Calendar-period trends in cervical precancer and cancer diagnoses since the introduction of human papillomavirus and cytology co-testing into routine cervical cancer screening at Kaiser Permanente Northern California.

OBJECTIVES: The longer-term impact of introducing human papillomavirus (HPV) testing into routine cervical cancer screening on precancer and cancer rates by histologic type has not been well described. Calendar trends in diagnoses were examined using data from Kaiser Permanente Northern California, which introduced triennial HPV and cytology co-testing in 2003 for women aged ≥30 years. METHODS: We examined trends in cervical precancer (cervical intraepithelial neoplasia grade 3 [CIN3] and adenocarcinoma in situ [AIS]) and cancer (squamous cell carcinoma [SCC] and adenocarcinoma [ADC]) diagnoses per 1000 screened during 2003-2018. We examined ratios of squamous vs. glandular diagnoses (SCC:ADC and CIN3:AIS). RESULTS: CIN3 and AIS diagnoses increased approximately 2% and 3% annually, respectively (ptrend < 0.001 for both). While SCC diagnoses decreased by 5% per annually (ptrend < 0.001), ADC diagnoses did not change. These patterns were generally observed within each age group (30-39, 40-49, and 50-64 years). ADC diagnoses per 1000 screened did not change even among those who underwent co-testing starting in 2003-2006. SCC:ADC decreased from approximately 2.5:1 in 2003-2006 to 1.3:1 in 2015-2018 while the CIN3:AIS remained relatively constant, ∼10:1. CONCLUSIONS: Since its introduction at KPNC, co-testing increased the detection of CIN3 over time, which likely caused a subsequent reduction of SCC. However, there has been no observed decrease in ADC. One possible explanation for lack of effectiveness against ADC is the underdiagnosis of AIS. Novel strategies to identify and treat women at high risk of ADC need to be developed and clinically validated.

Complementary value of electron microscopy and immunohistochemistry in the diagnosis of non-small cell lung cancer: A potential role for electron microscopy in the era of targeted therapy.

With the identification of therapeutic targets for lung adenocarcinoma, it has become mandatory to distinguish it from other entities. Some cases remain classified as non-small cell lung carcinoma, not otherwise specified (NSCLC-NOS) with immunohistochemistry. Electron microscopy (EM) can be useful, allowing the identification of glandular differentiation. The aim of this study was to determine the complementary value of immunohistochemistry and EM.Forty-eight NSCLC-NOS cases were selected (PSMAR-Biobank, Barcelona, Spain). Immunohistochemistry (TTF-1, p40) was performed. Tissue was retrieved from paraffin blocks. Results were compared to the final diagnosis, derived from combination of light microscopy, immunohistochemistry, EM, molecular studies and resection specimen.Immunohistochemistry concurred with final diagnosis in 36 cases (75%, Kappa = 0.517). EM agreed with final diagnosis in 35 (72.9%, Kappa = 0.471). Immunohistochemistry had a sensitivity = 73%, specificity = 100%, positive predictive value (PPV) = 100% and negative predictive value (NPV) = 52.4% for adenocarcinoma. All adenocarcinoma cases not solved by immunohistochemistry (n = 10) were classified by EM, and vice versa. Data from EM were identical to those of immunohistochemistry: sensitivity = 73%, specificity = 100%, PPV = 100% and NPV = 52.4%. Combining both techniques, 47 cases were coincident with final diagnosis (97.9%, Kappa = 0.943).EM can provide valuable information in subtyping NSCLC-NOS, being particularly useful when immunohistochemistry is inconclusive. EM could be considered as a complementary tool for decision-making in NSCLC-NOS.

Protein signatures of molecular pathways in non-small cell lung carcinoma (NSCLC): comparison of glycoproteomics and global proteomics.

