Adenocarcinoma Invasion Research Articles

Combined Radiomic and Visual Assessment for Improved Detection of Lung Adenocarcinoma Invasiveness on Computed Tomography Scans: A Multi-Institutional Study

ObjectiveThe timing and nature of surgical intervention for semisolid abnormalities are dependent upon distinguishing between adenocarcinoma-in-situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (INV). We sought to develop and evaluate a quantitative imaging method to determine invasiveness of small, ground-glass lesions on computed tomography (CT) chest scans.MethodsThe study comprised 268 patients from 4 institutions with resected (<=3 cm) semisolid lesions with confirmed histopathological diagnosis of MIA/AIS or INV. A total of 248 radiomic texture features from within the tumor nodule (intratumoral) and adjacent to the nodule (peritumoral) were extracted from manually annotated lung nodules of chest CT scans. The datasets were randomly divided, with 40% of patients used for training and 60% used for testing the machine classifier (Training DTrain, N=106; Testing, DTest, N=162).ResultsThe top five radiomic stable features included four intratumoral (Laws and Haralick feature families) and one peritumoral feature within 3 to 6 mm of the nodule (CoLlAGe feature family), which successfully differentiated INV from MIA/AIS nodules with an AUC of 0.917 [0.867-0.967] on DTrain and 0.863 [0.79-0.931] on DTest. The radiomics model successfully differentiated INV from MIA cases (<1 cm AUC: 0.76 [0.53-0.98], 1-2 cm AUC: 0.92 [0.85-0.98], 2-3 cm AUC: 0.95 [0.88-1]). The final integrated model combining the classifier with the radiologists’ score gave the best AUC on DTest (AUC=0.909, p<0.001).ConclusionsAddition of advanced image analysis via radiomics to the routine visual assessment of CT scans help better differentiate adenocarcinoma subtypes and can aid in clinical decision making. Further prospective validation in this direction is warranted.

A Nomogram Combined Radiomics and Clinical Features as Imaging Biomarkers for Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma

ObjectivesTo develop and validate a nomogram model based on radiomics features for preoperative prediction of visceral pleural invasion (VPI) in patients with lung adenocarcinoma.MethodsA total of 659 patients with surgically pathologically confirmed lung adenocarcinoma underwent CT examination. All cases were divided into a training cohort (n = 466) and a validation cohort (n = 193). CT features were analyzed by two chest radiologists. CT radiomics features were extracted from CT images. LASSO regression analysis was applied to determine the most useful radiomics features and construct radiomics score (radscore). A nomogram model was developed by combining the optimal clinical and CT features and the radscore. The model performance was evaluated using ROC analysis, calibration curve and decision curve analysis (DCA).ResultsA total of 1316 radiomics features were extracted. A radiomics signature model with a selection of the six optimal features was developed to identify patients with or without VPI. There was a significant difference in the radscore between the two groups of patients. Five clinical features were retained and contributed as clinical feature models. The nomogram combining clinical features and radiomics features showed improved accuracy, specificity, positive predictive value, and AUC for predicting VPI, compared to the radiomics model alone (specificity: training cohort: 0.89, validation cohort: 0.88, accuracy: training cohort: 0.84, validation cohort: 0.83, AUC: training cohort: 0.89, validation cohort: 0.89). The calibration curve and decision curve analyses suggested that the nomogram with clinical features is beyond the traditional clinical and radiomics features.ConclusionA nomogram model combining radiomics and clinical features is effective in non-invasively prediction of VPI in patients with lung adenocarcinoma.

Extracellular Vesicles-Encapsulated miR-153-3p Potentiate the Survival and Invasion of Lung Adenocarcinoma.

