Progress in the Management of Early-Stage Non-Small Cell Lung Cancer in 2017

Easily applicable predictive score for MPR based on parameters before neoadjuvant chemoimmunotherapy in operable NSCLC: a single-center, ambispective, observational study

BACKGROUND

Neoadjuvant chemoimmunotherapy (NACI) is promising for resectable nonsmall cell lung cancer (NSCLC), but predictive biomarkers are still lacking. The authors aimed to develop a model based on pretreatment parameters to predict major pathological response (MPR) for such an approach.

METHODS

The authors enrolled operable NSCLC treated with NACI between March 2020 and May 2023 and then collected baseline clinical-pathology data and routine laboratory examinations before treatment. The efficacy and safety data of this cohort was reported and variables were screened by Logistic and Lasso regression and nomogram was developed. In addition, receiver operating characteristic curves, calibration curves, and decision curve analysis were used to assess its power. Finally, internal cross-validation and external validation was performed to assess the power of the model.

RESULTS

In total, 206 eligible patients were recruited in this study and 53.4% (110/206) patients achieved MPR. Using multivariate analysis, the predictive model was constructed by seven variables, prothrombin time (PT), neutrophil percentage (NEUT%), large platelet ratio (P-LCR), eosinophil percentage (EOS%), smoking, pathological type, and programmed death ligand-1 (PD-L1) expression finally. The model had good discrimination, with area under the receiver operating characteristic curve (AUC) of 0.775, 0.746, and 0.835 for all datasets, cross-validation, and external validation, respectively. The calibration curves showed good consistency, and decision curve analysis indicated its potential value in clinical practice.

CONCLUSION

This real world study revealed favorable efficacy in operable NSCLC treated with NACI. The proposed model based on multiple clinically accessible parameters could effectively predict MPR probability and could be a powerful tool in personalized medication.

Development and validation of a deep learning signature for predicting lymphovascular invasion and survival outcomes in clinical stage IA lung adenocarcinoma: A multicenter retrospective cohort study

PURPOSE

The presence of lymphovascular invasion (LVI) influences the management and outcomes of patients with clinical stage IA lung adenocarcinoma. The objective was the development of a deep learning (DL) signature for the prediction of LVI and stratification of prognosis.

METHODS

A total of 2077 patients from three centers were retrospectively enrolled and divided into a training set (n = 1515), an internal validation set (n = 381), and an external set (n = 181). A -three-dimensional residual neural network was used to extract the DL signature and three models, namely, the clinical, DL, and combined models, were developed. Diagnostic efficiency was assessed by ROC curves and AUC values. Kaplan-Meier curves and Cox proportional hazards regression analyses were conducted to evaluate links between various factors and disease-free survival.

RESULTS

The DL model could effectively predict LVI, shown by AUC values of 0.72 (95 %CI: 0.68-0.76) and 0.63 (0.54-0.73) in the internal and external validation sets, respectively. The incorporation of DL signature and clinical-radiological factors increased the AUC to 0.74 (0.71-0.78) and 0.77 (0.70-0.84) in comparison with the DL and clinical models (AUC of 0.71 [0.68-0.75], 0.71 [0.61-0.81]) in the internal and external validation sets, respectively. Pathologic LVI, LVI predicted by both DL and combined models were associated with unfavorable prognosis (all p < 0.05).

CONCLUSION

The effectiveness of the DL signature in the diagnosis of LVI and prognosis prediction in patients with clinical stage IA lung adenocarcinoma was demonstrated. These findings suggest the potential of the model in clinical decision-making.

Differential efficacy of segmentectomy and wedge resection in sublobar resection compared to lobectomy for solid-dominant stage IA lung cancer: a systematic review and meta-analysis

BACKGROUND

Currently, the impact of sublobar resection versus lobectomy on the prognosis of solid-dominant stage IA lung cancer is contradictory in different studies, which requires further exploration.

METHODS

The authors analyzed 26 studies, including one randomized controlled trial and retrospective cohort studies. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using fixed-effects or random-effects models based on heterogeneity levels.

