Association of chromosome 7 aneuploidy measured by fluorescence in situ hybridization assay with muscular invasion in bladder cancer

Diao, Xiayao; Cai, Jinhua; Zheng, Junjiong; Kong, Jianqiu; Wu, Shaoxu; Yu, Hao; Huang, Hao; Xie, Weibin; Xiong, Chen; Huang, Chengran; Huang, Lifang; Qin, Haide; Huang, Jian; Lin, Tianxin

doi:10.1002/cac2.12017

Cited by 9 publications

(9 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Blood indicators, including lactate dehydrogenase (LDH) (18), the NLR (neutrophil-to-lymphocyte ratio) (19), the PLR (platelet-to-lymphocyte ratio) (20), the LMR (lymphocyteto-monocyte ratio) (21), carbohydrate antigen 125 (CA125) (22), and carbohydrate antigen 153 (CA153) (23), have shown important diagnostic and/or prognostic value in ovarian cancer. Additionally, nomograms, considered as a clinically easy-to-implement and reliable calculating model, have been established by combining related risk factors to help clinicians to develop individualized treatment and follow-up management strategies in breast, gastric and bladder cancers (24)(25)(26)(27). These have attracted our attention to devise such a model for HGSOC.…”

Section: Introductionmentioning

confidence: 99%

Nomograms to Predict the Density of Tumor-Infiltrating Lymphocytes in Patients With High-Grade Serous Ovarian Cancer

et al. 2021

View full text Add to dashboard Cite

BackgroundTumor-infiltrating lymphocytes (TILs) have important roles in predicting tumor therapeutic responses and progression, however, the method of evaluating TILs is complicated. We attempted to explore the association of TILs with clinicopathological characteristics and blood indicators, and to develop nomograms to predict the density of TILs in patients with high-grade serous ovarian cancer (HGSOC).MethodsThe clinical profiles of 197 consecutive postoperative HGSOC patients were retrospectively analyzed. Tumor tissues and matched normal fallopian tubes were immunostained for CD3+, CD8+, and CD4+ T cells on corresponding tissue microarrays and the numbers of TILs were counted using the NIH ImageJ software. The patients were classified into low- or high-density groups for each marker (CD3, CD4, CD8). The associations of the investigated TILs to clinicopathological characteristics and blood indicators were assessed and the related predictors for densities of TILs were used to develop nomograms; which were then further evaluated using the C-index, receiver operating characteristic (ROC) curves and calibration plots.ResultsMenopausal status, estrogen receptor (ER), Ki-67 index, white blood cell (WBC), platelets (PLT), lactate dehydrogenase (LDH), and carbohydrate antigen 153 (CA153) had significant association with densities of tumor-infiltrating CD3+, CD8+, or CD4+ T cells. The calibration curves of the CD3+ (C-index = 0.748), CD8+ (C-index = 0.683) and CD4+ TILs nomogram (C-index = 0.759) demonstrated excellent agreement between predictions and actual observations. ROC curves of internal validation indicated good discrimination for the CD8+ TILs nomogram [area under the curve (AUC) = 0.659, 95% CI 0.582–0.736] and encouraging performance for the CD3+ (AUC= 0.708, 95% CI 0.636–0.781) and CD4+ TILs nomogram (AUC = 0.730, 95% CI 0.659–0.801).ConclusionMenopausal status, ER, Ki-67 index, WBC, PLT, LDH, and CA153 could reflect the densities of T cells in the tumor microenvironment. Novel nomograms are conducive to monitor the immune status of patients with HGSOC and help doctors to formulate the appropriate treatment strategies.

show abstract

Section: Introductionmentioning

confidence: 99%

Nomograms to Predict the Density of Tumor-Infiltrating Lymphocytes in Patients With High-Grade Serous Ovarian Cancer

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The role of the tumor size in BCa staging has been evaluated in several studies, which revealed that the tumor size in MIBC was larger than that in non‐muscle‐invasive BCa 13,15,16 . In this study, the tumor's largest size over 3 cm was an independent risk factor for MIBC with stalk.…”

Section: Discussionmentioning

confidence: 59%

A Nomogram of MRI Features to Assess Muscle Invasion in VI‐RADS 2 Tumors With Stalk