Extracellular vesicles (EVs) play an essential role in the communication between cells and the tumor microenvironment. However, the effect of tumor-derived EVs on the growth and metastasis of lung adenocarcinoma (LUAD) remains to be explored. This study aimed to elucidate the role of miR-153-3p-EVs in the invasion and migration capabilities of LUAD cells and explore its mechanism through in vivo and in vitro experiments. We found that miR-153-3p was specifically and highly expressed in LUAD and its secreted EVs. Furthermore, the expression of BANCR was negatively regulated by miR-153-3p and identified as a target gene of miR-153-3p using luciferase reporter assays. Through further investigation, we found that the downregulation of BANCR activates the PI3K/AKT pathway and accelerates the process of epithelial-mesenchymal transition (EMT), which ultimately leads to the aggravation of LUAD. The orthotopic xenograft mouse model was established to illustrate the effect of miR-153-3p-EVs on LUAD. Animal studies showed that miR-153-3p-EVs accelerated tumor growth in mice. Besides, we found that miR-153-3p-EVs could damage the respiratory ability of mice and produce a mass of inflammatory cells around the lung tissue of mice. Nevertheless, antagomir-153-3p treatment could inhibit the deterioration of respiratory function and inhibit the growth of lung tumors in mice. In conclusion, our study reveals the potential molecular mechanism of miR-153-3p-EVs in the development of LUAD and provides a potential strategy for the treatment of LUAD.

Circ_0001998 Regulates the Proliferation, Invasion, and Apoptosis of Lung Adenocarcinoma via Sponging miR-145.

Circular RNA (circRNA) is considered an important regulator of cancer. Circ_0001998 is a newly discovered circRNA and its role in lung adenocarcinoma (LUAD) remains obscure and requires further study. The expression levels of circ_0001998 and miR-145 in LUAD were predicted by bioinformatics analysis and then verified by qRT-PCR in the LUAD cell lines. CCK-8, clone formation, EdU assay, and flow cytometry were applied to determine the effects of silencing circ_0001998 on the viability, proliferation, and apoptosis of LUAD cells. The target relationship between circ_0001998 and miR-145 was predicted by bioinformatics analysis and verified by a luciferase activity experiment. The effect of circ_0001998/miR-145 axis on the viability, proliferation, and apoptosis of LUAD cells was verified by the rescue experiment. Circ_0001998 was upregulated in LUAD, and silencing circ_0001998 suppressed viability, proliferation, and invasion of LUAD cells. The target gene of circ_0001998, miR-145, was downregulated in LUAD, and the low expression of miR-145 indicated a poor prognosis. The effect of silencing circ_0001998 on the biological function of LUAD cells was reversed by the miR-145 inhibitor. Circ_0001998 regulates the proliferation, invasion, and apoptosis of LUAD via sponging miR-145.

Case of needle tract seeding during preoperative neoadjuvant chemotherapy for resectable pancreatic cancer

Reports of needle tract seeding (NTS) as a complication of endoscopic ultrasound‐guided fine‐needle aspiration (EUS‐FNA) have been increasing. To date, most of the reported cases of NTS have been diagnosed during the postoperative follow‐up period. Herein, we report a case of NTS that occurred during preoperative neoadjuvant chemotherapy after EUS‐FNA for resectable pancreatic cancer. The patient underwent transgastric EUS‐FNA for a pancreatic tail tumor. He was diagnosed as having resectable pancreatic cancer and received preoperative neoadjuvant chemotherapy. After completion of the chemotherapy, computed tomography showed a thick‐walled cyst‐like structure appearing between the pancreas and the gastric wall. Combined resection revealed adenocarcinoma invasion into the cyst‐like structure. Based on the clinical course, and surgical and pathological findings, the condition was diagnosed as NTS. It is thus crucial that after EUS‐FNA, a detailed review of the imaging findings be conducted in the preoperative period. If adhesions between the stomach and the pancreas are observed after transgastric EUS‐FNA, combined resection of the gastric wall should be considered.

Development and validation of qualitative and quantitative models to predict invasiveness of lung adenocarcinomas manifesting as pure ground-glass nodules based on low-dose computed tomography during lung cancer screening.

