is a common jaw cyst with a high recurrence rate.OKC combined with basal cell carcinoma as well as skeletal and other developmental abnormalities is thought to be associated with Gorlin syndrome.Moreover,OKC needs to be differentiated from orthokeratinized odontogenic cyst and other jaw cysts.Because of the different prognosis,differential diagnosis of several cysts can contribute to clinical management.We collected 519 cases,comprising a total of 2157 hematoxylin and eosinstained images,to develop digital pathology-based artificial intelligence(AI)models for the diagnosis and prognosis of OKC.The Inception_v3 neural network was utilized to train and test models developed from patch-level images.Finally,whole slide imagelevel AI models were developed by integrating deep learning-generated pathology features with several machine learning algorithms.The AI models showed great performance in the diagnosis(AUC=0.935,95%CI:0.898–0.973)and prognosis(AUC=0.840,95%CI:0.751–0.930)of OKC.The advantages of multiple slides model for integrating of histopathological information are demonstrated through a comparison with the single slide model.Furthermore,the study investigates the correlation between AI features generated by deep learning and pathological findings,highlighting the interpretative potential of AI models in the pathology.Here,we have developed the robust diagnostic and prognostic models for OKC.The AI model that is based on digital pathology shows promise potential for applications in odontogenic diseases of the jaw.

Going straight for the gut:gut-brain axis pathology and treatment of Parkinson's disease

This perspective focuses on the recent literature regarding the role of the gut-brain axis(GBA) in fecal microbiota transplantation(FMT) and stem cell therapy(SCT) in Parkinson's disease(PD).PD is the second most common neurodegenerative disease in the United States,yet therapies remain limited.Current research suggests that the GBA may play a role in the pathogenesis of PD.GBAbased FMT as well as SCT offer promising new avenues for PD treatment.Pro bing the interactions between FMT and SCT with the GBA may reveal novel therapeutics for PD.

Hysterectomies for Gynaecological Pathology: 56 Cases at the Segou Regional Hospital in Mali

Introduction: Hysterectomy is a surgical procedure involving partial or total removal of the uterus. It is the most common gynaecological surgery in the world. Objective: To describe the epidemio-clinical and prognostic aspects of gynaecological hysterectomies. Patients and methods: This was an 18-month retrospective prospective descriptive study with a six-month follow-up period from 1 December 2020 to 31 May 2022 carried out in the gynaecology department of the Segou regional hospital. Results: Fifty-six (56) hysterectomies were performed out of 118 gynaecological surgical procedures (47.45%). The mean age was 47 ± 11.77 years. Large multiparous women were the most common (50%), with an average parity of 4.58. The main indications were uterine fibroids (30.4%), precancerous lesions of the cervix (17.85%) and uterine prolapse (17.85%). The abdominal route was the most commonly used surgical route (82.14%). Hysterectomy was total in 100% of cases and associated with bilateral adnexectomy in 48.2% of cases. The intra- and post-operative prognosis was satisfactory in 94.6% of cases. No deaths were recorded. The average length of stay was 3.28 days, irrespective of the surgical approach. Three cases of dyspareunia were noted among those who had resumed sexual activity.

Sarin Induced Lung Pathology and Protection by Standard Therapy Regime

The effects of atropine, diazepam and pralidoxime were studied for their ability to block the pathological lesions induced by sarin. Rats were exposed to an aerosol of sarin at a concentration of 51.2mg-m for 15 min following the pretreatment with one of the following combinations: atropine (10 mg/kg, i.m.) and diazepam (0.5 mg/kg, i.m.); atropine and pralidoxime (25 mg/kg, i.m.); diazepam and pralidoxime; atropine, diazepam and pralidoxime. Lung exposed to sarin aerosols revealed an increased cellular proliferation with progressive diffused interstitial thickening on the 4th day following exposure. On the 16th day, loss of alveolar space and consolidation of large areas of all lobes were observed. Sarin also caused damage to the respiratory bronchioles. All the therapy regime blocked the development of lung lesions in the descending orders: atropine, diazepam and pralidoxime, atropine and diazepam > diazepam and pralidoxime > atropine and pralidoxime. The result suggests that diazepam in combination with atropine and pralidoxime could be an effective drug combination regime for the lung lesions.