BACKGROUND: Non-small cell lung carcinoma (NSCLC) remains the leading cause of cancer deaths in the United States. More than half of NSCLC patients have clinical presentations with locally advanced or metastatic disease at the time of diagnosis. The large-scale genomic analysis of NSCLC has demonstrated that molecular alterations are substantially different between adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). However, a comprehensive analysis of proteins and glycoproteins in different subtypes of NSCLC using advanced proteomic approaches has not yet been conducted. METHODS: We applied mass spectrometry (MS) technology featuring proteomics and glycoproteomics to analyze six primary lung SqCCs and eleven ADCs, and we compared the expression level of proteins and glycoproteins in tumors using quantitative proteomics. Glycoproteins were analyzed by enrichment using a chemoenzymatic method, solid-phase extraction of glycopeptides, and quantified by iTRAQ-LC-MS/MS. Protein quantitation was further annotated via Ingenuity Pathway Analysis. RESULTS: Over 6000 global proteins and 480 glycoproteins were quantitatively identified in both SqCC and ADC. ADC proteins (8337) consisted of enzymes (22.11%), kinases (5.11%), transcription factors (6.85%), transporters (6.79%), and peptidases (3.30%). SqCC proteins (6967) had a very similar distribution. The identified glycoproteins, in order of relative abundance, included membrane (42%) and extracellular matrix (>33%) glycoproteins. Oncogene-coded proteins (82) increased 1.5-fold among 1047 oncogenes identified in ADC, while 124 proteins from SqCC were up-regulated in tumor tissues among a total of 827 proteins. We identified 680 and 563 tumor suppressor genes from ADC and SqCC, respectively. CONCLUSION: Our systematic analysis of proteins and glycoproteins demonstrates changes of protein and glycoprotein relative abundance in SqCC (TP53, U2AF1, and RXR) and in ADC (SMARCA4, NOTCH1, PTEN, and MST1). Among them, eleven glycoproteins were upregulated in both ADC and SqCC. Two glycoproteins (ELANE and IGFBP3) were only increased in SqCC, and six glycoproteins (ACAN, LAMC2, THBS1, LTBP1, PSAP and COL1A2) were increased in ADC. Ingenuity Pathway Analysis (IPA) showed that several crucial pathways were activated in SqCC and ADC tumor tissues.

Biology and treatment of cervical adenocarcinoma.

Uterine cervical adenocarcinoma (ADC) has been increasing in its prevalence world widely despite the decrease of squamous cell carcinoma (SCC). It comprises nearly 20-25% of the all cervical malignancy in developed countries. The worse biological behavior had been reported in patients with intermediate- and high risk factors after surgery, and in advanced stage over Ⅲ, radiotherapy (RT) alone and concurrent chemo-radiotherapy (CCRT) with cisplatin was not always effective. As for chemotherapy (CT), the induction CT has not established, as well. Further molecular targeted therapy (MTT) has been studied. The targets of oncogenic driver mutations were vascular endothelial growth factor (VEGF) in SCC, or tyrosine kinase (TK) of endothelial growth factor receptor 2 (EGFR2, Her2/neu)-Ras-MAPK-ERK pathway. Bevacizumab (Bev, anti-VEGF monoclonal antibody) is considered as one of key agent with paclitaxel and carboplatin in SCC, but not for ADC. This article focuses on up-to-date knowledge of biology and possible specific therapeutic directions to explore in the management of cervical ADC.

The prognostic significance of histologic type in early stage cervical cancer - A multi-institutional study.

