Frontal hypometabolism in the diagnosis of progressive supranuclear palsy clinical variants

OBJECTIVE

Frontal hypometabolism on FDG-PET is observed in progressive supranuclear palsy (PSP), although it is unclear whether it is a feature of all PSP clinical variants and hence whether it is a useful diagnostic feature. We aimed to compare the frequency, severity, and pattern of frontal hypometabolism across PSP variants and determine whether frontal hypometabolism is related to clinical dysfunction.

METHODS

Frontal hypometabolism in prefrontal, premotor, and sensorimotor cortices was visually graded on a 0-3 scale using CortexID Z-score images in 137 PSP patients. Frontal asymmetry was recorded. Severity scores were used to categorize patients as premotor-predominant, prefrontal-predominant, sensorimotor-predominant, mixed-predominance, or no regional predominance. Frontal ratings were compared across PSP clinical variants, and Spearman correlations were used to assess relationships with the Frontal Assessment Battery (FAB).

RESULTS

97% showed evidence of frontal hypometabolism which was most common (100%) in the speech-language (PSP-SL), corticobasal (PSP-CBS), and frontal (PSP-F) variants and least common in the progressive gait freezing (PSP-PGF) variant (73%). PSP-SL and PSP-CBS showed more severe hypometabolism than Richardson's syndrome (PSP-RS), Parkinsonism (PSP-P), and PSP-PGF. A premotor-predominant pattern was most common in PSP-SL and PSP-CBS, with more mixed patterns in the other variants. Hypometabolism was most commonly asymmetric in PSP-SL, PSP-P, PSP-F and PSP-CBS. Worse hypometabolism in nearly all frontal regions correlated with worse scores on the FAB.

CONCLUSIONS

Frontal hypometabolism is a common finding in PSP, although it varies in severity and pattern across PSP variants and will likely be the most diagnostically useful in PSP-SL and PSP-CBS.

in the Philippines

Blastocystis sp. is a gastrointestinal protozoan commonly encountered in humans and animals. Specificity to certain hosts may be associated with 38 known subtypes (STs) and 8 nonmammalian and avian STs (NMASTs). This can be determined by analyzing ST-host associations, ST-allele data, genetic variability analyses, and fixation index (FST) with sufficient data present. Thus, newly acquired and previously published data on Blastocystis sp. STs and NMASTs from the Philippines were compiled to determine the following: (1) ST-host associations, (2) ST-allele diversity per ST in certain hosts/sources, (3) intrasubtype diversity of certain STs found in different hosts using genetic variability analysis, and (4) comparison of similarities between specific ST populations to determine if these are the same circulating populations using FST. A total of 448 samples subtyped using both sequence-tagged site primers and the 600-bp barcoding region of the Blastocystis sp. SSU rRNA gene were analyzed in this study. Patterns of association for the Philippine samples were similar to those from neighboring Southeast Asian countries and around the world: ST1-ST4 were found in humans but ST3 was the most common, ST5 were found in pigs, and ST6 and ST7 were found in poultry. Blastocystis sp. from humans are mostly the same ST alleles (ST3 allele 34 and ST1 allele 4) while 3-5 ST alleles were found in the most common STs in pigs, macaques, and poultry. Also, ST1, ST3, ST5, and NMAST I are undergoing population expansion according to genetic variability analyses through possible addition of new alleles based on ST-allele diversity. Moreover, FST shows the same circulating population of ST1 in humans, pigs, and water indicating a possible waterborne route of cross-transmission. In contrast, ST3 found in humans possibly come from the same circulating population and is genetically distinct from those in nonhuman sources.

Identification of lung adenocarcinoma subtypes and a prognostic signature based on activity changes of the hallmark and immunologic gene sets

Background

Lung adenocarcinoma (LUAD) has a complex tumor heterogeneity. Our research attempts to clearness LUAD subtypes and build a reliable prognostic signature according to the activity changes of the hallmark and immunologic gene sets.

Methods

According to The Cancer Genome Atlas (TCGA) - LUAD dataset, changes in marker and immune gene activity were analyzed, followed by identification of prognosis-related differential gene sets (DGSs) and their related LUAD subtypes. Survival analysis, correlation with clinical characteristics, and immune microenvironment assessment for subtypes were performed. Moreover, the differentially expressed genes (DEGs) between different subtypes were identified, followed by the construction of a prognostic risk score (RS) model and nomogram model. The tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) of different risk groups were compared.

Results

Two LUAD subtypes were determined according to the activity changes of the hallmark and immunologic gene sets. Cluster 2 had worse prognosis, more advanced tumor and clinical stages than cluster 1. Moreover, a prognostic RS signature was established using two LUAD subtype-related DEGs, which could stratify patients at different risk levels. Nomogram model incorporated RS and clinical stage exerted good prognostic performance in LUAD patients. A shorter survival time and higher TMB were observed in the high-risk patients.

Conclusions

Our findings revealed that our constructed prognostic signature could exactly predict the survival status of LUAD cases, which was helpful in predicting the prognosis and guiding personalized therapeutic strategies for LUAD.

Association of TNFRSF19 with a TNF family-based prognostic model and subtypes in gliomas using machine learning

Purpose

TNF family members (TFMs) play a crucial role in different types of cancers, with TNF Receptor Superfamily Member 19 (TNFRSF19) standing out as a particularly important member in this category. Further research is necessary to investigate the potential impact of TFMs on prognosis prediction and to elucidate the function and potential therapeutic targets linked to TNFRSF19 expression in gliomas.

Methods

Three databases provided the data on gene expression and clinical information. Fourteen prognostic members were found through univariate Cox analysis and subsequently utilized to construct TFMs-based model in LASSO and multivariate Cox analyses. TFMs-based subtypes based on the expression profile were identified using an unsupervised clustering method. Machine learning algorithm identified key genes linked to prognostic model and subtype. A sequence of immune infiltrations was evaluated using the ssGSEA and ESTIMATE algorithms. Immunohistochemistry was used to examine the patterns of expression and the clinical significance of TNFRSF19.

Results

Our development of a prognostic model and subtypes based on the TNF family was successful, resulting in accurate predictions of prognosis. The findings indicate that TNFRSF19 exhibited strong performance. Upregulation of TNFRSF19 was correlated with malignant phenotypes and poor prognosis, which was confirmed through immunohistochemistry. TNFRSF19 played a role in reshaping the immunosuppressive microenvironment in gliomas, and multiple drug-targeted TNFRSF19 molecules were identified.

Conclusions

The TMF-based prognostic model and subtype can facilitate treatment decisions for glioma. TNFRSF19 is an outstanding representative of a predictor of prognosis and immunotherapy effect in gliomas.

Do HER2-Low Tumors Have a Distinct Clinicopathologic Phenotype?

BACKGROUND

Breast cancer subtypes, distinguished by hormone receptor (HR) and HER2 status, have different clinicopathologic features. With recognition of the clinical relevance of HER2-low, there is debate as to whether this is a distinct subtype. Our study aimed to determine whether HER2-low breast cancers have specific clinicopathologic features that differ from those of HER2-negative and HER2-positive cancers.

PATIENTS AND METHODS

A total of 11,072 patients undergoing upfront surgery from 1998 to 2010 were identified from a single-institution prospectively maintained database. HER2 status was classified by immunohistochemistry (IHC)/fluorescence in situ hybridization (FISH) as HER2 negative (41.2%), HER2 low (45%; IHC 1+ or 2+ with negative FISH), and HER2 positive (13.7%), and stratified by HR status. Univariate (UVA) and multivariable multinomial logistic regression analysis (MVA) were performed to determine associations among variables and subtypes.

RESULTS

Compared with HER2-negative tumors, HER2 low was associated with lymphovascular invasion [odds ratio (OR) 1.2, 95% confidence interval (CI) 1.06-1.36; p = 0.003], multifocality (OR 1.26, 95% CI 1.12-1.42; p < 0.001), nodal micrometastasis (OR 1.15, 95% CI 1.02-1.31; p = 0.024), and lower rates of ≥ 3 positive nodes (OR 0.77, 95% CI 0.66-0.90, p = 0.001). When stratified by HR expression, in both HR-positive and HR-negative tumors, age and multifocality were associated with HER2 low on UVA. On MVA, no variables were independently associated with both HR-negative and HR-positive/HER2-low tumors compared with HER2-negative tumors. In contrast, HER2-positive tumors, regardless of HR status, were associated with multifocality and an extensive intraductal component.

CONCLUSION

Clinicopathologic features of HER2-low tumors appear to be primarily related to HR status. Our findings do not support the characterization of HER2 low as a separate subtype.

Macular Neovascularization Type Influence on Anti-VEGF Intravitreal Therapy Outcomes in Age-Related Macular Degeneration

PURPOSE

To evaluate the influence of macular neovascularization (MNV) lesion type on 12-month clinical outcomes in treatment-naive eyes with neovascular age-related macular degeneration (nAMD) treated with anti-VEGF drugs nationwide.

DESIGN

Multicenter national nAMD database observational study.

SUBJECTS

One thousand six hundred six treatment-naive nAMD eyes (1330 patients) undergoing anti-VEGF therapy for 12 months nationwide.

METHODS

Demographics, visual acuity (VA) in logarithm of the minimum angle of resolution letters, number of injections and visits were was collected using a validated web-based tool. Neovascular lesion phenotype was classified as type 1 (T1, n = 711), type 2 (T2, n = 505), type 3 (T3, n = 315), and aneurysmal type 1 (A-T1, n = 75), according to the new proposed consensus classification.

MAIN OUTCOME MEASURES

Mean VA change at 12 months, final VA at 12 months, number of injections, time to lesion inactivation.

RESULTS

A total of 1606 treatment-naive nAMD eyes (1330 patients) received a median of 7 injections over 12 months. Mean (± standard deviation) baseline VA was significantly lower for T2 (49.4 ± 23.5 letters) compared with T1 (57.8 ± 20.8) and T3 (58.2 ± 19.4) (both P < 0.05) lesions. Mean VA change at 12 months was significantly greater for A-T1 (+9.5 letters) compared with T3 (+3.1 letters, P < 0.05). Patients with T3 lesions had fewer active visits (24.9%) than those with other lesion types (T1, 30.5%; T2, 32.6%; A-T1, 27.5%; all P < 0.05). Aflibercept was the most used drug in A-T1 lesions (70.1%) and ranibizumab in T1 (40.7%), T2 (57.7%), and T3 (47.6%) lesions.