Due to different management strategy and prognosis of different subtypes of lung adenocarcinomas appearing as pure ground-glass nodules (pGGNs), it is important to differentiate invasive adenocarcinoma (IA) from adenocarcinoma in situ/minimally invasive adenocarcinoma (AIS/MIA) during lung cancer screening. The aim of this study was to develop and validate the qualitative and quantitative models to predict the invasiveness of lung adenocarcinoma appearing as pGGNs based on low-dose computed tomography (LDCT) and compare their diagnostic performance with that of intraoperative frozen section (FS). A total of 223 consecutive pathologically confirmed pGGNs from March 2018 to December 2020 were divided into a primary cohort (96 IAs and 64 AIS/MIAs) and validation cohort (39 IAs and 24 AIS/MIAs) according to scans (Brilliance iCT and Somatom Definition Flash) performed at Sichuan Cancer Hospital and Institute. The following LDCT features of pGGNs were analyzed: the qualitative features included nodule location, shape, margin, nodule-lung interface, lobulation, spiculation, pleural indentation, air bronchogram, vacuole, and vessel type, and the quantitative features included the diameter, volume, and mean attenuation. Multivariate logistic regression analysis was used to build a qualitative model, quantitative model, and combined qualitative and quantitative model. The diagnostic performance was assessed according to the following factors: the area under curve (AUC) of the receiver operating characteristic (ROC) curve, sensitivity, specificity, and accuracy. The AUCs of the qualitative model, quantitative model, combined qualitative and quantitative model, and the FS diagnosis were 0.854, 0.803, 0.873, and 0.870, respectively, in the primary cohort and 0.884, 0.855, 0.875, and 0.946, respectively, in the validation cohort. No significant difference of the AUCs was found among the radiological models and the FS diagnosis in the primary or validation cohort (all corrected P>0.05). Among the radiological models, the combined qualitative and quantitative model consisting of vessel type and volume showed the highest accuracy in both the primary and validation cohorts (0.831 and 0.889, respectively). The diagnostic performances of the qualitative and quantitative models based on LDCT to differentiate IA from AIS/MIA in pGGNs are equivalent to that of intraoperative FS diagnosis. The vessel type and volume can be preoperative and non-invasive biomarkers to assess the invasive risk of pGGNs in lung cancer screening.

An Insight into the Role of Mesothelin in Pediatric Acute Myeloid Leukemia

Pediatric acute myeloid leukemia (AML) is characterized by the malignant transformation of hematopoietic stem and progenitor cells that lead to the accumulation of immature myeloid cells in the bone marrow. Standard treatment of AML includes intense cytotoxic chemotherapy and hematopoietic stem cell transplants with relatively low cure rates. Targeted therapy options for AML are limited. Mesothelin (MSLN) is a 40‐kDa glycosylphosphatidylinositol (GPI)‐anchored protein that is highly expressed on many tumors, but lacks expression in many normal tissues, making it an excellent target for cancer therapies. More recently, the identification of MSLN expression in a subset (about one‐third) of pediatric AML patients warranted preclinical studies with MSLN‐targeted therapies, including immunotherapy. Recently, our lab utilized bispecific T cell engaging antibodies to recruit T cells to MSLN‐expressing leukemic cells, increasing in vivo survival rates in patient‐derived xenograft models.MSLN has been shown to play a role in promoting proliferation and invasion in mesothelioma, ovarian cancer, and pancreatic adenocarcinoma, mainly through interactions with MUC16/CA125. Current investigative efforts in AML focus on MSLN‐targeted therapies, while the function of MSLN in AML remains unresolved. Previously, we identified a correlation between MSLN expression and extramedullary disease, as well as enhanced leukemic burden in xenograft models. Here, we report that MSLN expression is associated with increased rates of cell proliferation and migration.The proliferation rate of MSLN‐negative AML cell lines, MV4;11 &amp; NOMO‐1‐KO, and two MSLN‐expressing cell lines, MV4;11‐MSLN &amp; NOMO‐1, was evaluated by BrDU proliferation assay or direct measurement of cell numbers over 96 hours. MSLN‐expressing cells proliferated at an increased rate comparative to the non‐expressing cells. Consistent with higher proliferation rate in MSLN‐expressing cells, these cells showed reduced percentage of G1 population and increased population in the S phase of the cell cycle. In a Transwell migration assay, higher number of MV4;11‐MSLN cells migrated towards serum compared to their wild‐type counterpart, indicating that MSLN expression promoted cell migration. Our data suggest that MSLN expression in pediatric AML cells enhances proliferation and migration. Therefore, targeting MSLN may be beneficial to curb AML progression.

