Discovery of primary lung cancer following resection of rectal cancer lung metastasis:A case report

BACKGROUND Colorectal cancer(CRC)ranks high among the most common types of malignant tumors.The primary cause of cancer-related mortality is metastasis,with lung metastases accounting for 32.9%of all cases of metastatic CRC(MCRC).However,cases of MCRC in the lungs,which present concurrently with primary peripheral lung adenocarcinoma,are exceptionally rare.CASE SUMMARY This report describes the case of a 52-year-old female patient who,following a colonoscopy,was diagnosed with moderately differentiated adenocarcinoma based on rectal mucosal biopsy findings.A preoperative chest computed tomography scan revealed a ground-glass nodule in the right lung and a small nodule(approximately 0.6 cm in diameter)in the extramural basal segment of the left lower lobe,which suggested multiple lung metastases from rectal cancer.Subsequent treatment and follow-up led to a diagnosis of rectal cancer with left lung metastasis and peripheral adenocarcinoma of the lower lobe of the right lung.CONCLUSION This case report describes the therapeutic journey of a patient with lung metastasis from rectal cancer in addition to primary peripheral adenocarcinoma,thus underscoring the critical roles of multidisciplinary collaboration,personalized treatment strategies,and comprehensive patient rehabilitation guidance.

Small cell lung cancer with peripheral neuropathy as the first symptom:Two case reports

BACKGROUND Small cell lung cancer(SCLC)is the most malignant type of lung cancer.Even in the latent period and early stage of the tumor,SCLC is prone to produce distant metastases with complex and diverse clinical manifestations.SCLC is most closely related to paraneoplastic syndrome,and some cases present as paraneoplastic peripheral neuropathy(PPN).PPN in SCLC appears early,lacks specificity,and often occurs before diagnosis of the primary tumor.It is easy to be misdiagnosed as a primary disease of the nervous system,leading to missed diagnosis and delayed diagnosis and treatment.CASE SUMMARY This paper reports two cases of SCLC with limb weakness as the first symptom.The first symptoms of one patient were rash,limb weakness,and abnormal electromyography.The patient was repeatedly referred to the hospital for limb weakness and rash for>1 year,during which time,treatment with hormones and immunosuppressants did not lead to significant improvement,and the condition gradually aggravated.The patient was later diagnosed with SCLC,and the dyskinesia did not worsen as the dermatomyositis improved after antineoplastic and hormone therapy.The second case presented with limb numbness and weakness as the first symptom,but the patient did not pay attention to it.Later,the patient was diagnosed with SCLC after facial edema caused by tumor thrombus invading the vein.However,he was diagnosed with extensive SCLC and died 1 year after diagnosis.CONCLUSION The two cases had PPN and abnormal electromyography,highlighting its correlation with early clinical indicators of SCLC.

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.

Immunotherapy – new perspective in lung cancer

Lung carcinoma is associated with a high mortality worldwide,being the leading cause of cancer death.It is mainly classified into squamous non-small cell lung cancer(NSCLC),non-squamous NSCLC,and small cell lung cancer.However,such malignancy has been increasingly subdivided into histological and molecular subtypes to guide treatment.Therapies can be used in adjuvant and palliative settings.Regarding immunotherapy,it has been widely tested in both first or subsequent palliative lines.In this sense,drugs such as pembrolizumab,nivolumab,atezolizumab,ipilimumab,avelumab,and durvalumab have been assessed in large studies.Some of these trials have also studied these medicines in adjuvant and in maintenance therapy.In recent years,advances in immunotherapy have raised the hope that the unfavorable prognosis observed in several affected individuals can be changed.Immunotherapy has increased the overall survival in squamous NSCLC,non-squamous NSCLC,and small cell lung cancer.However,it has added to the oncology practice some side effects that are unusual in standard chemotherapy and require special clinical support.In order to show how immunotherapy is being applied in the treatment of lung carcinoma,we reviewed the main studies in adjuvant and palliative scenarios.What is the better scheme?What is the better combination?What is the better dose?When should we use immunotherapy?Does programmed cell death ligand 1 expression significantly interfere in immunotherapy efficiency?Some of these questions have already been answered,while others require more investigations.