CONCLUSIONS

This study highlights the relevance of MNV type on clinical outcomes in nAMD and reports significant differences in baseline VA, VA change, and lesion activity at 12 months. This report provides data about lesion-specific clinical features, which may guide the management of nAMD cases and potentially support personalized clinical decision making for these patients.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Genetic characteristics of Blastocystis sp. in cattle from Hebei Province, China

Blastocystis sp. is a protozoan parasite that infects the intestines of humans and animals, causing chronic diseases such as skin rashes, abdominal pain, and irritable bowel syndrome. A survey was conducted to determine the prevalence and genetic diversity of Blastocystis sp. infection in cattle, in Hebei Province, China. 2746 cattle fecal samples were collected from 11 cities in Hebei Province and analyzed using polymerase chain reaction targeting the Blastocystis sp. barcoding gene. MEGA, PhyloSuite, and PopART were used to analyze the subtype, sequence signature, pairwise genetic distance, and genetic diversity indices. The results showed that the Blastocystis sp. detection rate was 12.60% (346/2746). The infection rate in different herds was affected by region, age, breeding mode, and variety; that is, the infection rates in areas of southern Hebei, cattle under one year old, intensive raising, and dairy cattle were higher than the infection rates in northern Hebei, cattle over one year old, scatter feeding, and beef cattle. Seven Blastocystis subtypes were identified, namely, ST1, ST2, ST5, ST10, ST14, ST21, and ST26; ST10 was the dominant subtype, and ST14 was the second most common subtype. A total of 374 polymorphic and conserved sites were obtained, including 273 invariable (monomorphic) sites and 101 variable (polymorphic) sites, accounting for 27.01% of all nucleotides. The nucleotide diversity index (Pi) was 0.07749, and the haplotype (gene) diversity index (Hd) was 0.946. This study provides the first comprehensive information on the epidemiological situation of Blastocystis sp. infection in cattle from Hebei Province, China, and revealed rich genetic diversity of Blastocystis sp.

Uncovering the subtype-specific disease module and the development of drug response prediction models for glioma

The poor prognosis of glioma patients brought attention to the need for effective therapeutic approaches for precision therapy. Here, we deployed algorithms relying on network medicine and artificial intelligence to design the framework for subtype-specific target identification and drug response prediction in glioma. We identified the driver mutations that were differentially expressed in each subtype of lower-grade glioma and glioblastoma multiforme and were linked to cancer-specific processes. Driver mutations that were differentially expressed were also subjected to subtype-specific disease module identification. The drugs from the drug bank database were retrieved to target these disease modules. However, the efficacy of anticancer drugs depends on the molecular profile of the cancer and varies among cancer patients due to intratumor heterogeneity. Hence, we developed a deep-learning-based drug response prediction framework using the experimental drug screening data. Models for 30 drugs that can target the disease module were developed, where drug response measured by IC50 was considered a response and gene expression and mutation data were considered predictor variables. The model construction consists of three steps: feature selection, data integration, and classification. We observed the consistent performance of the models in training, test, and validation datasets. Drug responses were predicted for particular cell lines derived from distinct subtypes of gliomas. We found that subtypes of gliomas respond differently to the drug, highlighting the importance of subtype-specific drug response prediction. Therefore, the development of personalized therapy by integrating network medicine and a deep learning-based approach can lead to cancer-specific treatment and improved patient care.

The associations of herpes simplex virus and varicella zoster virus infection with dementia: a nationwide retrospective cohort study

BACKGROUND

In this study, the risk of dementia in patients with a history of herpes simplex virus (HSV) or varicella zoster virus (VZV) infection was evaluated.

METHODS

This nationwide cohort study used data from the Korean National Health Insurance Service collected between 2006 and 2017. A total of 752,205 subjects ≥ 45 years of age not diagnosed with dementia until 2006 were included. A multivariate Cox regression model, adjusted for age, sex, and other comorbidities, was used to assess the hazard ratio (HR) for dementia based on VZV or HSV infection. The interaction effects of both viral infections were analysed. Viral infections are classified into four categories: eye, central nervous system (CNS), simple, and complicated. The hazard ratio (HR) of viral infection was analysed based on the type of dementia.

RESULTS

In multivariable analysis, both HSV and VZV infection were associated with an increased risk of dementia (HR = 1.38, 95% confidence interval, CI:1.33-1.43) and (HR = 1.41, 95% CI:1.37-1.46), respectively. Patients who experienced both HSV and VZV infections were also at an increased risk of dementia (HR = 1.57, 95% CI:1.50-1.63). The co-infection group showed the shortest time from viral infection to dementia diagnosis (4.09 ± 3.02 years). In the subgroup analysis, all types of HSV and VZV infections were associated with an increased risk of dementia compared to the non-infection group. The eye, CNS, and complicated VZV infections were associated with a significantly higher risk than simple VZV infections. There were no significant differences between the subtypes of HSV infection. Furthermore, HSV, VSV, and co-infection were associated with an increased risk of all dementia types, including Alzheimer's disease (AD) and vascular dementia (VD).

CONCLUSIONS

Individual HSV and VZV infections were associated with an increased risk of all types of dementia, including AD and VD. Patients co-infected with HSV and VZV, VZV infection in the eye, CNS, or complicated type were more vulnerable to the development of dementia.

among children who have diarrheia or are asymptomatic in Wenzhou, Zhejiang Province, China

Blastocystis sp., a significant zoonotic parasite with a global distribution, was the focus of this study, which aimed to investigate its prevalence and genetic diversity among diarrheic and asymptomatic children in Wenzhou, China. We collected 1,032 fecal samples from Yuying Children's Hospital, Wenzhou, China, comprising 684 from children with diarrhea and 348 from asymptomatic children. Genomic DNA extracted from these samples was used to detect Blastocystis spp. by PCR, targeting the small subunit ribosomal RNA gene. Subsequently, a phylogenetic tree was constructed, applying the maximum likelihood method. Blastocystis spp. were detected in 67 (6.5%) of the fecal samples. The prevalence rate of Blastocystis spp. in diarrheic children (8.8%; 60/684) was significantly higher than that in asymptomatic children (2.0%; 7/348) (χ 2 = 17.3, p < 0.001). Sequence analysis of the SSU rRNA gene identified five known Blastocystis spp. subtypes, ST1 (n = 12), ST2 (n = 5), ST3 (n = 35), ST4 (n = 12), and ST7 (n = 3). ST1 and ST3 were present in both diarrheic and asymptomatic children, while ST2, ST4, and ST7 were exclusive to diarrheic children. Intra-subtype genetic polymorphisms were identified, comprising four variations in ST1 (ST1-1 to ST1-4), five in ST3 (ST3-1 to ST3-5), two in ST4 (ST4-1 and ST4-2), and two in ST7 (ST7-1 and ST7-2). Notably, ST1-2 to ST1-4, ST3-3 to ST3-5, and ST7-1 and ST7-2 represent newly identified variations. The composition and genetic characteristics of subtypes among children in this region suggest various sources of infection, including human-to-human and animal-to-human transmission.

Plasma proteome profiling reveals metabolic and immunologic differences between Anorexia Nervosa subtypes

AIMS/HYPOTHESIS

Anorexia Nervosa (AN) is a severe psychiatric disorder of an unknown etiology with a crude mortality rate of about 5 % per decade, making it one of the deadliest of all psychiatric illnesses. AN is broadly classified into two main subtypes, restricting and binge/purging disorder. Despite extensive research efforts during several decades, the underlying pathophysiology of AN remains poorly understood. In this study, we aimed to identify novel protein biomarkers for AN by performing a proteomics analysis of fasting plasma samples from 78 females with AN (57 restrictive and 21 binge/purge type) and 70 healthy controls.

METHODS

Using state-of-the-art mass spectrometry-based proteomics technology in conjunction with an advanced bioinformatics pipeline, we quantify >500 plasma proteins.

RESULTS

Differential expression analysis and correlation of proteomics data with clinical variables led to identification of a panel of novel protein biomarkers with potential pathophysiological significance for AN. Our findings demonstrate evidence of a humoral immune system response, altered lipid metabolism and potential alteration of plasma cells in AN patients. Additionally, we stratified AN patients based on the quantified proteins and suggest a potential autoimmune nature in the restrictive subtype of AN.

CONCLUSIONS/INTERPRETATION

In summary, on top of biomarkers of AN subtypes, this study provides a comprehensive map of plasma proteins that constitute a resource for further studies of the pathophysiology of AN.

2020 Annual Report of National Clinical Database-Breast Cancer Registry: 10-year mortality of elderly breast cancer patients in Japan

The Japanese Breast Cancer Society initiated the breast cancer registry in 1975, which transitioned to the National Clinical Database-Breast Cancer Registry in 2012. This annual report presents data from 2020 and analyzes the ten-year mortality rates for those aged 65 and older. We analyzed data from 93,784 breast cancer (BC) cases registered in 2020 and assessed 10-year mortality rates for 36,279 elderly patients diagnosed between 2008 and 2012. In 2020, 99.4% of BC cases were females with a median age of 61. Most (65%) were diagnosed at early stages (Stage 0 or I). Breast-conserving surgery rates varied with stages: 58.5% at cStage I, 30.8% at cStage II, and 13.1% at cStage III. Sentinel lymph node biopsy was done in 73.6% of cases, followed by radiotherapy in 70% of those post-conserving surgery and chemotherapy in 21.1% post-surgery. Pathology showed that 63.4% had tumors under 2.0 cm, 11.7% had pTis tumors, and 77.3% had no axillary lymph node metastasis. ER positivity was seen in 75.1%, HER2 in 14.3%, and 30% had a Ki67 positivity rate above 30%. Across all stages and subtypes, there was a trend where the 10-year mortality rates increased for individuals older than 65 years. In Stage I, many deaths were not directly linked to BC and, for those with HER2-type and triple-negative BC, breast cancer-related deaths increased with age. Within Stage II, patients older than 70 years with luminal-type BC often experienced deaths not directly linked to BC, whereas patients below 80 years with HER2-type and triple-negative BC, likely had breast cancer-related deaths. In Stage III, breast cancer-related deaths were more common, particularly in HER2 and triple-negative BC. Our prognostic analysis underscores distinct mortality patterns by stage, subtype, and age in elderly BC patients. It highlights the importance of personalized treatment strategies, considering subtype-specific aggressiveness, age-related factors, and comorbidities.

