Integrative Analysis of Bioinformatics and Machine Learning Algorithms Identifies a Novel Diagnostic Model Based on Costimulatory Molecule for Predicting Immune Microenvironment Status in Lung Adenocarcinoma.

Costimulatory molecules are an indispensable signal for activating immune cells. However, the features of many costimulatory molecule genes (CMGs) in lung adenocarcinoma (LUAD) are poorly understood. This study systematically explored expression patterns of CMGs in the tumor immune microenvironment (TIME) status of patients with LUAD. Their expression profiles were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Two robust TIME subtypes ("hot" and "cold") were classified by K-means clustering and estimation of stromal and immune cells in malignant tumor tissues using expression data. The "hot" subtype presented higher infiltration in activated immune cells and enrichments in the immune cell receptor signaling pathway and adaptive immune response. Three CMGs (CD80, LTB, and TNFSF8) were screened as final diagnostic markers by means of Least Absolute Shrinkage Selection Operator and Support Vector Machine-Recursive Feature Elimination algorithms. Accordingly, the diagnostic nomogram for predicting individualized TIME status showed satisfactory diagnostic accuracy in The Cancer Genome Atlas training cohort as well as GSE31210 and GSE180347 validation cohorts. Immunohistochemistry staining of 16 specimens revealed an apparently positive correlation between the expression of CMG biomarkers and pathologic response to immunotherapy. Thus, this diagnostic nomogram provided individualized predictions in TIME status of LUAD patients with good predictive accuracy, which could serve as a potential tool for identifying ideal candidates for immunotherapy.

The Effects of Drug Exposure and Single Nucleotide Polymorphisms on Aaptinib-Induced Severe Toxicities in Solid Tumors.

To investigate the value of drug exposure and host germline genetic factors in predicting apatinib (APA)-related toxicities. METHOD: In this prospective study, plasma APA concentrations were quantified using liquid chromatography with tandem mass spectrometry, and 57 germline mutations were genotyped in 126 advanced solid tumor patients receiving 250 mg daily APA, a vascular endothelial growth factor receptor II inhibitor. The correlation between drug exposure, genetic factors, and the toxicity profile was analyzed. RESULTS: Non-small cell lung cancer (NSCLC) was more prone to APA-related toxicities and plasma concentrations of APA, and its main metabolite M1-1 could be associated with high-grade adverse events (AEs) (P < 0.01; M1-1, P < 0.01) and high-grade antiangiogenetic toxicities (APA, P = 0.034; P < 0.05), including hypertension, proteinuria, and hand-foot syndrome, in the subgroup of NSCLC. Besides, CYP2C9 rs34532201 TT carriers tended to have higher levels of APA (P < 0.001) and M1-1 (P < 0.01), whereas CYP2C9 rs1936968 GG carriers were predisposed to higher levels of M1-1 (P < 0.01). CONCLUSION: Plasma APA and M1-1 exposures were able to predict severe AEs in NSCLC patients. Dose optimization and drug exposure monitoring might need consideration in NSCLC patients with CYP2C9 rs34532201 TT and rs1936968 GG. SIGNIFICANCE STATEMENT: Apatinib is an anti-VEGFR2 inhibitor for the treatment of multiple cancers. Though substantial in response, apatinib-induced toxicity has been a critical issue that is worth clinical surveillance. Few data on the role of drug exposure and genetic factors in apatinib-induced toxicity are available. Our study demonstrated a distinct drug-exposure relationship in NSCLC but not other tumors and provided invaluable evidence of drug exposure levels and single nucleotide polymorphisms as predictive biomarkers in apatinib-induced severe toxicities.

Metastasis pattern and prognosis in children with neuroblastoma.

