scholarly journals Desmin and CD31 immunolabeling for detecting venous invasion of the pancreatobiliary tract cancers

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242571
Author(s):  
Junyoung Shin ◽  
Laura D. Wood ◽  
Ralph H. Hruban ◽  
Seung-Mo Hong
Keyword(s):  
Disease Free Survival ◽  
Venous Invasion ◽  
Intraepithelial Neoplasia ◽  
Prognostic Indicator ◽  
Prognostic Information ◽  
Test Set ◽  
Poor Prognostic Factor ◽  
Tract Cancer ◽  
Added Benefit ◽  
Validation Set

Although venous invasion (VI) is a poor prognostic factor for patients with pancreatobiliary tract cancers, its histopathologic characteristics have not been well described. We evaluated the patterns of VI and the added benefit provided by CD31, desmin, and dual CD31‒desmin immunolabeling for identification of VI. We included 120 surgically resected pancreatobiliary tract cancer cases—59 cases as a test set with known VI and 61 cases as a validation set without information of VI. VI was classified into three patterns: intraepithelial neoplasia-like (IN-like), conventional, and destructive. Hematoxylin and eosin (H&E) staining and CD31, desmin, and dual CD31‒desmin immunolabeling were performed. Foci number and patterns of VI were compared with the test and validation sets. More foci of VI were detected by single CD31 (P = 0.022) than H&E staining in the test set. CD31 immunolabeling detected more foci of the conventional pattern of VI, and desmin immunolabeling detected more foci of the destructive pattern (all, P < 0.001). Dual CD31‒desmin immunolabeling identified more foci of VI (P = 0.012) and specifically detected more foci of IN-like (P = 0.045) and destructive patterns (P < 0.001) than H&E staining in the validation set. However, dual CD31‒desmin immunolabeling was not helpful for detecting the conventional pattern of VI in the validation set. Patients with VI detected by dual CD31‒desmin immunolabeling had shorter disease-free survival (P <0.001) than those without VI. VI detected by dual CD31‒desmin immunolabeling was a worse prognostic indicator (P = 0.009). More foci of VI could be detected with additional single CD31 or dual CD31‒desmin immunolabeling. The precise evaluation of VI with dual CD31‒desmin immunolabeling can provide additional prognostic information for patients with surgically resected pancreatobiliary tract cancers.

scholarly journals β-Catenin Expression Negatively Correlates with WIF1 and Predicts Poor Clinical Outcomes in Patients with Cervical Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jinxiao Liang ◽  
Hui Zhou ◽  
Yongpai Peng ◽  
Xiaofei Xie ◽  
Ruixin Li ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Disease Free Survival ◽  
Intraepithelial Neoplasia ◽  
Clinicopathological Characteristics ◽  
Poor Prognostic Factor ◽  
Node Metastasis ◽  
Canonical Wnt ◽  
Wnt Inhibitory Factor 1

Aberrant activation of the canonical Wnt pathway plays a significant role in cervical cancer (CC). However, limited data show the correlation between the cancer clinicopathological characteristics and the key molecules such as β-catenin and Wnt inhibitory factor 1 (WIF1). In this study, β-catenin and WIF1 expression were analyzed by immunohistochemistry for 196 patients with CC, 39 with cervical intraepithelial neoplasia (CIN), and 41 with normal cervical epithelium (NCE). Significant overexpression of β-catenin was detected in CC (67.9%) when compared to CIN (43.6%) or NCE (34.1%), p<0.01, while low WIF1 expression was detected in CC (24.0%) when compared to CIN (59.0%) or NCE (58.5%), p<0.001. Negative correlation was shown between β-catenin and WIF1 expression (r=-0.637, p<0.001). In addition, multivariate analysis revealed that both lymph node metastasis and β-catenin expression were the independent prognostic factors not only for disease-free survival (HR = 5.029, p<0.001; HR = 2.588, p=0.035, resp.), but also for overall survival (HR = 5.058, p<0.001; HR = 2.873, p=0.031, resp.). Our findings indicate that, besides lymph node metastasis, β-catenin expression may also be a poor prognostic factor for CC while WIF1 could be a potential drug target for treatment of advanced CC.

