Histone Deacetylase 6 Inhibitor 5-Phenylcarbamoylpentyl Selenocyanide (SelSA) Suppresses Hepatocellular Carcinoma by Downregulating Phosphorylation of the Extracellular Signal-Regulated Kinase 1/2 Pathway.

Histone deacetylase 6 (HDAC6) enzyme plays a crucial role in a variety of cellular processes related to cancer, and inhibition of HDAC6 is emerging as an effective strategy for cancer treatment. Although several hydroxamate-based HDAC6 inhibitors showed promising anticancer activities, the intrinsic defects such as poor selectivity, stability, and pharmacokinetics limited their application. In this study, a potent selenocyanide-bearing HDAC6 inhibitor, 5-phenylcarbamoylpentyl selenocyanide (SelSA), was evaluated for its antihepatocellular carcinoma (HCC) activity and further explored for its antitumor mechanisms. In vitro studies demonstrated that SelSA exhibited excellent antiproliferative activity against three HCC cells HepG2 (2.3 ± 0.29 µM), Huh7 (0.83 ± 0.48 µM), and LM3 (2.6 ± 0.24 µM). Further studies indicated that SelSA could downregulate the expression of extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylation, inhibit the growth, invasion, and migration of Huh7 cells, and promote their apoptosis. Moreover, SelSA significantly suppressed tumor growth in Huh7 xenograft mouse models. Our findings suggest that SelSA could be a potential therapeutic agent for HCC.

A Novel Instruction Driven 1-D CNN Processor for ECG Classification.

Electrocardiography (ECG) has emerged as a ubiquitous diagnostic tool for the identification and characterization of diverse cardiovascular pathologies. Wearable health monitoring devices, equipped with on-device biomedical artificial intelligence (AI) processors, have revolutionized the acquisition, analysis, and interpretation of ECG data. However, these systems necessitate AI processors that exhibit flexible configuration, facilitate portability, and demonstrate optimal performance in terms of power consumption and latency for the realization of various functionalities. To address these challenges, this study proposes an instruction-driven convolutional neural network (CNN) processor. This processor incorporates three key features: (1) An instruction-driven CNN processor to support versatile ECG-based application. (2) A Processing element (PE) array design that simultaneously considers parallelism and data reuse. (3) An activation unit based on the CORDIC algorithm, supporting both Tanh and Sigmoid computations. The design has been implemented using 110 nm CMOS process technology, occupying a die area of 1.35 mm2 with 12.94 µW power consumption. It has been demonstrated with two typical ECG AI applications, including two-class (i.e., normal/abnormal) classification and five-class classification. The proposed 1-D CNN algorithm performs with a 97.95% accuracy for the two-class classification and 97.9% for the five-class classification, respectively.

Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned.

Severe cases of COVID-19 often necessitate escalation to the Intensive Care Unit (ICU), where patients may face grave outcomes, including mortality. Chest X-rays play a crucial role in the diagnostic process for evaluating COVID-19 patients. Our collaborative efforts with Michigan Medicine in monitoring patient outcomes within the ICU have motivated us to investigate the potential advantages of incorporating clinical information and chest X-ray images for predicting patient outcomes. We propose an analytical workflow to address challenges such as the absence of standardized approaches for image pre-processing and data utilization. We then propose an ensemble learning approach designed to maximize the information derived from multiple prediction algorithms. This entails optimizing the weights within the ensemble and considering the common variability present in individual risk scores. Our simulations demonstrate the superior performance of this weighted ensemble averaging approach across various scenarios. We apply this refined ensemble methodology to analyze post-ICU COVID-19 mortality, an occurrence observed in 21% of COVID-19 patients admitted to the ICU at Michigan Medicine. Our findings reveal substantial performance improvement when incorporating imaging data compared to models trained solely on clinical risk factors. Furthermore, the addition of radiomic features yields even larger enhancements, particularly among older and more medically compromised patients. These results may carry implications for enhancing patient outcomes in similar clinical contexts.

Molecular landscape for risk prediction and personalized therapeutics of castration-resistant prostate cancer: at a glance.

