Cyclophilin A Facilitates HIV-1 DNA Integration.

Cyclophilin A (CypA) promotes HIV-1 infection by facilitating reverse transcription, nuclear entry and by countering the antiviral activity of TRIM5α. These multifunctional roles of CypA are driven by its binding to the viral capsid. Interestingly, recent studies suggest that the HIV-1 capsid lattice enters the nucleus of an infected cell and uncoats just before integration. Therefore, we tested whether CypA-capsid interaction regulates post-nuclear entry steps of infection, particularly integration. First, we challenged CypA-expressing (CypA +/+ ) and CypA-depleted (CypA -/- ) cells with HIV-1 particles and quantified the resulting levels of provirus. Surprisingly, CypA-depletion significantly reduced integration, an effect that was independent of CypA's effect on reverse transcription, nuclear entry, and the presence or absence of TRIM5α. Additionally, cyclosporin A, an inhibitor that disrupts CypA-capsid binding, inhibited HIV-1 integration in CypA +/+ cells but not in CypA -/- cells. Accordingly, HIV-1 capsid mutants (G89V and P90A) deficient in CypA binding were also blocked at integration in CypA +/+ cells but not in CypA -/- cells. Then, to understand the mechanism, we assessed the integration activity of HIV-1 preintegration complexes (PICs) extracted from infected cells. The PICs from CypA -/- cells had lower activity in vitro compared to those from CypA +/+ cells. PICs from cells depleted for CypA and TRIM5α also had lower activity, suggesting that CypA's effect on PIC activity is independent of TRIM5α. Finally, addition of CypA protein significantly stimulated the integration activity of PICs extracted from both CypA +/+ and CypA -/- cells. Collectively, these results suggest that CypA promotes HIV-1 integration, a previously unknown role of this host factor. Importance: HIV-1 capsid interaction with host cellular factors is essential for establishing a productive infection. However, the molecular details of such virus-host interactions are not fully understood. Cyclophilin A (CypA) is the first host protein identified to specifically bind to the HIV-1 capsid. Now it is established that CypA promotes reverse transcription and nuclear entry steps of HIV-1 infection. In this report, we show that CypA promotes HIV-1 integration by binding to the viral capsid. Specifically, our results demonstrate that CypA promotes HIV-1 integration by stimulating the activity of the viral preintegration complex and identifies a novel role of CypA during HIV-1 infection. This new knowledge is important because recent reports suggest that an operationally intact HIV-1 capsid enters the nucleus of an infected cell.

Associations of CSF BACE1 with amyloid pathology, neurodegeneration, and cognition in Alzheimer's disease.

Β-site amyloid precursor protein (APP) cleaving enzyme (BACE1) is a crucial protease in the production of amyloid-ß (Aß) in Alzheimer's disease (AD) patients. However, the side effects observed in clinical trials of BACE1 inhibitors, including reduction in brain volume and cognitive worsening, suggest that the exact role of BACE1 in AD pathology is not fully understood. To further investigate this, we examined cerebrospinal fluid (CSF) levels of BACE1 and its cleaved product sAPPß that reflects BACE1 activity in the China Aging and Neurodegenerative Disorder Initiative cohort. We found significant correlations between CSF BACE1 or sAPPß levels and CSF Aß40, Aß42, and Aß42/Aß40 ratio, but not with amyloid deposition detected by 18F-Florbetapir PET. Additionally, CSF BACE1 and sAPPß levels were positively associated with cortical thickness in multiple brain regions, and higher levels of sAPPß were linked to increased cortical glucose metabolism in frontal and supramarginal areas. Interestingly, individuals with higher baseline levels of CSF BACE1 exhibited slower rates of brain volume reduction and cognitive worsening over time. This suggests that increased levels and activity of BACE1 may not be the determining factor for amyloid deposition, but instead, may be associated with increased neuronal activity and potentially providing protection against neurodegeneration in AD.

