Prediction of Spread Through Air Spaces (STAS) By Intraoperative Frozen Section for Patients with cT1N0M0 Invasive Lung Adenocarcinoma: A Multi-Center Observational Study (ECTOP-1016).

OBJECTIVE: To investigate the value of intraoperative assessment of spread through air spaces (STAS) on frozen sections (FS) in peripheral small-sized lung adenocarcinoma. BACKGROUND: Surgical decision-making based on FS diagnosis of STAS may be useful to prevent local control failure after sublobar resection. METHODS: We conducted a multicenter prospective observational study of consecutive patients with cT1N0M0 invasive lung adenocarcinoma to evaluate the accuracy of FS for the intraoperative detection of STAS. The final pathology (FP) diagnosis of STAS was based on corresponding permanent paraffin sections. RESULTS: This study included 878 patients with cT1N0M0 invasive lung adenocarcinoma. A total of 833 cases (95%) were assessable for STAS on FS. 26.4% of the cases evaluated positive for STAS on FP, whereas 18.2% on FS. The accuracy, sensitivity, and specificity of FS diagnosis of STAS were 85.1%, 56.4%, and 95.4%, respectively, with moderate agreement (κ=0.575). Inter-observer agreement was substantial (κ=0.756) among the three pathologists. Subgroup analysis based on tumor size or consolidation-to-tumor ratio all showed moderate agreement for concordance. After rigorous reassessment of false-positive cases, the presence of artifacts may be the main cause of interpretation errors. Additionally, true positive cases showed more high-grade histological patterns and more advanced p-TNM stages than false negative cases. CONCLUSIONS: This is the largest prospective observational study to evaluate STAS on FS in patients with cT1N0M0 invasive lung adenocarcinoma. FS is highly specific with moderate agreement, but is not sensitive for STAS detection. While appropriately reporting STAS on FS may provide surgeons with valuable information for intraoperative decision-making, better approaches are needed.

Development of an Interpretable Deep Learning Model for Pathological Tumor Response Assessment After Neoadjuvant Therapy.

BACKGROUND: Neoadjuvant therapy followed by surgery has become the standard of care for locally advanced esophageal squamous cell carcinoma (ESCC) and accurate pathological response assessment is critical to assess the therapeutic efficacy. However, it can be laborious and inconsistency between different observers may occur. Hence, we aim to develop an interpretable deep-learning model for efficient pathological response assessment following neoadjuvant therapy in ESCC. METHODS: This retrospective study analyzed 337 ESCC resection specimens from 2020-2021 at the Pudong-Branch (Cohort 1) and 114 from 2021-2022 at the Puxi-Branch (External Cohort 2) of Fudan University Shanghai Cancer Center. Whole slide images (WSIs) from these two cohorts were generated using different scanning machines to test the ability of the model in handling color variations. Four pathologists independently assessed the pathological response. The senior pathologists annotated tumor beds and residual tumor percentages on WSIs to determine consensus labels. Furthermore, 1850 image patches were randomly extracted from Cohort 1 WSIs and binarily classified for tumor viability. A deep-learning model employing knowledge distillation was developed to automatically classify positive patches for each WSI and estimate the viable residual tumor percentages. Spatial heatmaps were output for model explanations and visualizations. RESULTS: The approach achieved high concordance with pathologist consensus, with an R^2 of 0.8437, a RAcc_0.1 of 0.7586, a RAcc_0.3 of 0.9885, which were comparable to two senior pathologists (R^2 of 0.9202/0.9619, RAcc_0.1 of 8506/0.9425, RAcc_0.3 of 1.000/1.000) and surpassing two junior pathologists (R^2 of 0.5592/0.5474, RAcc_0.1 of 0.5287/0.5287, RAcc_0.3 of 0.9080/0.9310). Visualizations enabled the localization of residual viable tumor to augment microscopic assessment. CONCLUSION: This work illustrates deep learning's potential for assisting pathological response assessment. Spatial heatmaps and patch examples provide intuitive explanations of model predictions, engendering clinical trust and adoption (Code and data will be available at https://github.com/WinnieLaugh/ESCC_Percentage once the paper has been conditionally accepted). Integrating interpretable computational pathology could help enhance the efficiency and consistency of tumor response assessment and empower precise oncology treatment decisions.