Clinical correlation of lymphovascular invasion and Silva pattern of invasion in early-stage endocervical adenocarcinoma: proposed binary Silva classification system

Silva invasion pattern can help predict lymph node metastasis risk in endocervical adenocarcinoma. We analysed Silva pattern of invasion and lymphovascular invasion to determine associations with clinical outcomes in stage IA and IB1 endocervical adenocarcinomas. International Federation of Gynecology and Obstetrics (FIGO; 2019 classification) stage IA-IB1 endocervical adenocarcinomas from 15 international institutions were examined for Silva pattern, presence of lymphovascular invasion, and other prognostic parameters. Lymph node metastasis status, local/distant recurrences, and survival data were compared using appropriate statistical tests. Of 399 tumours, 152 (38.1%) were stage IA [IA1, 77 (19.3%); IA2, 75 (18.8%)] and 247 (61.9%) were stage IB1. On multivariate analysis, lymphovascular invasion (p=0.008) and Silva pattern (p<0.001) were significant factors when comparing stage IA versus IB1 endocervical adenocarcinomas. Overall survival was significantly associated with lymph node metastasis (p=0.028); recurrence-free survival was significantly associated with lymphovascular invasion (p=0.002) and stage (1B1 versus 1A) (p=0.002). Five and 10 year overall survival and recurrence-free survival rates were similar among Silva pattern A cases and Silva pattern B cases without lymphovascular invasion (p=0.165 and p=0.171, respectively). Silva pattern and lymphovascular invasion are important prognostic factors in stage IA1-IB1 endocervical adenocarcinomas and can supplement 2019 International Federation of Gynecology and Obstetrics staging. Our binary Silva classification system groups patients into low risk (patterns A and B without lymphovascular invasion) and high risk (pattern B with lymphovascular invasion and pattern C) categories.

A Multi-Classification Model for Predicting the Invasiveness of Lung Adenocarcinoma Presenting as Pure Ground-Glass Nodules.

ObjectivesTo establish a multi-classification model for precisely predicting the invasiveness (pre-invasive adenocarcinoma, PIA; minimally invasive adenocarcinoma, MIA; invasive adenocarcinoma, IAC) of lung adenocarcinoma manifesting as pure ground-glass nodules (pGGNs).MethodsBy the inclusion and exclusion criteria, this retrospective study enrolled 346 patients (female, 297, and male, 49; age, 55.79 ± 10.53 (24-83)) presenting as pGGNs from 1292 consecutive patients with pathologically confirmed lung adenocarcinoma. A total of 27 clinical were collected and 1409 radiomics features were extracted by PyRadiomics package on python. After feature selection with L2,1-norm minimization, logistic regression (LR), extra w(ET) and gradient boosting decision tree (GBDT) were used to construct the three-classification model. Then, an ensemble model of the three algorithms based on model ensemble strategy was established to further improve the classification performance.ResultsAfter feature selection, a hybrid of 166 features consisting of 1 clinical (short-axis diameter, ranked 27th) and 165 radiomics (4 shape, 71 intensity and 90 texture) features were selected. The three most important features are wavelet-HLL_firstorder_Minimum, wavelet-HLL_ngtdm_Busyness and square_firstorder_Kurtosis. The hybrid-ensemble model based on hybrid clinical-radiomics features and the ensemble strategy showed more accurate predictive performance than other models (hybrid-LR, hybrid-ET, hybrid-GBDT, clinical-ensemble and radiomics-ensemble). On the training set and test set, the model can obtain the accuracy values of 0.918 ± 0.022 and 0.841, and its F1-scores respectively were 0.917 ± 0.024 and 0.824.ConclusionThe multi-classification of invasive pGGNs can be precisely predicted by our proposed hybrid-ensemble model to assist patients in the early diagnosis of lung adenocarcinoma and prognosis.