Employing a Backpropagation Neural Network for Predicting Fear of Cancer Recurrence among Non-Small Cell Lung Cancer Patients

Objective:Non-small cell lung cancer(NSCLC)patients often experience significant fear of recurrence.To facilitate precise identification and appropriate management of this fear,this study aimed to compare the efficacy and accuracy of a Backpropagation Neural Network(BPNN)against logistic regression in modeling fear of cancer recurrence prediction.Methods:Data from 596 NSCLC patients,collected between September 2023 and December 2023 at the Cancer Hospital of the Chinese Academy of Medical Sciences,were analyzed.Nine clinically and statistically significant variables,identified via univariate logistic regression,were inputted into both BPNN and logistic regression models developed on a training set(N=427)and validated on an independent set(N=169).Model performances were assessed using Area Under the Receiver Operating Characteristic(ROC)Curve and Decision Curve Analysis(DCA)in both sets.Results:The BPNN model,incorporating nine selected variables,demonstrated superior performance over logistic regression in the training set(AUC=0.842 vs.0.711,p<0.001)and validation set(0.7 vs.0.675,p<0.001).Conclusion:The BPNN model outperforms logistic regression in accurately predicting fear of cancer recurrence in NSCLC patients,offering an advanced approach for fear assessment.

Imbalance of Circulating Follicular Regulatory and Follicular Helper T Cell Subpopulations Is Associated with Disease Progression and Serum CYFRA 21-1 Levels in Patients with Non-small Cell Lung Cancer

Objective This study aimed to investigate the changes of follicular helper T(TFH)and follicular regulatory T(TFR)cell subpopulations in patients with non-small cell lung cancer(NSCLC)and their significance.Methods Peripheral blood was collected from 58 NSCLC patients at different stages and 38 healthy controls.Flow cytometry was used to detect TFH cell subpopulation based on programmed death 1(PD-1)and inducible co-stimulator(ICOS),and TFR cell subpopulation based on cluster determinant 45RA(CD45RA)and forkhead box protein P3(FoxP3).The levels of interleukin-10(IL-10),interleukin-17a(IL-17a),interleukin-21(IL-21),and transforming growth factor-β(TGF-β)in the plasma were measured,and changes in circulating B cell subsets and plasma IgG levels were also analyzed.The correlation between serum cytokeratin fragment antigen 21-1(CYFRA 21-1)levels and TFH,TFR,or B cell subpopulations was further explored.Results The TFR/TFH ratio increased significantly in NSCLC patients.The CD45RA^(+)FoxP3^(int) TFR subsets were increased,with their proportions increasing in stages Ⅱ to Ⅲ and decreasing in stage IV.PD-1^(+)ICOS+TFH cells showed a downward trend with increasing stages.Plasma IL-21 and TGF-β concentrations were increased in NSCLC patients compared with healthy controls.Plasmablasts,plasma IgG levels,and CD45RA^(+)FoxP3^(int) TFR cells showed similar trends.TFH numbers and plasmablasts were positively correlated with CYFRA 21-1 in stages Ⅰ-Ⅲ and negatively correlated with CYFRA 21-1 in stage IV.Conclusion Circulating TFH and TFR cell subpopulations and plasmablasts dynamically change in different stages of NSCLC,which is associated with serum CYFRA 21-1 levels and reflects disease progression.

Enhanced recovery after surgery in elderly patients with non-small cell lung cancer who underwent video-assisted thoracic surgery

BACKGROUND This study was designed to investigate the clinical outcomes of enhanced recovery after surgery(ERAS)in the perioperative period in elderly patients with nonsmall cell lung cancer(NSCLC).AIM To investigate the potential enhancement of video-assisted thoracic surgery(VATS)in postoperative recovery in elderly patients with NSCLC.METHODS We retrospectively analysed the clinical data of 85 elderly NSCLC patients who underwent ERAS(the ERAS group)and 327 elderly NSCLC patients who received routine care(the control group)after VATS at the Department of Thoracic Surgery of Peking University Shenzhen Hospital between May 2015 and April 2017.After propensity score matching of baseline data,we analysed the postoperative stay,total hospital expenses,postoperative 48-h pain score,and postoperative complication rate for the 2 groups of patients who underwent lobectomy or sublobar resection.RESULTS After propensity score matching,ERAS significantly reduced the postoperative hospital stay(6.96±4.16 vs 8.48±4.18 d,P=0.001)and total hospital expenses(48875.27±18437.5 vs 55497.64±21168.63 CNY,P=0.014)and improved the satisfaction score(79.8±7.55 vs 77.35±7.72,P=0.029)relative to those for routine care.No significant between-group difference was observed in postoperative 48-h pain score(4.68±1.69 vs 5.28±2.1,P=0.090)or postoperative complication rate(21.2%vs 27.1%,P=0.371).Subgroup analysis showed that ERAS significantly reduced the postoperative hospital stay and total hospital expenses and increased the satisfaction score of patients who underwent lobectomy but not of patients who underwent sublobar resection.CONCLUSION ERAS effectively reduced the postoperative hospital stay and total hospital expenses and improved the satisfaction score in the perioperative period for elderly NSCLC patients who underwent lobectomy but not for patients who underwent sublobar resection.