Ten-Year Follow-Up of Lung Cancer Patients with Resected Stage IA Invasive Non-Small Cell Lung Cancer.

OBJECTIVE: The purpose of this study was to assess 10-year follow-up outcomes after surgical resection in patients with stage IA invasive non-small cell lung cancer (NSCLC) based on postoperative pathological diagnosis. METHODS: Patients with stage IA invasive NSCLC who underwent resection between December 2008 and December 2013 were reviewed. Patients were categorized into the pure-ground glass opacity (pGGO), mixed-ground glass opacity (mGGO), and solid groups based on consolidation to tumor ratio (CTR). Postoperative survival and risk of recurrence and developing secondary primary lung cancer were analyzed in each group. RESULTS: Among the 645 stage IA invasive NSCLC, the 10-year overall survival and recurrence-free survival rate was 79.38% and 77.44%, respectively. The 10-year overall survival for pGGO, mGGO, and solid group of patients was 95.08%, 86.21%, and 72.39%, respectively. The respective recurrence-free survival rate was 100%, 89.82%, and 65.83%. Multivariable Cox regression analysis associated tumor size and GGO components with recurrence and younger age, and tumors with GGO components were associated with longer overall survival. The cumulative incidence curve indicated no recurrence of GGO lung cancer ≥ 5 years postoperatively. Our cohort indicated that the number and stations of dissected lymph node did not influence long-term prognosis of IA invasive NSCLC. CONCLUSIONS: Recurrence of invasive stage IA NSCLC with GGO was more prevalent in patients with tumor size >1 cm and CTR > 0.5, occurring within 5 years after surgery. This will provide important evidence for follow-up strategies in these patients.

Comparing a PD-L1 inhibitor plus chemotherapy to chemotherapy alone in neoadjuvant therapy for locally advanced ESCC: a randomized Phase II clinical trial : A randomized clinical trial of neoadjuvant therapy for ESCC.

BACKGROUND: A Phase II study was undertaken to evaluate the safety and efficacy of the neoadjuvant socazolimab, a novel PD-L1 inhibitor, in combination with nab-paclitaxel and cisplatin for locally advanced esophageal squamous cell carcinoma (ESCC). METHODS: Sixty-four patients were randomly divided between the Socazolimab + nab-paclitaxel + cisplatin (TP) arm (n = 32) and the control arm (n = 32), receiving either socazolimab (5 mg/kg intravenously (IV), day 1) or a placebo with nab-paclitaxel (125 mg/m2 IV, day 1/8) and cisplatin (75 mg/m2 IV, day 1) repeated every 21 days for four cycles before surgery. The primary endpoint was major pathological response (MPR), and the secondary endpoints were pathological complete response (pCR), R0 resection rate, event-free survival (EFS), overall survival (OS), and safety. RESULTS: A total of 29 (90.6%) patients in each arm underwent surgery, and 29 (100%) and 28 (98.6%) patients underwent R0 resection in the Socazolimab + TP and Placebo + TP arms, respectively. The MPR rates were 69.0 and 62.1% (95% Confidence Interval (CI): 49.1-84.0% vs. 42.4-78.7%, P = 0.509), and the pCR rates were 41.4 and 27.6% (95% CI: 24.1-60.9% vs. 13.5-47.5%, P = 0.311) in the Socazolimab + TP and Placebo + TP arms, respectively. Significantly higher incidence rates of ypT0 (37.9% vs. 3.5%; P = 0.001) and T downstaging were observed in the Socazolimab + TP arm than in the Placebo + TP arm. The EFS and OS outcomes were not mature. CONCLUSIONS: The neoadjuvant socazolimab combined with chemotherapy demonstrated promising MPR and pCR rates and significant T downstaging in locally advanced ESCC without increasing surgical complication rates. TRIAL REGISTRATION: Registration name (on clinicaltrials.gov): A Study of Anti-PD-L1 Antibody in Neoadjuvant Chemotherapy of Esophageal Squamous Cell Carcinoma. REGISTRATION NUMBER: NCT04460066.