BACKGROUND: We aimed to investigate the different metastases and prognoses of neuroblastoma (NB) and determine the risk factors of metastasis. METHOD: Data of 1224 patients with NB were obtained from the Surveillance, Epidemiology and End Results database (2010-2018). Pearson's chi-square test, Kaplan-Meier analysis, multivariable logistic regression and Cox regression analysis were used to determine the factors associated with prognosis. RESULTS: The overall incidence of NB was an age-adjusted rate of 8.2 patients per 1,000,000 children. In total, 1224 patients were included in our study, with 599 patients (48.9%) exhibiting distant metastases. Compared to patients with non-metastatic NB, a greater proportion of patients with metastatic NB were under 1 year, male, had an adrenal primary site, unilateral tumour, a tumour size > 10 cm, neuroblastoma-not otherwise specified (NB-NOS), second malignant neoplasms and were more likely to choose radiotherapy and chemotherapy. Multivariate Cox regression showed that metastasis was an independent risk factor for overall survival (OS) and cancer-specific survival (CSS). The survival rate of non-metastatic patients with NB was better than those with metastasis (OS: hazard ratio (HR): 0.248, P < 0.001; CSS: HR: 0.267, P < 0.001). The bone and liver were the two most common isolated metastatic sites in NB. However, no statistical difference was observed in OS and CSS between the only bone metastasis group, only liver metastasis group and bone metastasis combined with liver metastasis group (all P > 0.05). Additionally, age at diagnosis > 1 year (odds ratio (OR): 3.295, P < 0 .001), grades III-IV (OR: 26.228, P < 0 .001) and 5-10 cm tumours (OR: 1.781, P < 0 .001) increased the risk of bone metastasis of NB. Moreover, no surgical treatment (OR: 2.441, P < 0 .001) increased the risk of liver metastasis of NB. CONCLUSION: Metastatic NB has unique clinicopathological features, with the bone and liver as the most common single metastatic sites of NB. Therefore, more aggressive treatment is recommended for high-risk children with NB displaying distant metastases.

Evaluation of Fibrin Sealant in Prevention of Cervical Anastomotic Leakage After McKeown Esophagectomy: A Single-Center, Retrospective Study.

BACKGROUND: Anastomotic leakage remains an issue after esophagectomy for patients with esophageal or esophagogastric junction cancer. Previous studies have indicated that the intraoperative application of fibrin sealant may reduce the incidence of postoperative anastomotic leakage. This retrospective study was aimed to evaluate the efficacy and safety of fibrin sealant in the prevention of anastomotic leakage in patients undergoing McKeown esophagectomy. METHODS: We designed a single-center, retrospective study. Between January 2018 and December 2019, 227 patients with esophageal or esophagogastric junction cancer undergoing McKeown esophagectomy performed by our team were retrospectively identified, of whom 86 patients were included in the FS group and 141 patients were included in the control group. Intraoperatively, 2.5 ml of porcine fibrin sealant was applied circumferentially to the cervical anastomosis after the anastomosis was created in the FS group. The primary outcome was the incidence of cervical anastomotic leakage within the first three months after surgery. RESULTS: The differences in baseline clinical characteristics between the two groups were not significant except for a history of drinking. In the FS group, the postoperative cervical anastomotic leakage rate was lower (FS group: 4.7% [4 of 82] vs. control group: 19.9% [28 of 141], p < 0.01). Multivariate logistic regression showed that the intraoperative application of fibrin sealant was an independent protective factor for anastomotic leakage (OR 0.169, 95% CI 0.055-0.515, p = 0.002). CONCLUSIONS: The intraoperative application of fibrin sealant could possibly prevent cervical anastomotic leakage after McKeown esophagectomy with satisfactory safety. Further prospective clinical trials are warranted.

Endobronchial Ultrasound Improves Evaluation of Recurrent Laryngeal Nerve Lymph Nodes in Esophageal Squamous Cell Carcinoma Patients.

BACKGROUND: The bilateral recurrent laryngeal nerve (RLN) lymph nodes are the most common metastatic site for esophageal squamous cell carcinoma (ESCC); however, the RLNs are susceptible to injury during dissection. Clinically, there is an urgent need to determine an effective diagnostic method for RLN nodes to help achieve selective nodal dissection and avoid potential serious complications by performing more conservative surgery for those with nonmetastatic nodes. Here, we innovatively applied endobronchial ultrasonography (EBUS) and investigated its diagnostic performance for preoperative evaluation of RLN nodes in ESCC patients. PATIENTS AND METHODS: All 81 enrolled ESCC patients underwent preoperative EBUS and CT examinations. The ability of EBUS and CT to detect RLN node metastasis was evaluated based on the resulting sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: The diagnostic performance of EBUS was superior to that of CT; in particular, EBUS of the left RLN (L-RLN) nodes presented the best sensitivity, specificity, PPV, NPV, and accuracy compared with EBUS evaluations of the right RLN (R-RLN) nodes, CT of the L-RLN and R-RLN nodes. Moreover, EBUS combined with CT increased the NPV relative to that of EBUS or CT alone, promoting the ability to identify true-negative RLN nodes. In particular, the NPVs of the combined modality were 100% for both the L- and R-RLN nodes in early-T-stage (T1-T2) ESCC. CONCLUSIONS: EBUS is an efficient tool for RLN node evaluation, and the combination with CT may provide better guidance for selective RLN node dissection in ESCC patients.