RESULTS

The analysis included 12 667 patients, with 3488 undergoing sublobar resections and 9179 receiving lobectomies. The overall analysis revealed no statistically significant difference in overall survival (OS) (HR=1.28, 95% CI: 0.98-1.69) between sublobar resection and lobectomy, but lobectomy was associated with better recurrence-free survival (RFS) (HR=1.39, 95% CI: 1.10-1.75). Subgroup analyses revealed that, for tumors with a diameter ≤2 cm, sublobar resection versus lobectomy showed no significant difference in OS but sublobar resection had lower RFS. For 2-3 cm tumors, both OS and RFS were significantly lower in the sublobar resection group. When consolidation-to-tumor ratio (CTR) ranged from 0.5 to <1, OS did not differ significantly, but RFS was significantly lower in sublobar resection. Lung cancers with CTR=1 showed significantly lower OS and RFS in the sublobar resection group. Segmentectomy provided similar OS and RFS compared to lobectomy, while wedge resection had a detrimental effect on patient prognosis. However, wedge resection may have provided comparable outcomes for patients aged 75 years or older.

CONCLUSION

Our findings suggest that segmentectomy and lobectomy yield similar oncological outcomes. However, compared to lobectomy, wedge resection is associated with a poorer prognosis. Nevertheless, for elderly patients, wedge resection is also a reasonable surgical option.

Development and validation of prognostic nomogram for T1-3N0M0 non-small cell lung cancer after curative resection

BACKGROUND

Radical resection plus lymph node dissection is a common treatment for patients with T_1-3N₀M₀ non-small cell lung cancer (NSCLC). Few models predicted the survival outcomes of these patients. This study aimed to developed a nomogram for predicting their overall survival (OS).

MATERIALS AND METHODS

This study involved 3002 patients with T_1-3N₀M₀ NSCLC after curative resection between January 1999 and October 2013. 1525 Patients from Sun Yat-sen University Cancer Center were randomly allocated to training cohort and internal validation cohort in a ratio of 7:3. 1477 patients from ten institutions were recruited as external validation cohort. A nomogram was constructed based on the training cohort and validated by internal and external validation cohort to predict the OS of these patients. The accuracy and practicability were tested by Harrell's C-indexes, calibration plots and decision curve analyses (DCA).

RESULTS

Age, sex, histological classification, pathological T stage, and HI standard were independent factors for OS and were included in our nomogram. The C-index of the nomogram for OS estimates were 0.671 (95% CI, 0.637-0.705),0.632 (95% CI, 0.581-0.683), and 0.645 (95% CI, 0.617-0.673) in the training cohorts, internal validation cohorts, and external validation cohort, respectively. The calibration plots and DCA for predictions of OS were in excellent agreement. An online version of the nomogram was built for convenient clinical practice.

CONCLUSIONS

Our nomogram can predict the OS of patients with T_1-3N₀M₀ NSCLC after curative resection. The online version of our nomogram offer opportunities for fast personalized risk stratification and prognosis prediction in clinical practice.

A multilayer perceptron-based model applied to histopathology image classification of lung adenocarcinoma subtypes

Objective

Lung cancer is one of the most common malignant tumors in humans. Adenocarcinoma of the lung is another of the most common types of lung cancer. In clinical medicine, physicians rely on the information provided by pathology tests as an important reference for the fifinal diagnosis of many diseases. Thus, pathological diagnosis is known as the gold standard for disease diagnosis. However, the complexity of the information contained in pathology images and the increase in the number of patients far exceeds the number of pathologists, especially in the treatment of lung cancer in less-developed countries.

Methods

This paper proposes a multilayer perceptron model for lung cancer histopathology image detection, which enables the automatic detection of the degree of lung adenocarcinoma infifiltration. For the large amount of local information present in lung cancer histopathology images, MLP IN MLP (MIM) uses a dual data stream input method to achieve a modeling approach that combines global and local information to improve the classifification performance of the model. In our experiments, we collected 780 lung cancer histopathological images and prepared a lung histopathology image dataset to verify the effectiveness of MIM.

Results

The MIM achieves a diagnostic accuracy of 95.31% and has a precision, sensitivity, specificity and F1-score of 95.31%, 93.09%, 93.10%, 96.43% and 93.10% respectively, outperforming the diagnostic results of the common network model. In addition, a number of series of extension experiments demonstrated the scalability and stability of the MIM.

Conclusions

In summary, MIM has high classifification performance and substantial potential in lung cancer detection tasks.