Cancer/testis antigen, Kita-Kyushu lung cancer antigen-1 and ABCD stratification for diagnosing gastric cancers

BACKGROUND The ABCD stratification[combination of serum pepsinogen(PG)levels and titers of antibody(immunoglobulin G,IgG)against Helicobacter pylori(H.pylori)]is effective for the classification of individuals at risk of developing gastric cancer(GC).The Kita–Kyushu lung cancer antigen-1(KK-LC-1)is a Cancer/Testis antigen frequently expressed in GC.AIM To evaluate the effectiveness of KK-LC-1 and ABCD stratification in the diagnosis of GC.METHODS We analyzed the gene expression of KK-LC-1 in surgical specimens obtained from GC tumors.The levels of serum PG I/PG II and IgG against H.pylori were measured.According to their serological status,the patients were classified into the four groups of the ABCD stratification.RESULTS Of the 77 examined patients,63(81.8%)expressed KK-LC-1.The IgG titers of H.pylori and PG II were significantly higher in patients expressing KK-LC-1 than those measured in patients not expressing KK-LC-1(P=0.0289 and P=0.0041,respectively).The expression of KK-LC-1 in group C[PG method(+)/H.pylori infection(+)]was as high as 93.9%high.KK-LC-1 was also detected in group A[-/-].CONCLUSION The KK-LC-1 expression in GC was associated with H.pylori infection and atrophic status,so that,KK-LC-1 may be a useful marker for the diagnosis of GC.

Effect of Climate Change on Lung Cancer

This research paper aims to draw a relationship between lung cancer and climate change. With the rise of climate change in the last few decades, many organizations and people are concerned about the future of the world. Climate change has many side effects, such as air pollution, which can increase the incidence and death rates of lung and bronchus cancer. This paper aims to draw the relationship between climate change factors and lung cancer incidence and mortality rates. The main finding of this analysis was that there is a positive relationship between lung cancer incidence, death rates, and climate change indicators. The findings from this study have the potential to inform targeted public health interventions and policies, emphasizing the need for proactive strategies in mitigating the health impacts of a changing climate. Section 2 of this paper is a literature review and focuses on the findings of other scholars in this field. Section 3 of this paper is Methods and Processes and will highlight the steps used to create the program and get the results. Section 4 of this paper is Results and Analysis, and will go over the results produced by the machine learning algorithm, and will present graphs and visualizations regarding the relationship of the dependent and independent variables. The final section, Section 5, is Limitations and Conclusion, in which we will discuss possible limitations to both my dataset and my model, and will conclude the paper by presenting a big-picture view of these problems in our society.

Metaheuristic-Driven Two-Stage Ensemble Deep Learning for Lung/Colon Cancer Classification

This study investigates the application of deep learning,ensemble learning,metaheuristic optimization,and image processing techniques for detecting lung and colon cancers,aiming to enhance treatment efficacy and improve survival rates.We introduce a metaheuristic-driven two-stage ensemble deep learning model for efficient lung/colon cancer classification.The diagnosis of lung and colon cancers is attempted using several unique indicators by different versions of deep Convolutional Neural Networks(CNNs)in feature extraction and model constructions,and utilizing the power of various Machine Learning(ML)algorithms for final classification.Specifically,we consider different scenarios consisting of two-class colon cancer,three-class lung cancer,and fiveclass combined lung/colon cancer to conduct feature extraction using four CNNs.These extracted features are then integrated to create a comprehensive feature set.In the next step,the optimization of the feature selection is conducted using a metaheuristic algorithm based on the Electric Eel Foraging Optimization(EEFO).This optimized feature subset is subsequently employed in various ML algorithms to determine the most effective ones through a rigorous evaluation process.The top-performing algorithms are refined using the High-Performance Filter(HPF)and integrated into an ensemble learning framework employing weighted averaging.Our findings indicate that the proposed ensemble learning model significantly surpasses existing methods in classification accuracy across all datasets,achieving accuracies of 99.85%for the two-class,98.70%for the three-class,and 98.96%for the five-class datasets.