Prostate cancer (PCa) is commonly occurred with high incidence in men worldwide, and many patients will be eventually suffered from the dilemma of castration-resistance with the time of disease progression. Castration-resistant PCa (CRPC) is an advanced subtype of PCa with heterogeneous carcinogenesis, resulting in poor prognosis and difficulties in therapy. Currently, disorders in androgen receptor (AR)-related signaling are widely acknowledged as the leading cause of CRPC development, and some non-AR-based strategies are also proposed for CRPC clinical analyses. The initiation of CRPC is a consequence of abnormal interaction and regulation among molecules and pathways at multi-biological levels. In this study, CRPC-associated genes, RNAs, proteins, and metabolites were manually collected and integrated by a comprehensive literature review, and they were functionally classified and compared based on the role during CRPC evolution, i.e., drivers, suppressors, and biomarkers, etc. Finally, translational perspectives for data-driven and artificial intelligence-powered CRPC systems biology analysis were discussed to highlight the significance of novel molecule-based approaches for CRPC precision medicine and holistic healthcare.

Perineural Invasion as a Risk Factor For Soft Tissue Progression in Patients With Metastatic Castration-Resistant Prostate Cancer After Abiraterone Resistance.

BACKGROUND: Prostate cancer presents with soft tissue progression (STP) is highly aggressive. We analyzed the risk factor for STP in patients with metastatic castration-resistant prostate cancer (mCRPC) who developed abiraterone acetate (AA) resistance. METHODS: This retrospective study included patients with mCRPC who received AA between February 2018 and July 2022. STP was defined as recurrent lesions in situ, multiple regional lymph node metastases (mLNM), or visceral metastases. Clinical features of patients with STP were analyzed, and risk factors for STP were further investigated. RESULTS: Sixty-three patients (mean age, 75.0 years; median follow-up time, 22.3 months) were included in this study. Twenty-three patients (36.5%) presented STP during follow up, the overall survival (OS) after STP was 4.6 months. The serum neuron-specific enolase (NSE) were significantly elevated in patients with STP. Biopsies for 8 patients with STP showed neuroendocrine prostate cancer (NEPC, n = 5) was the major pathological types. Further analysis showed that perineural invasion (PNI) in primary tumor were the independent risk factors (HR = 3.145, P = 0.020) for STP, and PNI was related to the aggressiveness of tumor. Patients with PNI showed shorter castration-resistant progression free survival (median, 23.73 months vs. 25.59 months) and STP progression free survival (median, 19.7 months vs. not reached) compared with patients without PNI. CONCLUSIONS: STP showed extremely poor prognoses in patients with mCRPC after AA resistance, NEPC is the main pathological type of STP, and PNI in primary tumor was an independent risk factor for STP and indicated poor prognosis of prostate cancer.

Regulating the solvation structure of Zn2+ via glycine enables a long-cycling neutral zinc-ferricyanide flow battery.

Zinc-based flow batteries hold potential promise for extensive energy storage on a large scale owing to their high energy density and low cost. However, their widespread implementation is impeded by challenges associated with zinc (Zn) dendrites and side reactions like the hydrogen evolution reaction on the anode. Theoretical calculations have confirmed that glycine (Gly) has the ability to coordinate with Zn2+, displacing H2O molecules in the solvation shell, thereby restoring the solvation structure of Zn2+ and promoting the release of reactive Zn2+ during plating/stripping processes. As a result, the incorporation of Gly into the anolyte of a neutral zinc-ferricyanide (Zn/Fe) flow battery (ZIFB) effectively inhibits the formation of Zn dendrites and impedes side reactions, leading to highly reversible and stable Zn plating/stripping reactions. A Zn||Zn symmetric flow battery utilizing Gly in the anolyte demonstrated extended cycling durability, lasting over 550 h at a current density of 30 mA cm-2, in contrast to the failure of a Gly-free anolyte system after 150 h. Notably, this approach facilitates a neutral ZIFB achieving an impressive energy efficiency exceeding 70 %, even at a high current density of 70 mA cm-2, with a cycle lifespan exceeding 800 h (33 days) at a current density of 30 mA cm-2. Conversely, the neutral ZIFB lacking Gly showed a significantly shorter cycle life of only 260 h under identical operational conditions (30 mA cm-2). Due to the economic benefits of Gly and the proposed user-friendly route, this strategy demonstrates great potential for promoting the widespread adoption of zinc-based flow batteries with improved performance for practical use.

Additional impact of genetic ancestry over race/ethnicity to prevalence of KRAS mutations and allele-specific subtypes in non-small cell lung cancer.