Development and validation of a nomogram for predicting survival time and making treatment decisions for clinical stage IA NSCLC based on the SEER database

Background

The aim of this study was to establish and validate a nomogram model for accurate prediction of patients' survival with T1aN0M0 none small cell lung cancer (NSCLC).

Methods

The patients, diagnosed with the stage IA NSCLC from 2004-2015, were identified from the Surveillance, Epidemiology and End Results (SEER) database. The variables with a P-value < 0.05 in a multivariate Cox regression were selected to establish the nomogram. The discriminative ability of the model was evaluated by the concordance index (C-index). The proximity of the nomogram prediction to the actual risk was depicted by a calibration plot. The clinical usefulness was estimated by the decision curve analysis (DCA). Survival curves were made with Kaplan-Meier method and compared by Log-Rank test.

Results

Eight variables, including treatment, age, sex, race, marriage, tumor size, histology, and grade were selected to develop the nomogram model by univariate and multivariate cox regression. The C-index was 0.704 (95% CI, 0.694-0.714) in the training set and 0.713 (95% CI, 0.697-0.728) in the test set, which performed significantly better than 8th edition AJCC TNM stage system (0.550, 95% CI, 0.408-0.683, P < 0.001). The calibration curve showed that the prediction ability of 3-years and 5-years survival rate demonstrated a high degree of agreement between the nomogram model and the actual observation. The DCA curves also proved that the nomogram-assisted decisions could improve patient outcomes.

Conclusion

We established and validated a prognostic nomogram to predict 3-years and 5-years overall survival in stage IA NSCLC.

Cuproptosis-Related Gene - SLC31A1, FDX1 and ATP7B - Polymorphisms are Associated with Risk of Lung Cancer

Background

Cuproptosis is a novel copper-dependent cell death, and the copper level was increased in lung cancer patients. However, few studies evaluated the association between single-nucleotide polymorphisms (SNPs) in cuproptosis-related genes and lung cancer risk.

Methods

Six SNPs of the SLC31A1, FDX1 and ATP7B genes were genotyped in a case-control cohort including 650 lung cancer cases and 650 controls using the MassARRAY platform.

Results

The minor alleles of SLC31A1-rs10981694 and FDX1-rs10488764 were associated with an increased risk of lung cancer (rs10981694: OR=1.455, 95% CI: 1.201-1.763, p<0.001; rs10488764: OR=1.483, 95% CI: 1.244-1.768, p<0.001). In contrast, the minor alleles of rs9535826 and rs9535828 in ATP7B were related to a decreased risk of the disease (rs9535826: OR=0.714, 95% CI: 0.608-0.838 p<0.001; rs9535828: OR=0.679, 95% CI: 0.579-0.796, p<0.001). The frequencies of rs10981694-TG/GG and rs10488764-GA/AA genotypes were significantly higher in lung cancer cases than that in controls, making them risk genotypes for the disease (p < 0.001); while the rs9535826-TG/GG and rs9535828-GA/AA genotypes were protective genotypes and associated with a reduced risk of the disease (p<0.001). Genetic model evaluation revealed that SLC31A1-rs10981694 and FDX1-rs10488764 were associated with a growing risk of lung cancer in dominant, recessive and log-additive models (p<0.001). Moreover, rs9535826 and rs9535828 in ATP7B were related to a declining risk of the disease in three genetic models (p<0.001). In addition, stratification analysis showed that FDX1-rs10488764 was risk variant for lung cancer in both smokers and nonsmokers, and was associated with risk of each pathological type of lung cancer (p<0.008).

Conclusion

The results shed new light on the correlation between cuproptosis-related genes and risk of lung cancer.

DeepCUBIT: Predicting Lymphovascular Invasion or Pathological Lymph Node Involvement of Clinical T1 Stage Non-Small Cell Lung Cancer on Chest CT Scan Using Deep Cubical Nodule Transfer Learning Algorithm