Impact of Prior Cancer History on Outcomes of Resected Lung Cancer.

BACKGROUND: Previous studies concerning the impact of prior cancer on newly diagnosed lung cancer are mainly based on databases and obtained mixed results. Utilizing a large study population, we aimed to reveal this impact. PATIENTS AND METHODS: Lung cancer patients from January 2008 to April 2021 were enrolled. The Kaplan-Meier method was used to perform survival analyses. To investigate the impact of prior cancer, a Cox proportional hazards model was conducted. To minimize the influence of the heterogeneity of prior cancer, stratified analyses were carried out. RESULTS: In total, 17,423 lung cancer patients were reviewed, among which we identified 1469 (8.4%) patients with a history of prior cancer. Cox regression analysis revealed that prior cancer was an independent poor prognostic factor on overall survival (HR = 1.430, 95% CI: 1.147-1.784, p = 0.001) but did not affect lung cancer-specific survival (HR = 1.120, 95% CI: 0.876-1.434, p = 0.366). Interestingly, in further stratified analyses, we found that prior cancer history affected overall survival only in pTNM stage 0/I patients (HR = 1.670, 95% CI: 1.247-2.237, p = 0.001), but not in pTNM stage II/III/IV patients (HR = 1.237, 95% CI: 0.877-1.743, p = 0.226). Similarly, prior cancer was an independent poor prognostic factor on overall survival only for pN0 patients. Subsequently, subgroup analyses indicated that the impact of prior cancer varied in pTNM stage 0/I patients according to the type of prior cancer and the interval time. CONCLUSIONS: Considering that prior cancer affects overall survival in patients with clinically curable lung cancer, clinicians should pay attention to this effect and improve the management of these patients to achieve a better prognosis.

Long-Term Outcomes of Selected Patients with IIIA-N2 Non-small Cell Lung Cancer Receiving Upfront Surgical Resection.

BACKGROUND: Stage IIIA non-small cell lung cancer (NSCLC) is a diverse group that requires multimodality treatment. The aim of this study was to report the long-term outcomes for patients with IIIA-N2 disease. METHODS: We conducted a retrospective review of cases with IIIA-N2 (T1-2N2) NSCLC who underwent upfront surgery. Kaplan-Meier curves and Cox proportional hazard analyses were used to assess the impact of various variables on survival. RESULTS: A total of 475 patients were ultimately included. With a median follow-up time of 108 months, the 5- and 10-year overall survival (OS) rates were 42.2% and 27.7%, respectively. R0 resection was found to be associated with improved progression-free survival (PFS) and OS compared with R1/R2 resection (p = 0.041 for PFS; p = 0.015 for OS). Patients with single-station N2 disease demonstrated significantly better PFS and OS than those with multiple-station N2 disease (p < 0.001 for PFS; p = 0.002 for OS). Following surgical resection, adjuvant therapy was significantly correlated with prolonged PFS and OS compared with those patients without any treatment. However, there was no significant difference in PFS and OS between chemotherapy and radiochemotherapy (p = 0.915 for PFS; p = 0.287 for OS). Patients with EGFR exon 19 deletion had significantly improved OS compared with those with L858R (p = 0.040). CONCLUSIONS: Our study shows promising long-term outcomes for selected patients with stage IIIA-N2 NSCLC treated with upfront surgery followed by adjuvant therapy, especially those with R0 resection and single-station N2. This study sheds light on the potential management and treatment options for this challenging population.

Machine learning to predict occult metastatic lymph nodes along the recurrent laryngeal nerves in thoracic esophageal squamous cell carcinoma.