Using MsfNet to Predict the ISUP Grade of Renal Clear Cell Carcinoma in Digital Pathology Images

Clear cell renal cell carcinoma(ccRCC)represents the most frequent form of renal cell carcinoma(RCC),and accurate International Society of Urological Pathology(ISUP)grading is crucial for prognosis and treatment selection.This study presents a new deep network called Multi-scale Fusion Network(MsfNet),which aims to enhance the automatic ISUP grade of ccRCC with digital histopathology pathology images.The MsfNet overcomes the limitations of traditional ResNet50 by multi-scale information fusion and dynamic allocation of channel quantity.The model was trained and tested using 90 Hematoxylin and Eosin(H&E)stained whole slide images(WSIs),which were all cropped into 320×320-pixel patches at 40×magnification.MsfNet achieved a micro-averaged area under the curve(AUC)of 0.9807,a macro-averaged AUC of 0.9778 on the test dataset.The Gradient-weighted Class Activation Mapping(Grad-CAM)visually demonstrated MsfNet’s ability to distinguish and highlight abnormal areas more effectively than ResNet50.The t-Distributed Stochastic Neighbor Embedding(t-SNE)plot indicates our model can efficiently extract critical features from images,reducing the impact of noise and redundant information.The results suggest that MsfNet offers an accurate ISUP grade of ccRCC in digital images,emphasizing the potential of AI-assisted histopathological systems in clinical practice.

Microvascular structural changes in esophageal squamous cell carcinoma pathology according to intrapapillary capillary loop types under magnifying endoscopy

BACKGROUND The intrapapillary capillary loop(IPCL)characteristics,visualized using magnifying endoscopy,are commonly assessed for preoperative evaluation of the infiltration depth of esophageal squamous cell carcinoma(ESCC).Japan Esophageal Society(JES)classification is the most widely used classification.Microvascular structural changes are evaluated by magnifying endoscopy for the presence or absence of each morphological factor:tortuosity,dilatation,irregular caliber,and different shapes.However,the pathological characteristics of IPCLs have not been thoroughly investigated,especially the microvascular structures corresponding to the deepest parts of the lesions'infiltration.AIM To investigate differences in pathological microvascular structures of ESCC,which correspond to the deepest parts of the lesions'infiltration.METHODS Patients with ESCC and precancerous lesions diagnosed at Peking University Third Hospital were enrolled between January 2019 and April 2023.Patients first underwent magnified endoscopic examination,followed by endoscopic submucosal dissection or surgical treatment.Pathological images were scanned using a threedimensional slice scanner,and the pathological structural differences in different types,according to the JES classification,were analyzed using nonparametric tests and t-tests.RESULTS The 35 lesions were divided into four groups according to the JES classification:A,B1,B2,and B3.Statistical analyses revealed significant differences(aP<0.05)in the short and long calibers,area,location,and density between types A and B.Notably,there were no significant differences in these parameters between types B1 and B2 and between types B2 and B3(P>0.05).However,significant differences in the short calibers,long calibers,and area of IPCL were observed between types B1 and B3(aP<0.05);no significant differences were found in the density or location(P>0.05).CONCLUSION Pathological structures of IPCLs in the deepest infiltrating regions differ among various IPCL types classified by the JES classification under magnifying endoscopy,especially between the types A and B.

A Multi-Task Deep Learning Framework for Simultaneous Detection of Thoracic Pathology through Image Classification