Signature construction and molecular subtype identification based on liver-specific genes for prediction of prognosis, immune activity, and anti-cancer drug sensitivity in hepatocellular carcinoma

BACKGROUND

Liver specific genes (LSGs) are crucial for hepatocyte differentiation and maintaining normal liver function. A deep understanding of LSGs and their heterogeneity in hepatocellular carcinoma (HCC) is necessary to provide clues for HCC diagnosis, prognosis, and treatment.

METHODS

The bulk and single-cell RNA-seq data of HCC were downloaded from TCGA, ICGC, and GEO databases. Through unsupervised cluster analysis, LSGs-based HCC subtypes were identified in TCGA-HCC samples. The prognostic effects of the subtypes were investigated with survival analyses. With GSVA and Wilcoxon test, the LSGs score, stemness score, aging score, immune score and stromal score of the samples were estimated and compared. The HCC subtype-specific genes were identified. The subtypes and their differences were validated in ICGC-HCC samples. LASSO regression analysis was used for key gene selection and risk model construction for HCC overall survival. The model performance was estimated and validated. The key genes were validated for their heterogeneities in HCC cell lines with quantitative real-time PCR and at single-cell level. Their dysregulations were investigated at protein level. Their correlations with HCC response to anti-cancer drugs were estimated in HCC cell lines.

RESULTS

We identified three LSGs-based HCC subtypes with different prognosis, tumor stemness, and aging level. The C1 subtype with low LSGs score and high immune score presented a poor survival, while the C2 subtype with high LSGs score and immune score indicated an enduring survival. Although no significant survival difference between C2 and C3 HCCs was shown, the C2 HCCs presented higher immune score and stroma score. The HCC subtypes and their differences were confirmed in ICGC-HCC dataset. A five-gene prognostic signature for HCC survival was constructed. Its good performance was shown in both the training and validation datasets. The five genes presented significant heterogeneities in different HCC cell lines and hepatocyte subclusters. Their dysregulations were confirmed at protein level. Furthermore, their significant associations with HCC sensitivities to anti-cancer drugs were shown.

CONCLUSIONS

LSGs-based HCC subtype classification and the five-gene risk model might provide useful clues not only for HCC stratification and risk prediction, but also for the development of more personalized therapies for effective HCC treatment.

Exploring the importance of m5c in the diagnosis and subtype classification of COPD using the GEO database

BACKGROUND

5-Methylcytosine (m5C) is an mRNA modifier that is associated with the occurrence and development of viral infection, pulmonary fibrosis, lung cancer, and other diseases. However, the role of m5C regulators in chronic obstructive pulmonary disease (COPD) remains unknown.

METHODS

In this study, by analysing the GSE42057 dataset, the differential expression of m5c regulators in the COPD group and control group was obtained, and a correlation analysis was conducted. The random forest model and support vector machine model were used to predict the occurrence of COPD. A nomogram model was also constructed to predict the prevalence of COPD. The COPD patients were divided into subtypes by consistent cluster analysis based on m5c methylation regulators. Immune cell infiltration was performed on the m5c methylation subtypes. Differentially expressed genes (DEGs) between m5c methylation subtypes were screened, and the DEGs were analysed by Gene Ontology (GO) Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, we verified the expression of several m5C regulators and related pathways using a COPD cell model.

RESULTS

Seven m5c methylation regulators were differentially expressed. The random forest model based on the above genes was the most accurate for predicting the occurrence of COPD. A nomogram model based on the above genes could also accurately predict the prevalence of COPD, and the implementation of these models could benefit COPD patients. The consistent cluster analysis divided the COPD patients into two subtypes (Cluster A and Cluster B). The main component analysis algorithm determined the m5c methylation subtypes and found that patients in Cluster A had a higher m5c score than those in Cluster B. GO analysis of the DEGs between the m5c methylation COPD patient subtypes revealed that DEGS were mainly enriched in leukocyte-mediated immunity and regulation of T-cell activation. KEGG analysis revealed that DEGS were mainly enriched in Th1 and Th2 cell differentiation, neutrophil extracellular trap formation, and the NF-κB signalling pathway. Immunocyte correlation analysis revealed that Cluster B was associated with neutrophil- and macrophage-mediated immunity, while Cluster A was associated with CD4 + T-cell- and CD8 + T-cell-mediated immunity. Cell experiments have also verified some of the above research results.

CONCLUSION

The diagnosis and subtype classification of COPD patients based on m5c regulators may provide a new strategy for the diagnosis and treatment of COPD.

Irritable Bowel Syndrome Associated with Blastocystis hominis or Without Relationship to It? A Case-Control Study and Minireview

BACKGROUND

Blastocystis hominis (B. hominis) is a protozoan parasite that has a worldwide distribution. Some studies have suggested a link between B. hominis and the development of irritable bowel syndrome (IBS). The objective of this study was to determine the prevalence of B. hominis in patients with IBS compared to healthy individuals.

MATERIAL AND METHODS

A total of 65 stool samples from patients with IBS and 65 samples from healthy individuals in northern Iran were examined. The samples were tested using various methods including direct smear, formalin ether sedimentation and culture to detect the presence of B. hominis. Additionally, polymerase chain reaction (PCR) was performed on all culture-positive isolates to confirm the results and identify the genotype.

RESULTS

B. hominis was detected in 15.38% of IBS patients and 9.2% of the healthy group. The culture in RPMI1640 was found to be better than the formalin ether and direct smear methods. Positive samples were confirmed using the molecular method. No significant difference was observed in the order of B. hominis infection between the two groups.

CONCLUSIONS

The results of our study indicate that no significant difference was observed in the order of B. hominis infection between IBS patients and healthy groups. Therefore, further study is necessary to determine the potential pathogenic effects of this parasite and its role in causing IBS.

Genetics of Parkinson's disease heterogeneity: A genome-wide association study of clinical subtypes

INTRODUCTION

Substantial heterogeneity between individual patients in the clinical presentation of Parkinson's disease (PD) has led to the classification of distinct PD subtypes. However, genetic susceptibility factors for specific PD subtypes are not well understood. Therefore, the present study aimed to investigate the genetics of PD heterogeneity by performing a genome-wide association study (GWAS) of PD subtypes.

METHODS

A total of 799 PD patients were included and classified into tremor-dominant (TD) (N = 345), akinetic-rigid (AR) (N = 227), gait-difficulty (GD) (N = 82), and mixed (MX) (N = 145) phenotypic subtypes. After array genotyping and subsequent imputation, a total of 7,918,344 variants were assessed for association with each PD subtype using logistic regression models that were adjusted for age, sex, and the top five principal components of GWAS data.

RESULTS

We identified one genome-wide significant association (P < 5 × 10-8), which was between the MIR3976HG rs7504760 variant and the AR subtype (Odds ratio [OR] = 6.12, P = 2.57 × 10-8). Suggestive associations (P < 1 × 10-6) were observed regarding TD for RP11-497G19.3/RP11-497G19.1 rs7304254 (OR = 3.33, P = 3.89 × 10-7), regarding GD for HES2 rs111473931 (OR = 3.18, P = 6.85 × 10-7), RP11-400D2.3/CTD-2012I17.1 rs149082205 (OR = 8.96, P = 9.08 × 10-7), and RN7SL408P/SGK1 rs56161738 (OR = 2.97, P = 6.19 × 10-7), and regarding MX for MMRN2 rs112991171 (OR = 4.98, P = 1.02 × 10-7).

CONCLUSION

Our findings indicate that genetic variation may account for part of the clinical heterogeneity of PD. In particular, we found a novel genome-wide significant association between MIR3976HG variation and the AR PD subtype. Replication of these findings will be important in order to better define the genetic architecture of clinical variability in PD disease presentation.

Prevalence of S. aureus and/or MRSA in hospitalized patients with diabetic foot and establishment of LAMP methods for rapid detection of the SCCmec gene

BACKGROUND

Patients with diabetic feet are prone to be infected due to the impaired immune system. However, the prognostic outcome of different microbial infections remains controversial. Identification and rapid screening of the pathogenic microorganisms that pose the greatest threat to the prognosis of patients with diabetic foot infections (DFIs) is critical.

METHODS

Clinical data were statistically analyzed, which were obtained from 522 patients with DFIs, including pathogenic bacterial culture results and treatment outcomes at the last return visit. In addition, a loop-mediated isothermal amplification (LAMP) detection method was developed to identify the prevalent subtype of methicillin-resistant Staphylococcus aureus (MRSA) in DFIs patients. This study was approved by the Ethics Committee of Nanfang Hospital (NFEC-202012-K6) and registered on ClinicalTrials.gov (NCT04916457) on June 1, 2021.

RESULTS

We found that the proportion of patients with infections of Staphylococcus aureus (S. aureus) and MRSA was 27.7% (145/522) and 33.7% (49/145), respectively. Additionally, the incidence of osteomyelitis was 46.9% (23/49) and amputation/disability was 40.8% (20/49) in patients with MRSA infection, which were significantly higher compared to patients with other types of bacterial infections such as methicillin-susceptible Staphylococcus aureus (MSSA). Notably, we demonstrated that the main prevalent subtype of MRSA in DFIs patients in our hospital was Staphylococcal chromosomal cassettes mec (SCCmec) type II. In addition, it only takes 1.5 h to complete the entire experimental procedure in this LAMP assay, providing high sensitivity (100%) and specificity (77.8%) in hospitalized patients with DFIs.

