Identifying, Diagnosing, and Grading Malignant Peripheral Nerve Sheath Tumors in Genetically Engineered Mouse Models.

Patients with the autosomal dominant tumor susceptibility syndrome neurofibromatosis type 1 (NF1) commonly develop plexiform neurofibromas (PNs) that subsequently transform into highly aggressive malignant peripheral nerve sheath tumors (MPNSTs). Understanding the process by which a PN transforms into an MPNST would be facilitated by the availability of genetically engineered mouse (GEM) models that accurately replicate the PN-MPNST progression seen in humans with NF1. Unfortunately, GEM models with Nf1 ablation do not fully recapitulate this process. This led us to develop P0-GGFß3 mice, a GEM model in which overexpression of the Schwann cell mitogen neuregulin-1 (NRG1) in Schwann cells results in the development of PNs that progress to become MPNSTs with high frequency. However, to determine whether tumorigenesis and neoplastic progression in P0-GGFß3 mice accurately model the processes seen in NF1 patients, we had to first prove that the pathology of P0-GGFß3 peripheral nerve sheath tumors recapitulates the pathology of their human counterparts. Here, we describe the specialized methodologies used to accurately diagnose and grade peripheral nervous system neoplasms in GEM models, using P0-GGFß3 and P0-GGFß3;Trp53+/- mice as an example. We describe the histologic, immunohistochemical, and histochemical methods used to diagnose PNs and MPNSTs, how to distinguish these neoplasms from other tumor types that mimic their pathology, and how to grade these neoplasms. We discuss the establishment of early-passage cultures from GEM MPNSTs, how to characterize these cultures using immunocytochemistry, and how to verify their tumorigenicity by establishing allografts. Collectively, these techniques characterize the pathology of PNs and MPNSTs that arise in GEM models and critically compare the pathology of these murine tumors to their human counterparts.

Surgical Outcome of Open Radical Prostatectomy in Nigeria: A Five-Years Single-Surgeon Experience.

BACKGROUND: Organ-confined prostate cancer is curable through surgical treatment by radical prostatectomy. AIM: To report initial outcomes of open radical prostatectomy in Nigeria from 2014 to 2019. METHODS: Open radical prostatectomy in private hospital settings. Thirty-five patients underwent open radical prostatectomy in private hospital settings from 2014 to 2019. A retrospective study of the case notes was undertaken. RESULTS: The age range was 56-77 years (mean: 67.7 ± 5.6 years); presenting total PSA 7.3-32.0 ng/ml (mean: 16.2 ± 6.4); Gleason score range 6-10 and clinical stage T2c. Mean operation duration 192.4 ± 52.0 min. All patients received blood transfusion (average blood transfusion 4.58 ± 1.9 pints). The median length of hospital stay was 7 days and the catheterization duration was 16.6 days. The Gleason score ranges from 6 to 10. Biopsy and specimen histology Gleason scores correlated in all cases. Biochemical relapse within 1 year occurred in 12 (34.3%) patients. Adequate PSA control was achieved in 23 (65.7%) patients. Two cancer-related deaths occurred within 2 years of surgery. All patients voided well following removal of the catheter; persisting mild stress urinary incontinence resolved on conservative measures within 3-6 months. Anastomotic stricture occurred in one patient 1 (2.9%) in this present. Information on preoperative potency rate was unavailable; however, postoperation, 11 (31.4%) patients achieved erections sufficient for intercourse with oral therapy. All surviving 33 (94.3%) patients reported satisfactory performance status. CONCLUSIONS: Open radical prostatectomy was successfully performed in all the patients. Reasonable, comparative functional, and oncological outcomes were achieved during the study period.

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study.

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell-cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

Ultrasound contrast-enhanced radiomics model for preoperative prediction of the tumor grade of clear cell renal cell carcinoma: an exploratory study.