Thoracic diseases pose significant risks to an individual's chest health and are among the most perilous medical diseases. They can impact either one or both lungs, which leads to a severe impairment of a person’s ability to breathe normally. Some notable examples of such diseases encompass pneumonia, lung cancer, coronavirus disease 2019 (COVID-19), tuberculosis, and chronic obstructive pulmonary disease (COPD). Consequently, early and precise detection of these diseases is paramount during the diagnostic process. Traditionally, the primary methods employed for the detection involve the use of X-ray imaging or computed tomography (CT) scans. Nevertheless, due to the scarcity of proficient radiologists and the inherent similarities between these diseases, the accuracy of detection can be compromised, leading to imprecise or erroneous results. To address this challenge, scientists have turned to computer-based solutions, aiming for swift and accurate diagnoses. The primary objective of this study is to develop two machine learning models, utilizing single-task and multi-task learning frameworks, to enhance classification accuracy. Within the multi-task learning architecture, two principal approaches exist soft parameter sharing and hard parameter sharing. Consequently, this research adopts a multi-task deep learning approach that leverages CNNs to achieve improved classification performance for the specified tasks. These tasks, focusing on pneumonia and COVID-19, are processed and learned simultaneously within a multi-task model. To assess the effectiveness of the trained model, it is rigorously validated using three different real-world datasets for training and testing.

Expanding role and scope of artificial intelligence in the field of gastrointestinal pathology

Digital pathology(DP)and its subsidiaries including artificial intelligence(AI)are rapidly making inroads into the area of diagnostic anatomic pathology(AP)including gastrointestinal(GI)pathology.It is poised to revolutionize the field of diagnostic AP.Historically,AP has been slow to adopt digital technology,but this is changing rapidly,with many centers worldwide transitioning to DP.Coupled with advanced techniques of AI such as deep learning and machine learning,DP is likely to transform histopathology from a subjective field to an objective,efficient,and transparent discipline.AI is increasingly integrated into GI pathology,offering numerous advancements and improvements in overall diagnostic accuracy,efficiency,and patient care.Specifically,AI in GI pathology enhances diagnostic accuracy,streamlines workflows,provides predictive insights,integrates multimodal data,supports research,and aids in education and training,ultimately improving patient care and outcomes.This review summarized the latest developments in the role and scope of AI in AP with a focus on GI pathology.The main aim was to provide updates and create awareness among the pathology community.

Clinical and pathological characteristics and expression of related molecules in patients with airway disseminated lung adenocarcinoma

Objective:Lung adenocarcinoma exhibits diverse genetic and morphological backgrounds,in addition to considerable differences in clinical pathology and molecular biological characteristics.Among these,the phenomenon of spread through air space(STAS),a distinct mode of lung cancer infiltration,has rarely been reported.Therefore,this study aimed to explore the relationship between STAS tumor cells and the clinical and molecular characteristics of patients with lung adenocarcinoma,as well as their impact on prognosis.Methods:This study included 147 patients who were diagnosed with lung adenocarcinoma at the Inner Mongolia Autonomous Region Cancer Institute between January 2014 and December 2017.Surgical resection specimens were retrospectively analyzed.Using univariate and multivariate Cox analyses,we assessed the association between STAS and the clinicopathological features and molecular characteristics of patients with lung adenocarcinoma.Furthermore,we investigated the effects on patient prognosis.In addition,we developed a column–line plot prediction model and performed internal validation.Results:Patients with positive STAS had a significantly higher proportion of tumors with a diameter≥2 cm,with infiltration around the pleura,blood vessels,and nerves,and a pathological stage>IIB than in STAS-negative patients(P<0.05).Cox multivariate survival analysis revealed that clinical stage,STAS status,tumor size,and visceral pleural invasion were independent prognostic factors influencing the 5-year progression-free survival in patients with lung adenocarcinoma.The predictive values and P values from the Hosmer-Lemeshow test were 0.8 and 0.2,respectively,indicating no statistical difference.Receiver operating characteristic curve analysis demonstrated areas under the curve of 0.884 and 0.872 for the training and validation groups,respectively.The nomogram model exhibited the best fit with a value of 192.09.Conclusions:Clinical stage,pleural invasion,vascular invasion,peripheral nerve invasion,tumor size,and necrosis are independent prognostic factors for patients with STAS-positive lung adenocarcinoma.The nomogrambased on the clinical stage,pleural invasion,vascular invasion,peripheral nerve invasion,tumor size,and necrosis showed good accuracy,differentiation,and clinical practicality.

An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.