The prediction of lymphovascular invasion (LVI) or pathological nodal involvement of tumor cells is critical for successful treatment in early stage non-small cell lung cancer (NSCLC). We developed and validated a Deep Cubical Nodule Transfer Learning Algorithm (DeepCUBIT) using transfer learning and 3D Convolutional Neural Network (CNN) to predict LVI or pathological nodal involvement on chest CT images. A total of 695 preoperative CT images of resected NSCLC with tumor size of less than or equal to 3 cm from 2008 to 2015 were used to train and validate the DeepCUBIT model using five-fold cross-validation method. We also used tumor size and consolidation to tumor ratio (C/T ratio) to build a support vector machine (SVM) classifier. Two-hundred and fifty-four out of 695 samples (36.5%) had LVI or nodal involvement. An integrated model (3D CNN + Tumor size + C/T ratio) showed sensitivity of 31.8%, specificity of 89.8%, accuracy of 76.4%, and AUC of 0.759 on external validation cohort. Three single SVM models, using 3D CNN (DeepCUBIT), tumor size or C/T ratio, showed AUCs of 0.717, 0.630 and 0.683, respectively on external validation cohort. DeepCUBIT showed the best single model compared to the models using only C/T ratio or tumor size. In addition, the DeepCUBIT model could significantly identify the prognosis of resected NSCLC patients even in stage I. DeepCUBIT using transfer learning and 3D CNN can accurately predict LVI or nodal involvement in cT1 size NSCLC on CT images. Thus, it can provide a more accurate selection of candidates who will benefit from limited surgery without increasing the risk of recurrence.

Immunotherapy and Vaccination in Surgically Resectable Non-Small Cell Lung Cancer (NSCLC)

Early-stage NSCLC (stages I and II, and some IIIA diseases) accounts for approximately 30% of non-small cell lung cancer (NSCLC) cases, with surgery being its main treatment modality. The risk of disease recurrence and cancer-related death, however, remains high among NSCLC patients after complete surgical resection. In previous studies on the long-term follow-up of post-operative NSCLC, the results showed that the five-year survival rate was about 65% for stage IB and about 35% for stage IIIA diseases. Platinum-based chemotherapy with or without radiation therapy has been used as a neoadjuvant therapy or post-operative adjuvant therapy in NSCLC, but the improvement of survival is limited. Immune checkpoint inhibitors (ICIs) have effectively improved the 5-year survival of advanced NSCLC patients. Cancer vaccination has also been explored and used in the prevention of cancer or reducing disease recurrence in resected NSCLC. Here, we review studies that have focused on the use of immunotherapies (i.e., ICIs and vaccination) in surgically resectable NSCLC. We present the results of completed clinical trials that have used ICIs as neoadjuvant therapies in pre-operative NSCLC. Ongoing clinical trials investigating ICIs as neoadjuvant and adjuvant therapies are also summarized.

Outcomes of sublobar resection vs lobectomy for invasive clinical stage T1N0 non-small-cell lung cancer: A propensity-match analysis

BACKGROUND

The role of sub lobar resection (SLR; either segmentectomy or wedge resection) vs lobectomy (LBCT) for invasive clinical stage T1N0 non-small-cell-lung-cancer (NSCLC) has not been fully established yet.

AIM

We aimed to characterize the preoperative parameters leading to selecting SLR and compare the overall survival (OS) and disease-free survival (DFS) of these two surgical approaches.

METHODS

Clinical data on 162 patients (LBCT-107; SLR-55) were prospectively entered in our departmental database. Preoperative parameters associated with the performance of SLR were identified using univariate and multivariate cox regression analysis. The Kaplan-Meier method was used to compute OS and DFS. Comparison between LBCT and SLR groups and 32 propensity-matched groups was performed using Log-rank test.

RESULTS

Median follow-up time for the LBCT and SLR groups was 4.76 (Inter-quartile range [IQR] 2.96 to 8.23) and 3.38 (IQR 2.9 to 6.19) years respectively. OS and DFS rates were similar between the two groups in the entire cohort (OS-LBCT vs SLR P = .853, DSF-LBCT vs SLR P = .653) and after propensity matching (OS-LBCT vs SLR P = .563 DSF-LBCT vs SLR P = .632). Specifically, Two- and five-year OS rates for LBCT and SLR were 90.6.% vs 92.7%, 71.8% vs 75.9% respectively. Independent predictors of selecting for SLR included older age (P < .001), reduced FEV1% (P = .026), smaller tumor size (P = .025), smaller invasive component (P = .021) and higher American Society of Anesthesiology scores (P = .014).

CONCLUSIONS

In 162 consecutive and 32 matched cases, SLR and lobar resection had similar overall and disease-free survival rates. SLR may be considered as a reasonable oncological procedure in carefully selected T1N0 NSCLC patients that present with multiple comorbidities and relatively small tumors.