Primary biliary cholangitis presenting with granulomatous lung disease misdiagnosed as lung cancer:A case report

BACKGROUND There are few cases of pulmonary granulomatous changes secondary to primary biliary cirrhosis(PBC).No case of granulomatous lung disease secondary to PBC misdiagnosed as lung cancer had been reported.CASE SUMMARY A middle-aged woman presented with lung nodules and was misdiagnosed with lung cancer by positron emission tomography/computed tomography.She underwent left lobectomy,and the pathology of the nodules showed granulomatous inflammation,which was then treated with antibiotics.However,a new nodule appeared.Further investigation with lung biopsy and liver serology led to the diagnosis of PBC,and chest computed tomography indicated significant reduction in the pulmonary nodule by treatment with methylprednisolone and ursodeoxycholic acid.CONCLUSION Diagnosis of pulmonary nodules requires integrating various clinical data to avoid unnecessary pulmonary lobectomy.

Tongue image feature correlation analysis in benign lung nodules and lung cancer

Objective To analyze the differences in the correlation of tongue image indicators among patients with benign lung nodules and lung cancer.Methods From July 1;2020 to March 31;2022;clinical information of lung cancer patients and benign lung nodules patients was collected at the Oncology Department of Longhua Hos-pital Affiliated to Shanghai University of Traditional Chinese Medicine and the Physical Ex-amination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chi-nese Medicine;respectively.We obtained tongue images from patients with benign lung nod-ules and lung cancer using the TFDA-1 digital tongue diagnosis instrument;and analyzed these images with the TDAS V2.0 software.The extracted indicators included color space pa-rameters in the Lab system for both the tongue body(TB)and tongue coating(TC)(TB/TC-L;TB/TC-a;and TB/TC-b);textural parameters[TB/TC-contrast(CON);TB/TC-angular second moment(ASM);TB/TC-entropy(ENT);and TB/TC-MEAN];as well as TC parameters(perAll and perPart).The bivariate correlation of TB and TC features was analyzed using Pearson’s or Spearman’s correlation analysis;and the overall correlation was analyzed using canonical correlation analysis(CCA).Results Samples from 307 patients with benign lung nodules and 276 lung cancer patients were included after excluding outliers and extreme values.Simple correlation analysis indi-cated that the correlation of TB-L with TC-L;TB-b with TC-b;and TB-b with perAll in lung cancer group was higher than that in benign nodules group.Moreover;the correlation of TB-a with TC-a;TB-a with perAll;and the texture parameters of the TB(TB-CON;TB-ASM;TB-ENT;and TB-MEAN)with the texture parameters of the TC(TC-CON;TC-ASM;TC-ENT;and TC-MEAN)in benign nodules group was higher than lung cancer group.CCA further demon-strated a strong correlation between the TB and TC parameters in lung cancer group;with the first and second pairs of typical variables in benign nodules and lung cancer groups indicat-ing correlation coefficients of 0.918 and 0.817(P<0.05);and 0.940 and 0.822(P<0.05);re-spectively.Conclusion Benign lung nodules and lung cancer patients exhibited differences in correla-tion in the L;a;and b values of the TB and TC;as well as the perAll value of the TC;and the texture parameters(TB/TC-CON;TB/TC-ASM;TB/TC-ENT;and TB/TC-MEAN)between the TB and TC.Additionally;there were differences in the overall correlation of the TB and TC be-tween the two groups.Objective tongue diagnosis indicators can effectively assist in the diag-nosis of benign lung nodules and lung cancer;thereby providing a scientific basis for the ear-ly detection;diagnosis;and treatment of lung cancer.

