Tool For Prognosis Research Articles

Cardiopulmonary exercise test findings are not the same in distinct types of cardiac amyloidosis

Abstract Background Cardiopulmonary exercise testing (CPET) is a widely used tool for risk stratification and prognosis in patients with chronic heart failure. In amyloid patients, cardiac amyloid deposits are associated with poor prognosis, increased risk for arrhythmias, sudden death, and subsequent exercise limitation due to restrictive cardiomyopathy. The type of amyloidosis and its affectation of the heart are different, and little is known about the CPET parameters according to the type of cardiac amyloidosis. Purpose In this study, we aim to compare CPET data in different types of amyloidosis to determine if CPET variables evaluated could have a significant difference that could impact the follow-up or prognosis of the patients based on the type of amyloidosis. Methods We conducted a retrospective cohort study of 194 patients with a diagnosis of cardiac amyloidosis referred for CPET from February 2010 to February 2024. Patients with at least one CPET data were included in our analysis. The type of amyloidosis, comorbidities, and echocardiogram data were retrieved from medical records. Patients were divided into 3 different groups according to the type of amyloidosis: AL Amyloidosis(AL), Variant TTR Amyloidosis (vTRR), and Wild Type TTR Amyloidosis (wtTTR). Individuals with CPET studies after heart transplant were excluded from the analysis. Fisher’s exact test or chi-square was used to compare categorical variables. ANOVA and Tukey-Kramer (TK) were used to compare continuous variables. Adjustment using General Linear Models (GLM) procedure was used to identify any confounder that could affect the results. A p-value <0.05 was considered significant. Results Out of the 194 patients, 66 had AL Amyloidosis, 40 had vTTR Amyloidosis, and 88 had wtTTR Amyloidosis. Most of the patients were male, and the male predominance was higher in the wtTRR group. There were 41 (62.1%) males in the AL group, 35 (87.5%) in the vTRR group, and 83 (94.3%) in the wtTTR group (p<0.0001). Comorbidities were balanced among the groups. Additional demographic and comorbidities data are shown in Table 1. From the evaluated CPET variables, VE/VCO2 nadir and slope were significantly higher in the wtTTR group when compared to the other groups, as well as Peak VE and Peak TV(Figure A). However, after adjusting for sex, BMI, and age, VE/VCO2 nadir was still significantly higher in the wtTRR group (p=0.003) compared to the other groups, as well as Peak VE, which was higher again in vTTR patients (p=0.001), and Peak TV (Table 2). Conclusion Ventilation variables evaluated in CPET showed alterations in the wtTTR group. These findings suggest that wtTRR amyloid patients could have a severe problem in ventilation that could be of significant relevance in future prognosis.

Controlling Nutritional Status (CONUT) Score: a new tool for characterization and prognosis of patients with infective endocarditis