The KRAS mutation is the most common oncogenic driver in patients with non-small cell lung cancer (NSCLC). However, a detailed understanding of how self-reported race and/or ethnicity (SIRE), genetically inferred ancestry (GIA), and their interaction affect KRAS mutation is largely unknown. Here, we investigated the associations between SIRE, quantitative GIA, and KRAS mutation and its allele-specific subtypes in a multi-ethnic cohort of 3,918 patients from the Boston Lung Cancer Survival cohort and the Chinese OrigiMed cohort with an independent validation cohort of 1,450 patients with NSCLC. This comprehensive analysis included detailed covariates such as age at diagnosis, sex, clinical stage, cancer histology, and smoking status. We report that SIRE is significantly associated with KRAS mutations, modified by sex, with SIRE-Asian patients showing lower rates of KRAS mutation, transversion substitution, and the allele-specific subtype KRASG12C compared to SIRE-White patients after adjusting for potential confounders. Moreover, GIA was found to correlate with KRAS mutations, where patients with a higher proportion of European ancestry had an increased risk of KRAS mutations, especially more transition substitutions and KRASG12D. Notably, among SIRE-White patients, an increase in European ancestry was linked to a higher likelihood of KRAS mutations, whereas an increase in admixed American ancestry was associated with a reduced likelihood, suggesting that quantitative GIA offers additional information beyond SIRE. The association of SIRE, GIA, and their interplay with KRAS driver mutations in NSCLC highlights the importance of incorporating both into population-based cancer research, aiming to refine clinical decision-making processes and mitigate health disparities.

Exploration of the influence of GOLGA8B on prostate cancer progression and the resistance of castration-resistant prostate cancer to cabazitaxel.

Castration-resistant prostate cancer (CRPC) represents the final stage of prostate cancer (PCa). Cabazitaxel, a taxane chemotherapy drug, is used in treating CRPC. However, patients with CRPC eventually develop resistance to cabazitaxel, and the underlying mechanism remains unclear. Here, we aimed to investigate potential genetic alterations that may play a role in CRPC resistance to cabazitaxel. Using microarray data from the GSE158494 dataset, we identified ten critical genes (CXCL8, ITGB8, CLIP4, MAP1B, WIPI1, MMP13, CXCL1, C1S, GOLGA8B, and CXCL6) associated with CRPC cell resistance to cabazitaxel. The potential function of these key genes in PCa progression was analyzed using different databases, including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Chinese Prostate Cancer Genome and Epigenome Atlas (CPGEA). Our findings revealed altered expression of these genes in the development of PCa. Furthermore, CXCL1 and GOLGA8B were found to influence the disease-free survival (DFS) status of patients with PCa, with GOLGA8B affecting the overall prognosis in patients with PCa. Additionally, GOLGA8B expression was associated with the infiltration of various immune cells in PCa, and it was upregulated in clinical PCa and CRPC samples. Through CCK-8 assays, we established that GOLGA8B could influence the sensitivity of CRPC cells to cabazitaxel and docetaxel. In conclusion, we identified GOLGA8B as a crucial gene that influences PCa progression and contributes to CRPC resistance to cabazitaxel.

Activating Point Mutations in the MET Kinase Domain Represent a Unique Molecular Subset of Lung Cancer and Other Malignancies Targetable with MET Inhibitors.

Activating point mutations in the MET tyrosine kinase domain (TKD) are oncogenic in a subset of papillary renal cell carcinomas. Here, using comprehensive genomic profiling among >600,000 patients, we identify activating MET TKD point mutations as putative oncogenic driver across diverse cancers, with a frequency of ∼0.5%. The most common mutations in the MET TKD defined as oncogenic or likely oncogenic according to OncoKB resulted in amino acid substitutions at positions H1094, L1195, F1200, D1228, Y1230, M1250, and others. Preclinical modeling of these alterations confirmed their oncogenic potential and also demonstrated differential patterns of sensitivity to type I and type II MET inhibitors. Two patients with metastatic lung adenocarcinoma harboring MET TKD mutations (H1094Y, F1200I) and no other known oncogenic drivers achieved confirmed partial responses to a type I MET inhibitor. Activating MET TKD mutations occur in multiple malignancies and may confer clinical sensitivity to currently available MET inhibitors. Significance: The identification of targetable genomic subsets of cancer has revolutionized precision oncology and offers patients treatments with more selective and effective agents. Here, we demonstrate that activating, oncogenic MET tyrosine kinase domain mutations are found across a diversity of cancer types and are responsive to MET tyrosine kinase inhibitors.

Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification.

BACKGROUND: Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored. METHODS: Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold. RESULTS: Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12-3.50, P-value = 4.13 × 10-15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99-2.49, P-value = 5.70 × 10-46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72-0.74). CONCLUSIONS: Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.

