疏肝肺积方结合心理干预对原发性肺癌患者抑郁、焦虑的影响

Micro-RNAs are approximately 21-25-nucleotide-long noncoding RNAs that regulate gene expression primarily at the post-transcriptional level in animals. Here, we report that micro-RNA-1 (miR-1), abundant in the cardiac and smooth muscles, is expressed in the lung and is down-regulated in human primary lung cancer tissues and cell lines. In situ hybridization demonstrated localization of miR-1 in bronchial epithelial cells. The tumor suppressor C/EBPalpha, frequently suppressed in lung cancer, reactivated miR-1 expression in the lung cancer cells. Repressed miR-1 was also activated in lung cancer cells upon treatment with a histone deacetylase inhibitor. These observations led us to examine the antitumorigenic potential of miR-1 in lung cancer cells. Expression of miR-1 in nonexpressing A549 and H1299 cells reversed their tumorigenic properties, such as growth, replication potential, motility/migration, clonogenic survival, and tumor formation in nude mice. Exogenous miR-1 significantly reduced expression of oncogenic targets, such as MET, a receptor tyrosine kinase, and Pim-1, a Ser/Thr kinase, frequently up-regulated in lung cancer. Similarly, the levels of two additional targets, FoxP1, a transcription factor with oncogeneic property, and HDAC4 that represses differentiation-promoting genes, were reduced in miR-1-expressing cells. Conversely, depletion of miR-1 facilitated N417 cell growth with concomitant elevation of these targets. Further, ectopic miR-1 induced apoptosis in A549 cells in response to the potent anticancer drug doxorubicin. Enhanced activation of caspases 3 and 7, cleavage of their substrate PARP-1, and depletion of anti-apoptotic Mcl-1 contributed to the sensitivity of miR-1-expressing cells to doxorubicin. Thus, miR-1 has potential therapeutic application against lung cancers.

Informing Patient Surveillance for the Growing Number of Survivors of Lung Cancer

MULTIDISCIPLINARY APPROACH TO RECURRENCE AFTER RESECTION OF PRIMARY LUNG CANCER

Commentary: Postrecurrence survival in patients with lung cancer after curative surgery warrants systematic investigation to optimize management strategies

Synchronous Primary Lung Cancer, Breast Cancer Recurrence, and Mediastinal Silicon-Induced Lymphadenitis

The European Society of Thoracic Surgeons (ESTS) registry was created 10 years ago and represents an international database collecting thoracic surgery procedures from European contributors. The purpose of the present report was to offer an overview of baseline and surgical characteristics and outcomes of patients submitted to lung resections for malignant lung disease as derived from the ESTS registry. We retrieved data about all lung resections from 2007 to 2016 performed for primary and metastatic (secondary) lung cancer. We evaluated the baseline characteristics and the surgical management of this population. Within the subgroup of patients affected by primary lung cancer, we described the preoperative mediastinal staging management and the final pathological stage of disease. Finally, we analysed the morbidity and mortality rates for the cohort of patients submitted to anatomic lung resections for primary or secondary lung cancer. Outcomes were also evaluated in relation to several risk factors: type of resection, age, comorbidity, predicted postoperative forced expiratory volume in 1 s and surgical approach. We selected 62 774 patients submitted to lung resections (male 66.5%, median age 64 years). For the entire population, median predicted postoperative forced expiratory volume in 1 s was 73.3% (interquartile range: 59, 87.6), 33.8% of patients had cardiac comorbidities and 17.3% had other comorbidities. Among the patients with primary lung cancer (51 931 patients), 50.8% had Stage I disease and 23.2% Stage II disease; preoperative invasive mediastinal staging was performed in 70.3% of patients with computed tomography scan nodal enlargement and positron emission tomography scan nodal uptake. After anatomical lung resection (51 756 patients), overall morbidity was 18.5% and mortality (30 days or in-hospital) was 2.6%. Extent of resection, age ≥75 years, presence of cardiac comorbidity, predicted postoperative forced expiratory volume in 1 s <70% and open approach instead of video-assisted thoracic surgery were associated with worse outcomes. The results of the present report represent reliable European benchmarks for comparing the activities and outcomes of single institutions and surgeons at an international level.