Abstract Background malnutrition is a marker of unfavorable prognosis in different medical conditions, however, the association between new objective immunonutritional indexes and outcomes for patients with infective endocarditis (IE) is not fully studied. Purpose the aim of this study was to assess the role of the Controlling Nutritional Status (CONUT) Score in the characterization of patients with IE and its association with prognostic outcomes. Methods a total of 184 cases of confirmed IE were consecutively collected and followed during one year after diagnosis in two tertiary hospitals. CONUT score was calculated using serum albumin, total cholesterol and lymphocyte count [(range 0-12), the higher, the worse] at diagnosis, and patients were categorised as CONUT-high (>=6, n=98), and CONUT-low (<6, n=86) based on the sample median value. Results mean age was 70 [SD 15] years, 64% were men and community-acquired infections were 69%. Median score value was 6 (4). As shown in Table 1 and 2, diabetes and frailty were more prevalent in CONUT-high group, who showed a worse profile of nutritional biomarkers. Overall, the most frequent pathogen was S. viridans (n=43). By groups, S. aureus was predominantly isolated in CONUT-high (20 vs 8%; p 0.02), and non-viridans streptococci in CONUT-low (9 vs 2%, p 0.03). Regarding infection site, IE of aortic bioprostheses was more common in CONUT-high, whereas mechanical aortic valves and mitral bioprostheses were more frequently involved in CONUT-low. Larger vegetations [14 (11) vs 11 (7) mm, p 0.02], and more periannular abscesses (25 vs 13%, p 0.04) were detected in CONUT-high, who presented more acute kidney injury and septic shock during hospitalization. Despite higher predicted surgical risk in CONUT-high, neither the proportion of patients who underwent surgery nor in-hospital mortality, differed between groups. When analyzing according to the therapeutic approach, only among those medically managed patients without surgical indication, in-hospital mortality was higher in CONUT-high. At 1-year follow-up, rehospitalization rate tended to be lower in those with a better nutritional status (35% vs 51%, p 0.07). Conclusions in patients with IE and a high CONUT score, diabetes and frailty were more prevalent. In addition, virulent pathogens, larger vegetations and periannular complications were more frequently reported. Although surgery performance and in-hospital mortality did not differ between groups, a worse nutritional status was associated with a higher rate of clinical complications and higher mortality among patients with conservative management who did not meet surgical criteria.

Deep learning for quantification of myocardial scar and microvascular obstruction in late gadolinium enhancement cardiovascular magnetic resonance images

Abstract Objectives Detecting and measuring myocardial scar and microvascular obstruction (MVO) accurately following reperfusion therapy is clinically vital for patients with acute myocardial infarction (AMI). Current clinical practice relies on manual delineation of endocardial borders as well as hyper- and hypo-enhanced regions on late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) images for scar and MVO quantification, respectively. However, this approach is subjective, labor-intensive, and time-consuming. The objective of this study is to develop and assess a convolutional neural network (CNN)-based method for the automated quantification of LGE scar and MVO in AMI patients. Methods A total of 1836 LGE images from 252 patients with AMI were analyzed, with the cohort comprising 232 males and an average age of 56±9 years. Our approach, utilizing a combined architecture of cascaded YOLOv8 (You Only Look Once version 8) and nnU-Net, was implemented for the simultaneous segmentation of the left ventricular (LV) myocardium, scar, and MVO in LGE images. Independent datasets for training, validation, and testing were maintained in an 8:1:1 ratio. Performance evaluation was conducted by comparing the results to manual scar and MVO quantification, utilizing metrics such as the Dice similarity coefficient (DSC) and Bland-Altman analysis. Results The automated segmentation process took 0.05 seconds per image. The segmentation accuracy, as assessed by the DSC, yielded values of 0.96±0.04 (per-patient, n=25) and 0.96±0.05 (per-slice, n=184) for scar segmentation, and 0.86±0.17 (per-patient) and 0.89±0.15 (per-slice) for MVO segmentation. In per-patient analysis, the volumes of automatically segmented scar and MVO demonstrated strong agreement with manually derived results, with biases [limits of agreement] of -0.3 [-3.0, 2.4] cm³ and 0.1 [-0.2, 0.3] cm³, respectively. Furthermore, there was strong concordance between automatically and manually derived scar size as a percentage of LV mass (-0.2 [-3.1, 2.7] %) and MVO size as a percentage of scar (1.2 [-5.6, 8.0] %). Conclusions The findings demonstrate excellent agreement between our proposed automated deep-learning solution and clinical expert annotation, suggesting its potential as a predictive tool for prognosis and clinical outcomes in patients with AMI.

Imaging for upper tract urothelial carcinoma: update of the evidence and a glimpse into the future.