scholarly journals Correlation of p53 immunoexpression with DNA ploidy and apoptotic index in subsets of prostate cancer: A marker reiterated in progression and recurrence of prostate cancer

2015 ◽  
Vol 04 (02) ◽  
pp. 088-090 ◽  
Author(s):  
Anju Bansal ◽  
Anup Gupta ◽  
Sunita Saxena
Keyword(s):  
Prostate Cancer ◽  
Dna Ploidy ◽  
Intraepithelial Neoplasia ◽  
Predictive Biomarker ◽  
Prognostic Indicator ◽  
Apoptotic Index ◽  
Biological Behavior ◽  
Prognostic Information ◽  
Late Event ◽  
P53 Immunoreactivity

Abstract Background: Prediction of biological behavior in patients of prostate cancer (CaP) is a major challenge as current parameters only partially meet the need for prognostication. p53 as a prognostic indicator has been studied in several human cancers, including breast, lung, and colorectal carcinoma. However, its significance as a predictive biomarker for CaP is less well-studied. Materials and Methods: This study included 125 cases of CaP, 27 cases of prostatic intraepithelial neoplasia and 25 cases of benign prostatic hyperplasia. Immunohistochemical assessment for p53 nuclear protein was performed. Assessment for apoptotic index and DNA ploidy status by flow cytometry were also done. Results: p53 immunoreactivity was low in organ confined CaP cases having Gleason score ≤3 (P < 0.003). More hormone resistant cases 37 (83%) were aneuploid when compared with hormone sensitive cases 26 (33%) (P < 0.005). 93% of p53 positive cases and none of the p53 negative patient were aneuploid suggesting a significant relation between p53 immunoreactivity and aneuploidy. p53 positivity and DNA aneuploidy, independently, were also predictors of progression and relapse. Conclusion: DNA ploidy and p53 positivity go hand in hand and together yield additional prognostic information in CaP. p53 positivity is possibly a late event in carcinogenesis in CaP and a marker of change in biological behavior of CaP.

scholarly journals CEA and CYFRA 21-1 as prognostic biomarker and as a tool for treatment monitoring in advanced NSCLC treated with immune checkpoint inhibitors

2020 ◽  
Vol 12 ◽  
pp. 175883592095299
Author(s):  
Filippo G. Dall’Olio ◽  
Francesca Abbati ◽  
Francesco Facchinetti ◽  
Maria Massucci ◽  
Barbara Melotti ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Repeated Measures ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Cytokeratin 19 ◽  
Blood Levels ◽  
Prognostic Information ◽  
Test Set ◽  
Therapy Assessment ◽  
Validation Set

Aims: To assess prognostic value of pre-therapy carcinoembryonic antigen (CEA) and cytokeratin-19 fragments (CYFRA 21-1) blood levels in non-small cell lung cancer (NSCLC) patients treated with immune-checkpoint inhibitors (ICIs) and their early change as predictor of benefit. Materials and methods: This is a retrospective cohort study including patients with stage IIIB–IV NSCLC who received anti PD-1/PD-L1 in first or advanced lines of therapy in two institutions. A control cohort of patients treated only with chemotherapy has been enrolled as well. Results: A total of 133 patients treated with nivolumab or atezolizumab were included in the test set, 74 treated with pembrolizumab first line in the validation set and 89 in the chemotherapy only cohort. CYFRA 21-1 >8 ng/mL was correlated with overall survival (OS) in the test set, validation set and in univariate and multivariate analysis (pooled cohort hazard ratio (HR) 1.90, 95% confidence interval (CI) 1.24–2.93, p 0.003). Early 20% reduction after the third cycle was correlated with OS for CEA (HR 0.12; 95% CI 0.04–0.33; p < 0.001), and for CYFRA 21-1 (HR 0.19; 95% CI 0.07–0.55; p 0.002) Conclusions: CYFRA 21-1 pre-therapy assessment provides clinicians with relevant prognostic information about patients treated with ICI. CEA and CYFRA 21-1 repeated measures could be useful as an early marker of benefit.