Neutrophils are associated with developing cancer lesions and are the main immune component of primary non-small cell lung cancer (NSCLC). Multiple studies support the notion that tumor associated neutrophils (TANs) can promote tumor progression. We hypothesize that there is a hierarchy of molecular cues produced by developing lung cancers that guide circulating neutrophils to infiltrate the tumor microenvironment and become TANs. Identifying these cues may permit modulation of neutrophil infiltration within developing lung cancers and may thereby act as an immunotherapeutic tool to suppress cancer progression and improve response to existing therapeutics. To this end, we profiled 5 established NSCLC cell lines representing the common NSCLC subtypes using a qRT-PCR 84 gene panel (A549; KRAS mutant, PC9; EGFR mutant, H1993; MET amplification, H3122; EML4-ALK translocation, HCC78; ROS1 translocation). We focused on 4 of the most commonly upregulated genes in all cell lines, which were osteopontin (Spp1), vascular endothelial growth factor A (VEGF-A), macrophage inhibitory factor (MIF), and C-X-C motif ligand 1 (CXCL1). After confirming protein expression of these targets by western blot, we performed shRNA knock down (KD) of these genes and tested the migration of neutrophils towards treated and control cell lines in a novel microfluidic device that allows increased throughput studies of neutrophil attractants. Findings from KD experiments were confirmed via antibody-mediated inhibition. We observed a 3-fold increase of neutrophil migration to the A549 cancer cell line compared to the serum free control (p=0.0265). Furthermore, this increase was inhibited in Spp1 (64% decrease), MIF (84%), VEGF (82%) KDs and their corresponding neutralizing antibodies. We have therefore identified 4 proteins that play a key role in neutrophil recruitment to NSCLC cell lines in vitro and have demonstrated the application of a simple microfluidic device to test neutrophil migration patterns. This data provides the basis for in vivo investigations to elucidate the key molecular cues for neutrophil infiltration within developing lung cancers. Citation Format: Claire Wang, Roni Rayes, Jack Mouhanna, Betty Giannias, Arvind Chandrasekaran, Rachel Mot, Christopher Moraes, Sidong Huang, Jonathan Cools-Lartigue, Nicholas Bertos, Lorenzo Ferri, Jonathan Spicer. Molecular drivers of neutrophil recruitment to primary non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1099.

SC02.01 Multiple Primary Lung Cancers Versus Lung Metastases: Pathological Differential Diagnosis

Metachronous lung cancer: the role of improved postoperative surveillance

Although antibodies targeting the immune checkpoint protein programmed death-1 (PD-1) exert therapeutic effects in patients with primary or metastatic non-small cell lung cancer (NSCLC), the majority of patients exhibit partial or complete resistance to anti-PD1 treatment. Thus, the aim of the present study was to identify reliable biomarkers for predicting the response to anti-PD-1 therapy. The present study analyzed tumor specimens isolated from 24 patients (13 with primary and 11 with metastatic NSCLC) prior to treatment with approved PD1-targeting antibodies. The expression profile of 395 immune-related genes was examined using RNA immune-oncology panel sequencing. The results demonstrated that six immune-related differently expressed genes (DEGs), including HLA-F-AS1, NCF1, RORC, DMBT1, KLRF1 and IL-18, and five DEGs, including HLA-A, HLA-DPA1, TNFSF18, IFI6 and PTK7, may be used as single biomarkers for predicting the efficacy of anti-PD-1 treatment in patients with primary and with metastatic NSCLC, respectively. In addition, two DEG sets comprising either six (HLA-F-AS1, NCF1, RORC, DMBT1, KLRF and IL-18) or two (HLA-A and TNFSF18) DEGs as potential combination biomarkers for predicting the efficacy of anti-PD-1 therapy in patients with NSCLC. Patients with a calculated expression level of the DEG sets >6.501 (primary NSCLC) or >6.741 (metastatic NSCLC) may benefit from the anti-PD-1 therapy. Overall, these findings provided a basis for the identification of additional biomarkers for predicting the response to anti-PD-1 treatment.