BACKGROUND: This study aims to explore machine learning(ML) methods for non-invasive assessment of WHO/ISUP nuclear grading in clear cell renal cell carcinoma(ccRCC) using contrast-enhanced ultrasound(CEUS) radiomics. METHODS: This retrospective study included 122 patients diagnosed as ccRCC after surgical resection. They were divided into a training set (n = 86) and a testing set(n = 36). CEUS radiographic features were extracted from CEUS images, and XGBoost ML models (US, CP, and MP model) with independent features at different phases were established. Multivariate regression analysis was performed on the characteristics of different radiomics phases to determine the indicators used for developing the prediction model of the combined CEUS model and establishing the XGBoost model. The training set was used to train the above four kinds of radiomics models, which were then tested in the testing set. Radiologists evaluated tumor characteristics, established a CEUS reading model, and compared the diagnostic efficacy of CEUS reading model with independent characteristics and combined CEUS model prediction models. RESULTS: The combined CEUS radiomics model demonstrated the best performance in the training set, with an area under the curve (AUC) of 0.84, accuracy of 0.779, sensitivity of 0.717, specificity of 0.879, positive predictive value (PPV) of 0.905, and negative predictive value (NPV) of0.659. In the testing set, the AUC was 0.811, with an accuracy of 0.784, sensitivity of 0.783, specificity of 0.786, PPV of 0.857, and NPV of 0.688. CONCLUSIONS: The radiomics model based on CEUS exhibits high accuracy in non-invasive prediction of ccRCC. This model can be utilized for non-invasive detection of WHO/ISUP nuclear grading of ccRCC and can serve as an effective tool to assist clinical decision-making processes.

Can a nomogram predict apical prostate cancer pathology upgrade from fusion biopsy to final pathology? A multicenter study.

BACKGROUND: This study evaluates the efficacy of a nomogram for predicting the pathology upgrade of apical prostate cancer (PCa). METHODS: A total of 754 eligible patients were diagnosed with apical PCa through combined systematic and magnetic resonance imaging (MRI)-targeted prostate biopsy followed by radical prostatectomy (RP) were retrospectively identified from two hospitals (training: 754, internal validation: 182, internal-external validation: 148). A nomogram for the identification of apical tumors in high-risk pathology upgrades through comparing the results of biopsy and RP was established incorporating statistically significant risk factors based on univariable and multivariable logistic regression. The nomogram's performance was assessed via the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA). RESULTS: Univariable and multivariable analysis identified age, targeted biopsy, number of targeted cores, TNM stage, and the prostate imaging-reporting and data system score as significant predictors of apical tumor pathological progression. Our nomogram, based on these variables, demonstrated ROC curves for pathology upgrade with values of 0.883 (95% CI, 0.847-0.929), 0.865 (95% CI, 0.790-0.945), and 0.840 (95% CI, 0.742-0.904) for the training, internal validation and internal-external validation cohorts respectively. Calibration curves showed good consistency between the predicted and actual outcomes. The validation groups also showed great generalizability with the calibration curves. DCA results also demonstrated excellent performance for our nomogram with positive benefit across a threshold probability range of 0-0.9 for the training and internal validation group, and 0-0.6 for the internal-external validation group. CONCLUSION: The nomogram, integrating clinical, radiological, and pathological data, effectively predicts the risk of pathology upgrade in apical PCa tumors. It holds significant potential to guide clinicians in optimizing the surgical management of these patients.

Radiomic white matter parameters of functional integrity of the corticospinal tract in high-grade glioma.