Prognostic value of Bcl-2 in breast cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e11527-e11527
Author(s):  
Patricia Ibeas ◽  
Ana Lopez-Gonzalez ◽  
Bernard Gaston Doger de Speville ◽  
Miriam Huelves ◽  
Roberto Lopez ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factor ◽  
Hormone Receptors ◽  
Menopausal Status ◽  
Disease Free Survival ◽  
Independent Prognostic Factor ◽  
Prognostic Information ◽  
Poor Prognostic Factor ◽  
Age Of Diagnosis ◽  
The Moment

e11527 Background: Breast cancer is a heterogeneous disease with prognostic factors used by the oncologists to decide the treatment. Bcl2 is an antiapoptotic proto-oncogen involved in DNA break process that has been defined historically as a poor prognostic factor. This study was conducted to confirm whether or not bcl-2 is an independent prognostic factor. Methods: In this study, we have reviewed all patients who were diagnosed at our hospital between January 2007 and December 2008 (99 patients). Inclusion criteria were patients diagnosed of breast cancer whose anatomopathological report showed bcl-2 status as well as the rest of the parameters measured. The parameters measured were age, past medical history, menopausal status, TNM, hormone receptors, HER2, p53, Ki67, bcl-2, treatment applied, date of relapse (if any), date of death ( if occurred). All of them characterized by centralization measures. We conducted an analysis of prognostic factor that influenced survival. Results: The average age of diagnosis is 54.6 years (30-94 years). 42.4% were premenopausal. The average tumor size was 2.59 cm ( 0.5-7.5 cm). 81.8% had positive estrogen receptors. 92% were HER2 negative by inmunohistochemistry. 62.6% were p53 negative. Bcl-2 was 84.8% positive. The distribution by stage at diagnosis was: stage I 26.3%; stage II 49.5%; stage III 22.2%. Disease free survival for patients bcl2(+) was 45.6 months versus 22.6 months for patients bcl2 (-) (0.12-22.2; p: 0.00125). Overall survival for the group bcl2(+) was 48 months (41.6-54.3) and bcl2 (-) was 48.24 months (42.48 to 54). Conclusions: We can state that bcl2 is not an independent prognostic factor. Despite the value in other diseases, the determination of bcl-2 by inmunohistochemistry in breast cancer in stages I, II and III at the moment of the diagnosis does not provide any prognostic information.

Prognostic role of aberrant mTOR activation in patients with stage II and III colorectal cancer

2020 ◽  
Vol 14 (12) ◽  
pp. 1127-1137
Author(s):  
Tong-Tong Zhang ◽  
Yi-Qing Zhu ◽  
Hong-Qing Cai ◽  
Jun-Wen Zheng ◽  
Jia-Jie Hao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Stage Ii ◽  
Poor Prognostic Factor ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Risk Predictor

Aim: This study aimed to develop an effective risk predictor for patients with stage II and III colorectal cancer (CRC). Materials & methods: The prognostic value of p-mTOR (Ser2448) levels was analyzed using Kaplan–Meier survival analysis and Cox regression analysis. Results: The levels of p-mTOR were increased in CRC specimens and significantly correlated with poor prognosis in patients with stage II and III CRC. Notably, the p-mTOR level was an independent poor prognostic factor for disease-free survival and overall survival in stage II CRC. Conclusion: Aberrant mTOR activation was significantly associated with the risk of recurrence or death in patients with stage II and III CRC, thus this activated proteins that may serve as a potential biomarker for high-risk CRC.

scholarly journals A MYC-Driven Plasma Polyamine Signature for Early Detection of Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 913
Author(s):  
Johannes Fahrmann ◽  
Ehsan Irajizad ◽  
Makoto Kobayashi ◽  
Jody Vykoukal ◽  
Jennifer Dennison ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Stage ◽  
Area Under The Curve ◽  
Polyamine Metabolism ◽  
Healthy Controls ◽  
Test Set ◽  
Exact Test ◽  
Oncogenic Driver ◽  
Characteristic Area ◽  
Validation Set

