The effect of p53 on the activity of NRF2 and NDRG2 genes through apoptotic pathway in IDH-wildtype glioblastoma.

BACKGROUND: Tumor suppressor (p53) acts to integrate multiple stress signals into diverse antiproliferative responses. Its potential to transactivate or downregulate genes through apoptotic pathway in IDH-wildtype glioblastoma has never been explored. METHODS: A group of twenty patients diagnosed with IDH-wildtype glioblastoma, were tested for p53 expression and NDRG2/NRF2 genes activity through protein and gene profiling assays. The connotation between these elements has been explored. RESULTS: The mean patients' age was 64-years. All tumors were IDH-wildtype. p53 was expressed in 12 tumors and absent in 8 tumors. The activity of NDRG2 gene was downregulated in all cases. The activity of NRF2 gene was upregulated in 17 tumors and downregulated in 3 tumors. There was a significant statistical difference in PFS among tumors exhibiting different levels of p53 expression and NDRG2 gene activity [p-value= 0.025], in which 12 tumors with downregulated NDRG2 expression and positive p53 expression had earlier tumor recurrence. This statistical difference in PFS was insignificant when we compared p53 expression with NRF2 gene activity [p-value= 0.079]. CONCLUSIONS: During cell cycle arrest at G2 phase, p53 expression in IDH-wildtype glioblastoma in elderly individuals, coupled with the downregulation of NDRG2 gene activity, led to an aberrant increase in tumor cell proliferation and accelerated tumor recurrence. However, the influence of p53 on NRF2 gene activity was found to be insignificant.

Major Histocompatibility Class-I (MHC-I) downregulation in glioblastoma is a poor prognostic factor but not a predictive indicator for treatment failure.

BACKGROUND: MHC-I expression is a crucial factor in cancer immunity, and its regulations can impact tumor progression and recurrence. The mechanism through which glioblastoma use MHC-I to avoid immunosurveillance has been rarely investigated. METHODS: A retrospective cohort of 35 patients with IDH-mutant WHO-Grade 4 astrocytoma and IDH-wildtype glioblastoma were examined for MHC-I using protein and gene expression assays. The association between IDH mutation, TP53 mutation, and MHC-I expression with recurrence-free interval were investigated. RESULTS: The average patients' age was 49.6 year. IDH was wildtype in 13 tumors. MHC-I protein expression was absent in 30 tumors, faint in 4 tumors, and membrane bound dense expression in single tumor. MHC-I expression was upregulated in 10 tumors and 25 tumors showed MHC-I downregulation. P53 was positively expressed in 19 cases and lost in 13 cases. A significant statistical difference was observed in the RFI between tumors with distinct MHC-I expression and IDH-mutation [p-value = 0.008]. IDH-wildtype tumors with upregulated MHC-I expression showed late tumor recurrence compared to IDH-wildtype tumors with downregulated MHC-I expression. There was insignificant statistical difference in RFI among patients with varying degree of MHC-I expression, who received TMZ or TMZ and other chemotherapies [P-value = 0.44] CONCLUSIONS: Glioblastoma with upregulated MHC-I showed a delayed tumor recurrence in comparison to those with downregulated MHC-I expression. However, downregulated MHC-I may not necessarily be an indicator of poor problems.

Advancements in MRI-Based Radiomics and Artificial Intelligence for Prostate Cancer: A Comprehensive Review and Future Prospects.

The use of multiparametric magnetic resonance imaging (mpMRI) has become a common technique used in guiding biopsy and developing treatment plans for prostate lesions. While this technique is effective, non-invasive methods such as radiomics have gained popularity for extracting imaging features to develop predictive models for clinical tasks. The aim is to minimize invasive processes for improved management of prostate cancer (PCa). This study reviews recent research progress in MRI-based radiomics for PCa, including the radiomics pipeline and potential factors affecting personalized diagnosis. The integration of artificial intelligence (AI) with medical imaging is also discussed, in line with the development trend of radiogenomics and multi-omics. The survey highlights the need for more data from multiple institutions to avoid bias and generalize the predictive model. The AI-based radiomics model is considered a promising clinical tool with good prospects for application.

Dynamic interplay between corticosteroid treatment and the role of SRC-1 gene dysregulation in the progression of WHO-Grade 4 Astrocytoma.