PURPOSE: Esophageal squamous cell carcinoma (ESCC) metastasizes in an unpredictable fashion to adjacent lymph nodes, including those along the recurrent laryngeal nerves (RLNs). This study is to apply machine learning (ML) for prediction of RLN node metastasis in ESCC. METHODS: The dataset contained 3352 surgically treated ESCC patients whose RLN lymph nodes were removed and pathologically evaluated. Using their baseline and pathological features, ML models were established to predict RLN node metastasis on each side with or without the node status of the contralateral side. Models were trained to achieve at least 90% negative predictive value (NPV) in fivefold cross-validation. The importance of each feature was measured by the permutation score. RESULTS: Tumor metastases were found in 17.0% RLN lymph nodes on the right and 10.8% on the left. In both tasks, the performance of each model was comparable, with a mean area under the curve ranging from 0.731 to 0.739 (without contralateral RLN node status) and from 0.744 to 0.748 (with contralateral status). All models showed approximately 90% NPV scores, suggesting proper generalizability. The pathology status of chest paraesophgeal nodes and tumor depth had the highest impacts on the risk of RLN node metastasis in both models. CONCLUSION: This study demonstrated the feasibility of ML in predicting RLN node metastasis in ESCC. These models may potentially be used intraoperatively to spare RLN node dissection in low-risk patients, thereby minimizing adverse events associated with RLN injuries.

Synthesis and Characterization of Novel Triphenylamine-Containing Electrochromic Polyimides with Benzimidazole Substituents.

Two novel electrochromic aromatic polyimides (named as TPA-BIA-PI and TPA-BIB-PI, respectively) with pendent benzimidazole group were synthesized from 1,2-Diphenyl-N,N'-di-4-aminophenyl-5-amino-benzimidazole and 4-Amino-4'-aminophenyl-4″-1-phenyl-benzimidazolyl-phenyl-aniline with 4,4'-(hexafluoroisopropane) phthalic anhydride (6FDA) via two-step polymerization process, respectively. Then, polyimide films were prepared on ITO-conductive glass by electrostatic spraying, and their electrochromic properties were studied. The results showed that due to the π-π* transitions, the maximum UV-Vis absorption bands of TPA-BIA-PI and TPA-BIB-PI films were located at about 314 nm and 346 nm, respectively. A pair of reversible redox peaks of TPA-BIA-PI and TPA-BIB-PI films that were associated with noticeable color changed from original yellow to dark blue and green were observed in the cyclic voltammetry (CV) test. With increasing voltage, new absorption peaks of TPA-BIA-PI and TPA-BIB-PI films emerged at 755 nm and 762 nm, respectively. The switching/bleaching times of TPA-BIA-PI and TPA-BIB-PI films were 13 s/16 s and 13.9 s/9.5 s, respectively, showing that these polyimides can be used as novel electrochromic materials.

Distribution and concordance of PD-L1 expression by routine 22C3 assays in East-Asian patients with non-small cell lung cancer.

BACKGROUND: Currently, programmed death ligand-1 (PD-L1) expression has been widely applied in clinical trials and real-world clinical practice as a major biomarker for the efficacy of immune-checkpoint inhibitors. The purpose of this study is to reveal the distribution and concordance of PD-L1 expression in a large-scale consecutive cohort from East-Asian patients with non-small cell lung cancer (NSCLC). METHODS: PD-L1 testing was conducted using 22C3 assays, and cases were categorized into the high, low, and no expression of PD-L1 based on the tumor proportion score (TPS). Target-capture next-generation sequencing was used to identify molecular events. RESULTS: A total of 4550 patients and 4622 tests of PD-L1 expression were enrolled. There were 3017 (66.3%) patients with no PD-L1 expression (TPS < 1%), 1013 (22.3%) with low PD-L1 expression (TPS 1-49%), 520 (11.4%) with high PD-L1 expression (TPS ≥ 50%). Higher proportions of positive PD-L1 expression (TPS ≥ 1%) were observed in smokers, males, squamous cell carcinoma, and high-grade lung adenocarcinoma. Further analyses revealed fair agreement in primary and metastatic lesions (kappa = 0.533), poor agreement in multi-focal primary tumors (kappa = 0.045), and good agreement in biopsy and resection samples (kappa = 0.662) / two biopsy samples (kappa = 0.711). Mutational analyses revealed association between high PD-L1 expression (TPS ≥ 50%) and EGFR wild-type, KRAS mutation, ALK rearrangement, and TP53 mutation. CONCLUSION: The study reveals the unique distribution pattern of PD-L1 expression in a large-scale East-Asian cohort with NSCLC, the concordance of multiple PD-L1 tests, and the association between PD-L1 expression and molecular events. The results shed a light on the optimization of PD-L1 testing in clinical practice.