Rab22a promotes the proliferation, migration, and invasion of lung adenocarcinoma via up-regulating PI3K/Akt/mTOR signaling pathway

Rab22a, a member of the proto-oncogene RAS family, belongs to the Rab5 subfamily. It participates in early endosome formation and regulates vesicle trafficking. The relationship between Rab22a and tumorigenesis remains elusive. In non-small cell lung cancer specimens, immunohistochemical staining showed consistently high expression of Rab22a in lung adenocarcinoma, but not in squamous cell carcinoma. In lung adenocarcinoma cell lines, A549 and H1299, transfection with Rab22a significantly promoted cell proliferation, migration, and invasion, whereas interference with Rab22a specific siRNA significantly inhibited the above capacities. Transfection with Rab22a also up-regulated the phosphorylation levels of core effector proteins on the PI3K/Akt/mTOR pathway. The Co-IP assay further confirmed the interaction between Rab22a and PI3Kp85α, the core regulatory subunit of PI3K. Application of rapamycin, the mTOR inhibitor, significantly reduced the upregulation of the proliferation, migration, and invasion abilities of lung adenocarcinoma cells transfected with Rab22a. These results suggest that Rab22a can promote the malignant phenotype of lung adenocarcinoma by upregulating the PI3K/Akt/mTOR signaling pathway, and may function as a potential anti-tumor therapeutic target.

Radiomics in Early Lung Cancer Diagnosis: From Diagnosis to Clinical Decision Support and Education.

Lung cancer is the most frequent cause of cancer-related death around the world. With the recent introduction of low-dose lung computed tomography for lung cancer screening, there has been an increasing number of smoking- and non-smoking-related lung cancer cases worldwide that are manifesting with subsolid nodules, especially in Asian populations. However, the pros and cons of lung cancer screening also follow the implementation of lung cancer screening programs. Here, we review the literature related to radiomics for early lung cancer diagnosis. There are four main radiomics applications: the classification of lung nodules as being malignant/benign; determining the degree of invasiveness of the lung adenocarcinoma; histopathologic subtyping; and prognostication in lung cancer prediction models. In conclusion, radiomics offers great potential to improve diagnosis and personalized risk stratification in early lung cancer diagnosis through patient–doctor cooperation and shared decision making.

Perineural Invasion in Pancreatic Ductal Adenocarcinoma (PDAC): A Saboteur of Curative Intended Therapies?

(1) Background: Perineural invasion (PNI) is a common characteristic of pancreatic ductal adenocarcinoma (PDAC) and is present in most resection margins. We hypothesized that curative pancreatic tumor resection with long-term survival could only be achieved in PNI-negative patients. (2) Material and Methods: A retrospective investigation of PDAC patients who underwent curative-intended surgery during the period 2008 to 2019 was performed at our institution. (3) Results: We identified 571 of 660 (86.5%) resected patients with well-annotated reports and complete datasets. Of those, 531 patients (93%) exhibited tumors with perineural invasion (Pn1), while 40 (7%) were negative for PNI (Pn0). The majority of patients in the Pn1 group presented advanced tumor stage and positive lymph node infiltration. Patients in the Pn0 group showed an improved disease-free and long-term survival compared to the Pn1 group (p < 0.001). Subgroup analysis of all R0-resected patients indicated improved long-term survival and disease-free survival of R0 Pn0 patients when compared to R0 Pn1 patients (p < 0.001). (4) Conclusion: Our study confirmed that Pn0 improves the long-term survival of PDAC-resected cancer patients. Furthermore, PNI significantly challenges the long-term survival of formally curative (R0) resected patients. We provide new insights into the dynamics of PNI in pancreatic cancer patients which are needed to define subgroups of patients for risk stratification and multimodal treatment strategies.

A computerized tomography-based radiomic model for assessing the invasiveness of lung adenocarcinoma manifesting as ground-glass opacity nodules

BackgroundClinically differentiating preinvasive lesions (atypical adenomatous hyperplasia, AAH and adenocarcinoma in situ, AIS) from invasive lesions (minimally invasive adenocarcinomas, MIA and invasive adenocarcinoma, IA) manifesting as ground-glass opacity nodules (GGOs) is difficult due to overlap of morphological features. Hence, the current study was performed to explore the diagnostic efficiency of radiomics in assessing the invasiveness of lung adenocarcinoma manifesting as GGOs.MethodsA total of 1018 GGOs pathologically confirmed as lung adenocarcinoma were enrolled in this retrospective study and were randomly divided into a training set (n = 712) and validation set (n = 306). The nodules were delineated manually and 2446 intra-nodular and peri-nodular radiomic features were extracted. Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used for feature selection. Clinical and semantic computerized tomography (CT) feature model, radiomic model and a combined nomogram were constructed and compared. Decision curve analysis (DCA) was used to evaluate the clinical value of the established nomogram.Results16 radiomic features were selected and used for model construction. The radiomic model exhibited significantly better performance (AUC = 0.828) comparing to the clinical-semantic model (AUC = 0.746). Further analysis revealed that peri-nodular radiomic features were useful in differentiating between preinvasive and invasive lung adenocarcinomas appearing as GGOs with an AUC of 0.808. A nomogram based on lobulation sign and radiomic features showed the best performance (AUC = 0.835), and was found to have potential clinical value in assessing nodule invasiveness.ConclusionsRadiomic model based on both intra-nodular and peri-nodular features showed good performance in differentiating between preinvasive lung adenocarcinoma lesions and invasive ones appearing as GGOs, and a nomogram based on clinical, semantic and radiomic features could provide clinicians with added information in nodule management and preoperative evaluation.