CONCLUSIONS

We demonstrated there is a very high rate of MRSA isolation in patients with DFIs and revealed that patients infected with MRSA are at a higher risk of developing osteomyelitis, and amputation or disability. Importantly, we have developed a method for quickly screening newly admitted patients for MRSA.

[Comparison of Different Doses of ACTH Used in ACTH Stimulation Test to Determine the Subtypes of Primary Aldosteronism]

Objective

To compare the diagnostic value of adrenocorticotropic hormone (ACTH) stimulation test (AST) with different doses of ACTH combined with midnight administration of 1 mg dexamethasone for the determination of the subtypes of primary hyperaldosteronism (PA).

Methods

This is a prospective observational study. Patients diagnosed with PA in the Department of Endocrinology, the First Medical Center of of Chinese PLA General Hospital from January 1, 2020 to September 30, 2022 underwent AST with different doses of ACTH. All patients received 1 mg dexamethasone at midnight for inhibition. Then, the patients were randomly assigned to 25-unit and 50-unit ACTH treatment groups by a ratio of 1:2. Subtype classification and diagnosis of aldosterone-producing adenoma (APA) and idiopathic hyperaldosteronism (IHA) was made on the basis of adrenal venous blood samples and/or postoperative pathology and clinical follow-up findings. Receiver operating characteristics (ROC) curves were plotted to examine the diagnostic efficacy and the difference of AST by varying doses of ACTH in distinguishing APA and IHA.

Results

A total of 82 patients, including 49 patients with APA (59.8%) and 33 patients with IHA (40.2%), were enrolled. There were 29 patients in the 25-unit ACTH group (35.4%) and 53 patients in the 50-unit ACTH group (64.6%). There were no significant differences in age, sex, blood pressure, minimum serum potassium, and biochemical parameters between the 25-unit and 50-unit groups. After ACTH stimulation, plasma aldosterone concentration (PAC), cortisol (F), and PAC/F at different points of time showed no statistical difference between the two groups (P>0.05). The area under the curve (AUC) of PAC in the 25-unit group was higher than that of PAC/F. The AUC of PAC reached the maximum at 90 minutes (0.948, 95% confidence interval [CI]: 0870-1.000) and the optimal cutoff was 38.0 ng/dL, which had a sensitivity of 92.9% and a specificity of 86.7% for differentiating APA and IHA. Similar to the 25-unit group, the maximum AUC of PAC in the 50-unit group was greater than that of PAC/F. The AUC of PAC reached the maximum 90 minutes (0.930, 95% CI: 0.840-0.994) and the optimal cutoff was 39.6 ng/dL, which had a sensitivity of 91.2% and a specificity of 83.3%. The AUC of PAC at different points of time in the 25-unit ACTH group (0.862-0.948) was greater than that of 50-unit ACTH group (0.823-0.930), but the difference was not statistical significance.

Conclusion

AST with 25-unit or 50-unit ACTH combined with small-dose dexamethasone can be used in PA subtype determination, ie, differentiation between APA and IHA. The optimal PAC cut-off values for 25-unit or 50-unit ACTH are similar, being 38.0 ng/dL and 39.6 ng/dL, respectively, and both cutoff values show higher sensitivity and specificity at 90 min. The AST with 25-unit ACTH has the smaller dose and the better safety. Therefore, it is recommended for the diagnosis of PA subtypes.

Robustly uncovering the heterogeneity of neurodegenerative disease by using data-driven subtyping in neuroimaging: A review

Neurodegenerative diseases are associated with heterogeneity in genetics, pathology, and clinical manifestation. Understanding this heterogeneity is particularly relevant for clinical prognosis and stratifying patients for disease modifying treatments. Recently, data-driven methods based on neuroimaging have been applied to investigate the subtyping of neurodegenerative disease, helping to disentangle this heterogeneity. We reviewed brain-based subtyping studies in aging and representative neurodegenerative diseases, including Alzheimer's disease, mild cognitive impairment, frontotemporal dementia, and Lewy body dementia, from January 2000 to November 2022. We summarized clustering methods, validation, robustness, reproducibility, and clinical relevance of 71 eligible studies in the present study. We found vast variations in approaches between studies, including ten neuroimaging modalities, 24 cluster algorithms, and 41 methods of cluster number determination. The clinical relevance of subtyping studies was evaluated by summarizing the analysis method of clinical measurements, showing a relatively low clinical utility in the current studies. Finally, we conclude that future studies of heterogeneity in neurodegenerative disease should focus on validation, comparison between subtyping approaches, and prioritise clinical utility.

parvum IIdA24G2 subtype in dairy cattle in China

Cryptosporidium is an important gastrointestinal parasite that can cause mild to severe diarrhea in various vertebrates, including humans and domestic animals. Infection is prevalent in dairy cattle, particularly calves, resulting in diarrhea and increased mortality with significant production losses. However, the prevalence and identity of Cryptosporidium spp. in cattle in Heilongjiang Province is still poorly known. Our study aimed to investigate the prevalence and species and subtype distribution of Cryptosporidium in cattle in the region. In addition, we evaluated the zoonotic potential of Cryptosporidium isolates and assessed possible transmission routes and health effects of this organism. We collected 909 fecal samples from five different farms in Heilongjiang Province between August and September 2022. The samples underwent Cryptosporidium detection by nested PCR and small subunit (SSU) rRNA gene sequence analysis. Four Cryptosporidium species were identified, including C. parvum, C. bovis, C. ryanae, and C. andersoni, with an overall prevalence of 4.4% (40/909). Based on sequence analysis of the 60 kDa glycoprotein gene of C. parvum and C. bovis, three subtypes of C. parvum were identified, namely two previously known subtypes (IIdA19G1 and IIdA20G1), and one novel subtype (IIdA24G2). Two distinct subtype families were identified in C. bovis (XXVId and XXVIe). The high diversity of Cryptosporidium in dairy cattle and the emergence of a novel subtype of C. parvum in Heilongjiang Province suggest that dairy cattle may serve as a significant source of zoonotic cryptosporidiosis infection in this region.

Detection and molecular characterization of Cryptosporidium spp. in dairy calves in Lisbon and Tagus Valley, Portugal

Cryptosporidium is a protozoan parasite with worldwide distribution, infecting a wide range of hosts with some zoonotic species. Calves have been identified as one of the most common reservoirs of this parasite. However, little is known about the genetics of Cryptosporidium in calves in Portugal. This study aimed to molecularly characterize infections of Cryptosporidium in pre-weaned calves from the Lisbon and Tagus Valley (LTV) in Portugal. Fifty-two samples were collected from calves from eight dairy and two beef farms in LTV, Portugal. Cryptosporidium oocysts were detected by Modified Ziehl-Neelsen staining (MZN) and direct immunofluorescent assay (DFA). MZN and DFA revealed the presence of Cryptosporidium oocysts in 40.4% (21/52) and 67.3% (35/52) samples, respectively. Positive samples were analyzed by PCR-RFLP of the 18 s rRNA gene for species identification. DNA amplification of the 18S rRNA gene was successful for 88.6% (31/35) of samples. Cryptosporidium parvum was identified in 96.8% (30/31) of the samples, and from one sample Cryptosporidium bovis was identified. Cryptosporidium parvum positive samples were subtyped by sequencing the PCR product of a partial fragment of the 60 kDa glycoprotein (gp60) gene. Subtype analysis of the C. parvum isolates revealed that all isolates belonged to subtype family IIa. Four subtypes were recognized within this subtype family, including the hyper-transmissible IIaA15G2R1 subtype that is the most frequently reported worldwide (27/30), IIaA14G2R1 (1/30), IIaA16G2R1 (1/30) and IIaA19G2R1 (1/30). To our knowledge, this is the first report of C. bovis, and C. parvum subtypes IIaA14G2R1 and IIaA19G2R1 in cattle in LTV, Portugal. The presence of the zoonotic C. parvum subtype in this study suggests that pre-weaned calves are likely to be a significant reservoir of zoonotic C. parvum, highlighting the importance of animal-to-human infection transmission risk. Further molecular studies are required to better understand the epidemiology of cryptosporidiosis in Portugal.

Preoperative Prediction of Meningioma Subtype by Constructing a Clinical-Radiomics Model Nomogram Based on Magnetic Resonance Imaging

OBJECTIVE

We sought to investigate the value of a clinical-radiomics model based on magnetic resonance imaging in differentiating fibroblastic meningiomas from non-fibroblastic meningiomas.

METHODS

Clinical, imaging, and postoperative pathologic data of 423 patients (128 fibroblastic meningiomas and 295 non-fibroblastic meningiomas) were randomly categorized into training (n = 296) and validation (n = 127) groups at a 7:3 ratio. The Selectpercentile and LASSO were used to selected the highly correlated features from 3376 radiomics features. Different classifiers were used to train and verify the model. The receiver operating characteristic curves, accuracy (ACC), sensitivity (SEN), and specificity (SPE) were drawn to evaluate the performance. The optimal radiomics model was selected. Calibration curves and decision curve analysis were used to verify the clinical utility and consistency of the nomogram constructed from the radiomics features and clinical factors.

RESULTS

Thirteen radiomics features were selected from contrast-enhanced T1-weighted imaging and T2-weighted imaging after dimensionality reduction. The prediction performance of random forest radiomics model is slightly lower than that of the clinical-radiomics model. The area under the curve, SEN, SPE, and ACC of the clinical-radiomics model training set were 0.836 (95% confidence interval, 0.795-0.878), 0.922, 0.583, and 0.686, respectively. The area under the curve, SEN, SPE, and ACC of the validation set were 0.756 (95% confidence interval, 0.660-0.846), 0.816, 0.596, and 0.661, respectively.

CONCLUSIONS

The diagnostic efficacy of the clinical-radiomics model of fibroblastic meningioma and non-fibroblastic meningioma was better than that of the radiomics prediction model alone and can be used as a potential tool for clinical surgical planning and evaluation of patient prognosis.

Prevalence and clinical outcomes in subtypes of metabolic associated fatty liver disease

BACKGROUND/PURPOSE

In 2020, metabolic Associated Fatty Liver Disease (MAFLD) was proposed to replace non-alcoholic fatty liver disease (NAFLD) with new diagnostic criteria. The prevalence and clinical outcomes of MAFLD subtypes remained unclear.