DDX56 modulates post-transcriptional Wnt signaling through miRNAs and is associated with early recurrence in squamous cell lung carcinoma.

BACKGROUND: Early recurrence is a major obstacle to prolonged postoperative survival in squamous cell lung carcinoma (SqCLC). The molecular mechanisms underlying early SqCLC recurrence remain unclear, and effective prognostic biomarkers for predicting early recurrence are needed. METHODS: We analyzed primary tumor samples of 20 SqCLC patients using quantitative proteomics to identify differentially-expressed proteins in patients who experienced early versus late disease recurrence. The expression and prognostic significance of DDX56 was evaluated using a SqCLC tumor tissue microarray and further verified using different online databases. We performed in vitro and in vivo experiments to obtain detailed molecular insight into the functional role of DDX56 in SqCLC. RESULTS: We found that DDX56 exhibited increased expression in tumors of patients who experienced early versus late disease recurrence. Increased DDX56 expression in SqCLC tumors was subsequently confirmed as an independent prognostic factor of poor recurrence-free survival in independent SqCLC cohorts. Functionally, DDX56 promotes SqCLC cell growth and migration in vitro, and xenograft tumor progression in vivo. Mechanistically, DDX56 post-transcriptionally promotes expression of multiple Wnt signaling pathway-related genes, including CTNNB1, WNT2B, and represses a subset of miRNAs, including miR-378a-3p, a known suppressor of Wnt signaling. Detailed analysis revealed that DDX56 facilitated degradation of primary miR-378a, leading to down-regulation of mature miR-378a-3p and thus derepression of the target gene WNT2B. CONCLUSION: We identified DDX56 as a novel independent prognostic biomarker that exerts its oncogenic effects through miRNA-mediated post-transcriptional regulation of Wnt signaling genes to promote early SqCLC recurrence. DDX56 may assist in identifying SqCLC patients at increased risk of early recurrence and who could benefit from Wnt signaling-targeted therapies.

Targeted metabolomics study of early pathological features in hippocampus of triple transgenic Alzheimer's disease male mice.

Alzheimer's disease (AD) is a serious neurodegenerative disease in people of age 65 or above. The detailed etiology and pathogenesis of AD have not been elucidated yet. In this study, the hippocampi of 2- and 6-month-old triple transgenic Alzheimer's disease male mice and age-sex-matched wild-type (WT) mice were analyzed by using targeted metabolomics approach. Compared with WT mice, 24 and 60 metabolites were found with significant differences in 2- and 6-month-old AD mice. Among these, 14 metabolites were found common while 10 metabolites showed consistent variable trends in both groups. These differential metabolites are found associated with amino acid, lipid, vitamin, nucleotide-related base, neurotransmitter and energy metabolisms, and oxidative stress. The results suggest that these differential metabolites might play a critical role in AD pathophysiology, and may serve as potential biomarkers for AD. Moreover, the results highlight the involvement of abnormal purine, pyrimidine, arginine, and proline metabolism, along with glycerophospholipid metabolism in early pathology of AD. For the first time, several differential metabolites are found to be associated with AD in this study. Targeted metabolomics can be used for rapid and accurate quantitative analysis of specific target metabolites associated with AD.

In vivo CRISPR screening unveils histone demethylase UTX as an important epigenetic regulator in lung tumorigenesis.

Lung cancer is the leading cause of cancer-related death worldwide. Inactivation of tumor suppressor genes (TSGs) promotes lung cancer malignant progression. Here, we take advantage of the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-mediated somatic gene knockout in a KrasG12D/+ mouse model to identify bona fide TSGs. From individual knockout of 55 potential TSGs, we identify five genes, including Utx, Ptip, Acp5, Acacb, and Clu, whose knockout significantly promotes lung tumorigenesis. These candidate genes are frequently down-regulated in human lung cancer specimens and significantly associated with survival in patients with lung cancer. Through crossing the conditional Utx knockout allele to the KrasG12D/+ mouse model, we further find that Utx deletion dramatically promotes lung cancer progression. The tumor-promotive effect of Utx knockout in vivo is mainly mediated through an increase of the EZH2 level, which up-regulates the H3K27me3 level. Moreover, the Utx-knockout lung tumors are preferentially sensitive to EZH2 inhibitor treatment. Collectively, our study provides a systematic screening of TSGs in vivo and identifies UTX as an important epigenetic regulator in lung tumorigenesis.