MYC is an oncogenic driver in the pathogenesis of ovarian cancer. We previously demonstrated that MYC regulates polyamine metabolism in triple-negative breast cancer (TNBC) and that a plasma polyamine signature is associated with TNBC development and progression. We hypothesized that a similar plasma polyamine signature may associate with ovarian cancer (OvCa) development. Using mass spectrometry, four polyamines were quantified in plasma from 116 OvCa cases and 143 controls (71 healthy controls + 72 subjects with benign pelvic masses) (Test Set). Findings were validated in an independent plasma set from 61 early-stage OvCa cases and 71 healthy controls (Validation Set). Complementarity of polyamines with CA125 was also evaluated. Receiver operating characteristic area under the curve (AUC) of individual polyamines for distinguishing cases from healthy controls ranged from 0.74–0.88. A polyamine signature consisting of diacetylspermine + N-(3-acetamidopropyl)pyrrolidin-2-one in combination with CA125 developed in the Test Set yielded improvement in sensitivity at >99% specificity relative to CA125 alone (73.7% vs 62.2%; McNemar exact test 2-sided P: 0.019) in the validation set and captured 30.4% of cases that were missed with CA125 alone. Our findings reveal a MYC-driven plasma polyamine signature associated with OvCa that complemented CA125 in detecting early-stage ovarian cancer.

scholarly journals Predicting drug–target interactions Based on the Ensemble Models of Multiple Feature Pairs

2021 ◽  
Vol 22 (12) ◽  
pp. 6598
Author(s):  
Cheng Wang ◽  
Jun Zhang ◽  
Peng Chen ◽  
Bing Wang
Keyword(s):  
Drug Target ◽  
Essential Feature ◽  
Characteristic Curve ◽  
Prediction Method ◽  
New Drugs ◽  
Good Prediction ◽  
Ensemble Model ◽  
Test Set ◽  
Multiple Feature ◽  
Validation Set

Backgroud: The prediction of drug–target interactions (DTIs) is of great significance in drug development. It is time-consuming and expensive in traditional experimental methods. Machine learning can reduce the cost of prediction and is limited by the characteristics of imbalanced datasets and problems of essential feature selection. Methods: The prediction method based on the Ensemble model of Multiple Feature Pairs (Ensemble-MFP) is introduced. Firstly, three negative sets are generated according to the Euclidean distance of three feature pairs. Then, the negative samples of the validation set/test set are randomly selected from the union set of the three negative sets in the validation set/test set. At the same time, the ensemble model with weight is optimized and applied to the test set. Results: The area under the receiver operating characteristic curve (area under ROC, AUC) in three out of four sub-datasets in gold standard datasets was more than 94.0% in the prediction of new drugs. The effectiveness of the proposed method is also shown with the comparison of state-of-the-art methods and demonstration of predicted drug–target pairs. Conclusion: The Ensemble-MFP can weigh the existing feature pairs and has a good prediction effect for general prediction on new drugs.

scholarly journals NDRG3 overexpression is associated with a poor prognosis in patients with hepatocellular carcinoma

2018 ◽  
Vol 38 (6) ◽  
Author(s):  
Ji-sheng Jing ◽  
Hongbo Li ◽  
Shun-cai Wang ◽  
Jiu-ming Ma ◽  
La-qing Yu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Survival Curve ◽  
Disease Free Survival ◽  
Prognostic Indicator ◽  
Clinicopathological Characteristics ◽  
Pcr Analysis ◽  
Kaplan Meier ◽  
Tumor Tissues ◽  
The Relationship

N-myc downstream-regulated gene 3 (NDRG3), an important member of the NDRG family, is involved in cell proliferation, differentiation, and other biological processes. The present study analyzed NDRG3 expression in hepatocellular carcinoma (HCC) and explored the relationship between expression of NDRG3 in HCC patients and their clinicopathological characteristics. We performed quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry (IHC) analyses on HCC tissues to elucidate NDRG3 expression characteristics in HCC patients. Kaplan–Meier survival curve and Cox regression analyses were used to evaluate the prognoses of 102 patients with HCC. The results revealed that compared with non-tumor tissues, HCC tissues showed significantly higher NDRG3 expression. In addition, our analyses showed that NDRG3 expression was statistically associated with tumor size (P=0.048) and pathological grade (P=0.001). Survival analysis and Kaplan–Meier curves revealed that NDRG3 expression is an independent prognostic indicator for disease-free survival (P=0.002) and overall survival (P=0.005) in HCC patients. The data indicate that NDRG3 expression may be considered as a oncogenic biomarker and a novel predictor for HCC prognosis.