METHODS

The participants from Taiwan bio-bank cohort were included. MAFLD was defined as the presence of fatty liver, plus any of the following three conditions: overweight/obesity, diabetes mellitus (DM), or metabolic dysfunction. The patients with positive HBsAg or anti-HCV were considered as chronic HBV or HCV infection. NAFLD fibrosis score (NFS) > 0.676 plus fibrosis 4 (FIB-4) score > 2.67 was defined as advanced liver fibrosis. Atherosclerosis was diagnosed as having carotid plaques on duplex ultrasounds. The clinical outcomes were assessed among four subtypes of MAFLD including DM, obesity, chronic HBV infection, and chronic HCV infection.

RESULTS

A total of 21,885 participants (mean age 55.34 ± 10.31; 35.69% males) were included in the final analysis. Among them, 38.83% were diagnosed with MAFLD. The prevalence of MAFLD was 66.95% in DM patients, 65.07% in obese participants, 33.74% in chronic HBV patients, and 30.23% in chronic HCV patients. Logistic regression analysis showed that the subtypes of DM and chronic HCV infection were associated with an increased risk of advanced liver fibrosis in MAFLD patients. Additionally, the subtypes of DM and lean were associated with an increased risk of atherosclerosis, but a decreased risk of atherosclerosis in the subtype of chronic HBV infection.

CONCLUSION

This population-based study proves the concept that subtypes of MAFLD can help risk stratification of clinical outcomes.

Genomic analysis and filtration of novel prognostic biomarkers based on metabolic and immune subtypes in pancreatic cancer

PURPOSE

Patients with pancreatic cancer (PC) can be classified into various molecular subtypes and benefit from some precise therapy. Nevertheless, the interaction between metabolic and immune subtypes in the tumor microenvironment (TME) remains unknown. We hope to identify molecular subtypes related to metabolism and immunity in pancreatic cancer METHODS: Unsupervised consensus clustering and ssGSEA analysis were utilized to construct molecular subtypes related to metabolism and immunity. Diverse metabolic and immune subtypes were characterized by distinct prognoses and TME. Afterward, we filtrated the overlapped genes based on the differentially expressed genes (DEGs) between the metabolic and immune subtypes by lasso regression and Cox regression, and used them to build risk score signature which led to PC patients was categorized into high- and low-risk groups. Nomogram were built to predict the survival rates of each PC patient. RT-PCR, in vitro cell proliferation assay, PC organoid, immunohistochemistry staining were used to identify key oncogenes related to PC RESULTS: High-risk patients have a better response for various chemotherapeutic drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) database. We built a nomogram with the risk group, age, and the number of positive lymph nodes to predict the survival rates of each PC patient with average 1-year, 2-year, and 3-year areas under the curve (AUCs) equal to 0.792, 0.752, and 0.751. FAM83A, KLF5, LIPH, MYEOV were up-regulated in the PC cell line and PC tissues. Knockdown of FAM83A, KLF5, LIPH, MYEOV could reduce the proliferation in the PC cell line and PC organoids CONCLUSION: The risk score signature based on the metabolism and immune molecular subtypes can accurately predict the prognosis and guide treatments of PC, meanwhile, the metabolism-immune biomarkers may provide novel target therapy for PC.

Molecular evaluation of Cryptosporidium spp. in sheep in southern Xinjiang, China

Cryptosporidium spp. are diarrheagenic intestinal parasites with multiple hosts worldwide. A total of 1252 fresh fecal samples of sheep were collected from 10 large-scale farms in southern Xinjiang. Based on the small subunit ribosomal (SSU rRNA) gene of Cryptosporidium, 100 Cryptosporidium-positive samples (8.0%, 100/1252) were detected by PCR. Nine out of 10 farms were positive for Cryptosporidium, with the highest infection rate being 18.4% (23/125) on farm 9 in Qira. The infection rates of Cryptosporidium in pre-weaned lambs, weaned lambs, fattening sheep, and adult sheep were 20.3% (61/301), 10.3% (34/329), 0.9% (3/327), and 0.7% (2/295), respectively. Three Cryptosporidium species were identified, namely, C. xiaoi (n = 61), C. parvum (n = 22), and C. ubiquitum (n = 17). Of them, C. xiaoi was detected on all positive farms and in different age groups of sheep. The subtypes of C. parvum and C. ubiquitum were identified by PCR at the 60 kDa glycoprotein (gp60) gene. Two C. parvum subtypes were identified: IIdA19G1 (n = 21) and IIdA15G1 (n = 1). One C. ubiquitum subtype was identified with XIIa (n = 17). These results indicated the common transmission and genetic diversity of Cryptosporidium in sheep in southern Xinjiang, and further investigations are needed on the zoonotic potential of C. parvum and C. ubiquitum in this region.

Current status of GABA receptor subtypes in analgesia

Gamma-aminobutyric acid (GABA), a non-protein-producing amino acid synthesized from the excitatory amino acid glutamate via the enzyme glutamic acid decarboxylase, is extensively found in microorganisms, plants and vertebrates, and is abundantly expressed in the spinal cord and brain. It is the major inhibitory neurotransmitter in the mammalian nervous system. GABA plays crucial roles in the regulation of synaptic transmission, the promotion of neuronal development and relaxation, and the prevention of insomnia and depression. As the major inhibitory neurotransmitter, GABA plays pivotal roles in the regulation of pain sensation, which is initiated by the activation of peripheral nociceptors and transmitted to the spinal cord and brain along nerves. GABA exerts these roles by directly acting on three types of receptors: ionotropic GABAA and GABAC receptors and G protein-coupled GABAB receptor. The chloride-permeable ion channel receptors GABAA and GABAC mediate fast neurotransmission, while the metabotropic GABAB receptor mediates slow effect. Different GABA receptors regulate pain sensation via different signaling pathways. Here we highlight recent updates on the involvement of specific GABA receptors and their subtypes in the process of pain sensation. Further understanding of different GABA receptors and signaling pathways in pain sensation will benefit the development of novel analgesics for pain management by targeting specific GABA receptor subtypes and signaling pathways.

Tumor biology, immune infiltration and liver function define seven hepatocellular carcinoma subtypes linked to distinct drivers, survival and drug response

BACKGROUND & AIMS

Tumor heterogeneity is jointly determined by the components of the tumor ecosystem (TES) including tumor cells, immune cells, stromal cells, and non-cellular components. We aimed to identify subtypes using TES-related genes and determine subtype specific drivers and treatments for hepatocellular carcinoma (HCC).

METHODS

We collected 68 genesets depicting tumor biology, immune infiltration, and liver function, totaling 2831 genes, and collected mRNA profiles and clinical data for over 6000 tumors from 65 datasets in the GEO, TCGA, ICGC, and several other databases. We designed a three-step clustering pipeline to identify subtypes. The microenvironment, genomic alteration, and drug response differences were systematically compared among subtypes.

RESULTS

Seven subtypes (TES-1/2/3/4/5/6/7) were revealed in 159 tumors from the CHCC-HBV cohort. We constructed a single sample classifier using paired genes (sscpgsTES). TES subtypes were significantly associated with multiple clinical variables including etiology, and survival in 14 of 17 cohorts and the meta-cohort. TES-1 had the poorest prognosis and highest proliferation level. Both TES-2 and TES-7 were immune-enriched, however, TES-2 had a significantly worse prognosis, and hypoxic and immunosuppressive microenvironment. TES-4 had activated Wnt pathway, driven by CTNNB1 mutation. Good prognosis TES-6 exhibited the best differentiation. TES-5 and TES-3 were considered as novel subclasses by comparing with ten previous subtyping systems. TES-5 tumors had high AFP but good overall survival, and ∼45% of them harbored AXIN1 mutation. TES-3 was immune and stromal desert, may be driven by high copy number alteration burden, and had the poorest response to immune checkpoint inhibitor. TES-1 and TES-2 had significantly lower response to transarterial chemoembolization, but they showed significantly higher sensitivity to compound YM-155.

CONCLUSIONS

Tumor ecosystem subtypes expand existing HCC subtyping systems, have distinct drivers, prognosis, and treatment vulnerabilities.

Attenuated niacin response is associated with a subtype of first-episode drug-naïve psychosis characterized as serious negative symptoms

Although the phenomenon of attenuated niacin response (ANR) has been widely replicated in some patients with first-episode psychosis (FEP), its relevance to the negative symptoms (NS) of psychosis remains unclear. Total of 240 patients with drug-naïve FEP and 101 healthy controls (HCs) were recruited, and 209 were followed up for 1 year. Psychotic symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS), and niacin-induced responses were measured using laser Doppler flowmetry. We calculated the log-transform EC50 [concentration of methyl nicotinate required to elicit a half-maximal blood flow (MBF) response] and MBF values. Core-NS was generated by factor analysis of the PANSS-NS subscale and cluster analysis to produce subtypes. Significant differences were found in the log10 (EC50) values between the FEP and HC groups (p < 0.001), supporting the ANR in patients with FEP. A higher NS severity was found in the ANR subgroup than that in other patients. Factor analysis determined that a two-dimensional model included core NS and rigidity of thinking. The log10 (EC50) value was significantly associated with only the core NS. Cluster analysis revealed three subtypes-36.7% (cluster-1, n = 88), 16.7% (cluster-2, n = 40), and 46.7% (cluster-3, n = 112). Cluster-2 characterized by extensive NS appeared to have a more remarkable ANR and less symptomatic improvement than those with other clusters during follow-up. No significant changes were found in the niacin response trajectories between the baseline and follow-up. Our findings indicate a significant correlation between ANR and core NS in patients with FEP. ANR may be a potential biomarker for certain subtypes with NS-dominated characteristics and poor symptomatic remission.

Metabolomic profiles of intact tissues reflect clinically relevant prostate cancer subtypes

BACKGROUND

Prostate cancer (PC) is a heterogenous multifocal disease ranging from indolent to lethal states. For improved treatment-stratification, reliable approaches are needed to faithfully differentiate between high- and low-risk tumors and to predict therapy response at diagnosis.