Navigating Diagnostic and Treatment Decisions in Non-Small Cell Lung Cancer: Expert Commentary on the Multidisciplinary Team Approach

Non-small cell lung cancer (NSCLC) accounts for approximately one in five cancer-related deaths, and management requires increasingly complex decision making by health care professionals. Many centers have therefore adopted a multidisciplinary approach to patient care, using the expertise of various specialists to provide the best evidence-based, personalized treatment. However, increasingly complex disease staging, as well as expanded biomarker testing and multimodality management algorithms with novel therapeutics, have driven the need for multifaceted, collaborative decision making to optimally guide the overall treatment process. To keep up with the rapidly evolving treatment landscape, national-level guidelines have been introduced to standardize patient pathways and ensure prompt diagnosis and treatment. Such strategies depend on efficient and effective communication between relevant multidisciplinary team members and have both improved adherence to treatment guidelines and extended patient survival. This article highlights the value of a multidisciplinary approach to diagnosis and staging, treatment decision making, and adverse event management in NSCLC. IMPLICATIONS FOR PRACTICE: This review highlights the value of a multidisciplinary approach to the diagnosis and staging of non-small cell lung cancer (NSCLC) and makes practical suggestions as to how multidisciplinary teams (MDTs) can be best deployed at individual stages of the disease to improve patient outcomes and effectively manage common adverse events. The authors discuss how a collaborative approach, appropriately leveraging the diverse expertise of NSCLC MDT members (including specialist radiation and medical oncologists, chest physicians, pathologists, pulmonologists, surgeons, and nursing staff) can continue to ensure optimal per-patient decision making as treatment options become ever more specialized in the era of biomarker-driven therapeutic strategies.

Combined Treatment of Non-Small-Cell Lung Cancer Using Shenyi Capsule and Platinum-Based Chemotherapy: A Meta-Analysis and Systematic Review

Background

The efficacy and safety of combined treatment of non-small-cell lung cancer (NSCLC) using Shenyi capsules and platinum-based chemotherapy were comprehensively evaluated.

Methods

A computer-based search was used to identify reports on clinical randomized controlled trials (RCTs) on this combined treatment for NSCLC from the PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP, China Biomedical (CBM), and Wanfang Data electronic databases. The databases were searched from their start to February 2020. The quality of the included studies was evaluated and then crosschecked by two independent evaluators. A meta-analysis was conducted using RevMan5.3.

Results

A total of 27 RCTs involving 2,663 patients were included in the meta-analysis, including 1,380 and 1,283 patients in the treatment and control groups, respectively. The results of the meta-analysis showed that, compared to platinum-based chemotherapy alone, the 1-year survival rate (relative risk (RR) = 1.27, 95% confidence interval (CI) [1.10, 1.47], P < 0.01), 2-year survival rate (RR = 1.35, 95% CI [1.10, 1.65], P < 0.01), objective tumour remission rate (RR = 1.52, 95% CI [1.35, 1.71], P < 0.01), and body CD4⁺/CD8⁺ ratio (standardized mean difference (SMD) = 0.12, 95% CI [0.07, 0.17], P < 0.01) were increased for the combined treatment of NSCLC using Shenyi capsules and platinum-based chemotherapy; moreover, quality of life was also improved (RR = 2.09, 95%CI [1.75, 2.50], P < 0.01) and it reduced leukocyte toxicity (RR = 0.49, 95%CI [0.39, 0.63], P < 0.01), haemoglobin toxicity (RR = 0.48, 95% CI [0.28, 0.81], P < 0.01), platelet toxicity (RR = 0.44, 95% CI [0.28, 0.70], P < 0.01), vomiting reaction (RR = 0.60, 95% CI [0.45, 0.78], P < 0.01), and serum vascular endothelial growth factor level (SMD = -63.67, 95% CI [-67.59, -59.75], P < 0.01).

Conclusions

The treatment of NSCLC using Shenyi capsules together with routine platinum-based chemotherapy could enhance short- and long-term efficacy, improve patient quality of life, alleviate toxicity and side-effects of platinum-based chemotherapeutic drugs, boost body immune function, and inhibit tumour neovascularisation. These findings require further validation in large-sample, high-quality RCTs.