High Biologically Effective Dose Radiotherapy for Brain Metastases May Improve Survival and Decrease Risk for Local Relapse Among Patients With Small-Cell Lung Cancer: A Propensity-Matching Analysis.

To evaluate whether high biologically effective dose (BED) radiotherapy improves local control and survival outcomes for patients with brain metastases (BMs) from small-cell lung cancer (SCLC) and to determine possible prognostic factors. From January 1998 to June 2018, 250 patients with BM from SCLC were retrospectively analyzed. The Cutoff Finder program was used to classify patients by BED. Overall survival (OS) and BM progression-free survival (BM-PFS) were analyzed using the Kaplan-Meier method and log-rank test. A Cox regression model was used to calculate the hazard ratio and 95% CI for prognostic factors for OS among the study population and propensity score (PS)-matched patients. A BED of 47.4 was taken as the optimal cutoff value. Both OS and BM-PFS were significantly improved in the high-BED (>47.4 Gy) than in the low-BED (≤47.4 Gy) group (median OS: 17.5 months vs 9.5 months, P < .001, median BM-PFS: 14.4 months vs 8.3 months, P < .001). Biologically effective dose (P < .001), Eastern Cooperative Oncology Group performance status (P = .047), smoking (P = .005), and pleural effusion (P = .004) were independent prognostic factors for OS. Propensity score matching with a ratio of 1:2 resulted in 57 patients in the high-BED group and 106 patients in the low-BED group. In the PS-matched cohort, OS and BM-PFS were significantly prolonged in the high-BED group compared with the low-BED group (P < .001). Biologically effective dose >47.4 Gy improves survival among patients with BM from SCLC. Eastern Cooperative Oncology Group score, smoking, and pleural effusion independently affect OS of SCLC patients with BM.

Mutation Profile of Resected EGFR-Mutated Lung Adenocarcinoma by Next-Generation Sequencing.

BACKGROUND: The efficacy of adjuvant targeted therapy for operable lung cancer is still under debate. Comprehensive genetic profiling is needed for detecting co-mutations in resected epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma (ADC), which may interfere the efficacy of adjuvant tyrosine kinase inhibitor (TKI) treatment. MATERIALS AND METHODS: Mutation profiling of 416 cancer-relevant genes was conducted for 139 resected stage I-IIIa lung ADCs with EGFR mutations using targeted next-generation sequencing. Co-mutation profiles were systematically analyzed. RESULTS: Rare EGFR alterations other than exon 19 deletion and L858R, such as L861Q (∼3%) and G719A (∼2%), were identified at low frequencies. Approximately 10% of patients had mutations in EGFR exon 20 that could confer resistance to first-generation TKIs. Ninety-one percent of patients harbored at least one co-mutation in addition to the major EGFR mutation. TP53 was the top mutated gene and was found more frequently mutated at later stage. Markedly, NF1 mutations were found only in stage II-III ADCs. Conversely, RB1 mutations were more frequent in stage I ADCs, whereas APC mutations were observed exclusively in this group. Thirty-four percent of patients with EGFR TKI-sensitizing mutations had genetic alterations involving EGFR downstream effectors or bypass pathways that could affect the response to EGFR TKIs, such as PIK3CA, BRCA1, and NOTCH1. CONCLUSION: Operable lung ADCs with EGFR TKI-sensitizing mutations are associated with a high proportion of co-mutations. Mutation profiling of these resected tumors could facilitate in determining the applicability and efficacy of adjuvant EGFR TKI therapeutic strategy. IMPLICATIONS FOR PRACTICE: The efficacy of adjuvant epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) therapy for lung cancer harboring EGFR mutation after surgical resection is still under debate. Next-generation sequencing of 416 cancer-relevant genes in 139 resected lung cancers revealed the co-mutational landscape with background EGFR mutation. Notably, the study identified potential EGFR TKI-resistant mutations in 34.71% of patients with a drug-sensitizing EGFR mutation and who were naive in terms of targeted therapy. A comprehensive mutation profiling of these resected tumors could facilitate in determining the applicability and efficacy of adjuvant EGFR TKI therapeutic strategy for these patients.

Prognostic Effect of TP53 and PKD Co-Mutations in Patients with Resected Epidermal Growth Factor Receptor-Mutated Lung Adenocarcinoma.