Clinical pathology of nodal micrometasteses in non-small cell lung cancer

Objective： To explore whether the conventional pathologic stages of some non-small cell lung cancer （NSCLC） patients were underestimated. Methods： 195 lymph node samples were taken from 25 NSCLC patients during the operations. Firstly, each resulting tissue block was processed for routine paraffin embedding. Then the 6- 10 serial sections were chosen, each 5/am thick, from every paraffin block of the lymph node. Finally, the first and the second last sections of each lymph node were stained by hematoxylin eosin （HE）, and the other serial sections were used for the immunohistochemical （IHC） staining examination with the monoclonal antibody against cyokeratin 19. Results： With HE staining, 30 of the 195 regional lymph nodes revealed dominant nodal metastases, and none showed micrometastases. IHC staining was performed on 135 lymph nodes that were identified as free of metastases by HE staining, 31 showed micrometastases; none showed gross nodal metastases. There was a significant difference between HE staining staging and IHC staining staging （P〈0.05）. Conclusion： Conventional HE staining can accurately detect gross nodal metastases in the lymph nodes of NSCLC patients, but is unfit for detecting lymph nodal micrometastases. IHC staining analysis can significantly facilitate the detection of occult micrometastatic tumor cells in lymph nodes, and its assessment of nodal micrometastases can provide a refinement of TNM stage for NSCLC patients. Our results provide a rationale for extensive lymph nodes sampling

Furmonertinib re-challenge for epidermal growth factor receptormutant lung adenocarcinoma after osimertinib-induced interstitial lung disease:A case report

BACKGROUND Most non-small cell lung cancer patients have epidermal growth factor receptor(EGFR)activating mutations,such as exon 19 deletion and exon 21 replacement mutations.Osimertinib is a third-generation EGFR-tyrosine kinase inhibitors ap-proved for the treatment of lung cancer patients carrying EGFR activating mu-tations.Osimertinib-induced interstitial lung disease(ILD)is a rare and poten-tially fatal pulmonary toxic manifestation of drug therapy.At present,there is no international consensus on the risks and treatment of the osimertinib-induced ILD.CASE SUMMARY We report a case of a 56-year-old woman who was diagnosed with lung adenocar-cinoma with lung hilum,mediastinal lymph nodes and brain metastases(T4N3-M1c stage IVB).The patient received targeted treatment with osimertinib after radiotherapy and chemotherapy.But she developed ILD after osimertinib treat-ment.Following active symptomatic treatment and hormone treatment,the lung injury alleviated.The patient was retreated with furmonertinib combined with prednisone and did not experience ILD again.So far,she has survived for 14 months without disease progression.CONCLUSION Retreatment with furmonertinib under prednisone could be considered as an effective therapeutic option after risk-benefit assessment for EGFR-mutant lung adenocarcinoma patients.

Therapeutic insights into epidermal growth factor receptor/reactive oxygen species proto-oncogene 1-receptor co-mutated non-small cell lung cancer:Crizotinib as a promising option

This letter provides a review of the report by Peng et al on a unique case of non-small cell lung cancer(NSCLC),specifically lung adenocarcinoma,featuring reactive oxygen species proto-oncogene 1-receptor(ROS1)co-mutation.The case involves a 64-year-old patient who exhibited both epidermal growth factor receptor(EGFR)L858R mutation and ROS1 rearrangement,achieving significant disease stabilization following treatment with crizotinib.This rare EGFR/ROS1 co-mutation poses distinct challenges for clinical management and highlights the necessity of personalized treatment strategies.While third-generation EGFR tyrosine kinase inhibitors(TKIs),such as osimertinib,are commonly regarded as first-line therapies,recent studies indicate that crizotinib may offer superior disease control in certain EGFR-mutant patients,particularly those who exhibit poor responses to EGFR TKIs.The case also examines the influence of tumor cell genetic heterogeneity on treatment response,underscoring the importance of evaluating tumor characteristics.In patients with EGFR/ROS1 co-mutation,gefitinib is generally effective as a first-line treatment;however,its efficacy can be limited,whereas crizotinib has demonstrated improved disease control.Future research should focus on identifying optimal treatment strategies for patients with EGFR/ROS1 co-mutation to enhance patient outcomes.In conclusion,this case report not only illustrates the effectiveness of crizotinib in managing patients with EGFR/ROS1 co-mutation but also underscores the importance of personalized treatment approaches,offering valuable insights for improving clinical outcomes in NSCLC patients with complex genetic profiles.TO THE EDITOR I read with great interest the case report by Peng et al[1],titled“Concomitant Epidermal Growth Factor Receptor Mutation/C-ROS Oncogene 1 Rearrangement in Non-Small Cell Lung Cancer”,published in the World Journal of Clinical Oncology[1].This report presents a compelling case of the exceedingly rare epidermal growth factor receptor(EGFR)/reactive oxygen species proto-oncogene 1-receptor(ROS1)co-mutation in non-small cell lung cancer(NSCLC),specifically in a patient with lung adenocarcinoma.The authors describe a 64-year-old woman with an EGFR L858R mutation and ROS1 rearrangement,who achieved notable disease stability with prolonged crizotinib treatment.This case,with its distinct clinical features and challenges inherent to EGFR/ROS1 co-mutations,provides valuable insights for the oncology community and underscores the potential efficacy of ROS1-targeted therapies in treating co-mutated NSCLC.