A case report with COVID-19 during perioperative period of lobectomy

RATIONALE

Currently, COVID-19 has made a significant impact on many countries in the world. However, there have been no reported cases of pulmonary lobectomy with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) infection. We are the first to report such a case.

PATIENT CONCERNS

We report a 63-year-old Wuhan male patient with smoking history of 40 cigarettes per day for 40 years. He sought medical consultation for right lower lung nodules found by CT scan.

DIAGNOSES AND INTERVENTIONS

The patient's postoperative pathological diagnosis was squamous cell carcinoma of the right lower lung. On the fourth day after the operation, the real-time reverse transcription polymerase chain reaction test showed a positive result. After the operation, we routinely give symptomatic treatments such as anti-infection, nebulization and oxygen inhalation. We also change antibiotics several times depending on the patient's condition.

OUTCOMES

The patient's condition continued to deteriorate. On the fifth day after surgery, the patient died despite medical treatment.

LESSONS

We are the first to report the diagnosis and treatment process of patients with COVID-19 during perioperative period of lobectomy. It provides a case for the postoperative management of such patients.

Patterns and risks of postoperative recurrence in completely resected EGFR-mutant non-small cell lung cancer: prognostic significance of routine immunohistochemical markers

Background

Recent studies indicate that EGFR-mutant non-small cell lung cancer (NSCLC) is a heterogeneous disease with varying prognosis. In order to design an optimized surveillance strategy and identify potential candidates for adjuvant therapy, the patterns and risks of postoperative recurrence in completely resected EGFR-mutant NSCLC should be investigated, which are currently largely unknown.

Methods

Consecutive patients with curatively resected EGFR-positive NSCLC receiving standard adjuvant chemotherapy without EGFR tyrosine kinase inhibitors (TKI), with or without adjuvant radiotherapy, from January 2007 to December 2017 in our cancer center, were retrospectively reviewed. Prognostic significance of ten routine immunohistochemical (IHC) markers were examined.

Results

After a median follow-up of 32 (range, 5-122) months, disease recurrence occurred in 197 (37.1%) of the 531 enrolled patients. The frequencies of thoracic recurrence, brain recurrence, bone recurrence, abdominal recurrence and neck recurrence, were 69.0%, 20.8%, 20.8%, 7.1% and 6.6%, respectively. Using the Cox regression model, tumor size, Ki67, CK20, and N stage were identified as independent predictors of overall recurrence. A nomogram predicting the 1-, 2-, and 3-year cumulative rate of overall recurrence was then developed and internally validated, with a bias-corrected C-index of 0.723 (95% CI, 0.675 to 0.771) and a small extent of "over-fitting" (0.8%). Risk factors of site-specific recurrence were also discovered. Additionally, using competing risk analyses, N stage, lymphovascular invasion (LVI) and CK5/6 were found as independent predictors of loco-regional recurrence. Among patients with N2-positive disease (n=91), adjuvant radiotherapy tended to prolong disease free survival (DFS) (P=0.067), but not overall survival (OS) (P=0.271).

Conclusions

This study provides the proof of concept of using routine IHC markers, along with common clinical-pathological parameters, in predicting postoperative recurrence among completely resected EGFR-mutant NSCLC. Adjuvant radiotherapy may improve DFS, but hard to prolong OS in N2-positive EGFR-mutant NSCLC without further biomarker-guided patients' selection.

Multidisciplinary consensus statement on the clinical management of patients with stage III non-small cell lung cancer

Stage III non-small cell lung cancer (NSCLC) is a very heterogeneous disease that encompasses patients with resected, potentially resectable and unresectable tumours. To improve the prognostic capacity of the TNM classification, it has been agreed to divide stage III into sub-stages IIIA, IIIB and IIIC that have very different 5-year survival rates (36, 26 and 13%, respectively). Currently, it is considered that both staging and optimal treatment of stage III NSCLC requires the joint work of a multidisciplinary team of expert physicians within the tumour committee. To improve the care of patients with stage III NSCLC, different scientific societies involved in the diagnosis and treatment of this disease have agreed to issue a series of recommendations that can contribute to homogenise the management of this disease, and ultimately to improve patient care.