Clinical and molecular significance of homologous recombination deficiency positive non-small cell lung cancer in Chinese population:An integrated genomic and transcriptional analysis

Objective:The clinical significance of homologous recombination deficiency(HRD)in breast cancer,ovarian cancer,and prostate cancer has been established,but the value of HRD in non-small cell lung cancer(NSCLC)has not been fully investigated.This study aimed to systematically analyze the HRD status of untreated NSCLC and its relationship with patient prognosis to further guide clinical care.Methods:A total of 355 treatment-naïve NSCLC patients were retrospectively enrolled.HRD status was assessed using the AmoyDx Genomic Scar Score(GSS),with a score of≥50 considered HRD-positive.Genomic,transcriptomic,tumor microenvironmental characteristics and prognosis between HRD-positive and HRDnegative patients were analyzed.Results:Of the patients,25.1%(89/355)were HRD-positive.Compared to HRD-negative patients,HRDpositive patients had more somatic pathogenic homologous recombination repair(HRR)mutations,higher tumor mutation burden(TMB)(P<0.001),and fewer driver gene mutations(P<0.001).Furthermore,HRD-positive NSCLC had more amplifications in PI3K pathway and cell cycle genes,MET and MYC in epidermal growth factor receptor(EGFR)/anaplastic lymphoma kinase(ALK)mutant NSCLC,and more PIK3CA and AURKA in EGFR/ALK wild-type NSCLC.HRD-positive NSCLC displayed higher tumor proliferation and immunosuppression activity.HRD-negative NSCLC showed activated signatures of major histocompatibility complex(MHC)-II,interferon(IFN)-γand effector memory CD8+T cells.HRD-positive patients had a worse prognosis and shorter progressionfree survival(PFS)to targeted therapy(first-and third-generation EGFR-TKIs)(P=0.042).Additionally,HRDpositive,EGFR/ALK wild-type patients showed a numerically lower response to platinum-free immunotherapy regimens.Conclusions:Unique genomic and transcriptional characteristics were found in HRD-positive NSCLC.Poor prognosis and poor response to EGFR-TKIs and immunotherapy were observed in HRD-positive NSCLC.This study highlights potential actionable alterations in HRD-positive NSCLC,suggesting possible combinational therapeutic strategies for these patients.

IMpower210:A phase Ⅲ study of second-line atezolizumab vs. docetaxel in East Asian patients with non-small cell lung cancer

Objective: IMpower210(NCT02813785) explored the efficacy and safety of single-agent atezolizumab vs.docetaxel as second-line treatment for advanced non-small cell lung cancer(NSCLC) in East Asian patients.Methods: Key eligibility criteria for this phase Ⅲ, open-label, randomized study included age ≥18 years;histologically documented advanced NSCLC per the Union for International Cancer Control/American Joint Committee on Cancer staging system(7th edition);Eastern Cooperative Oncology Group performance status of 0 or 1;and disease progression following platinum-based chemotherapy for advanced or metastatic NSCLC. Patients were randomized 2:1 to receive either atezolizumab(1,200 mg) or docetaxel(75 mg/m^(2)). The primary study endpoint was overall survival(OS) in the intention-to-treat(ITT) population with wild-type epidermal growth factor receptor expression(ITT EGFR-WT) and in the overall ITT population.Results: Median OS in the ITT EGFR-WT population(n=467) was 12.3 [95% confidence interval(95% CI),10.3-13.8] months in the atezolizumab arm(n=312) and 9.9(95% CI, 7.8-13.9) months in the docetaxel arm[n=155;stratified hazard ratio(HR), 0.82;95% CI, 0.66-1.03]. Median OS in the overall ITT population was 12.5(95% CI, 10.8-13.8) months with atezolizumab treatment and 11.1(95% CI, 8.4-14.2) months(n=377) with docetaxel treatment(n=188;stratified HR, 0.87;95% CI, 0.71-1.08). Grade 3/4 treatment-related adverse events(TRAEs) occurred in 18.4% of patients in the atezolizumab arm and 50.0% of patients in the docetaxel arm.Conclusions: IMpower210 did not meet its primary efficacy endpoint of OS in the ITT EGFR-WT or overall ITT populations. Atezolizumab was comparatively more tolerable than docetaxel, with a lower incidence of grade3/4 TRAEs.