BACKGROUND: The impact of specific co-mutations in epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma is unclear. METHODS: Tissues from 147 consecutive patients with resected EGFR-mutated lung adenocarcinomas treated at Sun Yat-Sen University Cancer Center were analyzed by next-generation sequencing (NGS). Associations between mutation status, patient baseline characteristics, and survival outcomes (disease-free survival [DFS] and overall survival [OS]) after surgical resection were analyzed. RESULTS: TP53 and protein kinase D (PKD) mutations were the two most frequently observed co-mutations in this cohort. Dual PKD/EGFR and TP53/EGFR mutations were found in 39 (27%) and 72 patients (49%), respectively, with dual TP53/EGFR mutations more commonly observed in male patients (P = 0.021). Both TP53 (hazard ratio [HR] 2.08, 95% confidence interval [CI] 1.23-3.54, P = 0.007) and PKD co-mutations (HR 1.72, 95% CI 1.01-2.93, P = 0.044) were associated with shorter DFS, but not OS, in univariate analysis. In multivariate analysis, patients harboring PKD/TP53 co-mutations had shorter DFS compared with PKD-/TP53- cases (HR 2.49, 95% CI 1.15-5.37, P = 0.02). In a subgroup of never-smokers, TP53 co-mutations were associated with significantly worse OS (HR 50.11, 95% CI 2.39-1049.83, P = 0.012). CONCLUSION: TP53 and PKD mutations were the two most frequently observed co-mutations in resected EGFR-mutated lung adenocarcinoma. Both mutations were associated with poorer prognoses in affected patients.

Impact of treatment on the prognosis of childhood in hepatoblastoma: A SEER based analysis.

Background: The prognosis of patients with hepatoblastoma has been unsatisfactory. This study analyzed the effects of different treatment methods on cancer-specific survival (CSS) in children with hepatoblastoma. Method: From 2000 to 2018, patients with hepatoblastoma were included in the Surveillance, Epidemiology, and End Results (SEER) database. CSS was estimated using the Kaplan-Meier method. Cox regression analysis assessed prognostic factors. The predictive models were validated using the concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve. Result: Of the 785 included patients, 730 (93.0 %) underwent chemotherapy, 516 (65.7 %) underwent liver tumour resection and 129 (16.4 %) underwent liver transplantation. Both chemotherapy and surgery could significantly improve the CSS rate (all p < 0.001). However, there was no difference in CSS rate between the two surgical methods (liver tumour resection and liver transplantation) (p = 0.613). Further subgroup analysis revealed that children who underwent liver tumour resection or liver transplantation based on chemotherapy (all p > 0.05) had a similar prognosis. Multivariate analysis revealed that age (p = 0.003), race (p = 0.001), operative method (p < 0.001), chemotherapy (p < 0.001), distant metastasis (p < 0.001) and tumour size (p < 0.001) were independent factors related to CSS. The C-index of the new nomogram was 0.759, and its consistency was good. The ROC curves verified that the nomogram had a better prediction ability for 1-, 3- and 5-year CSS rates. Conclusion: In children with hepatoblastoma, there was no statistically significant difference in CSS between chemotherapy combined with liver transplantation and liver tumour resection. The nomogram we constructed demonstrated satisfactory CSS prediction ability.

Carbon dioxide gas-induced pneumothorax versus one-lung ventilation in minimally invasive esophagectomy: a multicenter propensity score matching cohort study.

BACKGROUND: Carbon dioxide gas-induced pneumoperitoneum might be the reason for the shorter postoperative survival of patients with malignant tumors. Whether CO 2 gas-induced pneumothorax has unfavorable impacts on the surgical and oncological outcomes of minimally invasive esophagectomy remains unclear. METHODS: Between 2010 and 2016, a total of 998 patients with squamous cell carcinoma of the esophagus who received video-assisted surgery were registered from three large-volume medical centers. The overall survival (OS) and disease-free survival (DFS) were compared after using propensity score-matched and inverse probability-weighted methods. In addition, the tumor-relapse state was evaluated, and the relapse pattern was compared. RESULTS: A total of 422 and 576 minimally invasive esophagectomies with intraoperative one-lung ventilation and CO 2 -induced pneumothorax were enrolled, respectively. The 5-year OS and DFS were similar between the CO 2 -induced pneumothorax (64.2% and 64.7%) and one-lung ventilation (65.3% and 62.4%) groups following propensity matching. The inverse probability weighting revealed similarly equal survival results in the two groups. The 5-year relapse rates were 35.1% and 30.6% in the one-lung ventilation and CO 2 -induced pneumothorax groups, respectively. Moreover, the relapse patterns were not significantly different between the two groups. CONCLUSION: The results of this study suggested that the use of intraoperative one-lung ventilation and CO 2 -induced pneumothorax have similar oncological outcomes; therefore, the two methods are both viable options in esophagectomy.