Development and validation of a five-gene model to predict postoperative brain metastasis in operable lung adenocarcinoma.

One of the most common sites of extra-thoracic distant metastasis of nonsmall-cell lung cancer is the brain. Our study was performed to discover genes associated with postoperative brain metastasis in operable lung adenocarcinoma (LUAD). RNA seq was performed in specimens of primary LUAD from seven patients with brain metastases and 45 patients without recurrence. Immunohistochemical (IHC) assays of the differentially expressed genes were conducted in 272 surgical-resected LUAD specimens. LASSO Cox regression was used to filter genes related to brain metastasis and construct brain metastasis score (BMS). GSE31210 and GSE50081 were used as validation datasets of the model. Gene Set Enrichment Analysis was performed in patients stratified by risk of brain metastasis in the TCGA database. Through the initial screening, eight genes (CDK1, KPNA2, KIF11, ASPM, CEP55, HJURP, TYMS and TTK) were selected for IHC analyses. The BMS based on protein expression levels of five genes (TYMS, CDK1, HJURP, CEP55 and KIF11) was highly predictive of brain metastasis in our cohort (12-month AUC: 0.791, 36-month AUC: 0.766, 60-month AUC: 0.812). The validation of BMS on overall survival of GSE31210 and GSE50081 also showed excellent predictive value (GSE31210, 12-month AUC: 0.682, 36-month AUC: 0.713, 60-month AUC: 0.762; GSE50081, 12-month AUC: 0.706, 36-month AUC: 0.700, 60-month AUC: 0.724). Further analyses showed high BMS was associated with pathways of cell cycle and DNA repair. A five-gene predictive model exhibits potential clinical utility for the prediction of postoperative brain metastasis and the individual management of patients with LUAD after radical resection.

Imaging Features Suggestive of Multiple Primary Lung Adenocarcinomas.

BACKGROUND: The tumor-node-metastasis classification system has proposed that lung cancers presenting as multifocal ground-glass nodules (multi-GGN) on computed tomography scan should be staged as multiple primaries instead of intrapulmonary metastases. However, the problem still exists for those synchronous multiple lung adenocarcinomas (SMLA) involving solid lesions. This study aimed to explore the distinct features of SMLA to better define the diagnosis and staging of this disease. METHODS: Between 2008 and 2016, consecutive patients with complete resection of SMLA were prospectively enrolled in the study. The patients were divided into three groups based on CT images as follows: multi-GGN, one solid nodule plus one or more GGNs (solid-GGN), and multiple solid lesions with or without GGN (multi-solid). Clinicopathologic features and survival outcomes were compared between these groups. Multivariate Cox proportional hazards analyses using bootstrap internal validation were performed to identify independent predictors for recurrence-free survival (RFS) and overall survival (OS). RESULTS: Of the 695 patients who met the inclusion criteria, 486 (69.9%) presented with multi-GGN tumor, 124 (17.9%) with solid-GGN tumor, and 85 (12.2%) with multi-solid tumor. The three groups had distinguished clinicopathologic features of gender, smoking history, nodal metastases, tumor size, subtype, and location (all P < 0.001). Multivariate analyses demonstrated that multi-solid tumor was an independent predictor for both decreased RFS [hazard ratio (HR) 2.941; 95% confidence interval (CI) 1.07-8.08; P = 0.036] and poor OS (HR 6.13; 95% CI 1.15-32.63; P = 0.034), but neither RFS (P = 0.384) nor OS (P = 0.811) differed between solid-GGN and multi-GGN tumors. CONCLUSIONS: Both multi-GGN and solid-GGN tumors should be staged as multiple primaries, whereas multi-solid tumor was indicated to be advanced disease.