Vitiligo-like rash in a patient with lung cancer caused by sintilimab: A case report

BACKGROUND This article discusses a case involving a 63-year-old man with non-small cell lung cancer,who was treated with a combination of chemotherapy and immunothe-rapy.The patient was treated with five cycles of chemotherapy(pemetrexed and carboplatin)combined with sintilimab,a programmed death 1 inhibitor.CASE SUMMARY After the fifth cycle of treatment,the patient developed skin itching and a vitiligo-like rash,which are known side effects of immunotherapy.Despite dermatologi-cal consultation and treatment with topical corticosteroids,the rash worsened while the itching subsided.The patient continued with the treatment,and after 15 cycles,the tumor showed a response with a reduction in size.The vitiligo-like rash increased,but the antitumor treatment remained effective.CONCLUSION The case highlights the use of immunotherapy in patients with non-small cell lung cancer and the potential side effect of vitiligo-like rash.The patient’s tumor res-ponded well to the treatment,and despite the skin reaction,the treatment was not discontinued due to its effectiveness.The article suggests that further studies are needed to understand the mechanism behind vitiligo in patients with lung cancer receiving immune checkpoint inhibitors and whether the development of vitiligo-like rash after immune checkpoint inhibitor therapy is associated with improved prognosis.The case also underscores the importance of managing immune-related adverse events in the context of effective antitumor treatment.

Tankyrase 2 as a therapeutic target in non-small cell lung cancer: Implications for apoptosis and migration

This letter addresses Wang and Zhang's investigation into the role of tankyrase 2(TNKS2)as a pivotal driver of malignancy in non-small cell lung cancer(NSCLC)through mechanisms including apoptosis inhibition,enhanced cellular migration,andβ-catenin pathway activation.Their study in NSCLC cell lines demonstrates that TNKS2 overexpression stabilizesβ-catenin,subsequently triggering onco-genic gene expression and facilitating cellular migration-key attributes of meta-static potential.These insights position TNKS2 as a compelling target for therapy and a potential prognostic marker in NSCLC.Nevertheless,translating these in vitro findings to clinical practice requires validation in in vivo models.Addi-tionally,further research should investigate TNKS2 expression in patient samples and assess its implications in therapy resistance and combination treatment strategies.

Diagnosis and treatment of lung cancer:A molecular perspective

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

Gastrointestinal bleeding due to small bowel metastasis from lung adenocarcinoma:A case report

BACKGROUND Lung cancer is the most prevalent malignant tumor in human body,and is characterized by a high level of malignancy.The most common metastatic sites include the liver,bone,brain,and adrenal gland,while lung cancer resulting in gastrointestinal tract metastasis is uncommon.CASE SUMMARY A 74-years-old man with lung cancer was hospitalized owing to blood in the stool,The cause was identified as metastasis to the small intestine,and the patient subsequently underwent radical resection of the small intestine tumor.Currently,the overall condition of the patient is good,and undergoing combined chemotherapy.CONCLUSION Early intervention in patients with metastatic tumors can significantly improve prognosis.