Dynamics of peripheral blood inflammatory index predict tumor pathological response and survival among patients with locally advanced non-small cell lung cancer who underwent neoadjuvant immunochemotherapy: a multi-cohort retrospective study.

Background: Static tumor features before initiating anti-tumor treatment were insufficient to distinguish responding from non-responding tumors under the selective pressure of immuno-therapy. Herein we investigated the longitudinal dynamics of peripheral blood inflammatory indexes (dPBI) and its value in predicting major pathological response (MPR) in non-small cell lung cancer (NSCLC). Methods: A total of 147 patients with NSCLC who underwent neoadjuvant immunochemotherapy were retrospectively reviewed as training cohort, and 26 NSCLC patients from a phase II trial were included as validation cohort. Peripheral blood inflammatory indexes were collected at baseline and as posttreatment status; their dynamics were calculated as their posttreatment values minus their baseline level. Least absolute shrinkage and selection operator algorithm was utilized to screen out predictors for MPR, and a MPR score was integrated. We constructed a model incorporating this MPR score and clinical predictors for predicting MPR and evaluated its predictive capacity via the area under the curve (AUC) of the receiver operating characteristic and calibration curves. Furthermore, we sought to interpret this MPR score in the context of micro-RNA transcriptomic analysis in plasma exosomes for 12 paired samples (baseline and posttreatment) obtained from the training cohort. Results: Longitudinal dynamics of monocyte-lymphocyte ratio, platelet-to-lymphocyte ratio, platelet-to-albumin ratio, and prognostic nutritional index were screened out as significant indicators for MPR and a MPR score was integrated, which was further identified as an independent predictor of MPR. Then, we constructed a predictive model incorporating MPR score, histology, and differentiated degree, which discriminated MPR and non-MPR patients well in both the training and validation cohorts with an AUC value of 0.803 and 0.817, respectively. Furthermore, micro-RNA transcriptomic analysis revealed the association between our MPR score and immune regulation pathways. A significantly better event-free survival was seen in subpopulations with a high MPR score. Conclusion: Our findings suggested that dPBI reflected responses to neoadjuvant immuno-chemotherapy for NSCLC. The MPR score, a non-invasive biomarker integrating their dynamics, captured the miRNA transcriptomic pattern in the tumor microenvironment and distinguished MPR from non-MPR for neoadjuvant immunochemotherapy, which could support the clinical decisions on the utilization of immune checkpoint inhibitor-based treatments in NSCLC patients.

Risk factors and novel predictive models for metastatic neuroblastoma in children.

INTRODUCTION: Neuroblastoma (NB) with distant metastasis (DM) is a high-risk condition with a poor prognosis. Early identify the risk and prognostic differences of DM in children, which is helpful for the development of clinical diagnosis and treatment. METHODS: The study cohort included patients with NB in surveillance, epidemiological, and final outcome databases between 2010 and 2018. To identify the risk and prognostic factors for DM, both univariate and multivariate logistic and Cox regression analyses were conducted. In addition, we created and verified three online clinical prediction models. Finally, we assess the performance of the proposed predictive model. RESULTS: Among the 1224 children with NB included in the study, 599 developed DM. Primary site is the most important factor affecting metastasis and prognosis. The training and validation groups of the diagnostic nomograms had area under curves (AUC) values of 0.872 and 0.824, respectively. In addition, in the training group, the AUC values at 12, 36, and 60 months were 0.68, 0.71, and 0.75 for the OS nomogram and 0.70, 0.72, and 0.75 for the CSS nomogram. In the validation group, the AUC values at 12, 36, and 60 months were 0.68, 0.72, and 0.70 for the OS nomogram and 0.67, 0.71, and 0.69 for the CSS nomogram, respectively. Calibration curve and decision curve analyses revealed good performance of the nomogram. CONCLUSIONS: The nomogram developed in this study could appropriately predict DM and assess its prognosis in patients with NB.

miR-4739 promotes epithelial-mesenchymal transition and angiogenesis in "driver gene-negative" non-small cell lung cancer via activating the Wnt/ß-catenin signaling.