Upper tract urothelial carcinoma (UTUC) is a rare malignancy posing significant diagnostic and management challenges. This review provides an overview of the evidence supporting various imaging modalities and offers insights into future innovations in UTUC imaging. With the growing use of advancements in computed tomography (CT) technologies for both staging and follow-up of UTUC patients, continuous innovations aim to enhance performance and minimize the risk of excessive exposure to ionizing radiation and iodinated contrast medium. In patients unable to undergo CT, magnetic resonance imaging serves as an alternative imaging modality, though its sensitivity is lower than CT. Positron emission tomography, particularly with innovative radiotracers and theranostics, has the potential to significantly advance precision medicine in UTUC. Endoscopic imaging techniques including advanced modalities seem to be promising in improved visualization and diagnostic accuracy, however, evidence remains scarce. Radiomics and radiogenomics present emerging tools for noninvasive tumor characterization and prognosis. The landscape of imaging for UTUC is rapidly evolving, with significant advancements across various modalities promising improved diagnostic accuracy, patient outcomes, and safety.

Integrating anoikis and ErbB signaling insights with machine learning and single-cell analysis for predicting prognosis and immune-targeted therapy outcomes in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) poses a significant global health challenge due to its poor prognosis and limited therapeutic modalities. Anoikis and ErbB signaling pathways are pivotal in cancer cell proliferation and metastasis, but their relevance in HCC remains insufficiently explored. This study evaluates the prognostic significance of anoikis and ErbB signaling pathways in HCC by utilizing data from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), three additional independent validation cohorts, and an in-house cohort. Advanced bioinformatics analyses and 167 machine learning models based on leave-one-out cross-validation (LOOCV) were used to predict HCC prognosis and assess outcomes of immune-targeted therapies. Additionally, key biological processes of the anoikis and ErbB signaling pathways in HCC were further investigated. The single sample Gene Set Enrichment Analysis revealed a strong correlation between upregulated ErbB signaling in high anoikis-expressing tumors and poor clinical outcomes. The development of the Anoikis-ErbB Related Signature (AERS) using the LASSO + RSF model demonstrated robust predictive capabilities, as validated across multiple patient cohorts, and proved effective in predicting responses to immune-targeted therapies. Further investigation highlighted activated NOTCH signaling pathways and decreased macrophage infiltration was associated with resistance to sorafenib and immune checkpoint inhibitors, as evidenced by bulk and single-cell RNA sequencing (scRNA-seq). AERS provides a novel tool for clinical prognosis and paves the way for immune-targeted therapeutic approaches, underscoring the potential of integrated molecular profiling in enhancing treatment strategies for HCC.

Hypoxia-Associated GPNMB+ Macrophages Promote Malignant Progression of Colorectal Cancer and Its RelatedRisk Signature Are Powerful Predictive Tool for theTreatment of Colorectal Cancer Patients.

Colorectal cancer (CRC) is a highly malignant tumor with hypoxia being a crucial feature during its progression. This study utilized multiple independent CRC cohorts for bioinformatics analysis and in vitro experiments to investigate the role of hypoxia-related subgroups in CRC. Machine learning was employed to construct risk features associated with this subgroup and further explore its therapeutic value in CRC. The study identified the GPNMB+ Macrophage (GPNMB+ Macr) subgroup as most relevant to hypoxia. GPNMB+ Macr showed significantly higher infiltration in tumor tissues compared to non-tumor tissues, increasing with CRC stage. High infiltration of GPNMB+ Macr was associated with poor prognosis in terms of overall and recurrence-free survival in CRC patients. GPNMB+ Macrophages exhibit M2-like characteristics and have the ability to promote 5-FU resistance, proliferation, and metastasis of CRC cells. The study developed the Hypoxia-Related Macrophage Risk Score (HMRS), which not only served as an independent prognostic factor for CRC patients but also demonstrated robust prognostic performance compared to 84 previously published prognostic features. Patients with low HMRS were sensitive to fluorouracil, oxaliplatin (FOLFOX), and anti-PD-1 immunotherapy, while those with high HMRS showed resistance. Additionally, HMRS was identified as an independent prognostic factor in other digestive tract tumors (hepatocellular carcinoma, pancreatic cancer, esophageal cancer, and gastric cancer), indicating potential extrapolation to other tumor types. In conclusion, GPNMB+ Macr promotes the malignant progression of CRC, and HMRS serves as a powerful predictive tool for prognosis, chemotherapy, and immunotherapy in CRC patients, aiding in improving the quality of survival.