To differentiate the primary small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) for patients with brain metastases (BMs) based on a deep learning (DL) model using contrast-enhanced magnetic resonance imaging (MRI) T1 weighted (T1CE) images. Out of 711 patients with BMs of lung cancer origin (SCLC 232, NSCLC 479), the MRI datasets of 192 patients (lesions' widths and heights > 30 pixels) with BMs from lung cancer (73 SCLC and 119 NSCLC) confirmed pathologically were enrolled, retrospectively. A typical convolutional neural network ResNet18 was applied for the automatic classification of BMs lesions from lung cancer based on T1CE images, with training and testing groups randomized per patient to eliminate learning bias. A 5-fold cross-validation was performed to evaluate the classification of the model. The receiver operating characteristic (ROC) curve, accuracy, precision, recall and f1 score were calculated. For a 5-fold cross-validation test, the DL model achieved AUCs of 0.8019 and 0.8024 for SCLC and NSCLC patients with BMs, respectively, and a mean overall accuracy of 0.7515±0.04. The DL model performed well in differentiating the primary SCLC and NSCLC with BMs. The proposed DL model is feasible and effective in differentiating the pathological subtypes of SCLC and NSCLC causing BMs, which may be used as a new tool for oncologists to diagnose noninvasively BMs and guide therapy based on the imaging structure of tumors.

Introduction: Lung cancer is the leading cause of cancer death in the U.S. Despite recent survival improvements, racial and socioeconomic disparities still exist in lung cancer incidence and survival. Furthermore, recent studies showed that lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). While racial and socioeconomic disparities have long been examined for lung cancer survival and incidence, little is known about their impacts on SPLC risk among lung cancer survivors. This study evaluated the disparities in SPLC incidence by calculating the standardized incidence ratio (SIR) of the observed SPLC incidence versus the expected incidence of initial primary lung cancer (IPLC) across different socioeconomic, acculturation, and smoking-related factors using county-level data obtained from the Surveillance, Epidemiology, and End Results Program (SEER). Methods: We identified 158,018 patients diagnosed with IPLC between 2000 and 2013 in SEER. SPLC was defined as a newly developed primary lung cancer after 2 years from IPLC diagnosis and was followed through 2018. The SIR was calculated as the ratio of the observed SPLC incidence versus the expected incidence of IPLC in the general population across different factors. Indicators of socioeconomic status, acculturation factors, and smoking prevalence in SEER were derived from county-level data using the American Community Survey and the Behavioral Risk Factor Surveillance System (BRFSS). The quintiles of these indicators were created using the data obtained across all 3,142 valid U.S. counties. We applied the Pearson's chi-squared test to evaluate the difference in SIRs across quintiles of the indicators we created, applying a statistical significance of α &amp;lt; 0.005 after adjusting for multiple testing. Results: Among 158,018 IPLC patients, 10,650 (6.7%) developed SPLC over 626,853 person-years. The incidence of SPLC was 6 times higher than the IPLC incidence in the general population, with an overall SIR of 6.2 (95% Confidence Interval (CI): 6.09-6.32). Notably, the SIR, i.e., the ratio between the SPLC incidence and the IPLC incidence, was significantly higher among individuals who live in counties with the lowest quintile of median family income (&amp;lt;$51,770) versus the highest quintile (&amp;gt;$74,331) (SIR 7.18 versus 6.10, P&amp;lt;1 × 10−6). Furthermore, the ratio between the SPLC versus the IPLC incidence was highest (SIR 8.01, CI: 7.36-8.71) among those who live in counties with the highest quintile of smoking prevalence (&amp;gt;29.6%) versus SIR of 5.77 (CI: 5.63-5.91) with the lowest quintile of smoking prevalence (&amp;lt;20.4%) (P=3.4 × 10−3). Race/ethnicity and acculturation factors, including immigration status, did not achieve statistical significance. Discussion: Significant disparities exist in SPLC incidence among lung cancer survivors who live in areas with a low median family income and high smoking prevalence. Targeted SPLC surveillance for lung cancer survivors from an underserved population would be needed to reduce the existing disparities. Citation Format: Eunji Choi, Sophia J. Luo, Jacqueline V. Aredo, Joel W. Neal, Leah M. Backhus, Heather A. Wakelee, Summer S. Han. Disparities in risk of second primary lung cancer among lung cancer patients in the United States [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-130.