BACKGROUND: Cervical adenocarcinomas (ADC) have been viewed as more aggressive than squamous cell carcinoma (SCC). We analyzed an international cohort of early stage cervical cancer to determine the impact of histologic type. METHODS: Retrospective analysis of patients with SCC (148 patients) and ADC (130 patients) stages IA1-IB2 who underwent surgery at our three institutions (two from Detroit, one from Mexico) from 2000-2010 was performed for: age, stage, tumor size, lymphovascular invasion (LVI), invasion depth, lymph node status (LN), recurrence and survival. Pathologic review proceeded inclusion. RESULTS: In the Latino population, ADC's tended to be higher grade (p=0.01), while SCC's were larger with deeper invasion (p<0.001). LVI and LN were not significantly different. Recurrence rate (RR) was 8% (8/101) in ADC and 11.8% (9/76) in SCCs. 5 year survival (OS) was equivalent (98.2% and 95.2% for ADC and SCC respectively, p=0.369). In the Detroit cohort, we noted no difference in size, grade, depth of invasion, LVI, LN. RR was 8/72 (13.7%) for SCC and 4/29 (13.7%) but not statistically different between the tumor types (p=0.5). 5 year survival was 91% and 92% for ADC and SCC, respectively. In this population 33% of the patients with SCC and 34% of the patients with ADC received adjuvant chemo-radiation (p=0.4). Histologic type demonstrated no significant outcome difference for any type of adjuvant therapy. CONCLUSION: Comparing early stage disease cervical ADC and SCC suggests equivalent recurrence and survival. Therefore, the paradigm of more aggressive management of early stage cervical ADC warrants further investigation.

Aurora-A is a novel predictor of poor prognosis in patients with resected lung adenocarcinoma.

BACKGROUND: The Aurora-A (Aur-A) gene, a key regulator of mitosis, has been proved as an oncogene in a variety of cancers. The Aur-A overexpression has been proved correlated with aggressiveness of cancer cells. However, the frequency of Aur-A protein overexpression, as well as its association with clinicopathologic parameters and prognosis remain unclear in lung adenocarcinoma (ADC). This study tried to clarify the clinical significance of Aur-A in patients with resected lung ADC. PATIENTS AND METHODS: A total of 142 informative patients with surgically resected lung ADC and 20 normal lung tissues were enrolled. Western blot and immunohistochemistry (IHC) were utilized to assess protein expression of Aur-A. RESULT: The expression of Aur-A was elevated in most of tumor tissues compared with the adjacent tissues by western blot. The IHC results showed that Aur-A protein was over-expressed in 98 of 142 (69.0%) tumor sections, while Aur-A was low-expressed in all normal lung sections. A positive correlation between Aur-A overexpression rate and ascending pathologic stages was observed (P<0.05). Kaplan-Meier analysis demonstrated that patients with Aur-A high expression had significantly inferior survival compared to those with Aur-A low expression. Both overall survival (OS) and disease-free survival (DFS) of positive overexpression patients were shorter than the negative group (P=0.036, P=0.041, respectively). Multivariate analysis confirmed that Aur-A expression, as an independent and significant factor for both DFS and OS, could predict a poor prognosis in patients with resected lung ADC (P=0.022, P=0.049, respectively). CONCLUSIONS: Aur-A was overexpressed in lung ADC and overexpression of Aur-A might be a novel predictor for poor prognosis and potential therapeutic target in lung ADC.

The presence of micropapillary and/or solid subtypes is an independent prognostic factor for patients undergoing curative resection for stage I lung adenocarcinoma with ground-glass opacity.