Molecular Signature Associated With Acute Rejection in Vascularized Composite Allotransplantation.

A deeper understanding of acute rejection in vascularized composite allotransplantation is paramount for expanding its utility and longevity. There remains a need to develop more precise and accurate tools for diagnosis and prognosis of these allografts, as well as alternatives to traditional immunosuppressive regimens. Twenty-seven skin biopsies collected from 3 vascularized composite allotransplantation recipients, consisting of face and hand transplants, were evaluated by histology, immunohistochemistry staining, and gene expression profiling. Biopsies with clinical signs and symptoms of rejection, irrespective of histopathological grading, were significantly enriched for genes contributing to the adaptive immune response, innate immune response, and lymphocyte activation. Inflammation episodes exhibited significant fold change correlations between the face and hands, as well as across patients. Immune checkpoint genes were upregulated during periods of inflammation that necessitated treatment. A gene signature consisting of CCL5, CD8A, KLRK1, and IFNγ significantly predicted inflammation specific to vascularized composite allografts that required therapeutic intervention. The mechanism of vascularized composite allograft-specific inflammation and rejection appears to be conserved across different patients and skin on different anatomical sites. A concise gene signature can be utilized to ascertain graft status along with a continuous scale, providing valuable diagnostic and prognostic information to supplement current gold standards of graft evaluation.

Biochanin-A co-crystal formulation improves bioavailability and ameliorates cerulein-induced pancreatitis by attenuating the inflammation

Co-crystallization of a therapeutic ingredient with an appropriate co-former is a powerful technique to augment the physicochemical and pharmacokinetic properties and the effectiveness of Active Pharmaceutical Ingredients (APIs). Biochanin A (BCA), a flavonoid with medicinal potential, is limited by poor solubility and low oral bioavailability. This study aimed to design and develop a novel BCA-nicotinamide cocrystal as BCC to enhance BCA’s oral bioavailability and explore its therapeutic potential for ameliorating cerulein-induced acute pancreatitis (CIAP) by elucidating the target identification utilizing tissue/serum metabolite profiles. The cocrystal was designed by the supramolecular synthon approach and characterized by single-crystal X-ray diffraction that confirms a robust three-dimensional hydrogen-bonded network of BCA and Nicotinamide (NCT) in the crystal. FT-IR and DSC were used to analyze the cocrystal’s intermolecular interactions and thermal behavior. BCC exhibited enhanced solubility and drug release compared to BCA alone, resulting in enhanced oral bioavailability and pancreatic tissue concentration. Comparing BCC to BCA in the CIAP model, BCC therapy remarkably reduced cerulein-induced pancreatitis, evidenced by significant reductions in inflammation, acinar cell atrophy, and amylase levels in pancreatic tissues. Further, the cocrystal formulation also down-regulated the oxidative stress markers, inflammatory cytokines and macrophage-related proteins. The study has identified distinct metabolomic signatures linked with AP with the help of Orbitrap Exploris mass spectrometry, which could pave the way for creating focused diagnostic tools for a better prognosis. In conclusion, these results offer new insights into exploring mechanistic pathways associated with specific biomarkers and underscore BCC cocrystals as a promising approach to enhance BCA’s therapeutic potential.