BACKGROUND: Corticosteroid is commonly used before surgery to control cerebral oedema in brain tumours and is frequently continued throughout treatment. Its long-term effect of on the recurrence of WHO-Grade 4 astrocytoma remains controversial. The interaction between corticosteroid, SRC-1 gene and cytotoxic T-cells has never been investigated. METHODS: A retrospective cohort of 36 patients with WHO-Grade 4 astrocytoma were examined for CD8 + T-cell and SRC-1 gene expressions through IHC and qRT-PCR. The impact of corticosteroid on CD8+T-cells infiltration, SRC-1 expression, and tumour recurrence was analyzed. RESULTS: The mean patients age was 47-years, with a male to female ratio 1.2. About 78% [n = 28] of the cases showed reduced or no CD8+T-cell expression while 22% [n = 8] of cases have showed medium to high CD8+T-cell expression. SRC-1 gene was upregulated in 5 cases [14%] and 31 cases [86%] showed SRC-1 downregulation. The average of total days and doses of administered corticosteroid from the preoperative period to the postoperative period was at range of 14-106 days and 41-5028 mg, respectively. There was no significant statistical difference in RFI among tumours expressing high or low CD8+T-cells when corticosteroid was administered in recommended or exceeded doses [p-value = 0.640]. There was a significant statistical difference in RFI between CD8+T-Cell expression and SRC-1 gene dysregulation [p-value = 002]. Tumours with high CD8+T T-cell expression and SRC-1 gene downregulation had late recurrence. CONCLUSIONS: Corticosteroid treatment can directly affect the SRC-1 gene regulation but does not directly influence cytotoxic T-cells infiltration or tumor progression. However, SRC-1 gene downregulation can facilitate late tumor recurrence.

Deep Survival Analysis With Clinical Variables for COVID-19.

OBJECTIVE: Millions of people have been affected by coronavirus disease 2019 (COVID-19), which has caused millions of deaths around the world. Artificial intelligence (AI) plays an increasing role in all areas of patient care, including prognostics. This paper proposes a novel predictive model based on one dimensional convolutional neural networks (1D CNN) to use clinical variables in predicting the survival outcome of COVID-19 patients. METHODS AND PROCEDURES: We have considered two scenarios for survival analysis, 1) uni-variate analysis using the Log-rank test and Kaplan-Meier estimator and 2) combining all clinical variables ([Formula: see text]=44) for predicting the short-term from long-term survival. We considered the random forest (RF) model as a baseline model, comparing to our proposed 1D CNN in predicting survival groups. RESULTS: Our experiments using the univariate analysis show that nine clinical variables are significantly associated with the survival outcome with corrected p < 0.05. Our approach of 1D CNN shows a significant improvement in performance metrics compared to the RF and the state-of-the-art techniques (i.e., 1D CNN) in predicting the survival group of patients with COVID-19. CONCLUSION: Our model has been tested using clinical variables, where the performance is found promising. The 1D CNN model could be a useful tool for detecting the risk of mortality and developing treatment plans in a timely manner. CLINICAL IMPACT: The findings indicate that using both Heparin and Exnox for treatment is typically the most useful factor in predicting a patient's chances of survival from COVID-19. Moreover, our predictive model shows that the combination of AI and clinical data can be applied to point-of-care services through fast-learning healthcare systems.

The Cancer Driver Genes IDH1 and IDH2 and CD204 in WHO-Grade 4 Astrocytoma: Crosstalk Between Cancer Metabolism and Tumour Associated Macrophage Recruitment in Tumour Microenvironment.