Background: Non-predominant or even minimal micropapillary and/or solid (MP/S) subtypes have been reported to exert an unfavorable prognostic influence on surgically resected lung adenocarcinoma (ADC). Currently, there is a lack of evidence to demonstrate that high-grade pathological subtypes, including MP/S components, impact the prognosis of patients with surgically resected lung ADCs with ground-glass opacity (GGO). In this investigation, we explored the prognostic implications of minimal MP/S components in lung ADCs with GGO. Methods: A retrospective cohort study was conducted on 1,004 consecutive patients undergoing curative resection for pathologic stage (p-stage) I lung ADCs featuring GGO on computed tomography (CT) scans between January 2014 and December 2016. Tumors were categorized into MP/S positive (MP/S+) group and MP/S negative (MP/S-) group. MP/S+ tumors were defined when MP/S subtypes constituted ≥1% of the entire tumor. The prognostic impact of MP/S subtypes was evaluated using Kaplan-Meier analysis, Cox proportional hazard model and restricted cubic spine (RCS) model. Results: A total of 86 (8.6%) cases with MP/S+ tumors and 918 (91.4%) cases with MP/S- tumors were identified. The solid component tumor diameter and pathological invasive tumor size of MP/S+ tumors were both significantly larger than that of MP/S- tumors (13.0 vs. 4.0 mm, P<0.001, and 18.0 vs. 10.0 mm, P<0.001, respectively). After a median follow-up of 7.3 years, the presence of MP/S components was significantly associated with decreased RFS (5-year RFS, MP/S+ 88.3% vs. MP/S- 97.4%; P<0.001; HR =1.02). The presence of a histologic lepidic (Lep) component demonstrated a prognostic advantage in both MP/S- (5-year RFS, MP/S-Lep+ 98.0% vs. MP/S-Lep- 95.3%; P=0.01; HR =0.89) and MP/S+ subgroups (5-year RFS, MP/S+Lep+ 93.4% vs. MP/S+Lep- 83.2%; P=0.10; HR =0.84). MP/S+ components ≥5% were the only tumor-related factor that independently affected RFS [hazard ratio (HR) =1.77; 95% confidence interval (CI): 1.07-2.94] according to multivariate analysis. There was a progressively negative impact of the proportion of MP/S subtypes on RFS as illustrated by RCS model. Conclusions: The presence of MP/S patterns in stage I GGO-featured lung ADCs exhibit significant prognostic value and may have implications for tailored postoperative treatment and surveillance strategies, especially when the proportion exceeds 5% of the entire tumor.

Differentiating between pulmonary adenocarcinoma and squamous cell carcinoma by spectral CT volumetric quantitative analysis: a comparative study with conventional spectral analysis.

Background: Unlike the conventional spectral analyses of spectral computed tomography (CT) that cannot fully represent the whole lesion, the volumetric quantitative analysis reveals the information of the whole lesion and is of more accurate. So this study sought to evaluate the value of volumetric quantitative analysis in the differential diagnosis of pulmonary adenocarcinoma (ADC) and squamous cell carcinoma (SQCC). Methods: Fifty-seven patients with lung cancer confirmed by pathology, including 35 ADC and 22 SQCC patients, were retrospectively analyzed. Calcium concentration and effective-Z (Eff-Z) in plain scan (PS), iodine concentration, and water concentration in the arterial phase (AP) were measured. The Student t-test or rank-sum test was used to determine the statistically significant parameters. Receiver operating characteristic (ROC) curve was used, and the corresponding area under the curve (AUC), sensitivity and specificity was calculated to evaluate the diagnostic efficacy in differential diagnosis of ADC and SQCC. Results: In the volumetric quantitative analysis of spectral CT, the concentration of calcium [(6.97±2.83) mg/cm3], Eff-Z (7.90±0.14), and iodine [1.42 (0.84) mg/cm3] was significantly higher in ADC than SQCC [(5.14±2.39) mg/cm3, (7.80±0.10), 1.16 (0.65) mg/cm3, t=2.513, 2.860, Z=-2.246, P=0.015, 0.006, 0.025], but the concentration of water was significantly lower in ADC [995.00 (38.70) mg/cm3] than SQCC [1,007.00 (14.38) mg/cm3, Z=-2.082, P=0.037]. Moreover, whether it's ADC or SQCC, the concentrations of calcium [(8.51±4.28) mg/cm3, (5.96±2.50) mg/cm3], Eff-Z (7.97±0.20, 7.86±0.13), and water [1,007.00 (14.38) mg/cm3, 1,029.28 (10.49) mg/cm3] were lower in the volumetric spectral analysis than the conventional spectral analysis, while the concentration of iodine [1.33 (0.80) mg/cm3, 0.94 (0.63) mg/cm3] was significantly higher in the volumetric spectral analysis than the conventional spectral analysis. The ROC curve analysis showed that the areas under the curves (AUC) (0.76, 0.76, 0.75, 0.71), sensitivity (66.7%, 66.7%, 66.7%, 85.2%), and specificity (92.3%, 84.6%, 86.9%, 69.2%) of the volumetric spectral analysis parameters for the differential diagnosis of ADC and SQCC were higher than those of the conventional spectral analysis [(0.65, 0.66, 0.73, 0.63), (44.4%, 48.1%, 59.3%, 66.7%), (69.2%, 69.2%, 84.6%, 53.8%)] parameters. Conclusions: The volumetric quantitative analysis has a promising advantage in the observation range of whole lesions, it may be invaluable in the differential diagnosis of ADC and SQCC, and is worthy of clinical recommendation.