The value of apparent diffusion coefficient values in predicting Gleason grading of low to intermediate-risk prostate cancer.

OBJECTIVES: To investigate the diagnostic performance of the apparent diffusion coefficient (ADC) for low to intermediate-risk prostate cancer (PCa), as well as its correlation with the prognostic Gleason score (GS). MATERIALS AND METHODS: Retrospective analysis of MRI images and relevant clinical data from patients with prostate disease. The differences in ADC between different GS groups were compared, and the efficacy of ADC in PCa diagnosis were analyzed. Furthermore, the diagnostic performance of the mean ADC (ADCmean) and minimum ADC (ADCmin) values was compared. RESULTS: There were 1414 patients with 1631 lesions. In terms of GS, both ADCmin and ADCmean values of the GS 4 + 3 group were significantly lower than those of the GS 3 + 4 group, GS 3 + 3 group, and the benign group, with all differences being statistically significant (p < 0.01). The AUC values for diagnosing PCa based on ADCmin and ADCmean were 0.914 and 0.944, respectively. The corresponding diagnostic thresholds were 0.703 × 10-3 mm2/s for ADCmin and 0.927 × 10-3 mm2/s for ADCmean. The magnitudes of ADCmin and ADCmean values exhibited a negative correlation with GS values (ρ = -0.750, p < 0.001; ρ = -0.752, p < 0.001). CONCLUSIONS: ADC values demonstrate an inverse relationship with the invasiveness of PCa, indicating that higher invasiveness is associated with lower ADC values. Additionally, ADC values exhibit high diagnostic potential, sensitivity, and specificity for distinguishing between GS 3 + 4 and GS 4 + 3 lesions. Moreover, the diagnostic value of ADCmean is even more significant, highlighting its crucial role in the diagnosis of low to intermediate-risk PCa. CRITICAL RELEVANCE STATEMENT: ADC values are a valuable tool for distinguishing different levels of aggressiveness in PCa. They help in the preoperative assessment of the biological characteristics of PCa, allowing clinicians to develop personalized treatment strategies, effectively mitigating the risk of unnecessary interventions. KEY POINTS: The preoperative GS is crucial for planning the clinical treatment of PCa. The invasiveness of PCa is inversely correlated with ADC values. ADC values play a crucial role in the accurate preoperative evaluation of low to intermediate-risk PCa, thus aiding clinicians in developing tailored treatment plans.

Clinicopathologic and Molecular Characterization of Xanthomatous Giant Cell Renal Cell Carcinomas: Further Support for a Close Morphologic Spectrum to Eosinophilic Solid and Cystic Renal Cell Carcinomas.

A recent study described a rare subtype of tuberous sclerosis complex ( TSC )-mutated renal cell carcinoma primarily characterized by Xanthomatous giant cell morphology. Only 2 cases in young individuals have been reported so far, making the correct diagnosis challenging from a pathological perspective. It remains unknown whether this tumor represents an independent subtype or belongs to other TSC -mutated tumors. We conducted a clinicopathologic evaluation and immunohistochemical profiling of 5 cases of Xanthomatous Giant Cell Renal Cell Carcinoma (XGC RCC) with confirmed TSC2 mutations through targeted DNA sequencing. In addition, we analyzed transcriptomic profiles using RNA-seq for the following samples: XGC RCC, Low-grade Oncocytic tumors (LOT), High-grade Oncocytic tumors/Eosinophilic Vacuolar Tumors (HOT/EVT), Eosinophilic Solid and Cystic Renal Cell Carcinomas (ESC RCC), Chromophobe cell Renal Cell Carcinomas (ChRCC), Renal Oncocytomas (RO), clear cell Renal Cell Carcinomas (ccRCC), and normal renal tissues. There were 2 female and 3 male patients, aged 22 to 58 years, who underwent radical nephrectomy for tumor removal. The tumor sizes ranged from 4.7 to 9.5 cm in diameter. These tumors exhibited ill-defined boundaries, showed an expansive growth pattern, and featured distinctive tumor giant cells with abundant eosinophilic to Xanthomatous cytoplasm and prominent nucleoli. All tumors had low Ki-67 proliferation indices (<1%) and demonstrated immune reactivity for CD10, PAX8, CK20, CathepsinK, and GPNMB. Next-generation sequencing confirmed TSC2 mutations in all cases. RNA sequencing-based clustering indicated a close similarity between the tumor and ESC RCC. One patient (1/5) died of an accident 63 months later, while the remaining patients (4/5) were alive without tumor recurrences or metastases at the time of analysis, with a mean follow-up duration of 43.4 months. Our research supports the concept that Xanthomatous giant cell renal cell carcinoma (XGC RCC) shares clinicopathological and molecular characteristics with ESC RCC and shows a relatively positive prognosis, providing further support for a close morphologic spectrum between the two. We propose considering XGC RCC as a distinct subtype of ESC RCC.