Integration of whole-genome sequencing and functional screening identifies a prognostic signature for lung metastasis in triple-negative breast cancer.

Lung metastasis is one of the leading causes of death for triple-negative breast cancer (TNBC). We sought to characterize the genetic alterations underlying TNBC lung metastases by integrating whole-genome sequencing and functional screening. Furthermore, we aimed to develop a metastasis-related gene signature for TNBC patients to improve risk stratification. In this prospective observational study, we first conducted whole-genome sequencing of paired primary tumor and lung metastasis from one TNBC patient to identify potential genetic driver alterations. An in vivo gain-of-function screening using an amplified open reading frame library was then employed to screen candidate genes promoting lung metastasis. Finally, we applied Cox proportional hazard regression modeling to develop a prognostic gene signature from 14 candidate genes in TNBC. Compared to the primary tumor, copy number amplifications of chromosomes 3q and 8q were identified in the lung metastasis. We discovered an enrichment of 14 genes from chromosomes 3q and 8q in mouse lung metastases model. We further developed and validated a four-gene signature (ENY2, KCNK9, TNFRSF11B and KCNMB2) that predicts recurrence-free survival and lung metastasis in TNBC. Our data also demonstrated that upregulated expression of ENY2 could promote invasion and lung metastasis of TNBC cells both in vitro and in vivo. In conclusion, our study reveals functional genes with copy number amplifications among chromosome 3q and 8q in lung metastasis of TNBC. And we develop a functional gene signature that can effectively stratify patients into low- and high-risk subgroups of recurrence, helping frame personalized treatments for TNBC.

Frequency and clinical significance of NF1 mutation in lung adenocarcinomas from East Asian patients.

NF1 is a tumor suppressor gene that negatively regulates Ras signaling. NF1 deficiency plays an important role in carcinogenesis. To investigate the frequency and clinical significance of NF1 mutation, we examined mutation status of NF1, TP53, LKB1 and RB1 in 704 surgically resected lung adenocarcinomas from East Asian patients using semiconductor-based Ion Torrent sequencing platform. Common driver events, including mutations in EGFR, KRAS, HER2, BRAF, MET, and fusions affecting ALK, RET and ROS1, were also concurrently detected. The correlation between NF1 mutations and clinicomolecular features of patients was further evaluated. Among 704 patients, 42 NF1 mutations were found in 33 patients (33/704, 4.7%), including 14 patients harboring EGFR/NF1 comutations (14/33, 42.4%). Comparing with EGFR-mutant patients, patients harboring NF1 mutations were closely associated with solid component subtype (p = 0.028). Comparing with KRAS mutations, NF1 mutations were found more common in female and never smokers (p = 0.003 and p = 0.004, respectively). Kaplan-Meier survival analysis revealed that patients harboring NF1 mutation had similar disease-free survival (DFS) and overall survival (OS) with patients with KRAS mutation. Although frequently overlapped with EGFR mutation, patients harboring NF1 mutation had significantly shorter DFS (p = 0.019) and OS (p = 0.004) than patients with EGFR mutation. During follow-up, one female patient with EGFR exon 19 deletion and NF1 Q1815X comutation showed poor response to EGFR TKIs (Gefitinib and Osimertinib) after disease relapse. In conclusion, NF1 mutations define a unique molecular and clinicopathologic subtype of lung adenocarcinoma. Examination of NF1 mutation may contribute to molecular subtyping and therapeutic intervention of lung adenocarcinoma.

tRNA-based prognostic score in predicting survival outcomes of lung adenocarcinomas.