MiR-218-5p Suppresses the Killing Effect of Natural Killer Cell to Lung Adenocarcinoma by Targeting SHMT1

PURPOSE

Lung adenocarcinoma (LA) is one of the major types of lung cancer. MicroRNAs (miRNAs) play an essential role in regulating responses of natural killer (NK) cells to cancer malignancy. However, the mechanism of miR-218-5p involved in the killing effect of NK cells to LA cells remains poorly understood.

MATERIALS AND METHODS

The expression of miR-218-5p was examined by quantitative real-time polymerase chain reaction (qRT-PCR). Serine hydroxymethyl transferase 1 (SHMT1) level was detected by qRT-PCR or western blots. Cytokines production of interferon-γ (IFN-γ) and tumor necrosis factor-α (TNF-α) were detected by ELISA. The killing effect of NK cells to LA cells was investigated using lactate dehydrogenase cytotoxicity assay kit. The interaction of miR-218-5p and SHMT1 was probed by luciferase activity assay. Xenograft model was established to investigate the killing effect of NK cells in vivo.

RESULTS

miR-218-5p was enhanced and SHMT1 was inhibited in NK cells of LA patients, whereas stimulation of interleukin-2 (IL-2) reversed their abundances. Addition of miR-218-5p reduced IL-2-induced cytokines expression and cytotoxicity in NK-92 against LA cells. Moreover, SHMT1 was negatively regulated by miR-218-5p and attenuated miR-218-5p-mediated effect on cytotoxicity, IFN-γ and TNF-α secretion in IL-2-activated NK cells. In addition, miR-218-5p exhaustion inhibited tumor growth by promoting killing effect of NK cells.

CONCLUSION

miR-218-5p suppresses the killing effect of NK cells to LA cells by targeting SHMT1, providing a potential target for LA treatment by ameliorating NK cells function.

Survival after lobectomy versus sub-lobar resection in elderly with stage I NSCLC: a meta-analysis

BACKGROUND

We present a critical comparison of lobectomy and sub-lobar resection in elderly patients with early stage non-small cell lung cancer using meta-analytical techniques.

METHODS

A literature search was conducted between the period of December 1997 to March 2019 to identify the comparative studies evaluating 1-, 3-, and 5-year survival rates. The pooled odds ratios (OR) and the 95% confidence intervals (95% CI) were calculated with either the fixed or random effect models, respectively.

RESULTS

Six retrospective studies are included in our meta-analysis for a total of 1205 patients. 843 of the individuals were treated with lobectomy, while 362 were treated with sub-lobar resection. We found no significant difference between the lobectomy and the sub-lobar resection in either of the 1-, 3-, or 5-year survival rates.

CONCLUSIONS

This study suggests that in elderly individuals with stage I NSCLC, a sub-lobar resection is statistically equivalent to the lobectomy in terms of 1-, 3-, and 5-year survival rates. Further large-scale randomized studies are needed to confirm our results.

Long noncoding RNA VPS9D1-AS1 overexpression predicts a poor prognosis in non-small cell lung cancer

Long noncoding RNAs (LncRNAs) have been reported to play vital roles in non-small cell lung cancer (NSCLC). Recently, LncRNA/VPS9D1-AS1 has been reported to be overexpressed in various cancers. In this study, we aimed to investigate its expression pattern and clinical significance and further evaluate its prognostic value for NSCLC. VPS9D1-AS1 expression was examined in 184 NSCLC patients using a highly sensitive in situ hybridization protocol (RNAscope), and the expression values were correlated with the clinicopathological features. Another cohort including 12 NSCLC patients was used to validate the differential expression of VPS9D1-AS1 by qRT-PCR. TCGA datasets were further used to validate the main findings. We found that the levels of VPS9D1-AS1 were significantly higher in cancer tissues than in paired normal tissues from both lung squamous cell carcinoma (SCC) and adenocarcinoma (ADC) (P < 0.001). Importantly, the levels of VPS9D1-AS1 in patients with lung SCC were significantly higher than those in patients with lung ADC. The high levels of VPS9D1-AS1 were found to be associated with cancer lymph node metastasis (P = 0.020). Prognostic analysis revealed that the survival time for SCC patients with high levels of VPS9D1-AS1 was significantly shorter than that of patients with low levels of VPS9D1-AS1 (P = 0.007). Therefore, our findings suggest that the overexpression of VPS9D1-AS1 serves as a promising biomarker to predict the prognosis of NSCLC.