Cai,

Yu,

Liu

et al. 2023

Magnetic Resonance Imaging

View full text Add to dashboard Cite

BackgroundVesical Imaging–Reporting and Data System (VI‐RADS) is widely used to assess the muscle‐invasive status of bladder cancer. However, the current classification efficacy of VI‐RASD 2 tumors of stalk is unsatisfactory.PurposeTo develop a nomogram to assess muscle‐invasive bladder cancer (MIBC) in VI‐RADS 2 tumors with stalk.Study TypeRetrospective.PopulationA total of 186 patients (age: 67.8 ± 12.7 years) with 15.1% females, divided randomly into a training cohort (N = 130) and validation cohort (N = 56).Field Strength/Sequence3‐T, T2‐weighted imaging (turbo spin‐echo), diffusion‐weighted imaging (breathing‐free spin‐echo), and dynamic contrast‐enhanced imaging (gradient‐echo).AssessmentTwenty‐one MRI features of tumors and stalks were developed from training cohort. The mean apparent diffusion coefficient (ADC) values of the tumor, stalk, and psoas muscles were calculated from the three circular regions of interest. The normalized T . The normalized ST . Three readers assessed the morphology of tumors and stalks.Statistical TestsThe final features of nomogram were selected by univariable logistic and the least absolute shrinkage and selection operator (LASSO) regression. The performance of the nomogram was assessed by the receiver operating characteristic (ROC) curve, calibration, and decision curve analysis.ResultsIn VI‐RADS 2 tumors with stalk, tumor size over 3 cm, increased stalk width, stalk morphology, decreased normalized T value, and increased normalized ST value were selected as the risk factors for MIBC. The AUC, accuracy, sensitivity, and specificity of the nomogram to assess MIBC were 0.969 (95% CI: 0.941–0.997), 92.3%, 94.1%, and 92.0% in training cohort and 0.940 (95% CI: 0.859–1.000), 89.3%, 75.0%, and 91.7% in validation cohort.Data ConclusionThis study constructed a nomogram for preoperative assessment of MIBC and modifying the current VI‐RADS.Level of Evidence3Technical EfficacyStage 2

show abstract

“…), which may lead to tumor recurrence or a poor prognosis. 32 The histological grade of BLAC represents the degree of tumor differentiation and is usually used to evaluate the prognosis of tumor treatment. 33 High-grade BLCA represents a higher risk of recurrence, metastasis, and poor prognosis.…”

Section: Discussionmentioning

confidence: 99%

“…If MIBC patients are undertreated or their treatment is delayed due to understaging as NMIBC, they will not receive optimal treatment (such as neoadjuvant chemotherapy, RC, etc. ), which may lead to tumor recurrence or a poor prognosis 32 . The histological grade of BLAC represents the degree of tumor differentiation and is usually used to evaluate the prognosis of tumor treatment 33 .…”

Section: Discussionmentioning

confidence: 99%

Radiomics Analysis Based on Ultrasound Images to Distinguish the Tumor Stage and Pathological Grade of Bladder Cancer

Gao

Wen

et al. 2021

J of Ultrasound Medicine

View full text Add to dashboard Cite

Objectives-To identify the clinical value of ultrasound radiomic features in the preoperative prediction of tumor stage and pathological grade of bladder cancer (BLCA) patients.Methods-We retrospectively collected patients who had been diagnosed with BLCA by pathology. Ultrasound-based radiomic features were extracted from manually segmented regions of interest. Participants were randomly assigned to a training cohort and a validation cohort at a ratio of 7:3. Radiomic features were Z-score normalized and submitted to dimensional reduction analysis (including Spearman's correlation coefficient analysis, the random forest algorithm, and statistical testing) for core feature selection. Classifiers for tumor stage and pathological grade prediction were then constructed. Prediction performance was estimated by the area under the curve (AUC) of the receiver operating characteristic curve and was verified by the validation cohort.Results-A total of 5936 radiomic features were extracted from each of the ultrasound images obtained from 157 patients. The BLCA tumor stage and pathological grade prediction models were developed based on 30 and 35 features, respectively. Both models showed good predictive ability. For the tumor stage prediction model, the AUC was 0.94 in the training cohort and 0.84 in the validation cohort. For the pathological grade model, the AUCs obtained were 0.84 in the training cohort and 0.75 in the validation cohort.Conclusions-The ultrasound-based radiomics models performed well in the preoperative tumor staging and pathological grading of BLCA. These findings should be applied clinically to optimize treatment and to assess prognoses for BLCA.

show abstract

Association of chromosome 7 aneuploidy measured by fluorescence in situ hybridization assay with muscular invasion in bladder cancer

Cited by 9 publications

References 45 publications

Nomograms to Predict the Density of Tumor-Infiltrating Lymphocytes in Patients With High-Grade Serous Ovarian Cancer

Nomograms to Predict the Density of Tumor-Infiltrating Lymphocytes in Patients With High-Grade Serous Ovarian Cancer

A Nomogram of MRI Features to Assess Muscle Invasion in VI‐RADS 2 Tumors With Stalk

Radiomics Analysis Based on Ultrasound Images to Distinguish the Tumor Stage and Pathological Grade of Bladder Cancer

Contact Info

Product

Resources

About