SENSE-Cog Lewy: Investigating the Impact of Sensory Loss on the Diagnosis, Clinical Features and Prognosis of Lewy Body Dementia

Abstract Background Lewy Body Dementia (LBD) accounts for 20% of the nearly 65,000 people with dementia in Ireland, but fewer than 5% of those affected receive a formal diagnosis. LBD includes both Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB) and can be characterised by fluctuating and progressive cognitive difficulties, vivid visual hallucinations and REM sleep behaviour disturbances. Sensory function such hearing, vision and olfactory function declines with age—but increasing evidence shows that abnormal patterns of sensory dysfunction can be one of the earliest clinical signs and predictors of progression of neurodegenerative diseases such as Lewy body dementia and Parkinson’s disease dementia. Methods A scoping review was undertaken using Embase, CINAHL, PsychINFO and PubMed. Only reports on people with LBD (DLB and PDD) from any stage, prodromal to late stage were considered. Papers primarily addressing other forms of neurocognitive disorders were excluded. Sensory loss was conceptualised as the loss of smell, vision and hearing. Two reviewers independently assessed each study for inclusion, and disagreements were resolved by a third reviewer. Results Reports on sensory loss in LBD were very few and most often were comparing sensory loss across different dementia types. Strong associations were observed between olfactory loss and particular visual impairment patterns and the severity of both cognitive and non-cognitive DLB symptoms. Olfactory impairment is a potential early biomarker of DLB and PDD and severity of olfactory dysfunction can predict cognitive decline. Visual hallucinations, for example, were found to be closely linked to visual impairment patterns such as pareidolia. Conclusion This study highlights a knowledge gap regarding the patterns of sensory loss in LBD and their relationship with cognitive and non-cognitive LBD symptoms. Sensory assessments represent potentially valuable diagnostic and prognosis tool in LBD, with further research required to understand the aetiological mechanisms underlying sensory impairment in LBD and other dementias.

Role of Exosomes in Salivary Gland Tumors and Technological Advances in Their Assessment.

Backgroud: Salivary gland tumors (SGTs) are rare and diverse neoplasms, presenting significant challenges in diagnosis and management due to their rarity and complexity. Exosomes, lipid bilayer vesicles secreted by almost all cell types and present in all body fluids, have emerged as crucial intercellular communication agents. They play multifaceted roles in tumor biology, including modulating the tumor microenvironment, promoting metastasis, and influencing immune responses. Results: This review focuses on the role of exosomes in SGT, hypothesizing that novel diagnostic and therapeutic approaches can be developed by exploring the mechanisms through which exosomes influence tumor occurrence and progression. By understanding these mechanisms, we can leverage exosomes as diagnostic and prognostic biomarkers, and target them for therapeutic interventions. The exploration of exosome-mediated pathways contributing to tumor progression and metastasis could lead to more effective treatments, transforming the management of SGT and improving patient outcomes. Ongoing research aims to elucidate the specific cargo and signaling pathways involved in exosome-mediated tumorigenesis and to develop standardized techniques for exosome-based liquid biopsies in clinical settings. Conclusions: Exosome-based liquid biopsies have shown promise as non-invasive, real-time systemic profiling tools for tumor diagnostics and prognosis, offering significant potential for enhancing patient care through precision and personalized medicine. Methods like fluorescence, electrochemical, colorimetric, and surface plasmon resonance (SPR) biosensors, combined with artificial intelligence, improve exosome analysis, providing rapid, precise, and clinically valid cancer diagnostics for difficult-to-diagnose cancers.

Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing's sarcoma: nomogram and webpage.