Identification of EMT-Related lncRNAs as Potential Prognostic Biomarkers and Therapeutic Targets for Pancreatic Adenocarcinoma.

Epithelial-mesenchymal transition (EMT) can promote carcinoma progression by multiple mechanisms; many studies demonstrated the invasiveness of pancreatic adenocarcinoma (PAAD) associated with the EMT, but how it acts through an lncRNA-dependent manner is unknown. Here, we investigated 146 samples from The Cancer Genome Atlas (TCGA) and 92 samples from the International Cancer Genome Consortium (ICGC). By gene set variation analysis (GSVA) and weighted correlation network analysis (WGCNA), we explored the EMT-related long noncoding RNAs (EMTlnc). Then, we performed univariate Cox regression analysis to screen their prognostic value for PAAD. The least absolute contraction and selection operator (LASSO) Cox regression was used to establish EMT-related lncRNA prognostic signal (EMT-LPS). In addition, we established a competitive endogenous ceRNA network. Then, we identified 33 prognostic EMTlnc as prognostic lncRNAs and established an EMT-LPS which showed strong prognostic ability in stratification analysis. By corresponding risk scores, patients were divided into low-risk and high-risk subgroups. Principal component analysis (PCA) showed that these subgroups had individual EMT status. Enrichment analysis showed that in the high-risk subgroup, biological processes, pathways, and hallmarks related to malignant tumors are more common. What is more, we constructed a nomogram that had powerful ability to predict the overall survival rate (OS) of PAAD patients in two datasets. So, EMT-LPS are a principal element in PAAD's carcinoma progression and may help us in choosing the way of prognosis assessment and provide some clues to design the new drugs for PAAD.

A novel EHD1/CD44/Hippo/SP1 positive feedback loop potentiates stemness and metastasis in lung adenocarcinoma.

There is growing evidence that endocytosis plays a pivotal role in cancer metastasis. In this study, we first identified endocytic and metastasis-associated genes (EMGs) and then investigated the biological functions and mechanisms of EMGs. Cancer stem cells (CSCs)-like characteristics were evaluated by tumour limiting dilution assays, three-dimensional (3D) spheroid cancer models. Microarray analysis was used to identify the pathways significantly regulated by mammalian Eps15 homology domain protein 1 (EHD1) knockdown. Mass spectrometry (MS) was performed to identify EHD1-interacting proteins. The function of EHD1 as a regulator of cluster of differentiation 44 (CD44) endocytic recycling and lysosomal degradation was determined by CD44 biotinylation and recycling assays. EHD1 was identified as a significant EMG. Knockdown of EHD1 suppressed CSCs-like characteristics, epithelial-mesenchymal transition (EMT), migration and invasion of lung adenocarcinoma (LUAD) cells by increasing Hippo kinase cascade activation. Conversely, EHD1 overexpression inhibited the Hippo pathway to promote cancer stemness and metastasis. Notably, utilising MS analysis, the CD44 protein was identified as a potential binding partner of EHD1. Furthermore, EHD1 enhanced CD44 recycling and stability. Indeed, silencing of CD44 or disruption of the EHD1/CD44 interaction enhanced Hippo pathway activity and reduced CSCs-like traits, EMT and metastasis. Interestingly, specificity protein 1 (SP1), a known downstream target gene of the Hippo-TEA-domain family members 1 (TEAD1) pathway, was found to directly bind to the EHD1 promoter region and induce its expression. Among clinical specimens, the EHD1 expression level in LUAD tissues of metastatic patients was higher than that of non-metastatic patients. Our findings emphasise that EHD1 might be a potent anti-metastatic target and present a novel regulatory mechanism by which the EHD1/CD44/Hippo/SP1 positive feedback circuit plays pivotal roles in coupling modules of CSCs-like properties and EMT in LUAD. Targeting this loop may serve as a remedy for patients with advanced metastatic LUAD.