Prognostic role of immune microenvironment in pleural metastases from breast and lung adenocarcinomas.

Background: Pleural metastatic disease is a common disease with dismal prognosis. The immune microenvironment of metastatic pleural tissue remains largely unknown. Thus, we aimed to investigate the presence of different immune cell populations, and to compare them with clinical characteristics. Methods: We included 70 patients with lung and breast adenocarcinoma (ADC) diagnosed with pleural metastasis during a 2-year period with the primary endpoint to investigate if the main immune cell populations are present in pleural metastases and if they have any prognostic role. Secondary endpoints were to detect any differences in their presence between lung and breast primaries and to search for any correlation with the macroscopic (thoracoscopic) findings. We used immunohistochemical techniques for the detection of CD4+, CD8+, CD20+, CD163+ and S100+ cells in whole tissue pleural biopsies of lung and breast metastases. Results: Primary endpoint: all these populations are present in the biopsies from lung and higher stromal and intratumoral CD4 counts, as well as higher stromal CD20 cells were positive prognostic factors for lung cancer metastases, while higher S100 intratumoral counts were positive prognostic factors in lung and marginally breast cancer metastases. Secondary endpoints: significant higher values for the stromal CD163 group (P=0.04) and for the intratumoral S100 group (P=0.006) were seen in lung compared to breast metastases. Interesting correlations were also noted between thoracoscopic findings (nodules, masses, pachypleuritis) and the different factors studied. Conclusions: Our data show that the immune microenvironment may be important in this advanced tumoral setting and that possible targets of the nowadays numerous treatment strategies implicating the immune system may merit further exploration in this poor prognosis disease.

Deep Learning Analysis of CT Images Reveals High-Grade Pathological Features to Predict Survival in Lung Adenocarcinoma.

We aimed to develop a deep learning (DL) model for predicting high-grade patterns in lung adenocarcinomas (ADC) and to assess the prognostic performance of model in advanced lung cancer patients who underwent neoadjuvant or definitive concurrent chemoradiation therapy (CCRT). We included 275 patients with 290 early lung ADCs from an ongoing prospective clinical trial in the training dataset, which we split into internal-training and internal-validation datasets. We constructed a diagnostic DL model of high-grade patterns of lung ADC considering both morphologic view of the tumor and context view of the area surrounding the tumor (MC3DN; morphologic-view context-view 3D network). Validation was performed on an independent dataset of 417 patients with advanced non-small cell lung cancer who underwent neoadjuvant or definitive CCRT. The area under the curve value of the DL model was 0.8 for the prediction of high-grade histologic patterns such as micropapillary and solid patterns (MPSol). When our model was applied to the validation set, a high probability of MPSol was associated with worse overall survival (probability of MPSol >0.5 vs. <0.5; 5-year OS rate 56.1% vs. 70.7%), indicating that our model could predict the clinical outcomes of advanced lung cancer patients. The subgroup with a high probability of MPSol estimated by the DL model showed a 1.76-fold higher risk of death (HR 1.76, 95% CI 1.16-2.68). Our DL model can be useful in estimating high-grade histologic patterns in lung ADCs and predicting clinical outcomes of patients with advanced lung cancer who underwent neoadjuvant or definitive CCRT.

Rethinking a Non-Predominant Pattern in Invasive Lung Adenocarcinoma: Prognostic Dissection Focusing on a High-Grade Pattern.