Tractography has become a widely available tool for the planning of neurosurgical operations as well as for neuroscientific research. The absence of patient interaction makes it easily applicable. However, it leaves uncertainty about the functional relevance of the identified bundles. We retrospectively analyzed the correlation of white matter markers with their clinical function in 24 right-handed patients who underwent first surgery for high-grade glioma. Morphological affection of the corticospinal tract (CST) and grade of paresis were assessed before surgery. Tractography was performed manually with MRTrix3 and automatically with TractSeg. Median and mean fractional anisotropy (FA) from manual tractography showed a significant correlation with CST affection (p = 0.008) and paresis (p = 0.015, p = 0.026). CST affection correlated further most with energy, and surface-volume ratio (p = 0.014) from radiomic analysis. Paresis correlated most with maximum 2D column diameter (p = 0.005), minor axis length (p = 0.006), and kurtosis (p = 0.008) from radiomic analysis. Streamline count yielded no significant correlations. In conclusion, mean or median FA can be used for the assessment of CST integrity in high-grade glioma. Also, several radiomic parameters are suited to describe tract integrity and may be used to quantitatively analyze white matter in the future.

The interplay mechanism between IDH mutation, MGMT-promoter methylation, and PRMT5 activity in the progression of grade 4 astrocytoma: unraveling the complex triad theory.

Background: The dysregulation of Isocitrate dehydrogenase (IDH) and the subsequent production of 2-Hydroxyglutrate (2HG) may alter the expression of epigenetic proteins in Grade 4 astrocytoma. The interplay mechanism between IDH, O-6-methylguanine-DNA methyltransferase (MGMT)-promoter methylation, and protein methyltransferase proteins-5 (PRMT5) activity, with tumor progression has never been described. Methods: A retrospective cohort of 34 patients with G4 astrocytoma is classified into IDH-mutant and IDH-wildtype tumors. Both groups were tested for MGMT-promoter methylation and PRMT5 through methylation-specific and gene expression PCR analysis. Inter-cohort statistical significance was evaluated. Results: Both IDH-mutant WHO grade 4 astrocytomas (n = 22, 64.7%) and IDH-wildtype glioblastomas (n = 12, 35.3%) had upregulated PRMT5 gene expression except in one case. Out of the 22 IDH-mutant tumors, 10 (45.5%) tumors showed MGMT-promoter methylation and 12 (54.5%) tumors had unmethylated MGMT. All IDH-wildtype tumors had unmethylated MGMT. There was a statistically significant relationship between MGMT-promoter methylation and IDH in G4 astrocytoma (p-value = 0.006). Statistically significant differences in progression-free survival (PFS) were also observed among all G4 astrocytomas that expressed PRMT5 and received either temozolomide (TMZ) or TMZ plus other chemotherapies, regardless of their IDH or MGMT-methylation status (p-value=0.0014). Specifically, IDH-mutant tumors that had upregulated PRMT5 activity and MGMT-promoter methylation, who received only TMZ, have exhibited longer PFS. Conclusions: The relationship between PRMT5, MGMT-promoter, and IDH is not tri-directional. However, accumulation of D2-hydroxyglutarate (2-HG), which partially activates 2-OG-dependent deoxygenase, may not affect their activities. In IDH-wildtype glioblastomas, the 2HG-2OG pathway is typically inactive, leading to PRMT5 upregulation. TMZ alone, compared to TMZ-plus, can increase PFS in upregulated PRMT5 tumors. Thus, using a PRMT5 inhibitor in G4 astrocytomas may help in tumor regression.

Real-world treatment patterns and clinical outcomes in patients with prostate cancer.: A single institution experience in Saudi Arabia.

OBJECTIVES: To describe the current real-world treatment landscape, sequence of therapies, and outcomes in patients with prostate cancer (PC). METHODS: A retrospective cohort study for PC patients diagnosed at King Abdullah Medical City Cancer Center in Makkah, Saudi Arabia, between January 2011 and December 2021. Data extracted from electronic medical records. RESULTS: A total of 282 patients with PC, with a mean age of 70 years and body mass index of 27. Among them, 274 (99%) had no family history of cancer, while 164 (58%) had hypertension and 125 (44%) had diabetes mellitus. Adenocarcinoma was the most common histology, found in 275 (97%) patients, with 99 (35%) having a Gleason score of 9. Notably, 184 (65%) patients presented with metastatic disease, and 147 (52%) with bone metastasis. While 198 (70%) patients underwent surgery, 184 (65%) did not receive radiotherapy. The most common first-line metastatic therapy was abiraterone in 23 (8%) patients, followed by enzalutamide in 7 (2.5%). During the study period, 167 (59%) patients survived, with an average treatment duration of 2.5 years. CONCLUSION: This study provides insights into real-world treatment patterns and clinical outcomes in patients with PC. The findings of this study highlight the importance of adhering to treatment standards and making informed clinical decisions.

Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images.

BACKGROUND: Nottingham histological grade (NHG) is a well established prognostic factor in breast cancer histopathology but has a high inter-assessor variability with many tumours being classified as intermediate grade, NHG2. Here, we evaluate if DeepGrade, a previously developed model for risk stratification of resected tumour specimens, could be applied to risk-stratify tumour biopsy specimens. METHODS: A total of 11,955,755 tiles from 1169 whole slide images of preoperative biopsies from 896 patients diagnosed with breast cancer in Stockholm, Sweden, were included. DeepGrade, a deep convolutional neural network model, was applied for the prediction of low- and high-risk tumours. It was evaluated against clinically assigned grades NHG1 and NHG3 on the biopsy specimen but also against the grades assigned to the corresponding resection specimen using area under the operating curve (AUC). The prognostic value of the DeepGrade model in the biopsy setting was evaluated using time-to-event analysis. RESULTS: Based on preoperative biopsy images, the DeepGrade model predicted resected tumour cases of clinical grades NHG1 and NHG3 with an AUC of 0.908 (95% CI: 0.88; 0.93). Furthermore, out of the 432 resected clinically-assigned NHG2 tumours, 281 (65%) were classified as DeepGrade-low and 151 (35%) as DeepGrade-high. Using a multivariable Cox proportional hazards model the hazard ratio between DeepGrade low- and high-risk groups was estimated as 2.01 (95% CI: 1.06; 3.79). CONCLUSIONS: DeepGrade provided prediction of tumour grades NHG1 and NHG3 on the resection specimen using only the biopsy specimen. The results demonstrate that the DeepGrade model can provide decision support to identify high-risk tumours based on preoperative biopsies, thus improving early treatment decisions.

Clinical implications of DNA methylation-based integrated classification of histologically defined grade 2 meningiomas.

The combination of DNA methylation analysis with histopathological and genetic features allows for a more accurate risk stratification and classification of meningiomas. Nevertheless, the implications of this classification for patients with grade 2 meningiomas, a particularly heterogeneous tumor entity, are only partially understood. We correlate the outcomes of histopathologically confirmed grade 2 meningioma with an integrated molecular-morphologic risk stratification and determine its clinical implications. Grade 2 meningioma patients treated at our institution were re-classified using an integrated risk stratification involving DNA methylation array-based data, copy number assessment and TERT promoter mutation analyses. Grade 2 meningioma cases according to the WHO 2021 criteria treated between 2007 and 2021 (n = 100) were retrospectively analyzed. The median clinical and radiographic follow-up periods were 59.8 and 54.4 months. A total of 38 recurrences and 17 deaths were observed. The local control rates of the entire cohort after 2-, 4-, and 6-years were 84.3%, 68.5%, and 50.8%, with a median local control time of 77.2 months. The distribution of the integrated risk groups were as follows: 31 low, 54 intermediate, and 15 high risk cases. In the multivariable Cox regression analysis, integrated risk groups were significantly associated with the risk of local recurrence (hazard ratio (HR) intermediate: 9.91, HR high-risk: 7.29, p < 0.01). Gross total resections decreased the risk of local tumor progression (HR gross total resection: 0.19, p < 0.01). The comparison of 1p status and integrated risk groups (low vs. intermediate/high) revealed nearly identical local control rates within their respective subgroups. In summary, only around 50% of WHO 2021 grade 2 meningiomas have an intermediate risk profile. Integrated molecular risk stratification is crucial to guide the management of patients with grade 2 tumors and should be routinely applied to avoid over- and undertreatment, especially concerning the use of adjuvant radiotherapy.