PURPOSE: "Driver gene-negative" non-small cell lung cancer (NSCLC) currently has no approved targeted drug, due to the lack of common actionable driver molecules. Even though miRNAs play crucial roles in various malignancies, their roles in "driver gene-negative" NSCLC keep unclear. METHODS: miRNA expression microarrays were utilized to screen miRNAs associated with "driver gene-negative" NSCLC malignant progression. Quantitative real-time PCR (RT-qPCR) and in situ hybridization (ISH) were employed to validate the expression of miR-4739, and its correlation with clinicopathological characteristics was analyzed in tumor specimens using univariate and multivariate analyses. The biological functions and underlying mechanisms of miR-4739 were investigated both in vitro and in vivo. RESULTS: our research demonstrated, for the first time, that miR-4739 was substantially increased in "driver gene-negative" NSCLC tumor tissues and cell lines, and overexpression of miR-4739 was related to clinical staging, metastasis, and unfavorable outcomes. Functional experiments discovered that miR-4739 dramatically enhanced tumor cell proliferation, migration, and metastasis by promoting the epithelial-to-mesenchymal transition (EMT). Meanwhile, miR-4739 can be transported from cancer cells to the site of vascular epithelial cells through exosomes, consequently facilitating the proliferation and migration of vascular epithelial cells and inducing angiogenesis. Mechanistically, miR-4739 can activate Wnt/ß-catenin signaling both in tumor cells and vascular epithelial cells by targeting Wnt/ß-catenin signaling antagonists APC2 and DKK3, respectively. CONCLUSION: Our work identifies a valuable oncogene, miR-4739, that accelerates malignant progression in "driver gene-negative" NSCLC and serves as a potential therapeutic target for this group of tumors.

Risk stratification and prognosis prediction based on inflammation-related gene signature in lung squamous carcinoma.

BACKGROUND: Inflammation is known to have an intricate relationship with tumorigenesis and tumor progression while it is also closely related to tumor immune microenvironment. Whereas the role of inflammation-related genes (IRGs) in lung squamous carcinoma (LUSC) is barely understood. Herein, we recognized IRGs associated with overall survival (OS), built an IRGs signature for risk stratification and explored the impact of IRGs on immune infiltration landscape of LUSC patients. METHODS: The RNA-sequencing and clinicopathological data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, which were defined as training and validation cohorts. Cox regression and least absolute shrinkage and selection operator analyses were performed to build an IRG signature. CIBERSORT, microenvironment cell populations-counter and tumor immune dysfunction and rejection (TIDE) algorithm were used to perform immune infiltration analysis. RESULTS: A two-IRG signature consisting of KLF6 and SGMS2 was identified according to the training set, which could categorize patients into two different risk groups with distinct OS. Patients in the low-risk group had more anti-tumor immune cells infiltrated while patient with high-risk had lower TIDE score and higher levels of immune checkpoint molecules expressed. The IRG signature was further identified as an independent prognostic factor of OS. Subsequently, a prognostic nomogram including IRG signature, age, and cancer stage was constructed for predicting individualized OS, whose concordance index values were 0.610 (95% CI: 0.568-0.651) in the training set and 0.652 (95% CI: 0.580-0.724) in validation set. Time-dependent receiver operator characteristic curves revealed that the nomogram had higher prediction accuracy compared with the traditional tumor stage alone. CONCLUSION: The IRG signature was a predictor for patients with LUSC and might serve as a potential indicator of the efficacy of immunotherapy. The nomogram based on the IRG signature showed a relatively good predictive performance in survival.

A novel lncRNA SNHG29 regulates EP300- related histone acetylation modification and inhibits FLT3-ITD AML development.

Internal tandem duplication (ITD) mutations within the FMS-like tyrosine kinase-3 (FLT3) occur in up to 25% of acute myeloid leukemia (AML) patients and indicate a very poor prognosis. The role of long noncoding RNAs (lncRNAs) in FLT3-ITD AML progression remains unexplored. We identified a novel lncRNA, SNHG29, whose expression is specifically regulated by the FLT3-STAT5 signaling pathway and is abnormally down-regulated in FLT3-ITD AML cell lines. SNHG29 functions as a tumor suppressor, significantly inhibiting FLT3-ITD AML cell proliferation and decreasing sensitivity to cytarabine in vitro and in vivo models. Mechanistically, we demonstrated that SNHG29's molecular mechanism is EP300-binding dependent and identified the EP300-interacting region of SNHG29. SNHG29 modulates genome-wide EP300 genomic binding, affecting EP300-mediated histone modification and consequently influencing the expression of varies downstream AML-associated genes. Our study uncovers a novel molecular mechanism for SNHG29 in mediating FLT3-ITD AML biological behaviors through epigenetic modification, suggesting that SNHG29 could be a potential therapeutic target for FLT3-ITD AML.