Efficacy and safety of dacomitinib as first-line treatment for advanced non-small cell lung cancer patients with epidermal growth factor receptor 21L858R mutation:A multicenter,case-series study in China

Objective:To provide real-world evidence for the application of first-line dacomitinib treatment for epidermal growth factor receptor(EGFR)21L858R mutant non-small cell lung cancer(NSCLC)patients in China and to explore the factors influencing the efficacy and safety.Methods:A longitudinal,consecutive case-series,multicenter study with mixed prospective and retrospective data was conducted.The primary endpoint was progression-free survival(PFS),and the secondary endpoints included duration of treatment(DOT),overall survival(OS),objective response rate(ORR),disease control rate(DCR)and safety.Results:A total of 155 EGFR 21L858R mutant patients treated with first-line dacomitinib were included.The median follow-up time for these patients was 20.4 months.Among 134 patients with evaluable lesions,the ORR was 70.9%and the DCR was 96.3%.The median PFS was 16.3[95%confidence interval(95%CI),13.7−18.9]months.Multivariate Cox regression analysis suggested that the baseline brain metastasis(BM)status[with vs.without BM:hazard ratio(HR),1.331;95%CI,0.720−2.458;P=0.361]and initial doses(45 mg vs.30 mg:HR,0.837;95%CI,0.427−1.641;P=0.604)did not significantly affect the median PFS.The median DOT was 21.0(95%CI,17.5−24.6)months and the median OS was not reached.Genetic tests were performed in 64 patients after progression,among whom 29(45.3%)patients developed the EGFR 20T790M mutation.In addition,among the 46 patients who discontinued dacomitinib treatment after progression,31(67.4%)patients received subsequent third-generation EGFR-tyrosine kinase inhibitors.The most common grade 3−4 adverse events were rash(10.4%),diarrhea(9.1%),stomatitis(7.1%)and paronychia(4.5%).The incidence of grade 3−4 rash was significantly higher in the 45 mg group than that in the 30 mg group(21.9%vs.7.5%,P=0.042).Conclusions:First-line dacomitinib treatment demonstrated promising efficacy and tolerable adverse events among EGFR 21L858R mutant NSCLC patients in China.

Analysis and Review of Downregulated Actin Cytoskeletal Proteins in Non-Small Cell Lung Cancer

Actin, a highly conserved protein, plays a dominant role in Non-small cell lung cancer (NSCLC). Late diagnosis and the aggressive nature of NSCLC pose a significant threat. Studying the clinic pathological properties of NSCLC proteins is a potential alternative for developing treatment strategies. Towards this, 35 downregulated actin cytoskeletal proteins on NSCLC prognosis and treatment were studied by examining their protein-protein interactions, gene ontology enrichment terms, and signaling pathways. Using PubMed, various proteins in NSCLC were identified. The protein-protein interactions and functional associations of these proteins were examined using the STRING database. The focal adhesion signaling pathway was selected from all available KEGG and Wiki pathways because of its role in regulating gene expression, facilitating cell movement and reproduction, and significantly impacting NSCLC. The protein-protein interaction network of the 35 downregulated actin cytoskeleton proteins revealed that ACTG1, ACTR2, ACTR3, ANXA2, ARPC4, FLNA, TLN1, CALD1, MYL6, MYH9, MYH10, TPM1, TPM3, TPM4, PFN1, IQGAP1, MSN, and ZXY exhibited the highest number of interactions. Whereas HSPB1, CTNNA1, KRT17, KRT7, FLNB, SEPT2, and TUBA1B displayed medium interactions, while UTRN, TUBA1B, and DUSP23 had relatively fewer interactions. It was discovered that focal adhesions are critical in connecting membrane receptors with the actin cytoskeleton. In addition, protein kinases, phosphatases, and adapter proteins were identified as key signaling molecules in this process, greatly influencing cell shape, motility, and gene expression. Our analysis shows that the focal adhesion pathway plays a crucial role in NSCLC and is essential for developing effective treatment strategies and improving patient outcomes.

Clinical Practice of Evidence-Based PDCA Cycle Management Model in Accelerated Recovery of Lung Cancer Patients

Objective: To explore the nursing effect of evidence-based PDCA cycle management mode in accelerated rehabilitation of patients undergoing thoracoscopic lung cancer radical surgery. Methods: 104 patients who underwent thoracoscopic lung cancer radical surgery in our hospital from June 2022 to February 2023 were randomly divided into control group and intervention group, with 52 cases in each group. The control group implemented evidence-based ERAS clinical pathway management, while the intervention group implemented evidence-based PDCA cycle quality management. The postoperative recovery of the two groups of patients was compared. Results: The postoperative recovery of the intervention group was significantly better than that of the control group. The first time to get out of bed, the first time to eat, the duration of chest drainage tube placement, and the length of hospital stay were significantly shorter than those of the control group. The incidence of postoperative chest complications and hospitalization costs were significantly lower than those of the control group, and patient satisfaction was significantly higher than that of the control group (P Conclusion: Evidence-based PDCA cycle quality management mode can effectively improve the implementation quality of accelerated rehabilitation nursing for patients undergoing thoracoscopic lung cancer radical surgery, and it is worthy of clinical promotion.