Computed tomography versus frozen sections for distinguishing lung adenocarcinoma: A cohort study of concordance rate

BackgroundComputed tomography (CT) imaging can help to predict the pathological invasiveness of early-stage lung adenocarcinoma and guide surgical resection. This retrospective study investigated whether CT imaging could distinguish pre-invasive lung adenocarcinoma from IAC. It also compared final pathology prediction accuracy between CT imaging and intraoperative frozen section analysis. MethodsThis study included 2093 patients with early-stage peripheral lung adenocarcinoma who underwent CT imaging and intraoperative frozen section analysis between March 2013 and November 2014. Nodules were classified as ground-glass (GGNs), part-solid (PSNs), and solid nodules according to CT findings; they were classified as pre-IAC and IAC according to final pathology. Univariate, multivariate, and receiver operating characteristic (ROC) curve analyses were performed to evaluate whether CT imaging could distinguish pre-IAC from IAC. The concordance rates of CT imaging and intraoperative frozen section analyses with final pathology were also compared to determine their accuracies. ResultsMultivariate analysis identified tumor size as an independent distinguishing factor. ROC curve analyses showed that the optimal cut-off sizes for distinguishing pre-IAC from IAC for GGNs, PSNs, and solid nodules were 10.79, 11.48, and 11.45 mm, respectively. The concordance rate of CT imaging with final pathology was significantly greater than the concordance rate of intraoperative frozen section analysis with final pathology (P = 0.041). ConclusionCT imaging could distinguish pre-IAC from IAC in patients with early-stage lung adenocarcinoma. Because of its accuracy in predicting final pathology, CT imaging could contribute to decisions associated with surgical extent. Multicenter standardized trials are needed to confirm the findings in this study.

Diagnosis of Serosal Invasion in Gastric Adenocarcinoma by Dual-Energy CT Radiomics: Focusing on Localized Gastric Wall and Peritumoral Radiomics Features

ObjectivesTo build a radiomics model and combined model based on dual-energy CT (DECT) for diagnosing serosal invasion in gastric adenocarcinoma.Materials and methods231 gastric adenocarcinoma patients were enrolled and randomly divided into a training (n = 132), testing (n = 58), and independent validation (n = 41) cohort. Radiomics features were extracted from the rectangular ROI of the 120-kV equivalent mixed images and iodine map (IM) images in the venous phase of DECT, which was manually delineated perpendicularly to the gastric wall in the deepest location of tumor infiltration, including the peritumoral adipose tissue within 5 mm outside the serosa. The random forest algorithm was used for radiomics model construction. Traditional features were collected by two radiologists. Univariate and multivariate logistic regression was used to construct the clinical model and combined model. The diagnostic efficacy of the models was evaluated using ROC curve analysis and compared using the Delong’s test. The calibration curves were used to evaluate the calibration performance of the combined model.ResultsBoth the radiomics model and combined model showed high efficacy in diagnosing serosal invasion in the training, testing and independent validation cohort, with AUC of 0.90, 0.90, and 0.85 for radiomics model; 0.93, 0.93, and 0.89 for combined model. The combined model outperformed the clinical model (AUC: 0.76, 0.76 and 0.81).ConclusionThe radiomics model and combined model constructed based on tumoral and peritumoral radiomics features derived from DECT showed high diagnostic efficacy for serosal invasion in gastric adenocarcinoma.