METHODS

A metabolomic approach based on high resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) analysis was applied on intact biopsies samples (n = 111) obtained from patients (n = 31) treated by prostatectomy, and combined with advanced multi- and univariate statistical analysis methods to identify metabolomic profiles reflecting tumor differentiation (Gleason scores and the International Society of Urological Pathology (ISUP) grade) and subtypes based on tumor immunoreactivity for Ki67 (cell proliferation) and prostate specific antigen (PSA, marker for androgen receptor activity).

RESULTS

Validated metabolic profiles were obtained that clearly distinguished cancer tissues from benign prostate tissues. Subsequently, metabolic signatures were identified that further divided cancer tissues into two clinically relevant groups, namely ISUP Grade 2 (n = 29) and ISUP Grade 3 (n = 17) tumors. Furthermore, metabolic profiles associated with different tumor subtypes were identified. Tumors with low Ki67 and high PSA (subtype A, n = 21) displayed metabolite patterns significantly different from tumors with high Ki67 and low PSA (subtype B, n = 28). In total, seven metabolites; choline, peak for combined phosphocholine/glycerophosphocholine metabolites (PC + GPC), glycine, creatine, combined signal of glutamate/glutamine (Glx), taurine and lactate, showed significant alterations between PC subtypes A and B.

CONCLUSIONS

The metabolic profiles of intact biopsies obtained by our non-invasive HR MAS NMR approach together with advanced chemometric tools reliably identified PC and specifically differentiated highly aggressive tumors from less aggressive ones. Thus, this approach has proven the potential of exploiting cancer-specific metabolites in clinical settings for obtaining personalized treatment strategies in PC.

[Molecular detection and subtyping of Blastocystis sp. in pigs in Anhui Province]

OBJECTIVE

To investigate the prevalence and subtype distribution of Blastocystis sp. in pigs in Anhui Province.

METHODS

A total of 500 stool samples were collected from large-scale pig farms in Bozhou, Anqing, Chuzhou, Hefei, Fuyang, and Lu'an cities in Anhui Province from October to December 2015. Blastocystis was detected in pig stool samples using a PCR assay based on the small subunit ribosomal RNA (SSU rRNA) gene, and positive samples were subjected to sequencing and sequence analysis. Blastocystis subtypes were characterized in the online PubMLST database, and verified using phylogenetic tree created with the neighbor-joining algorithm in the Meta software.

RESULTS

The prevalence of Blastocystis infection was 43.2% (216/500) in pigs in 6 cities of Anhui Province, and all pig farms were tested positive for Blastocystis. There was a region-specific prevalence rate of Blastocystis (17.2% to 50.0%) (χ2 = 26.084, P < 0.01), and there was a significant difference in the prevalence of Blastocystis sp. among nursery pigs (39.6%), preweaned pigs (19.1%), and growing pigs (62.3%) (χ2 = 74.951, P < 0.01). Both online inquiry and phylogenetic analysis revealed ST1, ST3, and ST5 subtypes in pigs, with ST5 as the predominant subtype.

CONCLUSIONS

The prevalence of Blastocystis sp. is high in pigs in Anhui Province, with three zoonotic subtypes identified, including ST1, ST3, and ST5.

A prospective cohort study of familial versus sporadic essential tremor cases: Do clinical features evolve differently across time?

BACKGROUND

Although essential tremor (ET) is often divided into familial and sporadic cases, few data compare the evolution of clinical features in these groups over time. Leveraging data from a prospective, longitudinal study, we present analyses of the evolution of a broad range of cognitive, motor (i.e., tremor, tandem gait) and other features (e.g., disability) of ET.

METHODS

Sixty-six familial and 23 sporadic ET cases completed in-home evaluations at baseline and 18, 36, and 54-month follow-ups. Assessments included detailed neuropsychological testing and videotaped neurological examinations. Analyses compared the longitudinal course of 16 clinical features in familial and sporadic cases.

RESULTS

Baseline mean age was 75.2 ± 8.8 years and mean observation period was 4.7 ± 0.3 years. Tremor onset age was lower and childhood onset more common in familial than sporadic cases (p's = 0.02). Longitudinal analyses revealed no significant differences between clinical features displayed by familial and sporadic cases, or differences between the patterns of change in clinical features observed in these groups across time. Sporadic cases' daily activity skills declined significantly, whereas familial cases' did not, p's = 0.04 and 0.34, respectively; however, this finding was non-significant when controlling for false discovery rate. Several additional non-significant trends were noted.

CONCLUSION

Familial and sporadic ET cases differed in onset age, and in the prevalence of childhood tremor onset. Although a number of interesting trends were observed, no significant differences in the evolution of clinical features over time in patients with and without a family history of ET were revealed.

Is adjustment disorder genetically correlated with depression, anxiety, or risk-tolerant personality trait?

Adjustment disorder has three main subtypes: adjustment disorder with depressed mood, adjustment disorder with anxiety, and adjustment disorder with disturbance of conduct. The disorder is moderately heritable and has lifetime comorbidities with major depressive disorder (MDD), anxiety disorders, or risk-tolerant personality. However, it remains unclear whether the degrees of genetic correlations between adjustment disorder and other psychiatric disorders and intermediate phenotypes are similar or different to those between MDD, anxiety disorders or risk-tolerant personality and these other psychiatric disorders and intermediate phenotypes. To compare patterns of genetic correlations, we utilized large-scale genome-wide association study summary statistics for adjustment disorder-related disorders and personality trait, eleven other psychiatric disorders and fifteen intermediate phenotypes. Adjustment disorder had highly positive genetic correlations with MDD, anxiety disorders, and risk-tolerant personality. Among other psychiatric disorders, adjustment disorder, MDD, anxiety disorders and risk-tolerant personality were positively correlated with risks for schizophrenia (SCZ), bipolar disorder (BD), SCZ + BD, attention-deficit/hyperactivity disorder, and cross disorders. In contrast, adjustment disorder was not significantly correlated with risks for obsessive-compulsive disorder, Tourette syndrome, or posttraumatic stress disorder despite significant genetic correlations of MDD or anxiety disorders with these disorders. Among intermediate phenotypes, adjustment disorder, MDD, anxiety disorders, and risk-tolerant personality commonly had a younger age at first sexual intercourse, first birth, and menopause, lower cognitive ability, and higher rate of smoking initiation. Adjustment disorder was not genetically correlated with extraversion, although the related disorder and personality were correlated with extraversion. Only adjustment disorder was correlated with a higher smoking quantity. These findings suggest that adjustment disorder could share a genetic etiology with MDD, anxiety disorders and risk-tolerant personality trait, as well as have a disorder-specific genetic etiology.

Delirium and Delirium Prevention in the Emergency Department

This article covers the epidemiology of delirium and the overlapping condition of altered mental status and encephalopathy that is relevant to those who practice in the emergency department.

Brain metastasis in de novo stage IV breast cancer

OBJECTIVES

Information of brain metastasis (BM) in de novo stage IV breast cancer is lacking, which is an unavoidable problem and dilemma in practice. Understanding the current situation is helpful for the clinical cognition and decision-making.

METHODS

We retrospectively analyzed the clinical and survival information of de novo stage IV breast cancer with BM between 2015 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariable logistic and Cox regression analyses were performed to identify predictors of BM and factors associated with all-cause mortality in de novo stage IV breast cancer, respectively. Overall survival (OS) was calculated using Kaplan-Meier and log-rank tests.

RESULTS

Our cohort consisted of 1366 patients with BM in de novo stage IV breast cancer, with an incidence of 8.38% in patients with metastatic disease to any distant site. Incidence was highest among patients with metastatic disease with HR-HER2+ (12.95%) and HR-HER2- (13.40%) subtypes. The higher the number of extracranial metastases, the higher the BM incidence. The median OS was 12.0 (95%CI: 10.426-13.574) months in BM group; it was longest in HR + HER2+ (19.0[95%CI: 11.793-26.207] months), and shortest in HR-HER2- (7.0 [95%CI:5.354-8.646] months). Marital status, subtype, and abundance of metastatic sites influenced morbidity and OS of BM in de novo stage IV breast cancer.

CONCLUSIONS

Population-based estimates of the incidence and prognosis for patients with BM in de novo stage IV breast cancer were closely associated with subtype and metastatic burden. These findings may be helpful in developing diagnostic strategies, especially for brain screening.

More extensive structural damage in temporal lobe epilepsy with hippocampal sclerosis type 1

OBJECTIVE

To explore clinical and structural differences between mesial temporal lobe epilepsy (mTLE) patients with different hippocampal sclerosis (HS) subtypes.

METHODS

High-resolution T1-weighted MRI and diffusion tensor imaging data were obtained in 41 refractory mTLE patients and 52 age- and sex-matched healthy controls. Postoperative histopathological examination confirmed HS type 1 in 30 patients and HS type 2 in eleven patients. Clinical features, postoperative seizure outcomes, hippocampal subfields volumes, fractional anisotropy (FA) values of white matter regions and graph theory parameters were explored and compared between the HS type 1 and HS type 2 groups.

RESULTS

No significant differences in clinical features and postsurgical seizure outcomes were found between the HS type 1 and type 2 groups. However, the HS type 1 group showed extra atrophy in ipsilateral parasubiculum than healthy controls and more severe atrophy in contralateral hippocampal fissure than the HS type 2 group. More extensive FA decrease were also observed in the HS type 1 group, involving ipsilateral optic radiation, superior fronto-occipital fasciculus, contralateral uncinate fasciculus, tapetum, bilateral hippocampal cingulum, corona radiata, etc. Furthermore, in spite of similar impairments in characteristic path length, global efficiency and local efficiency in two HS groups, the HS type 1 group showed additional decrease of clustering coefficient than healthy controls.

CONCLUSIONS

HS type 1 and 2 groups had similar clinical characteristics and postoperative seizure outcomes. More widespread neuronal cell loss in the HS type 1 group contributed to more extensive structural damage and connectivity abnormality. These results shed new light on the imaging correlates of different HS pathology.