The objective of this study was to analyze the incidence and overall survival (OS) of osteosarcoma (OSC) and Ewing's sarcoma (EWS) in a pediatric and adolescent population, employing machine learning (ML) and deep learning (DL) models to predict the likelihood of metastasis. Involving 2465 OSC and 1373 EWS patients aged 0-19 years, from 2004 to 2020. ML techniques-Lasso, Ridge Regression, Elastic Net, and Random Forest-were used alongside a deep learning model based on TensorFlow and Keras, to construct predictive models for metastasis. These models were optimized using grid search with cross-validation and evaluated on their performance metrics, including AUC, sensitivity, and accuracy. The variables' importance in metastasis prediction was determined using SHAP values. Statistical analysis was performed using R software, and an online nomogram was developed for clinical use. The age-adjusted incidence of OSC and EWS from 2004 to 2020 showed a significant uptrend. The deep learning model, iterated 50 times, outperformed the Random Forest model in both loss and accuracy stabilization. The nomogram created demonstrated accurate survival predictions, as evidenced by its calibration curves and the distinction between high and low-risk groups. The increasing trend in age-adjusted incidence of OSC and EWS highlights the need for continued research and improved therapeutic strategies in this domain. The study employed ML and DL models to predict distant metastasis in pediatric and adolescent patients with OSC and EWS, providing a valuable tool for prognosis. The online nomogram developed as a part of this research enhances the models' clinical utility, offering an accessible means for clinicians to predict survival outcomes effectively.

The biological function of extracellular vesicles in prostate cancer and their clinical application as diagnostic and prognostic biomarkers.

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and main causes of cancer-related deaths worldwide. It is characterized by high heterogeneity, ranging from slow-growing tumor to metastatic disease. Since both therapy selection and outcome strongly rely on appropriate patient stratification, it is crucial to differentiate benign from more aggressive conditions using new and improved diagnostic and prognostic biomarkers. Extracellular vesicles (EVs) are membrane-coated particles carrying a specific biological cargo composed of nucleic acids, proteins, and metabolites. Here, we provide an overview of the role of EVs in PCa, focusing on both their biological function and clinical value. Specifically, we summarize the oncogenic role of EVs in mediating the interactions with PCa microenvironment as well as the horizontal transfer of metastatic traits and drug resistance between PCa cells. Furthermore, we discuss the potential usage of EVs as innovative tools for PCa diagnosis and prognosis.

Prognostic aging gene-based score for colorectal cancer: unveiling links to drug resistance, mutation burden, and personalized treatment strategies

ObjectiveColorectal cancer (CRC) is characterized by high incidence and mortality rates worldwide. In this study, we present a novel aging-related gene-based risk scoring system (Aging score) as a predictive tool for CRC prognosis. Method: We identified prognostic aging-related genes using univariate Cox regression analysis, revealing key biological processes in CRC progression. We then constructed a robust prognostic model using LASSO and multivariate Cox regression analyses, including four critical genes: CAV1, FOXM1, MAD2L1, and WT1. Result: The Aging score demonstrated high prognostic performance across the training, testing, and entire TCGA-CRC datasets, proving its reliability. High-risk patients identified by the Aging score had significantly shorter overall survival times than low-risk patients, indicating its potential for patient stratification and personalized treatment. The Aging score remained an independent prognostic factor compared to age, gender, and tumor stage. Additionally, the score was linked to tumor mutation burden and microsatellite instability, indicators of immune checkpoint inhibitor response. High-risk patients also showed higher estimated IC50 values for common chemotherapeutic drugs, suggesting possible treatment resistance. Conclusion: Our findings highlight the Aging score's potential to enhance clinical decision-making and pave the way for personalized CRC management.

The Importance of Proteomics in Saliva and Tears as Potential Non-invasive Methods for Identifying Biomarkers in the Prognosis and Diagnosis of Multiple Sclerosis Patients

: Over the past two decades, the advancement of analytical examinations like proteomics for investigating neuronal-related biomarkers has emerged as one of the most important and effective tools for clinical evaluation and prognosis. However, there remains an unmet need in this area. With advances in quantifying methods and detection in omics research, including proteomics and metabolomics, the close association of the salivary glands and tears with the nervous system has become increasingly evident. As noninvasive specimens, saliva and tears serve as attractive substitutes for neuronal biomarkers, containing numerous proteins and metabolites that represent various ailments in neurodegenerative illnesses like multiple sclerosis (MS). These noninvasive biomarkers might potentially correlate with susceptibility, severity, and pathogenesis of neurological disorders and could be utilized in early diagnosis and prognosis. Therefore, tear and salivary proteomics present novel insights into understanding disease progression and offer personalized treatment options with greater sensitivity. This approach helps highlight the most relevant experimental outcomes related to tear and salivary biomarkers for multiple sclerosis.