Pan-Immune-Inflammatory Value in Patients with Non-Small-Cell Lung Cancer Undergoing Neoadjuvant Immunochemotherapy.

Background: We aimed to investigate the predictive value of a systematic serum inflammation index, pan-immune-inflammatory value (PIV), in pathological complete response (pCR) of patients treated with neoadjuvant immunotherapy to further promote ideal patients' selection. Methods: The clinicopathological and baseline laboratory information of 128 NSCLC patients receiving neoadjuvant immunochemotherapy between October 2019 and April 2022 were retrospectively reviewed. We performed least absolute shrinkage and selection operator (LASSO) algorithm to screen candidate serum biomarkers for predicting pCR, which further entered the multivariate logistic regression model to determine final biomarkers. Accordingly, a diagnostic model for predicting individual pCR was established. Kaplan-Meier method was utilized to estimate curves of disease-free survival (DFS), and the Log rank test was analyzed to compare DFS differences between patients with and without pCR. Results: Patients with NSCLC heterogeneously responded to neoadjuvant immunotherapy, and those with pCR had a significant longer DFS than patients without pCR. Through LASSO and the multivariate logistic regression model, PIV was identified as a predictor for predicting pCR of patients. Subsequently, a diagnostic model integrating with PIV, differentiated degree and histological type was constructed to predict pCR, which presented a satisfactory predictive power (AUC, 0.736), significant agreement between actual and our nomogram-predicted pathological response. Conclusion: Baseline PIV was an independent predictor of pCR for NSCLC patients receiving neoadjuvant immunochemotherapy. A significantly longer DFS was achieved in patients with pCR rather than those without pCR; thus, the PIV-based diagnostic model might serve as a practical tool to identify ideal patients for neoadjuvant immunotherapeutic guidance.

Invasiveness assessment by artificial intelligence against intraoperative frozen section for pulmonary nodules ≤ 3 cm.

PURPOSE: To investigate the performance of an artificial intelligence (AI) algorithm for assessing the malignancy and invasiveness of pulmonary nodules in a multicenter cohort. METHODS: A previously developed deep learning system based on a 3D convolutional neural network was used to predict tumor malignancy and invasiveness. Dataset of pulmonary nodules no more than 3 cm was integrated with CT images and pathologic information. Receiver operating characteristic curve analysis was used to evaluate the performance of the system. RESULTS: A total of 466 resected pulmonary nodules were included in this study. The areas under the curves (AUCs) of the deep learning system in the prediction of malignancy as compared with pathological reports were 0.80, 0.80, and 0.75 for all, subcentimeter, and solid nodules, respectively. Additionally, the AUC in the AI-assisted prediction of invasive adenocarcinoma (IA) among subsolid lesions (n = 184) was 0.88. Most malignancies that were misdiagnosed by the AI system as benign diseases with a diameter measuring greater than 1 cm (26/250, 10.4%) presented as solid nodules (19/26, 73.1%) on CT. In an exploratory analysis involving nodules underwent intraoperative pathologic examination, the concordance rate in identifying IA between the AI model and frozen section examination was 0.69, with a sensitivity of 0.50 and specificity of 0.97. CONCLUSION: The deep learning system can discriminate malignant diseases for pulmonary nodules measuring no more than 3 cm. The AI model has a high positive predictive value for invasive adenocarcinoma with respect to intraoperative frozen section examination, which might help determine the individualized surgical strategy.

A Predictive Nomogram for Atypical Meningioma Based On Preoperative Magnetic Resonance Imaging and Routine Blood Tests.

OBJECTIVE: The objective of the study was to establish a 5-year progression-free survival prediction nomogram using preoperative routine blood tests and magnetic resonance imaging to guide postoperative treatment. METHODS: Our study was a retrospective analysis of patients with atypical meningioma admitted into our facility from January 31, 2010, to January 31, 2016. We used single-factor logistic analysis to extract valuable indicators from preoperative blood test results and 3D Slicer software to extract radiomic features from magnetic resonance imaging. The radiomics score was calculated by least absolute shrinkage and selection operator logistic regression analysis. We then combined blood indicators and radiomic signatures to construct a radiomic nomogram image. The performance of the model was evaluated comprehensively using the following three aspects: recognition ability, accuracy, and clinical value. RESULTS: Six significant radiological features were selected through least absolute shrinkage and selection operator logistic regression analysis. The radiometric label established by these six features has satisfactory predictive performance. The area under the curve in the training group was 0.885 (95% confidence interval, 0.8037-0.9659), and the area under the curve in the validation set was 0.789 (95% confidence interval, 0.6092-0.9686). We used the combined image tags and preoperative leukocyte and neutrophil count to construct a 5-year progression-free survival prediction nomogram. CONCLUSIONS: The analysis results of the calibration curve and the decision curve show that the nomogram constructed by combining radiomics and preoperative blood tests has a good predictive value for 5-year progression-free survival in atypical meningioma and can provide a reference for selecting postoperative treatment options.