Cross talk between tumor stemness and microenvironment for prognosis and immunotherapy of uveal melanoma

PURPOSE

Tumor stem cells have emerged as a crucial focus of investigation and a therapeutic target in the context of cancer metastasis and drug resistance. They represent a promising novel approach to address the treatment of uveal melanoma (UVM).

METHODS

According to the one-class logistic regression (OCLR) approach, we first estimated two stemness indices (mDNAsi and mRNAsi) in a cohort of UVM (n = 80). The prognostic value of stemness indices among four subtypes of UVM (subtype A-D) was investigated. Moreover, univariate Cox regression and Lasso-penalized algorithms were conducted to identify a stemness-associated signature and verify in several independent cohorts. Besides, UVM patients classified into subgroups based on the stemness-associated signature. The differences in clinical outcomes, tumor microenvironment, and probability of immunotherapeutic response were investigated further.

RESULTS

We observed that mDNAsi was significantly linked with overall survival (OS) time of UVM, but no association was discovered between mRNAsi and OS. Stratification analysis indicated that the prognostic value of mDNAsi was only limited in subtype D of UVM. Besides, we established and verified a prognostic stemness-associated gene signature which can classify UVM patients into subgroups with distinct clinical outcomes, tumor mutation, immune microenvironment, and molecular pathways. The high risk of UVM is more sensitive to immunotherapy. Finally, a well-performed nomogram was constructed to predict the mortality of UVM patients.

CONCLUSIONS

This study offers a comprehensive examination of UVM stemness characteristics. We discovered mDNAsi-associated signatures improved the prediction capacity of individualized UVM prognosis and indicated prospective targets for stemness-regulated immunotherapy. Analysis of the interaction between stemness and tumor microenvironment may shed light on combinational treatment that targets both stem cell and the tumor microenvironment.

Hounsfield Units Predict Survival of Patients With Estrogen Receptor-Positive and Human Epithelial Growth Factor Receptor 2-Negative Breast Cancer

BACKGROUNDS

Tumor vascularity plays a fundamental role in cancer progression, including breast cancer. This study aimed to elucidate tumor vascularity and its impact on patient survival in the context of breast cancer subtypes using Hounsfield units (HU) on contrast-enhanced computed tomography (CT).

MATERIALS AND METHODS

Patients with early-stage breast cancer who completed planned treatment between 2003 and 2013 were retrospectively assessed.

RESULTS

The final cohort comprised 440 patients. Of the 440 patients, 262 had estrogen receptor (ER)-positive disease and 119 had human epidermal growth factor receptor 2 (HER2)-overexpressing disease. The tumor-to-aorta ratio of Hounsfield units (TAR) was related to significantly worse recurrence-free interval (RFI) (P < .001) and overall survival (OS) (P < .001) in patients with TAR > 0.33 for RFI and > 0.35 for OS than their counterparts. In the subgroup analysis, the survival disadvantage was limited only to patients with ER-positive and HER2-negative disease (P < .001 for both RFI and OS).

CONCLUSION

This study showed that TAR, which reflects tumor vascularity, was significantly related to patients' RFI and OS, suggesting its capacity as a feasible biomarker. This study also showed that TAR was associated with the survival in patients with ER-positive and HER2-negative disease.

Genetic polymorphisms in the C19orf66 gene influenced HIV-1 infection in a Yunnan population

Background

Due to the deficiencies of vaccines and effective medicine, the human immunodeficiency virus (HIV) infection mechanism should be studied. The C19orf66 gene, one of the interferon-stimulated genes (ISGs), expresses broad-spectra anti-viral activity, including inhibiting HIV replication.

Methods

In this study, we collect 421 HIV-1 infected patients and 448 controls to genotype three SNPs in the C19orf66 gene. Then, the association between SNPs and biochemical indices/ HIV-1 subtypes are analyzed.

Results

Genotypes CC and CT of rs12611087 show statistically lower and higher frequencies in HIV-1 infected patients than in controls, respectively. Alleles C and T of rs12611087 play protective and risk roles in Yunnan HIV population, respectively. Biochemical indices analysis shows that HIV-1 infected persons carried genotype TT of rs77076061 express significantly lower CD3+/CD45+ ratio level and higher IBIL level. The epidemic subtypes of HIV-1 patients in this study are CRF 07_BC and CRF 08_BC. Moreover, subtype CRF 08_BC tends to infect persons with genotype CC of rs12611087.

Conclusion

The genetic polymorphisms of the C19orf66 gene are firstly studied and reported to associate with HIV-1 infection and biochemical indices of patients in Yunnan. Furthermore, subtype CRF 08_BC infection could be influenced by genotypes of SNP in the C19orf66 gene.

The impact of microRNAs on the resistance of breast cancer subtypes to chemotherapy

Breast cancer (BC) formation is primarily influenced by genetics, epigenetics and environmental factors. Aberrant Genetics and epigenetics leads to a condition known as heterogeneity. The heterogeneity of BC can be divided into several subtypes. Among the epigenetic factors, microRNAs (miRNAs) have been shown to play a crucial role in the development and progression of malignancies. These small non-coding RNAs regulate gene expression through a variety of mechanisms, resulting in either mRNA degradation or translation repression. As miRNAs directly control many proteins, genetic anomalies affect tumor metastasis, apoptosis, proliferation, and cell transportation. Consequently, miRNA dysregulations contribute not only in cancer development but also in invasiveness, proliferation rate and more importantly, drug response. Findings mostly indicate subtype-specified identical miRNA profile in BC. Among the BC subtypes, TNBC, HER2 + and luminal are the most resistant to therapy, respectively. Therapy resistance is greatly associated with miRNA expression profile. Hence, concentration of miRNA is the first marker of its role in chemotherapy response. Overexpressed miRNAs may disrupt drug efflux transporters and decrease the drug accumulation in cell. While down-regulated miRNAs which mediate drug resistance processes are mostly correlated with poor treatment response. Moreover, other mechanisms in which miRNAs play crucial roles in chemoresistance such as cell receptor mediations, dysregulation by environmental factors, DNA defects, etc. Recently, several miRNA-based treatments have shown promising results in cancer treatment. Inhibition of up-regulated miRNAs is one of these therapeutic approaches whilst transfecting cell with down-regulated miRNAs also show promising results. Moreover, drug-resistance could also be determined while in the pre-treatment phase via expression levels of miRNAs. Therefore, miRNAs provide intriguing insights and challenges in overcoming chemoresistance. In this article, we have discussed how miRNAs regulate breast cancer subtypes-specific chemoresistance.

Subtype of SCLC Is an Intrinsic and Persistent Feature Through Systemic Treatment

Introduction

SCLC is an aggressive malignancy with poor outcome. Most patients have disease recurrence despite treatments with multiple modalities. Subtyping of SCLC has been proposed recently, and novel agents targeting specific subtypes are actively being investigated. In this study, we evaluated the plasticity of subtypes in paired pre- and post-treatment samples. The aim was to understand possible subtype evolution after chemotherapy resistance that could lead to alternate targeted therapy strategies.

Methods

A total of 68 samples from 32 patients with sufficient paired specimens were identified from 1998 to 2022. ASCL1, NEUROD1, and POU2F3 immunohistochemistry studies were performed on all cases, and subtyping by predominant expression was determined. Subtype comparison in each patient was performed, and expression analysis was performed on the basis of subtypes.

Results

Of 32 cases, 28 (88%) had the same subtype in pre- and first post-treatment specimens. Protein expression level of subtype-specific transcription factor remained stable after chemotherapy. Two of five (40%) NEUROD1-predominant SCLC switched to ASCL1-predominant phenotype after treatment. One case had a pitfall of scoring ASCL1 on specimen with marked crushing artifacts. One case revealed the challenge of proper subtyping for samples with borderline POU2F3 expression.

Conclusions

Subtype of SCLC generally remains the same after acquiring chemotherapy resistance. Plasticity was observed with rare cases switching from NEUROD1-predominant to ASC1-predominant SCLC. Resubtyping is unnecessary for the consideration of novel subtype-specific targeted agents, except cases with NEUROD1-predominant subtype.

A pairwise immune gene model for predicting overall survival and stratifying subtypes of colon adenocarcinoma

OBJECTIVES

There is increasing evidence for a close correlation between risk stratification, prognosis and the immune environment in colon adenocarcinoma (COAD). However, the efficacy of immunotherapy is different among different patients with COAD. Therefore, the current work tends to use immune-related gene to develop a gene-pair model to evaluate the COAD prognosis, and to develop a new method for risk stratification of COAD, which is conducive to better predict the immunotherapy effect of patients.

METHODS

Specifically, from the TCGA and GEO (GSE14333 and GSE39582) databases, we first collected gene expression profiles, associated survival follow-up information of COAD patients. Through systematic bioinformatics analysis, we established a prognosis-related model of colon cancer with three pairs of "immune gene pairs", with uni- and multivariate and lasso cox regression analyses verifying the model stability. Most immune cells showed markedly different levels of infiltration between the two risk subgroups calculated by the model. More, single-cell RNA-seq analyses were also performed to validate the selected genes in the immune gene-pair model.

RESULTS

A prognosis-related model of colon cancer with three pairs of "immune gene pairs" were built and validated by several datasets. The analysis of immune landscape of COAD revealed that low-risk subgroup obtained by the prognosis-related model for COAD can be further divided into three subclusters with different prognosis. Then, we applied the Tumor online Prognostic analyses Platform (ToPP) to construct a prognostic model using these five genes. Results show that APOD, ISG20 and STC2 are risk factors, while CXCL9 and IL7R are protection factors. We also found that only the five-gene model could also predict the prognosis of COAD patients, indicating the robustness of the gene-pair model. Among the five genes, including CXCL9, APOD, STC2, ISG20, and IL7R, in the gene-pair model, single-cell RNA sequencing reveals the high expression of CXCL9 and IL7R in inflammatory macrophages. Using cell-cell interaction and trajectory analysis, data indicate that CXCL9+/IL7R+ pro-inflammatory macrophages were capable of secreting and activating more anti-tumor pathways than CXCL9-/IL7R- pro-inflammatory macrophages.