The Circulating miR-107 as a Potential Biomarker Up-Regulated in Castration-Resistant Prostate Cancer.

Prostate cancer (PCa) is a prevalent malignancy in men globally. Current diagnostic methods like PSA testing have limitations, leading to overdiagnosis and unnecessary treatment. Castration-resistant prostate cancer (CRPC) emerges in some patients receiving androgen deprivation therapy (ADT). This study explores the potential of circulating microRNA-107 (miR-107) in liquid biopsies as a prognosis tool to differentiate CRPC from non-castration-resistant PCa (NCRPC). We designed a case-control study to evaluate circulating miR-107 in serum as a potential prognosis biomarker. We analyzed miR-107 expression in liquid biopsies and found significantly higher levels (p < 0.005) in CRPC patients, compared to NCRPC. Notably, miR-107 expression was statistically higher in the advanced stage (clinical stage IV), compared to stages I-III. Furthermore, CRPC patients exhibited significantly higher miR-107 levels (p < 0.05), compared to NCRPC. These findings suggest that miR-107 holds promise as a non-invasive diagnostic biomarker for identifying potential CRPC patients.

Biological functions and therapeutic potential of CKS2 in human cancer.

The incidence of cancer is increasing worldwide and is the most common cause of death. Identification of novel cancer diagnostic and prognostic biomarkers is important for developing cancer treatment strategies and reducing mortality. Cyclin-dependent kinase subunit 2 (CKS2) is involved in cell cycle and proliferation processes, and based on these processes, CKS2 was identified as a cancer gene. CKS2 is expressed in a variety of tissues in the human body, but its abnormal expression is associated with cancer in a variety of systems. CKS2 is generally elevated in cancer, plays a role in almost all aspects of cancer biology (such as cell proliferation, invasion, metastasis, and drug resistance) through multiple mechanisms regulating certain important genes, and is associated with clinicopathological features of patients. In addition, CKS2 expression patterns are closely related to cancer type, stage and other clinical variables. Therefore, CKS2 is considered as a tool for cancer diagnosis and prognosis and may be a promising tumor biomarker and therapeutic target. This article reviews the biological function, mechanism of action and potential clinical significance of CKS2 in cancer, in order to provide a new theoretical basis for clinical molecular diagnosis, molecular targeted therapy and scientific research of cancer.

Associative study of maternal genetic variations with preeclampsia in Russian population: SNP-SNP interactions and haplotypes association

Preeclampsia is a pregnancy-associated hypertensive pathology that affects maternal and fetal quality of life. It was linked to several environmental and genetic factors including genetic polymorphisms. This study aimed to study the association, SNP-SNP interactions and haplotypes associations of thrombophilia, folate cycle and hypertension maternal genetic variations with preeclampsia risk in Russian women from Rostov region. 53 pregnant women diagnosed with preeclampsia were compared with 3108 women with relatively healthy pregnancy. DNA was extracted from blood samples and real time allele specific PCR was used for genotyping. MDR analysis was used for SNP-SNP interactions study. According to our data, F5(G1691A) and ITGB3(T1565C) mutant homozygotes were associated with higher risk of preeclampsia. MTRR (A66G) mutant allele (G) was shown as significant preeclampsia risk factor. ADD1 (G1378T) showed significantly higher frequency of mutant allele (T) and mutant homozygote genotype (TT) in preeclampsia patients comparing to control group. MDR showed that this polymorphism has the higher entropy among targeted variations which was confirmed by binary haplotypes association study. We have also examined linkage disequilibrium showing two haploblocks in between the studied genetic variations included MTHFR (C677T) and MTHFR (A1298C) block and AGT (T704C) with AGT (C521T) block. Results suggest several genetic variations and haplotypes as perspective maternal marker for preeclampsia which will contribute to improve prognosis tools and accordingly treatment and prevention possibilities.