Immunotherapy for Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a poorly differentiated, highly malignant neuroendocrine tumor characterized by rapid growth, aggressiveness, and easy recurrence. It is usually found in late clinical stage and the opportunity for surgery is lost. Therefore, surgery is often not used in clinical treatment. Although it is sensitive to chemoradiotherapy, it has a high recurrence rate and lacks effective treatment methods at present. Following chemotherapy and radiotherapy, immunotherapy for small cell lung cancer has become the mainstream research direction. Immunotherapy is profoundly changing the approach to cancer treatment due to its tolerable safety profile, sustained treatment response due to the production of immune memory, and effectiveness in a broad patient population. Immunotherapy for small cell lung cancer is one of the effective treatment methods for small cell lung cancer, and relevant studies are not rare, but there are still shortcomings such as intolerance of side effects and inaccurate evaluation of treatment timing. This article reviews the history of immunotherapy, the mechanism of action of immunodrugs, and the current immunodrugs used in the first-line treatment of extensive small cell lung cancer.

Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy

BACKGROUND Non-small cell lung cancer(NSCLC)is the primary form of lung cancer,and the combination of chemotherapy with immunotherapy offers promising treatment options for patients suffering from this disease.However,the emergence of drug resistance significantly limits the effectiveness of these therapeutic strategies.Consequently,it is imperative to devise methods for accurately detecting and evaluating the efficacy of these treatments.AIM To identify the metabolic signatures associated with neutrophil extracellular traps(NETs)and chemoimmunotherapy efficacy in NSCLC patients.METHODS In total,159 NSCLC patients undergoing first-line chemoimmunotherapy were enrolled.We first investigated the characteristics influencing clinical efficacy.Circulating levels of NETs and cytokines were measured by commercial kits.Liquid chromatography tandem mass spectrometry quantified plasma metabolites,and differential metabolites were identified.Least absolute shrinkage and selection operator,support vector machine-recursive feature elimination,and random forest algorithms were employed.By using plasma metabolic profiles and machine learning algorithms,predictive metabolic signatures were established.RESULTS First,the levels of circulating interleukin-8,neutrophil-to-lymphocyte ratio,and NETs were closely related to poor efficacy of first-line chemoimmunotherapy.Patients were classed into a low NET group or a high NET group.A total of 54 differential plasma metabolites were identified.These metabolites were primarily involved in arachidonic acid and purine metabolism.Three key metabolites were identified as crucial variables,including 8,9-epoxyeicosatrienoic acid,L-malate,and bis(monoacylglycerol)phosphate(18:1/16:0).Using metabolomic sequencing data and machine learning methods,key metabolic signatures were screened to predict NET level as well as chemoimmunotherapy efficacy.CONCLUSION The identified metabolic signatures may effectively distinguish NET levels and predict clinical benefit from chemoimmunotherapy in NSCLC patients.

Chemotherapy combined with bevacizumab for small cell lung cancer with brain metastases:A case report

BACKGROUND Small cell lung cancer(SCLC)is a common and aggressive subtype of lung cancer.It is characterized by rapid growth and a high mortality rate.Approximately 10%of patients with SCLC present with brain metastases at the time of diagnosis,which is associated with a median survival of 5 mo.This study aimed to summarize the effect of bevacizumab on the progression-free survival(PFS)and overall survival of patients with brain metastasis of SCLC.CASE SUMMARY A 62-year-old man was referred to our hospital in February 2023 because of dizziness and numbness of the right lower extremity without headache or fever for more than four weeks.The patient was diagnosed with limited-stage SCLC.He received 8 cycles of chemotherapy combined with maintenance bevacizumab therapy and achieved a PFS of over 7 mo.CONCLUSION The combination of bevacizumab and irinotecan effectively alleviated brain metastasis in SCLC and prolonged PFS.