BACKGROUND: Prognostic considerations for non-predominant patterns are necessary because most lung adenocarcinomas (ADCs) have a mixed histologic pattern, and the spectrum of actual prognosis varies widely even among lung ADCs with the same most predominant pattern. We aimed to identify prognostic stratification by second most predominant pattern of lung ADC and to more accurately assess prognostic factors with CT imaging analysis, particularly enhancing non-predominant but high-grade pattern. METHODS: In this prospective study, patients with early-stage lung ADC undergoing curative surgery underwent preoperative dual-energy CT (DECT) and positron emission tomography (PET)/CT. Histopathology of ADC, the most predominant and second most predominant histologic patterns, and preoperative imaging parameters were assessed and correlated with patient survival. RESULTS: Among the 290 lung ADCs included in the study, 231 (79.7%) were mixed-pathologic pattern. When the most predominant histologic pattern was intermediate-grade, survival curves were significantly different among the three second most predominant subgroups (p = 0.004; low, lepidic; intermediate, acinar and papillary; high, micropapillary and solid). When the second most predominant pattern was high-grade, recurrence risk increased by 4.2-fold compared with the low-grade group (p = 0.005). To predict a non-predominant but high-grade pattern, the non-contrast CT value of tumor was meaningful with a lower HU value associated with the histologic combination of lower grade (low-grade as most predominant and intermediate-grade as second most predominant pattern, OR = 6.15, p = 0.005; intermediate-grade as most predominant and high-grade as second most predominant pattern, OR = 0.10, p = 0.033). SUVmax of the tumor was associated with the non-predominant but high-grade pattern, especially in the histologic combination of intermediate-high grade (OR = 1.14, p = 0.012). CONCLUSIONS: The second most predominant histologic pattern can stratify lung ADC patients according to prognosis. Thus, predicting the malignant potential and establishing treatment policies should not rely only on the most predominant pattern. Moreover, imaging parameters of non-contrast CT value and SUVmax could be useful in predicting a non-predominant but high-grade histologic pattern.

Integration of clinicopathological and mutational data offers insight into lung cancer with tumor spread through air spaces.

BACKGROUND: Tumor spread through air spaces (STAS) was defined as a unique tumor invasion pattern in adenocarcinoma (ADC) by The World Health Organization Classification of Lung Tumors in 2015. Since then, STAS had been shown to be associated with local recurrence and poor survival results, as the typical signature and potential mechanisms of STAS remained unclear. Our objectives were to comprehensively demonstrate the clinicopathological and genetic signatures in STAS-positive lung cancer patients. METHODS: The clinicopathological and gene alteration characteristics of 878 STAS-positive lung cancer patients were presented. Associations between parameters were evaluated using the Chi-square test, Fisher's exact test, and logistic regression. The capture-based targeted next generation sequencing (NGS) with a platform of 68 lung cancer-related genes was conducted in 139 cases, and the mutational spectrum was summarized. RESULTS: STAS was identified in 391 female and 481 male patients, of which ADC accounted for the majority of cases (92.6%). The concomitant solid or micropapillary subtype was observed in 92.12% patients with ADC. Poorly differentiated histological subtypes were more frequent and negatively correlated with tumor size in smaller tumor cases (P=0.036, Pearson's R=-0.075). Furthermore, in the subgroup of nodules within 3 cm, the distribution of the solid and micropapillary subtypes were significantly frequent in lymph node-positive patients (P<0.001). Tumor protein p53 (TP53) alterations were more frequent in smoking patients (27.6%, P=0.007), human epidermal growth factor receptor 2 (HER2) alterations were more common in female (10.8%, P=0.025), while Kirsten rat sarcoma viral oncogene (KRAS) (20.3%, P=0.024) and TP53 (45.9%, P=0.003) were more prevalent in males. CONCLUSIONS: Poorly differentiated histological subtypes likely played a crucial role in promoting the invasiveness of STAS, especially in small tumor-size cases. Epidermal growth factor receptor (EGFR), TP53, KARS, anaplastic lymphoma kinase (ALK), and ROS proto-oncogene 1 (ROS1) were the five most frequent alterations in STAS-positive ADC.