PRL-mediated STAT5B/ARRB2 pathway promotes the progression of prostate cancer through the activation of MAPK signaling.

Previous study showed that higher expression of prolactin (PRL) was found in CRPC samples compared with hormone-naive prostate cancer (HNPC) and benign prostatic hyperplasia (BPH) samples. We further investigate the function of PRL in prostate cancer (PCa) and explored its downstream effects. We found heterogeneous expression of the PRLR in clinical prostate samples. The VCaP and 22Rv1 cells exhibited PRLR expression. Among the downstream proteins, STAT5B was the dominant subtype in clinical samples and cell lines. Human recombinant PRL stimulation of PCa cells with PRLR expression resulted in increased phosphorylation of STAT5B(pSTAT5B) and progression of PCa in vitro and in vivo, and STAT5B knockdown can suppress the malignant behavior of PCa. To understand the mechanism further, we performed Bioinformatic analysis, ChIP qPCR, and luciferase reporter gene assay. The results revealed that ARRB2 was the transcription target gene of STAT5B, and higher expression of ARRB2 was related to higher aggression and poorer prognosis of PCa. Additionally, Gene set enrichment analysis indicated that higher expression of ARRB2 was significantly enriched in the MAPK signaling pathway. Immunohistochemistry (IHC) demonstrated elevated pSTAT5B, ARRB2, and pERK1/2 expression levels in CRPC tissues compared to HNPC and BPH. Mechanically, ARRB2 enhanced the activation of the MAPK pathway by binding to ERK1/2, thereby promoting the phosphorylation of ERK1/2 (pERK1/2). In conclusion, our study demonstrated that PRL stimulation can promote the progression of PCa through STAT5B/ARRB2 pathway and activation of MAPK signaling, which can be suppressed by intervention targeting STAT5B. Blockade of the STAT5B can be a potential therapeutic target for PCa.

Glycolysis related lncRNA SNHG3 / miR-139-5p / PKM2 axis promotes castration-resistant prostate cancer (CRPC) development and enzalutamide resistance.

Although androgen deprivation therapy (ADT) by the anti-androgen drug enzalutamide (Enz) may improve the survival level of patients with castration-resistant prostate cancer (CRPC), most patients may eventually fail due to the acquired resistance. The reprogramming of glucose metabolism is one type of the paramount hallmarks of cancers. PKM2 (Pyruvate kinase isozyme typeM2) is a speed-limiting enzyme in the glycolytic mechanism, and has high expression in a variety of cancers. Emerging evidence has unveiled that microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have impact on tumor development and therapeutic efficacy by regulating PKM2 expression. Herein, we found that lncRNA SNHG3, a highly expressed lncRNA in CRPC via bioinformatics analysis, promoted the invasive ability and the Enz resistance of the PCa cells. KEGG pathway enrichment analysis indicated that glucose metabolic process was tightly correlated with lncRNA SNHG3 level, suggesting lncRNA SNHG3 may affect glucose metabolism. Indeed, glucose uptake and lactate content determinations confirmed that lncRNA SNHG3 promoted the process of glycolysis. Mechanistic dissection demonstrated that lncRNA SNHG3 facilitated the advance of CRPC by adjusting the expression of PKM2. Further explorations unraveled the role of lncRNA SNHG3 as a 'sponge' of miR-139-5p and released its binding with PKM2 mRNA, leading to PKM2 up-regulation. Together, Our studies suggest that lncRNA SNHG3 / miR-139-5p / PKM2 pathway promotes the development of CRPC via regulating glycolysis process and provides valuable insight into a novel therapeutic approach for the disordered disease.

Genomic and Immunophenotypic Landscape of Acquired Resistance to PD-(L)1 Blockade in Non-Small-Cell Lung Cancer.