Purpose: IDH1 and IDH2 are hotspot mutations commonly identified in WHO-grade 4 astrocytomas. Their association with TAMs has never been investigated. We aim to explore the crosstalk between the IDH1/2 mutation metabolic effect and TAMs in tumour microenvironment and how this relationship affects the tumour recurrence. Patients and Methods: The study included 20 samples of patients with WHO-grade 4 astrocytoma. The alteration hotspot in codon IDH1R132 and IDH2R172 was examined using direct sequencing. The protein expression of CD204 on TAM was detected through immunohistochemistry. Results: IDH1R132 and IDH2R172 were symmetrically identified as wildtype in 18/20 tumours (90%) and the remaining 2 tumours (10%) showed synonymous mutations on both codons. Tumours with IDH1/2-wildtype showed high expression of CD204+TAMs in 10 cases and low expression in 8 cases. Typical expression was seen equally in IDH1/2 mutant tumours. There was no significant association between IDH1/2 and CD204+TAM expression (p= 0.999). The association between the two groups was significantly observed among IDH-wildtype tumours (p=0.027). Highly expressed CD204 in IDH-wildtype tumours showed a median recurrence at 10 months compared to low CD204 expression, showed a median recurrence interval at 24 months. Conclusion: IDH1R132 or IDHR172 has the same impact on the classification and prognosis of WHO-grade 4 astrocytoma. There was no crosstalk between IDH1/2 metabolic effect and CD204+TAM. However, IDH-wildtype glioblastomas with dense CD204+TAM are associated with early recurrence. Because the sample size is small, a larger study is recommended to determine the impact of IDH1/2 on TAMs.

The Rate of Prostatic Involvement in Men Treated With Radical Cystectomy for Muscle Invasive Bladder Cancer.

PURPOSE: Radical cystoprostatectomy (RC) is one standard treatment for muscle-invasive bladder cancer (MIBC) in male patients. Another therapeutic option is trimodal therapy. Including the prostate in the trimodal therapy radiation therapy volume is based on MIBC surgical series showing prostatic stromal (PS) involvement. Our aim was to establish the rate of pathologic PS involvement by preoperative T stage in men treated with RC for MIBC. METHODS AND MATERIALS: We conducted a retrospective review of men with MIBC treated with RC between 2006 and 2019. Electronic medical records were reviewed, and preoperative clinical staging data were collected. χ2 test was done to test for a statistically significant difference in the rate of prostatic involvement between clinical tumor (cT) stages. Preoperatively identified carcinoma in situ, lymph node involvement, tumor location, and urethral involvement were also analyzed to see if they conferred a higher risk of PS involvement. Multivariate analysis using multiple logistic regression was performed. RESULTS: We identified 283 men with bladder cancer treated with RC. Patients with non-MIBC or incomplete medical data were excluded (n = 72). We analyzed 211 patients, and 46 (22%) had pathologic PS involvement. PS involvement by preoperative T stage was cT2 = 18%, cT3 = 23%, and cT4 = 48%. Twenty-nine (12%) patients had clinical lymph node involvement, of whom 19 (76%) had PS involvement. Thirty-four (16%) had urethral involvement, of whom 17 (50%) had PS involvement. Sixteen percent and 17% of percent of clinical T2 and T3 patients had bladder neck/trigone tumors, of whom 57% and 50% had prostatic involvement. Clinical T2 and T3 were not statistically different with regards to PS involvement (P = .385). Preoperative urethral involvement, lymph node involvement, cT4, and bladder neck/trigone location were statistically significant predictors of pathologic PS involvement (all P < .05). On multivariate analysis, only clinical urethral involvement was significant (P < .0001). CONCLUSIONS: The high rate of pathologic PS involvement seen in cT2 patients and the lack of ability of cT stage to predict PS involvement support routinely treating the prostate in trimodal therapy. Patients with preoperatively identified bladder neck/trigone tumors, urethral involvement, positive lymph nodes, or prostatic involvement are a subset at even higher risk of having pathologic PS involvement.

Simple approach for the histomolecular diagnosis of central nervous system gliomas based on 2021 World Health Organization Classification.

The classification of central nervous system (CNS) glioma went through a sequence of developments, between 2006 and 2021, started with only histological approach then has been aided with a major emphasis on molecular signatures in the 4th and 5th editions of the World Health Organization (WHO). The recent reformation in the 5th edition of the WHO classification has focused more on the molecularly defined entities with better characterized natural histories as well as new tumor types and subtypes in the adult and pediatric populations. These new subclassified entities have been incorporated in the 5th edition after the continuous exploration of new genomic, epigenomic and transcriptomic discovery. Indeed, the current guidelines of 2021 WHO classification of CNS tumors and European Association of Neuro-Oncology (EANO) exploited the molecular signatures in the diagnostic approach of CNS gliomas. Our current review presents a practical diagnostic approach for diffuse CNS gliomas and circumscribed astrocytomas using histomolecular criteria adopted by the recent WHO classification. We also describe the treatment strategies for these tumors based on EANO guidelines.