A subregion-based positron emission tomography/computed tomography (PET/CT) radiomics model for the classification of non-small cell lung cancer histopathological subtypes.

BACKGROUND: This study classifies lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) using subregion-based radiomics features extracted from positron emission tomography/computed tomography (PET/CT) images. METHODS: In this study, the standard 18F-fluorodeoxyglucose (FDG) PET/CT images of 150 patients with lung ADC and 100 patients with SCC were retrospectively collected from the PET Center of the First Affiliated Hospital, College of Medicine, Zhejiang University. First, the 3D feature vector of each tumor voxel (whose basis is PET value, CT value, and CT local dominant orientation) was extracted. Using K-means individual clustering and population clustering, each tumor was divided into 4 subregions that reflect intratumoral regional heterogeneity. Next, based on each subregion, 385 radiomics features were extracted. Clinical features including age, gender, and smoking history were included. Thus, there were a total of 1,543 features extracted from PET/CT images and clinical reports. Statistical tests were then used to eliminate irrelevant and redundant features, and the recursive feature elimination (RFE) algorithm was used to select the best feature subset to classify SCC and ADC. Finally, 7 types of classifiers were tested to achieve the optimized model for the classification: support vector machine (SVM) with linear kernel, SVM with radial basis function kernel (SVM-RBF), random forest, logistic regression, Gaussian process classifier, linear discriminant analysis, and the AdaBoost classifier. Furthermore, 5-fold cross-validation was applied to obtain the sensitivity, specificity, accuracy, and area under the curve (AUC) for performance evaluation. RESULTS: Our model exhibited the best performance with the subregion radiomics features and SVM-RBF classifier, with a 5-fold cross-validation sensitivity, specificity, accuracy, and AUC of 0.8538, 0.8758, 0.8623, and 0.9155, respectively. The interquartile range feature from subregion 2 of CT and the gender feature from the clinical reports are the 2 optimized features that achieved the highest comprehensive score. CONCLUSIONS: Our proposed model showed that SCC and ADC could be classified successfully using PET/CT images, which could be a promising tool to assist radiologists or medical physicists during diagnosis. The subregion-based method illustrated that non-small cell lung cancer (NSCLC) depicts intratumoral regional heterogeneity on both CT and PET images. By defining these heterogeneities through a subregion-based method, the diagnostic performance was improved. The 3D feature vector (whose basis is PET value, CT value, and CT local dominant orientation) showed superiority in reflecting NSCLC intratumoral regional heterogeneity.

Lung cancer in women in 21th century.

Lung cancer is the first cause of death from malignant disease. The distressing epidemiological data show the increasing female to male incidence ratio for this tumor. A high incidence of lung cancer in never smokers with importance of environmental agents makes a problem among women. Adenocarcinoma (ADC) is noted in women with increasing rate and ethnic background impacts female lung cancer with differences in the incidence of genetic aberrations. The conception of different hormonal status is taken into consideration as potential explanation of variant cancer biology and clinical manifestation in women and men. The impact of 17-ß-estradiol, estrogen receptors, aromatase expression, pituitary sex hormones receptors in carcinogenesis with relation between estrogens and genetic aberrations are investigated. The response to newest therapies among female is also different than in men. This overview summarizes currently available evidence on the specificity of female lung cancer and presents the direction of necessary studies.

Clinical T category for lung cancer staging: A pragmatic approach for real-world practice.