Stereotactic Body Radiation Therapy to Multiple Sites of Intrathoracic Disease: A Multi-Institutional Analysis

Primary and metastatic lung cancer is a leading cause of cancer-related death and novel therapies are urgently needed. Epidermal growth factor receptor (EGFR) and death receptor (DR) 4/5 are both highly expressed in primary and metastatic non-small cell lung cancer (NSCLC); however, targeting these receptors individually has demonstrated limited therapeutic benefit in patients. In this study, we created and characterized diagnostic and therapeutic stem cells (SC), expressing EGFR-targeted nanobody (EV) fused to the extracellular domain of death DR4/5 ligand (DRL) (EVDRL) that simultaneously targets EGFR and DR4/5, in primary and metastatic NSCLC tumor models. We show that EVDRL targets both cell surface receptors, and induces caspase-mediated apoptosis in a broad spectrum of NSCLC cell lines. Utilizing real-time dual imaging and correlative immunohistochemistry, we show that allogeneic SCs home to tumors and when engineered to express EVDRL, alleviate tumor burden and significantly increase survival in primary and brain metastatic NSCLC. This study reports mechanistic insights into simultaneous targeting of EGFR- and DR4/5 in lung tumors and presents a promising approach for translation into the clinical setting.

Lung cancer can be classified into two main categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), which are different in treatment strategy and survival probability. The lung CT images of SCLC and NSCLC are similar such that their subtle differences are hardly visually discernible by the human eye through conventional imaging evaluation. We hypothesize that SCLC/NSCLC differentiation could be achieved via computerized image feature analysis and classification in feature space, as termed a radiomic model. The purpose of this study was to use CT radiomics to differentiate SCLC from NSCLC adenocarcinoma. Patients with primary lung cancer, either SCLC or NSCLC adenocarcinoma, were retrospectively identified. The post-diagnosis pre-treatment lung CT images were used to segment the lung cancers. Radiomic features were extracted from histogram-based statistics, textural analysis of tumor images and their wavelet transforms. A minimal-redundancy-maximal-relevance method was used for feature selection. The predictive model was constructed with a multilayer artificial neural network. The performance of the SCLC/NSCLC adenocarcinoma classifier was evaluated by the area under the receiver operating characteristic curve (AUC). Our study cohort consisted of 69 primary lung cancer patients with SCLC (n = 35; age mean ± SD = 66.91± 9.75 years), and NSCLC adenocarcinoma (n = 34; age mean ± SD = 58.55 ± 11.94 years). The SCLC group had more male patients and smokers than the NSCLC group (P < 0.05). Our SCLC/NSCLC classifier achieved an overall performance of AUC of 0.93 (95% confidence interval = [0.85, 0.97]), sensitivity = 0.85, and specificity = 0.85). Adding clinical data such as smoking history could improve the performance slightly. The top ranking radiomic features were mostly textural features. Our results showed that CT radiomics could quantitatively represent tumor heterogeneity and therefore could be used to differentiate primary lung cancer subtypes with satisfying results. CT image processing with the wavelet transformation technique enhanced the radiomic features for SCLC/NSCLC classification. Our pilot study should motivate further investigation of radiomics as a non-invasive approach for early diagnosis and treatment of lung cancer.