State of the Art in Low-Grade Glioma Management: Insights From Isocitrate Dehydrogenase and Beyond.

Low-grade gliomas present a formidable challenge in neuro-oncology because of the challenges imposed by the blood-brain barrier, predilection for the young adult population, and propensity for recurrence. In the past two decades, the systematic examination of genomic alterations in adults and children with primary brain tumors has uncovered profound new insights into the pathogenesis of these tumors, resulting in more accurate tumor classification and prognostication. It also identified several common recurrent genomic alterations that now define specific brain tumor subtypes and have provided a new opportunity for molecularly targeted therapeutic intervention. Adult-type diffuse low-grade gliomas are frequently associated with mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2), resulting in production of 2-hydroxyglutarate, an oncometabolite important for tumorigenesis. Recent studies of IDH inhibitors have yielded promising results in patients at early stages of disease with prolonged progression-free survival (PFS) and delayed time to radiation and chemotherapy. Pediatric-type gliomas have high rates of alterations in BRAF, including BRAF V600E point mutations or BRAF-KIAA1549 rearrangements. BRAF inhibitors, often combined with MEK inhibitors, have resulted in radiographic response and improved PFS in these patients. This article reviews emerging approaches to the treatment of low-grade gliomas, including a discussion of targeted therapies and how they integrate with the current treatment modalities of surgical resection, chemotherapy, and radiation.

Clinical analysis of 314 patients with high-grade squamous intraepithelial lesion who underwent total hysterectomy directly: a multi-center, retrospective cohort study.

OBJECTIVE: To identify the risk factors of cervical high-grade squamous intraepithelial lesion(HSIL) complicated with occult cervical cancer and standardize the management of initial treatment for HSIL. METHOD: The clinical data of patients who underwent total hysterectomy directly due to HSIL in the obstetrics and gynecology department of two tertiary hospitals and three secondary hospitals from 2018 to 2023 were collected. Their general characteristics, pathological parameters and survival status were analyzed. Logistic regression model was used to analyze the correlation between clinical parameters and postoperative pathological upgrading. RESULT: 1. Among the 314 patients with HSIL who underwent total hysterectomy directly, 73.2% were from primary hospitals. 2. 25 patients (7.9%) were pathologically upgraded to cervical cancer, all of which were early invasive cancer. 3. Up to now, there was no recurrence or death in the 25 patients with early-stage invasive cancer, and the median follow-up period was 21 months(range 2-59 months). 4. Glandular involvement(OR 3.968; 95%CI 1.244-12.662) and lesion range ≥ 3 quadrants (OR 6.527; 95% CI 1.78-23.931), HPV 16/18 infection (OR 5.382; 95%CI 1.947-14.872), TCT ≥ ASC-H (OR 4.719; 95%CI 1.892-11.766) were independent risk factors that affected the upgrading of postoperative pathology. 5. The area under the curve (AUC) calculated by the Logistic regression model was 0.840, indicating that the predictive value was good. CONCLUSION: There is a risk of occult cervical cancer in patients with HSIL. Glandular involvement, Lesion range ≥ 3 quadrants, HPV 16/18 infection and TCT ≥ ASC-H are independent risk factors for HSIL combined with occult cervical cancer. The prognosis of biopsy-proved HSIL patients who underwent extrafascial hysterectomy and unexpected early invasive cancer was later identified on specimen may be good.

Synchronous profiling of mRNA N6-methyladenosine modifications and mRNA expression in high-grade serous ovarian cancer: a pilot study.