BACKGROUND: To determine which components should be measured and which window settings are appropriate for computerized tomography (CT) size measurements of lung adenocarcinoma (ADC) and to explore interobserver agreement and accuracy according to the eighth edition of TNM staging. METHODS: A total of 165 patients with surgically resected lung ADC earlier than stage 3A were included in this study. One radiologist and two pulmonologists independently measured the total and solid sizes of components of tumors on different window settings and assessed solidity. CT measurements were compared with pathologic size measurements. RESULTS: In categorizing solidity, 25% of the cases showed discordant results among observers. Measuring the total size of a lung adenocarcinoma predicted pathologic invasive components to a degree similar to measuring the solid component. Lung windows were more accurate (intraclass correlation [ICC] = 0.65-0.81) than mediastinal windows (ICC = 0.20-0.72) at predicting pathologic invasive components, especially in a part-solid nodule. Interobserver agreements for measurement of solid components were good with little significant difference (lung windows, ICC = 0.89; mediastinal windows, ICC = 0.91). A high level of interobserver agreement was seen between the radiologist and pulmonologists and between residents (from the division of pulmonology and critical care) versus a fellow (from the division of pulmonology and critical care) on different windows. CONCLUSIONS: A considerable percentage (25%) of discrepancies was encountered in categorizing the solidity of lesions, which may decrease the accuracy of measurements. Lung window settings may be superior to mediastinal windows for measuring lung ADCs, with comparable interobserver agreement and moderate accuracy for predicting pathologic invasive components. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: Lung window settings are better for evaluating part-solid lung adenocarcinoma (ADC), with comparable interobserver agreement and moderate accuracy for predicting pathologic invasive components. The considerable percentage (25%) of discrepancies in categorizing solidity of the lesions may also have decreased the accuracy of measurements. WHAT THIS STUDY ADDS: For accurate measurement and categorization of lung ADC, robust quantitative analysis is needed rather than a simple visual assessment.

High expression of forkhead box M1 (FOXM1) is a poor prognostic biomarker in lung adenocarcinoma.

BACKGROUND: Forkhead box M1 (FOXM1) is closely related to the formation and development of cancer. Because of differences in cellular origin, lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SCC) usually exhibit different signatures. Therefore, it is essential to investigate the abnormalities of FOXM1 in the two subtypes separately. METHODS: Through the Oncomine and TCGA databases, we investigated the expression of FOXM1 mRNA, its prognostic value and possible mechanisms leading to its dysregulation. Furthermore, networks involving FOXM1 and its significantly altered neighboring genes were identified using the cBioPortal database. GO and KEGG enrichment analyses were performed using DAVID. RESULTS: Expression of FOXM1 mRNA was higher in lung tumor tissues than in normal tissues, and higher in SCC tissues than in ADC tissues. FOXM1 mRNA expression was correlated with N stage, TNM stage, age, sex and smoking history in ADC, but only correlated with N stage, age and sex in SCC. Survival analysis indicated that high expression of FOXM1 mRNA resulted to poor overall survival (OS) for ADC patients, but not for SCC patients. Cox regression analysis confirmed that FOXM1 mRNA expression was an independent prognostic indicator for ADC patients, and regression analysis identified a moderately positive correlation between FOXM1 mRNA levels and copy number alterations (CNAs), but a weakly negative association with DNA methylation. FOXM1 was mainly involved in cell cycle regulation, G2/M transition, G1/S transition and p53, PI3K-Akt and TGF-beta signaling pathway. CONCLUSIONS: High expression of FOXM1 mRNA might be an independent biomarker of poor OS in ADC patients.

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

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

Surgical pathology of early stage non-small cell lung carcinoma.

The histologic classification of non-small cell lung carcinoma (NSCLC), particularly adenocarcinoma (ADC), has undergone extensive study in recent decades, ultimately resulting in an extensively updated classification system. The 2015 World Health Organization (WHO) classification of ADC provides greatly improved prognostic information in comparison to the 2004 WHO classification. Several issues still require further investigation: lepidic predominant ADC, prognostic significance of poor prognostic subtypes such as micropapillary carcinoma, the more recently described concept of spread of tumor through airspaces (STAS), and the utility of sublobar resections. While limited resection appears to be suitable for tumors with a ground glass radiographic appearance, which typically correspond to adenocarcinoma in situ (MIS) or minimally invasive adenocarcinoma (MIA) histologically, the role of sublobar resection in radiographic solid tumors is not as clear, and the impact of histologic subtypes with a poor prognosis needs further evaluation. Squamous cell carcinoma (SCC) has not been as extensively studied and the current classification lacks subclassification with significant prognostic information.