CTHRC1 targeted by miR-30a-5p regulates cell adhesion, invasion and migration in lung adenocarcinoma

The morbidity of lung cancer ranks first among all cancers. Lung adenocarcinoma (LUAD) is a classification of lung cancer, and cell invasion and migration of LUAD are the main causes for its high mortality. Therefore, further exploring the potential mechanism of LUAD metastasis may provide bases for following targeted drug development and treatment of LUAD. In this study, clinical data as well as gene expression profiles were obtained from TCGA-LUAD and GEO to analyze CTHRC1 expression. The result found that CTHRC1 was significantly high in LUAD. Similar results were also discovered in 4 cancer cell lines. Moreover, overexpressed/knock-down CTHRC1 cell lines were constructed. It was uncovered that overexpressing CTHRC1 promoted LUAD cell migration and invasion, and inhibited cell adhesion, while knocked down CTHRC1 had the opposite effect. Afterward, the upstream miRNAs that regulated CTHRC1 were predicted by several bioinformatics websites. It was testified by dual-luciferase method that CTHRC1 was negatively mediated by miR-30a-5p. Overexpressed miR-30a-5p suppressed cell invasion/migration, and increased cell adhesion, while overexpressing CTHRC1 as well reversed such impacts. In conclusion, it was disclosed in this study that CTHRC1 worked as a cancer promoter in LUAD, and miR-30a-5p could target and downregulate CTHRC1 to regulate cell adhesion, and inhibited LUAD cell invasion and migration. These results elucidated at cellular level that upregulated CTHRC1 may be a marker protein for LUAD metastasis.

The small molecule chemical compound cinobufotalin attenuates resistance to DDP by inducing ENKUR expression to suppress MYH9-mediated c-Myc deubiquitination in lung adenocarcinoma.

The small molecule chemical compound cinobufotalin (CB) is reported to be a potential antitumour drug that increases cisplatin (DDP) sensitivity in nasopharyngeal carcinoma. In this study, we first found that CB decreased DDP resistance, migration and invasion in lung adenocarcinoma (LUAD). Mechanistic studies showed that CB induced ENKUR expression by suppressing PI3K/AKT signalling to downregulate c-Jun, a negative transcription factor of ENKUR. Furthermore, ENKUR was shown to function as a tumour suppressor by binding to β-catenin to decrease c-Jun expression, thus suppressing MYH9 transcription. Interestingly, MYH9 is a binding protein of ENKUR. The Enkurin domain of ENKUR binds to MYH9, and the Myosin_tail of MYH9 binds to ENKUR. Downregulation of MYH9 reduced the recruitment of the deubiquitinase USP7, leading to increased c-Myc ubiquitination and degradation, decreased c-Myc nuclear translocation, and inactivation of epithelial-mesenchymal transition (EMT) signalling, thus attenuating DDP resistance. Our data demonstrated that CB is a promising antitumour drug and may be a candidate chemotherapeutic drug for LUAD patients.

Fibroblast Activation Protein-Alpha is a Prognostic Biomarker Associated With Ferroptosis in Stomach Adenocarcinoma.

Background: The potential role of fibroblast activation protein-alpha (FAP) in modulating the progression and invasion of stomach adenocarcinoma (STAD) has not yet been comprehensively investigated. This study aimed to explore the role of FAP in STAD and the underlying association between FAP and the tumor microenvironment (TME) and ferroptosis. Methods: Overall survival was analyzed to evaluate the prognostic value of FAP based on gene expression data and clinical information on STAD. Associations between FAP expression, clinical parameters, and immune characteristics were comprehensively analyzed. The ferroptosis-related patterns of STAD samples were investigated based on 43 ferroptosis-related genes, and the correlations between these clusters and clinical characteristics were evaluated. The possible biological functions and pathways were explored using gene set enrichment analysis (GSEA). Results: FAP was identified as a novel biomarker that significantly contributed to the poor prognosis of STAD (hazard ratio = 1.270, P = 0.013). The elevated level of FAP expression was related to a more advanced tumor stage in STAD. The close relationship between FAP and the TME was validated. Four distinct ferroptosis-related clusters (A–D) were evident. Evaluating ferroptosis-related clusters could illustrate the stages of STAD and patient prognosis. Cluster C displayed the lowest FAP expression and a better prognosis than the other clusters. The different clusters were linked to different biological mechanisms, including epithelial-mesenchymal transition and immune-relevant pathways. Conclusion: FAP is a promising biomarker to distinguish prognosis and is associated with the TME and ferroptosis in STAD.