This study aimed to synchronously determine epitranscriptome-wide RNA N6-methyladenosine (m6A) modifications and mRNA expression profile in high grade serous ovarian cancer (HGSOC). The methylated RNA immunoprecipitation sequencing (MeRIP-seq) was used to comprehensively examine the m6A modification profile and the RNA-sequencing (RNA-seq) was performed to analyze the mRNA expression profile in HGSOC and normal fallopian tube (FT) tissues. Go and KEGG analyses were carried out in the enrichment of those differentially methylated and expressed genes. MeRIP-seq data showed 53,794 m6A methylated peaks related to 19,938 genes in the HGSOC group and 51,818 m6A peaks representing 19,681 genes in the FT group. RNA-seq results revealed 2321 upregulated and 2486 downregulated genes in HGSOC. Conjoint analysis of MeRIP-seq and RNA-seq data identified differentially expressed genes in which 659 were hypermethylated (330 up- and 329 down-regulated) and 897 were hypomethylated (475 up- and 422 down-regulated). Functional enrichment analysis indicated that these differentially modulated genes are involved in pathways related to cancer development. Among methylation regulators, the m6A eraser (FTO) expression was significantly lower, but the m6A readers (IGF2BP2 and IGF2BP3) were higher in HGSOC, which was validated by the subsequent real-time PCR assay. Exploration through public databases further corroborated their possible clinical application of certain methylation regulators and differentially expressed genes. For the first time, our study screens the epitranscriptome-wide m6A modification and expression profiles of their modulated genes and signaling pathways in HGSOC. Our findings provide an alternative direction in exploring the molecular mechanisms of ovarian pathogenesis and potential biomarkers in the diagnosis and predicting the prognosis of the disease.

Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach.

BACKGROUND: The role of isocitrate dehydrogenase (IDH) mutation status for glioma stratification and prognosis is established. While structural magnetic resonance image (MRI) is a promising biomarker, it may not be sufficient for non-invasive characterisation of IDH mutation status. We investigated the diagnostic value of combined diffusion tensor imaging (DTI) and structural MRI enhanced by a deep radiomics approach based on convolutional neural networks (CNNs) and support vector machine (SVM), to determine the IDH mutation status in Central Nervous System World Health Organization (CNS WHO) grade 2-4 gliomas. METHODS: This retrospective study analyzed the DTI-derived fractional anisotropy (FA) and mean diffusivity (MD) images and structural images including fluid attenuated inversion recovery (FLAIR), non-enhanced T1-, and T2-weighted images of 206 treatment-naïve gliomas, including 146 IDH mutant and 60 IDH-wildtype ones. The lesions were manually segmented by experienced neuroradiologists and the masks were applied to the FA and MD maps. Deep radiomics features were extracted from each subject by applying a pre-trained CNN and statistical description. An SVM classifier was applied to predict IDH status using imaging features in combination with demographic data. RESULTS: We comparatively assessed the CNN-SVM classifier performance in predicting IDH mutation status using standalone and combined structural and DTI-based imaging features. Combined imaging features surpassed stand-alone modalities for the prediction of IDH mutation status [area under the curve (AUC) = 0.846; sensitivity = 0.925; and specificity = 0.567]. Importantly, optimal model performance was noted following the addition of demographic data (patients' age) to structural and DTI imaging features [area under the curve (AUC) = 0.847; sensitivity = 0.911; and specificity = 0.617]. CONCLUSIONS: Imaging features derived from DTI-based FA and MD maps combined with structural MRI, have superior diagnostic value to that provided by standalone structural or DTI sequences. In combination with demographic information, this CNN-SVM model offers a further enhanced non-invasive prediction of IDH mutation status in gliomas.

Low-Density Lipoprotein Cholesterol and Prostate Cancer: A Retrospective Study.