XRCC2 driven homologous recombination subtypes and therapeutic targeting in lung adenocarcinoma metastasis

Lung adenocarcinoma (LUAD) is a leading cause of cancer mortality, with many patients facing poor prognosis, particularly those with metastatic or drug-resistant tumors. Homologous recombination genes (HRGs) are crucial in tumor progression and therapy resistance, but their clinical significance in LUAD is not well understood. In this study, we systematically characterize key HRGs in LUAD patients, identifying two distinct HR subtypes associated with different outcomes and biological functions. We establish a 5-gene scoring system (XRCC2, RAD51, BRCA1, FANCA, and CHEK1) that reliably predicts patient outcomes and immunotherapy responses in LUAD. Bioinformatics analysis and clinical validation highlight XRCC2 as a crucial biomarker in LUAD. Functional investigations through in vivo and in vitro experiments reveal the role of XRCC2 in promoting lung cancer migration and invasion. Mechanistically, XRCC2 stabilizes vimentin (VIM) protein expression through deubiquitylation. We predict c-MYC as a potential regulator of XRCC2 and demonstrate that inhibiting c-MYC with compound 10058-F4 reduces XRCC2 and VIM expression. Preclinical studies show the synergistic inhibition of metastasis in vivo when combining 10058-F4 with doxorubicin (Dox). Our findings present a potential personalized predictive tool for LUAD prognosis, identifying XRCC2 as a critical biomarker. The c-Myc-XRCC2-VIM axis emerges as a promising therapeutic target for overcoming lung metastasis. This study provides valuable insights into LUAD, proposing a prognostic tool for further clinical validation and unveiling a potential therapeutic strategy for combating lung metastasis by targeting c-Myc-XRCC2-VIM.

Analysis of individual alpha frequency in a large cohort from a tertiary memory center.

Precise and timely diagnosis is crucial for the optimal use of emerging disease-modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost-effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients. This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting-state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance. IAF was higher in amyloid-negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A-T-N- from the A+T+N+ and A+T-N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38). IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease-modifying treatments.

Plasma-Derived Extracellular Vesicles and Non-Extracellular Vesicle Components from APCMin/+ Mice Promote Pro-Tumorigenic Activities and Activate Human Colonic Fibroblasts via the NF-κB Signaling Pathway.

Colorectal cancer (CRC) is the third most prevalent cancer worldwide. Current studies have demonstrated that tumor-derived extracellular vesicles (EVs) from different cancer cell types modulate the fibroblast microenvironment to contribute to cancer development and progression. Here, we isolated and characterized circulating large EVs (LEVs), small EVs (SEVs) and non-EV entities released in the plasma from wild-type (WT) mice and the APCMin/+ CRC mice model. Our results showed that human colon fibroblasts exposed from APC-EVs, but not from WT-EVs, exhibited the phenotypes of cancer-associated fibroblasts (CAFs) through EV-mediated NF-κB pathway activation. Cytokine array analysis on secreted proteins revealed elevated levels of inflammatory cytokine implicated in cancer growth and metastasis. Finally, non-activated cells co-cultured with supernatant from fibroblasts treated with APC-EVs showed increased mRNA expressions of CAFs markers, the ECM, inflammatory cytokines, as well as the expression of genes controlled by NF-κB. Altogether, our work suggests that EVs and non-EV components from APCMin/+ mice are endowed with pro-tumorigenic activities and promoted inflammation and a CAF-like state by triggering NF-κB signaling in fibroblasts to support CRC growth and progression. These findings provide insight into the interaction between plasma-derived EVs and human cells and can be used to design new CRC diagnosis and prognosis tools.