Immunolocalization of neurokinin 1 receptor in WHO grade 4 astrocytomas, oral squamous cell and urothelial carcinoma.

INTRODUCTION: Neurokinin-1 receptor (NK-1R) induces inflammatory reactions in peripheral tissues but its regulatory effects in target tissues is dependent on receptor signalling. Substance P (SP) has a high affinity for the NK-1R, to which it binds preferentially. We aimed to investigate the expression of NK-1R in World Health Organization (WHO) grade 4 astrocytomas as well as in oral squamous cell carcinoma (OSCC) and urothelial carcinoma, and its association with disease progression. MATERIAL AND METHODS: The study included tissue samples from 19 brain astrocytomas, 40 OSCCs and 10 urothelial carcinomas. NK-1R expression was quantitatively assessed in the tumour cells using immunohistochemistry. The relationship between NK-1R expression in astrocytomas and recurrence-free interval has been explored. RESULTS: The results showed that the NK-1R was intensely expressed in patients with WHO grade 4 astrocytoma, OSCC and urothelial carcinoma. However, cases clinically diagnosed as a low-grade cancer showed reduced NK-1R expression. CONCLUSIONS: NK-1R is overexpressed in all cases of WHO grade 4 astrocytoma, OSCC and urothelial carcinoma. The ubi-quitous presence of SP/NK-1R complex during tumour development and progression suggests a possible therapeutic key strategy to use NK-1R antagonist as an adjuvant therapy in the future.

Association Between CD204-Expressed Tumor-Associated Macrophages and MGMT-Promoter Methylation in the Microenvironment of Grade 4 Astrocytomas.

Background: Tumor-associated macrophages (TAMs) are principal immune cells in glioma microenvironment which support tumor growth and proliferation. Our aim in this study was to assess the relationship between CD204-expressed TAMs and O6-methylguanine-DNA methyltransferase (MGMT)-promoter methylation in World Health Organization (WHO) grade 4 astrocytomas, and its impact on patient's clinical outcome. Methods: The expression of CD204 + TAMs was quantitively assessed on 45 samples of WHO grade 4 astrocytomas using immunohistochemistry. MGMT-promoter methylation was tested by methylation techniques. The relationship between TAMs, MGMT-promoter methylation, and recurrence-free interval (RFI) was statistically analyzed. Results: There were 10 cases (22.2%) with isocitrate dehydrogenase (IDH)-mutant grade 4 astrocytoma and 35 cases (77.8%) with IDH-wildtype glioblastoma. MGMT-promotor was methylated in 18 cases (40%), unmethylated in 15 cases (33%), and the remaining 12 cases showed no MGMT status because of nucleic acid degradations. The expression of CD204+ TAMs was high in 32 cases (71.7%) and low in 13 cases (28.8%). The relationship between IDH1 mutation and CD204+ TAM expression was insignificant (P = 0.93). However, the significant difference was found between MGMT methylation and CD204+ TAMs expression (P = 0.01), in which CD204+ TAMs were diffusely expressed in MGMT-methylated cases. There was no significant difference in RFI between CD204+ TAMs expression, MGMT-promoter methylation and treatment modalities. Conclusions: Grade 4 astrocytomas with diffusely expressed CD204+ TAMs are usually associated with MGMT-promoter methylation. Although this association is unclear, CD204+ TAMs may neutralize the effect of MGMT-DNA protein to loss its function, which contributes to tumor progression. This relationship had no significant impact on the patient's clinical outcome after different treatment modalities.

Accuracy of Classifying Lung Carcinoma Using Immunohistochemical Markers on Limited Biopsy Material: A Two-Center Study.