scholarly journals Interleukin-35 Expression in Non-Small Cell Lung Cancer is Associated with Tumor Progression

2018 ◽  
Vol 51 (4) ◽  
pp. 1839-1851 ◽  
Author(s):  
Mingfei Sun ◽  
Xianjie Zheng ◽  
Qingjiang Meng ◽  
Yanjun Dong ◽  
Guoyu Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cancer Progression ◽  
Cell Lung Cancer ◽  
Disease Free Survival ◽  
Prognostic Indicator ◽  
Small Cell ◽  
Inflammatory Factor ◽  
Small Cell Lung ◽  
Chemotherapy Drugs

Background/Aims: Lung cancer continues to be the leading cause of cancer related deaths worldwide due to its high incidence, malignant behavior and lack of major advancements in treatment strategy. The occurrence and development of lung cancer is closely related to inflammation. Thus, we conducted the present study to investigate the effects of IL-35 (Interleukin 35), a newly identified anti-inflammatory factor, on non-small cell lung cancer (NSCLC), which accounts for about 85% of all lung cancers. Methods: We first evaluated the IL-35 expression in 384 pairs of NSCLC samples and their adjacent normal mucosa by realtime PCR, ELISA (Enzyme-linked immunoassay) and tissue microarrays. Then the role of IL-35 on patient survival rates, cancer progression and their sensitivity to chemotherapy drugs were assessed. Results: IL-35 was barely expressed in the NSCLC tissues but highly expressed in the adjacent normal tissues. The down-regulation of IL-35 was significantly correlated with the results of American Joint Committee on Cancer stage, differentiation and it was also shown to be an independent prognostic indicator of disease-free survival and overall survival for patients with NSCLC. Overexpression of IL-35 in NSCLC cells suppressed cell migration, invasion, proliferation, colony formation through suppressing β-catenin. IL-35 inhibited NSCLC formation in the mice model and sensitize the cancer cells to chemotherapy drugs. Conclusion: Our results showed that IL-35 plays an inhibitory role in NSCLC development and function as a novel prognostic indicator and a potential therapeutic target.

scholarly journals Investigating the impact of development and internal validation design when training prognostic models using a retrospective cohort in big US observational healthcare data

BMJ Open ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. e050146
Author(s):  
Jenna M Reps ◽  
Patrick Ryan ◽  
P R Rijnbeek
Keyword(s):  
Big Data ◽  
Retrospective Cohort ◽  
Cross Validation ◽  
Test Validation ◽  
Set Design ◽  
Validation Process ◽  
Test Set ◽  
Internal Validation ◽  
Validation Set ◽  
The Impact

ObjectiveThe internal validation of prediction models aims to quantify the generalisability of a model. We aim to determine the impact, if any, that the choice of development and internal validation design has on the internal performance bias and model generalisability in big data (n~500 000).DesignRetrospective cohort.SettingPrimary and secondary care; three US claims databases.Participants1 200 769 patients pharmaceutically treated for their first occurrence of depression.MethodsWe investigated the impact of the development/validation design across 21 real-world prediction questions. Model discrimination and calibration were assessed. We trained LASSO logistic regression models using US claims data and internally validated the models using eight different designs: ‘no test/validation set’, ‘test/validation set’ and cross validation with 3-fold, 5-fold or 10-fold with and without a test set. We then externally validated each model in two new US claims databases. We estimated the internal validation bias per design by empirically comparing the differences between the estimated internal performance and external performance.ResultsThe differences between the models’ internal estimated performances and external performances were largest for the ‘no test/validation set’ design. This indicates even with large data the ‘no test/validation set’ design causes models to overfit. The seven alternative designs included some validation process to select the hyperparameters and a fair testing process to estimate internal performance. These designs had similar internal performance estimates and performed similarly when externally validated in the two external databases.ConclusionsEven with big data, it is important to use some validation process to select the optimal hyperparameters and fairly assess internal validation using a test set or cross-validation.

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