BACKGROUND: This work aimed to investigate the potential role of abnormal lipid metabolism in the development of prostate cancer (PCa). METHODS: A retrospective study design was used. The clinical data of 520 patients who underwent rectal prostate biopsy in our hospital from January 2020 to June 2023 were analysed. The patients were enrolled and divided into the anterior PCa group including 112 patients and benign prostatic hyperplasia (BPH) group including 408 patients. Univariate and multivariate logistic regression analyses were performed for the two patient groups, and further comparisons were made according to the Gleason score and TNM staging. RESULTS: Low-density lipoprotein cholesterol (LDL-C) level may be an independent risk factor for PCa, and it was significantly associated with the risk of PCa (odds ratio (OR) = 1.363, p = 0.030). Patients with PCa were further divided into the low risk group and the high risk group according to the Gleason score. Univariate analysis (p = 0.047) and logistic regression analysis (OR = 2.249, p = 0.036) revealed that LDL-C was a significant factor influencing the Gleason score. Patients with PCa were categorised into four groups based on TNM staging. One-way analysis of variance (ANOVA) analysis (p = 0.015) and ordinal logistic regression analysis (OR = 2.414, p = 0.007) demonstrated that LDL-C was a significant factor influencing TNM staging. CONCLUSIONS: This study revealed the important role of LDL-C in the development of PCa, highlighting its influence as an independent risk factor. Thus, LDL-C may promote the proliferation and invasion of PCa cells.

Active surveillance of low-grade prostate cancer using the SurACaP Criteria: A multi-institutional series with a median follow-up of 10years.

PURPOSE: To report on the oncological outcomes of active surveillance (AS) in low-grade prostate cancer (PCa) patients using the French SurACaP protocol, with a focus on long-term outcomes. METHODS: This multicenter study recruited patients with low-grade PCa between 2007 and 2013 in four referral centers in France. The cohort included patients meeting the SurACaP inclusion criteria, i.e., aged ≤75years, with low-grade PCa (i.e., ISUP 1), clinical stage T1c/T2a, PSA ≤10ng/mL and ≤3 positive cores and tumor length ≤3mm per core. The SurACaP protocol included a digital rectal examination every six months, PSA level measurement every three months for the first two years after inclusion and twice a year thereafter, a confirmatory biopsy in the first year after inclusion, and then follow-up biopsy every two years or if disease progression was suspected. Multiparametric magnetic resonance imaging (mpMRI) was progressively included over the study period. RESULTS: A total of 86 consecutive patients were included, with a median follow-up of 10.6 years. Only one patient developed metastases and died of PCa. The estimated rates of grade reclassification and treatment-free survival at 15 years were 53.4% and 21.2%, respectively. A negative mpMRI at baseline and a negative confirmatory biopsy were significantly associated with a lower risk of disease progression (P<0.05). CONCLUSIONS: AS using the French SurACaP protocol is a safe and valuable strategy for patients with low-risk PCa, with excellent oncological outcomes after more than 10 years' follow-up. Future studies are crucial to broaden the inclusion criteria and develop a personalized, risk based AS protocol with the aim of de-escalating follow-up examinations. LEVEL OF EVIDENCE: Grade 4.

Significance of Staining Intensity in Ki-67 Proliferation Index in Meningiomas, and a Critical Review of the Literature on Proliferation Index Assessment.

OBJECTIVE: Meningioma is the most common primary adult intracranial neoplasm, and proliferation indices (PI) rise with increasing grade from WHO CNS grade 1 to 3. Ki-67 immunohistochemistry (IHC) poses a variety of technical and interpretative challenges. Here, we specifically investigated the staining intensity and its effect on interpretation and final diagnosis. METHODS: 124 high and low-grade meningiomas of various grades were blindly evaluated using different counting strategies (CS) based on the staining intensity of the nuclei as darkest (CS1), darkest+intermediate (CS2), and any staining (CS3) in hot-spots (HS) and in the context of overall proliferative activity (OPA). RESULT: CSs in HS, OPA, and their average results were significantly different between low-grade and high-grade groups. PI obtained using CS3 yielded results that matched best with values expected for the corresponding WHO grade. CS had a profound impact on whether a LG meningioma would be diagnosed as one with a "high proliferation index." CONCLUSION: A large body of work exists on the counting methods, clinically significant cut-off values, and inter- and intra-observer variability for Ki-67 PI interpretation. We show that Ki-67 IHC staining intensity, which to our knowledge has not been previously systematically investigated, can have a significant effect on PI interpretation in settings that influence diagnostic and clinical management decisions.