Introduction Accurate classification of lung cancer into primary and metastatic carcinomas is critical for treatment approaches. Immunohistochemistry (IHC) has always been pivotal in unveiling the diverse cell differentiation lineages present in lung cancer by using specific biomarkers such as TTF1 and p63/p40, which closely reflect the relationship between genotype and phenotype.. Methods A retrospective cross-sectional study was conducted to evaluate 57 Tru-Cut biopsies over two years, from 2020-2022. Tumour morphology was evaluated, and IHC for TTF-1, Napsin A, CK-7, P-63, P-40, and CD-56 was performed in two steps. Results Of the lung cancer cases, 58.5% were adenocarcinoma (ADC), 24.5% were squamous cell carcinoma (SCC), 9.4% were small cell carcinoma, and 7.5% were poorly differentiated carcinoma. TTF1 stain had sensitivity and specificity of 78.9% and 50% in 33 cases of ADC, respectively, while CK7 and Napsin A had 100% sensitivity. P63 stain had 77% sensitivity and 50% specificity in 15 cases of SCC, while P-40 had 100% sensitivity. The CD56 stain was 100% sensitive in five cases of small cell carcinoma. Conclusion IHC staining on small lung biopsies allows accurate sub-classification of poorly differentiated lung cancers; however, there is still significant variability. Surgical resection specimens can be further classified due to architectural features that biopsies lack. Morphological findings would be beneficial in the development of an algorithm for sub-classifying lung carcinoma using a variety of markers.

Future artificial intelligence tools and perspectives in medicine.

PURPOSE OF REVIEW: Artificial intelligence has become popular in medical applications, specifically as a clinical support tool for computer-aided diagnosis. These tools are typically employed on medical data (i.e., image, molecular data, clinical variables, etc.) and used the statistical and machine-learning methods to measure the model performance. In this review, we summarized and discussed the most recent radiomic pipeline used for clinical analysis. RECENT FINDINGS: Currently, limited management of cancers benefits from artificial intelligence, mostly related to a computer-aided diagnosis that avoids a biopsy analysis that presents additional risks and costs. Most artificial intelligence tools are based on imaging features, known as radiomic analysis that can be refined into predictive models in noninvasively acquired imaging data. This review explores the progress of artificial intelligence-based radiomic tools for clinical applications with a brief description of necessary technical steps. Explaining new radiomic approaches based on deep-learning techniques will explain how the new radiomic models (deep radiomic analysis) can benefit from deep convolutional neural networks and be applied on limited data sets. SUMMARY: To consider the radiomic algorithms, further investigations are recommended to involve deep learning in radiomic models with additional validation steps on various cancer types.

Magnetic Resonance Imaging Based Radiomic Models of Prostate Cancer: A Narrative Review.

The management of prostate cancer (PCa) is dependent on biomarkers of biological aggression. This includes an invasive biopsy to facilitate a histopathological assessment of the tumor's grade. This review explores the technical processes of applying magnetic resonance imaging based radiomic models to the evaluation of PCa. By exploring how a deep radiomics approach further optimizes the prediction of a PCa's grade group, it will be clear how this integration of artificial intelligence mitigates existing major technological challenges faced by a traditional radiomic model: image acquisition, small data sets, image processing, labeling/segmentation, informative features, predicting molecular features and incorporating predictive models. Other potential impacts of artificial intelligence on the personalized treatment of PCa will also be discussed. The role of deep radiomics analysis-a deep texture analysis, which extracts features from convolutional neural networks layers, will be highlighted. Existing clinical work and upcoming clinical trials will be reviewed, directing investigators to pertinent future directions in the field. For future progress to result in clinical translation, the field will likely require multi-institutional collaboration in producing prospectively populated and expertly labeled imaging libraries.

Expression of SIRT1 and DBC1 in Developing and Adult Retinas.

Sirtuin 1 (SIRT1) is a deacetylase that can regulate various biological processes via repression of transcription. Its activity has been linked to the differentiation of neural progenitor cells, although little is known about its function during retinal development. The study described herein was undertaken to evaluate the expression of SIRT1 and its innate inhibitor, DBC1, in retinal tissues and progenitor cells. We found both SIRT1 and DBC1 to be widely expressed in mouse and human retinas, with subtle differences in subcellular distribution of each protein. We further demonstrate that nuclear-localized SIRT1 is only seen in human-derived retinal progenitor cells and not in adult retinas, suggesting that this nuclear localization may be important in retinal development. Moreover, we observed cytoplasmic DBC1 in a subset of progenitor cells as well as in mature ganglion cells, indicating that the progenitor cell subset, which was comprised predominantly of small cells, may represent a population of ganglion cell precursors. Collectively, the data presented in this study provide support for SIRT1 and DBC1 as regulators of retinal development and normal retinal physiology.