PURPOSE: Although immune checkpoint inhibitors (ICI) have extended survival in patients with non-small-cell lung cancer (NSCLC), acquired resistance (AR) to ICI frequently develops after an initial benefit. However, the mechanisms of AR to ICI in NSCLC are largely unknown. METHODS: Comprehensive tumor genomic profiling, machine learning-based assessment of tumor-infiltrating lymphocytes, multiplexed immunofluorescence, and/or HLA-I immunohistochemistry (IHC) were performed on matched pre- and post-ICI tumor biopsies from patients with NSCLC treated with ICI at the Dana-Farber Cancer Institute who developed AR to ICI. Two additional cohorts of patients with intervening chemotherapy or targeted therapies between biopsies were included as controls. RESULTS: We performed comprehensive genomic profiling and immunophenotypic characterization on samples from 82 patients with NSCLC and matched pre- and post-ICI biopsies and compared findings with a control cohort of patients with non-ICI intervening therapies between biopsies (chemotherapy, N = 32; targeted therapies, N = 89; both, N = 17). Putative resistance mutations were identified in 27.8% of immunotherapy-treated cases and included acquired loss-of-function mutations in STK11, B2M, APC, MTOR, KEAP1, and JAK1/2; these acquired alterations were not observed in the control groups. Immunophenotyping of matched pre- and post-ICI samples demonstrated significant decreases in intratumoral lymphocytes, CD3e+ and CD8a+ T cells, and PD-L1-PD1 engagement, as well as increased distance between tumor cells and CD8+PD-1+ T cells. There was a significant decrease in HLA class I expression in the immunotherapy cohort at the time of AR compared with the chemotherapy (P = .005) and the targeted therapy (P = .01) cohorts. CONCLUSION: These findings highlight the genomic and immunophenotypic heterogeneity of ICI resistance in NSCLC, which will need to be considered when developing novel therapeutic strategies aimed at overcoming resistance.

Analysis of cardiovascular disease factors on SARS-CoV-2 infection severity

Background:At present, COVID-19 is a global pandemic and is seriously harmful to humans. In this retrospective study, the aim was to investigate the interaction between CVD and COVID-19.Methods:A total of 180 patients diagnosed with COVID-19 in Yichang Central People's Hospital from 29 January to 17 March 2020 were initially included. The medical history, clinical manifestations at the time of admission, laboratory test results, hospitalization time and complications were recorded. According to the medical history, the patients were assigned to the nonsevere group with non-CVD (n=90), the nonsevere group with CVD (n=22), the severe group with non-CVD (n=40) and the severe group with CVD (n=28).Results:In the severe group, compared with non-CVD patients, CVD patients had a significantly higher incidence of fever (P<0.05). However, compared with the nonsevere group, the severe group had significantly higher proportions of patients with hypertension, type 2 diabetes mellitus, CHD and HF (all P<0.05). Among the patients with nonsevere COVID-19, the WBC count and the levels of IL-6, CRP, D-dimer, NT-proBNP, and FBG were significantly higher and the Hb level was significantly lower in the CVD patients than in the non-CVD patients (all P<0.05). However, among the patients with severe COVID-19, only the level of NT-proBNP was significantly higher in CVD patients than in non-CVD patients (P<0.05). In addition, the WBC count and the levels of IL-6, CRP, D-dimer, CKMB, ALT, AST, SCR, NT-proBNP, and FBG were significantly higher and the Hb level was significantly lower in the severe group than in the nonsevere group (all P<0.05). (AU)

Antecedentes:La infección por SARS-CoV-2 está provocando graves consecuencias en la humanidad. El objetivo de este estudio retrospectivo fue investigar el impacto de las enfermedades cardiovasculares (ECV) en la gravedad de dicha infección.Métodos:Entre el 29 de enero y el 17 de marzo de 2020, se diagnosticaron 180 pacientes con neumonía por SARS-CoV-2 en el Hospital Popular Central de Yichang. Se registraron los antecedentes, manifestaciones clínicas, resultados de laboratorio, tiempo de hospitalización y complicaciones. Los pacientes se dividieron en cuatro grupos: 1) infección no grave sin ECV (n=90), 2) infección no grave con ECV (n=22), 3) infección grave sin ECV (n=40) y 4) infección grave con ECV (n=28).Resultados:La prevalencia de fiebre en los pacientes con ECV fue significativamente mayor que en aquellos sin ECV (P<0,05). Sin embargo, en comparación con los pacientes no graves, la proporción de pacientes con hipertensión, diabetes mellitus tipo 2, cardiopatía coronaria e insuficiencia cardíaca en los pacientes graves fue significativamente mayor (p<0,05). Los niveles de recuento de leucocitos, IL-6, PCR, dímero D, NT-proBNP y glucemia en ayunas (GA) en pacientes con ECV fueron significativamente mayores que en los de pacientes sin ECV, aunque los niveles de Hb fueron significativamente menores que los de los pacientes sin ECV (p<0,05). Sin embargo, los valores de NT-proBNP en pacientes con ECV fueron significativamente mayores que en los pacientes sin ECV (P<0,05). (AU)