As the most abundant noncoding RNA in cells, tRNA plays an important role in tumorigenesis and development. The report of tRNA on the pathogenesis of lung adenocarcinoma is rare. It is of great clinical significance to explore the relationship between tRNA expression and prognosis of lung adenocarcinoma. The expression level of tRNAs in lung adenocarcinoma tissues and paracarcinoma tissues was detected using a tRNA RT-qPCR array. A total of 104 lung adenocarcinomas were included in the analysis of the correlation between candidate tRNAs expression and prognosis. A tRNA-based prognostic model was constructed and validated using Cox proportional hazards regression. A nomogram was built to help clinicians develop treatment strategies. We screened a series of differentially expressed tRNAs between lung adenocarcinoma tissues and paracarcinoma tissues. Among these tRNAs, tRNAAsnATT , tRNAIleAAT , tRNALeuTAA , mt-tRNATrpTCA , mt-tRNALeuTAA , tRNAProAGG , tRNALysCTT-1 and tRNALeuAAG were associated with the clinicopathological characteristics of lung adenocarcinoma. tRNALysCTT-1 , mt-tRNASerGCT and tRNATyrATA were associated with cancer-specific survival. We constructed a prognostic model for lung adenocarcinoma using specific tRNA expression levels as reference factors. Multivariate analyses showed that tRNA-based prognostic score was a significant and important prognostic factor. The prognostic model based on the tRNAs expression signatures can help predict the prognosis of patients with lung adenocarcinoma.

Predicting the Value of Adjuvant Therapy in Esophageal Squamous Cell Carcinoma by Combining the Total Number of Examined Lymph Nodes with the Positive Lymph Node Ratio.

BACKGROUND: The value of adjuvant therapy for esophageal squamous cell carcinoma (ESCC) has been controversial, at least partially due to the lack of efficient criteria for selecting suitable patients. This study aimed to explore the existence of parameters related to lymph node (LN) status that can predict the value of adjuvant therapy in ESCC. METHODS: The study included 298 patients with ESCC who had undergone radical esophagectomy with lymphadenectomy. Adjuvant therapy was defined as reception of adjuvant chemotherapy, radiotherapy, or chemoradiotherapy. For the study, LN ratio (LNR), total number of resected LNs (TLNs), and pN stage were selected for Cox regression analyses, including their correlations and prognostic values for survival. Log-rank tests were used to compare the survival rates of the patients with and without adjuvant therapy stratified by pN stage, TLNs, LNR, or their combinations. RESULTS: The independent prognostic factors for survival were TLNs, LNR, and pN stage. Whereas pN stage was significantly related to TLNs and LNR, TLNs were not correlated with LNR. The survival rates between the patients with and those without adjuvant therapy stratified by pN stage, TLNs, or LNR did not differ significantly. We used the median values of TLNs and LNR to group the patients into four groups. The patients in the group with fewer TLNs and higher LNR who had undergone adjuvant therapy showed a significantly better survival than those without adjuvant therapy (p = 0.030). CONCLUSIONS: In contrast to TLNs, LNR, and pN stage as single factors, the combination of TLNs and LNR can predict the value of adjuvant therapy.

Proteomic analysis of plasma exosomes to differentiate malignant from benign pulmonary nodules.

BACKGROUND: It is difficult to distinguish benign pulmonary nodules (PNs) from malignant PNs by conventional examination. Therefore, novel biomarkers that can identify the nature of PNs are needed. Exosomes have recently been identified as an attractive alternative approach since tumor-specific molecules can be found in exosomes isolated from biological fluids. METHODS: Plasma exosomes were extracted via the exoEasy reagent method. The major proteins from plasma exosomes in patients with PNs were identified via labelfree analysis and screened for differentially expressed proteins. A GO classification analysis and KEGG pathway analysis were performed on plasma exosomal protein from patients with benign and malignant PNs. RESULTS: Western blot confirmed that protein expression of CD63 and CD9 could be detected in the exosome extract. Via a search of the human Uniprot database, 736 plasma exosome proteins from patients with PNs were detected using high-confidence peptides. There were 33 differentially expressed proteins in the benign and malignant PNs. Of these, 12 proteins were only expressed in the benign PNs group, while 9 proteins were only expressed in the malignant PNs group. We further obtained important information on signaling pathways and nodal proteins related to differential benign and malignant PNs via bioinformatic analysis methods such as GO, KEGG, and String. CONCLUSIONS: This study provides a new perspective on the identification of novel detection strategies for benign and malignant PNs. We hope our findings can provide clues for the identification of benign and malignant PNs.