Postoperative locoregional recurrence pattern and treatment management of stage pT4 sigmoid colon cancer: a retrospective cohort study.

BACKGROUND: This study aimed to explore the pattern of locoregional recurrence after surgery in patients with non-metastatic stage pT4 sigmoid colon cancer and the role of adjuvant radiotherapy on survival. METHODS: We retrospectively analyzed data from 208 patients who underwent surgery in our hospital. The patients were randomly divided into training and validation groups at a 1:1 ratio. Patients at high risk for locoregional recurrence were screened using Cox regression analysis. Based on the data of 2,886 patients in the Surveillance, Epidemiology, and End Results (SEER) database, the effect of adjuvant radiotherapy on overall survival (OS) and cancer-specific survival (CSS) was evaluated by Kaplan-Meier curves. RESULTS: Of the 208 patients, 57 (27.4%) presented with locoregional recurrences (14 anastomotic and 43 abdominal or pelvic lymph node recurrences). Multivariate analysis showed that serum CEA, differentiation, lymph node dissection number, and N stage were independent predictors of locoregional recurrence-free survival (all p < 0.05). A risk-stratification model was constructed, and a total score of ≥ 6.5 points was considered the high-risk group for locoregional recurrence. Both the training and validation sets presented that the model had a good predictive ability (area under the curve = 0.828 and 0.724, respectively). Analysis of SEER data revealed that adjuvant radiotherapy significantly prolonged OS and CSS in the high-risk population (all p < 0.05, vs. no radiotherapy). CONCLUSIONS: Patients with a total risk score of 6.5 or more had a high likelihood of locoregional recurrence, and perhaps adjuvant radiotherapy could improve their survival.

Comprehensive 18F-FDG PET-based radiomics in elevating the pathological response to neoadjuvant immunochemotherapy for resectable stage III non-small-cell lung cancer: A pilot study.

Purpose: To develop a comprehensive PET radiomics model to predict the pathological response after neoadjuvant toripalimab with chemotherapy in resectable stage III non-small-cell lung cancer (NSCLC) patients. Methods: Stage III NSCLC patients who received three cycles of neoadjuvant toripalimab with chemotherapy and underwent 18F-FDG PET/CT were enrolled. Baseline 18F-FDG PET/CT was performed before treatment, and preoperative 18F-FDG PET/CT was performed three weeks after the completion of neoadjuvant treatment. Surgical resection was performed 4-5 weeks after the completion of neoadjuvant treatment. Standardized uptake value (SUV) statistics features and radiomics features were derived from baseline and preoperative PET images. Delta features were derived. The radiologic response and metabolic response were assessed by iRECIST and iPERCIST, respectively. The correlations between PD-L1 expression, driver-gene status, peripheral blood biomarkers, and the pathological responses (complete pathological response [CPR]; major pathological response [MPR]) were assessed. Associations between PET features and pathological responses were evaluated by logistic regression. Results: Thirty patients underwent surgery and 29 of them performed preoperative PET/CT. Twenty patients achieved MPR and 16 of them achieved CPR. In univariate analysis, five SUV statistics features and two radiomics features were significantly associated with pathological responses. In multi-variate analysis, SUVmax, SUVpeak, SULpeak, and End-PET-GLDM-LargeDependenceHighGrayLevelEmphasis (End-GLDM-LDHGLE) were independently associated with CPR. SUVpeak and SULpeak performed better than SUVmax and SULmax for MPR prediction. No significant correlation, neither between the radiologic response and the pathological response, nor among PD-L1, driver gene status, and baseline PET features was found. Inflammatory response biomarkers by peripheral blood showed no difference in different treatment responses. Conclusion: The logistic regression model using comprehensive PET features contributed to predicting the pathological response after neoadjuvant toripalimab with chemotherapy in resectable stage III NSCLC patients.