Multiphase comparative study for WHO/ISUP nuclear grading diagnostic model based on enhanced CT images of clear cell renal cell carcinoma.

To compare and analyze the diagnostic value of different enhancement stages in distinguishing low and high nuclear grade clear cell renal cell carcinoma (ccRCC) based on enhanced computed tomography (CT) images by building machine learning classifiers. A total of 51 patients (Dateset1, including 41 low-grade and 10 high-grade) and 27 patients (Independent Dateset2, including 16 low-grade and 11 high-grade) with pathologically proven ccRCC were enrolled in this retrospective study. Radiomic features were extracted from the corticomedullary phase (CMP), nephrographic phase (NP), and excretory phase (EP) CT images, and selected using the recursive feature elimination cross-validation (RFECV) algorithm, the group differences were assessed using T-test and Mann-Whitney U test for continuous variables. The support vector machine (SVM), random forest (RF), XGBoost (XGB), VGG11, ResNet18, and GoogLeNet classifiers are established to distinguish low-grade and high-grade ccRCC. The classifiers based on CT images of NP (Dateset1, RF: AUC = 0.82 ± 0.05, ResNet18: AUC = 0.81 ± 0.02; Dateset2, XGB: AUC = 0.95 ± 0.02, ResNet18: AUC = 0.87 ± 0.07) obtained the best performance and robustness in distinguishing low-grade and high-grade ccRCC, while the EP-based classifier performance in poorer results. The CT images of enhanced phase NP had the best performance in diagnosing low and high nuclear grade ccRCC. Firstorder_Kurtosis and firstorder_90Percentile feature play a vital role in the classification task.

Tumour growth rate predicts overall survival in patients with recurrent WHO grade 4 glioma.

PURPOSE: Accurate prognostication may aid in the selection of patients who will benefit from surgery at recurrent WHO grade 4 glioma. This study aimed to evaluate the role of serial tumour volumetric measurements for prognostication at first tumour recurrence. METHODS: We retrospectively analyzed patients with histologically-diagnosed WHO grade 4 glioma at initial and at first tumour recurrence at a tertiary hospital between May 2000 and September 2018. We performed auto-segmentation using ITK-SNAP software, followed by manual adjustment to measure serial contrast-enhanced T1W (CE-T1W) and T2W lesional volume changes on all MRI images performed between initial resection and repeat surgery. RESULTS: Thirty patients met inclusion criteria; the median overall survival using Kaplan-Meier analysis from second surgery was 10.5 months. Seventeen (56.7%) patients received treatment post second surgery. Univariate cox regression analysis showed that greater rate of increase in lesional volume on CE-T1W (HR = 2.57; 95% CI [1.18, 5.57]; p = 0.02) in the last 2 MRI scans leading up to the second surgery was associated with a higher mortality likelihood. Patients with higher Karnofsky Performance Score (KPS) (HR = 0.97; 95% CI [0.95, 0.99]; p = 0.01) and who received further treatment following second surgery (HR = 0.43; 95% CI [0.19, 0.98]; p = 0.04) were shown to have a better survival. CONCLUSION: Higher rate of CE-T1W lesional growth on the last 2 MRI images prior to surgery at recurrence was associated with increase mortality risk. A larger prospective study is required to determine and validate the threshold to distinguish rapidly progressive tumour with poor prognosis.