Oncogenic Roles of Laminin Subunit Gamma-2 in Intrahepatic Cholangiocarcinoma via Promoting EGFR Translation.

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal biliary epithelial cancer in the liver. Here, Laminin subunit gamma-2 (LAMC2) with important oncogenic roles in iCCA is discovered. In a total of 231 cholangiocarcinoma patients (82% of iCCA patients) across four independent cohorts, LAMC2 is significantly more abundant in iCCA tumor tissue compared to normal bile duct and non-tumor liver. Among 26.3% of iCCA patients, LAMC2 gene is amplified, contributing to its over-expression. Functionally, silencing LAMC2 significantly blocks tumor formation in orthotopic iCCA mouse models. Mechanistically, it promotes EGFR protein translation via interacting with nascent unglycosylated EGFR in the endoplasmic reticulum (ER), resulting in activated EGFR signaling. LAMC2-mediated EGFR translation also depends on its interaction with the ER chaperone BiP via their C-terminus. Together LAMC2 and BiP generate a binding "pocket" of nascent EGFR and facilitate EGFR translation. Consistently, LAMC2-high iCCA patients have poor prognosis in two iCCA cohorts. LAMC2-high iCCA cells are highly sensitive to EGFR tyrosine kinase inhibitors (TKIs) treatment both in vitro and in vivo. Together, these data demonstrate LAMC2 as an oncogenic player in iCCA by promoting EGFR translation and an indicator to identify iCCA patients who may benefit from available EGFR-targeted TKIs therapies.

Highly accurate and effective deep neural networks in pathological diagnosis of prostate cancer.

PURPOSE: To established an AI system to make the pathological diagnosis of prostate cancer. METHODS: Prostate histopathological whole mount (WM) sections from patients underwent robot-assisted laparoscopic prostatectomy were prepared. All the prostate WM pathological sections were converted to digital image data and marked with different colors on the basis of the ISUP Gleason grade group. The image was then fed into a segmentation algorithm. We chose modified U-Net as our fundamental network architecture. RESULTS: 172 patients were involved in this study. 896 pieces of prostate WM pathological sections from 160 patients, in which 826 pieces of WM sections from 148 patients were assigned to the training set randomly. After image segmentation there were totally 2,138,895 patches, of which 1,646,535 patches were valid for training. The other WM section was arranged for testing. Based on the whole image testing, AI and pathologists presented the same answers among 21 of 22 pieces of sections. To evaluate the diagnostic results at the pixel level, we anticipated correct cancer or non-cancer diagnose from this AI system. The area under the ROC curve as 96.8%. The value of pixel accuracy of three methods (binary analysis, clinically oriented analysis and analysis for different ISUP Gleason grade) were 96.93%, 95.43% and 93.88%, respectively. The value of frequency weighted IoU were 94.32%, 92.13% and 90.21%, respectively. CONCLUSIONS: This AI system is able to assist pathologists to make a final diagnosis, indicating the great potential and a wide-range of applications of AI in the medical field.