CONCLUSIONS

In short, we have successfully developed an "immune gene pair" related model that can judge the prognostic status of patients with COAD and may contribute to risk stratification and evaluate potential beneficiaries of immunotherapy, providing new ideas for the anti-COAD management and therapy.

Molecular subtyping and immune score system by a novel pyroptosis-based gene signature precisely predict immune infiltrating, survival and response to immune-checkpoint blockade in breast cancer

Breast cancer is one of the most prevalent and lethal types of cancer affecting women globally. Pyroptosis is a recently elucidated form of inflammatory cell death mediated by the gasdermin family and is considered to be associated with the tumor immune microenvironment. However, the impact of pyroptosis on breast cancer patients remains unclear. In this study, we identified 31 Pyroptosis-Related-Genes (PRGs) and investigated their association with patient survival using data from the TCGA database. We then established a gene signature comprising 6 PRGs that were significantly correlated with prognosis, and used these genes to classify breast cancer into 2 molecular subtypes. We investigated the characteristics of these two subtypes and found that our molecular subtyping accurately separated the samples into two groups with distinct immune infiltration and prognosis. Patients with higher expression of these genes had significantly greater immune infiltrating, T cell signaling, and better prognosis. Moreover, we developed an immune score system based on these 6 genes that accurately predicted the immune infiltrating of patients and their response to immune-checkpoint blockade, which was difficult to achieve with previous models. Additionally, through single-cell analyses, we found that patients with higher immune scores had stronger cytotoxic immune cells. In summary, our study identified a novel gene set and developed an immune scoring system based on this gene set that can precisely predict the immune microenvironment and responses to immunotherapy of breast cancer (BRCA) patients, which could be useful in clinical trials.

Machine learning-based identification of lower grade glioma stemness subtypes discriminates patient prognosis and drug response

Glioma stem cells (GSCs) remodel their tumor microenvironment to sustain a supportive niche. Identification and stratification of stemness related characteristics in patients with glioma might aid in the diagnosis and treatment of the disease. In this study, we calculated the mRNA stemness index in bulk and single-cell RNA-sequencing datasets using machine learning methods and investigated the correlation between stemness and clinicopathological characteristics. A glioma stemness-associated score (GSScore) was constructed using multivariate Cox regression analysis. We also generated a GSC cell line derived from a patient diagnosed with glioma and used glioma cell lines to validate the performance of the GSScore in predicting chemotherapeutic responses. Differentially expressed genes (DEGs) between GSCs with high and low GSScores were used to cluster lower-grade glioma (LGG) samples into three stemness subtypes. Differences in clinicopathological characteristics, including survival, copy number variations, mutations, tumor microenvironment, and immune and chemotherapeutic responses, among the three LGG stemness-associated subtypes were identified. Using machine learning methods, we further identified genes as subtype predictors and validated their performance using the CGGA datasets. In the current study, we identified a GSScore that correlated with LGG chemotherapeutic response. Through the score, we also identified a novel classification of the LGG subtype and associated subtype predictors, which might facilitate the development of precision therapy.

Finding Similarities in Differences Between Autistic Adults: Two Replicated Subgroups

Autism is heterogeneous, which complicates providing tailored support and future prospects. We aim to identify subgroups in autistic adults with average to high intelligence, to clarify if certain subgroups might need support. We included 14 questionnaire variables related to aging and/or autism (e.g., demographic, psychological, and lifestyle). Community detection analysis was used for subgroup identification in an original sample of 114 autistic adults with an adulthood diagnosis (autism) and 58 non-autistic adults as comparison group (COMP), and a replication sample (N_Autism = 261; N_COMP = 287), both aged 30-89 years. Next, we identified subgroups and assessed external validity (for cognitive and psychological difficulties, and quality of life [QoL]) in the autism samples. To test specificity, we repeated the analysis after adding 123 adults with ADHD, aged 30-80 years. As expected, the autism and COMP groups formed distinct subgroups. Among autistic adults, we identified three subgroups of which two were replicated. One of these subgroups seemed most vulnerable on the cluster variables; this subgroup also reported the most cognitive and psychological difficulties, and lowest QoL. Adding the ADHD group did not alter results. Within autistic adults, one subgroup could especially benefit from support and specialized care, although this must be tested in future studies.

Retrospective study of transcriptomic profiling identifies Thai triple-negative breast cancer patients who may benefit from immune checkpoint and PARP inhibitors

Background

Triple-negative breast cancer (TNBC) is a rare and aggressive breast cancer subtype. Unlike the estrogen receptor-positive subtype, whose recurrence risk can be predicted by gene expression-based signature, TNBC is more heterogeneous, with diverse drug sensitivity levels to standard regimens. This study explored the benefit of gene expression-based profiling for classifying the molecular subtypes of Thai TNBC patients.

Methods

The nCounter-based Breast 360 gene expression was used to classify Thai TNBC retrospective cohort subgroups. Their expression profiles were then compared against the previously established TNBC classification system. The differential characteristics of the tumor microenvironment and DNA damage repair signatures across subgroups were also explored.

Results

Thai TNBC cohort could be classified into four main subgroups, corresponding to the LAR, BL-2, and M subtypes based on Lehmann's TNBC classification. The PAM50 gene set classified most samples as basal-like subtypes except for Group 1. Group 1 exhibited similar enrichment of the metabolic and hormone response pathways to the LAR subtype. Group 2 shared pathway activation with the BL-2 subtype. Group 3 showed an increase in the EMT pathway, similar to the M subtype. Group 4 showed no correlation with Lehmann's TNBC. The tumor microenvironment (TME) analysis showed high TME cell abundance with increased expression of immune blockade genes in Group 2. Group 4 exhibited low TME cell abundance and reduced immune blockade gene expressions. We also observed distinct signatures of the DNA double-strand break repair genes in Group 1.

Conclusions

Our study reported unique characteristics between the four TNBC subgroups and showed the potential use of immune checkpoint and PARP inhibitors in subsets of Thai TNBC patients. Our findings warrant further clinical investigation to validate TNBC's sensitivity to these regimens.

Deep learning classification of uveal melanoma based on histopathological images and identification of a novel indicator for prognosis of patients

BACKGROUND

Deep learning has been extensively used in digital histopathology. The purpose of this study was to test deep learning (DL) algorithms for predicting the vital status of whole-slide image (WSI) of uveal melanoma (UM).

METHODS

We developed a deep learning model (Google-net) to predict the vital status of UM patients from histopathological images in TCGA-UVM cohort and validated it in an internal cohort. The histopathological DL features extracted from the model and then were applied to classify UM patients into two subtypes. The differences between two subtypes in clinical outcomes, tumor mutation, and microenvironment, and probability of drug therapeutic response were investigated further.

RESULTS

We observed that the developed DL model can achieve a high accuracy of >  = 90% for patches and WSIs prediction. Using 14 histopathological DL features, we successfully classified UM patients into Cluster1 and Cluster2 subtypes. Compared to Cluster2, patients in the Cluster1 subtype have a poor survival outcome, increased expression levels of immune-checkpoint genes, higher immune-infiltration of CD8 + T cell and CD4 + T cells, and more sensitivity to anti-PD-1 therapy. Besides, we established and verified prognostic histopathological DL-signature and gene-signature which outperformed the traditional clinical features. Finally, a well-performed nomogram combining the DL-signature and gene-signature was constructed to predict the mortality of UM patients.

CONCLUSIONS

Our findings suggest that DL model can accurately predict vital status in UM patents just using histopathological images. We found out two subgroups based on histopathological DL features, which may in favor of immunotherapy and chemotherapy. Finally, a well-performing nomogram that combines DL-signature and gene-signature was constructed to give a more straightforward and reliable prognosis for UM patients in treatment and management.

Data-driven subtyping of Parkinson's disease: comparison of current methodologies and application to the Bochum PNS cohort

Considerable efforts have been made to better describe and identify Parkinson's disease (PD) subtypes. Cluster analyses have been proposed as an unbiased development approach for PD subtypes that could facilitate their identification, tracking of progression, and evaluation of therapeutic responses. A data-driven clustering analysis was applied to a PD cohort of 114 subjects enrolled at St. Josef-Hospital of the Ruhr University in Bochum (Germany). A wide spectrum of motor and non-motor scores including polyneuropathy-related measures was included into the analysis. K-means and hierarchical agglomerative clustering were performed to identify PD subtypes. Silhouette and Calinski-Harabasz Score Elbow were then employed as supporting evaluation metrics for determining the optimal number of clusters. Principal Component Analysis (PCA), analysis of variance (ANOVA), and analysis of covariance (ANCOVA) were conducted to determine the relevance of each score for the clusters' definition. Three PD cluster subtypes were identified: early onset mild type, intermediate type, and late-onset severe type. The between-cluster analysis consistently showed highly significant differences (P < 0.01), except for one of the scores measuring polyneuropathy (Neuropathy Disability Score; P = 0.609) and Levodopa dosage (P = 0.226). Parkinson's Disease Questionnaire (PDQ-39), Non-motor Symptom Questionnaire (NMSQuest), and the MDS-UPDRS Part II were found to be crucial factors for PD subtype differentiation. The present analysis identifies a specific set of criteria for PD subtyping based on an extensive panel of clinical and paraclinical scores. This analysis provides a foundation for further development of PD subtyping, including k-means and hierarchical agglomerative clustering.Trial registration: DRKS00020752, February 7, 2020, retrospectively registered.

Epstein-Barr virus variation in people living with human immunodeficiency virus in southeastern China

BACKGROUND

Patients infected with HIV are at high risk of developing Epstein-Barr Virus (EBV)-related diseases. The genotype and viral biological behavior of EBV infection in patients with human immunodeficiency virus-1 (HIV) in China remain unclear. This study analyzed the characteristics of EBV in patients infected with HIV in southeastern China.

METHODS

A total of 162 HIV-infected patients and 52 patients without HIV were enrolled in this study. EBV viral load in blood was determined by fluorescence quantitative PCR. EBV typing was performed using saliva according to polymorphisms in the EBNA3C region. EBV LMP-1 carboxy terminus (C-ter) was sequenced, and compared with the epidemic strains in the world.

RESULTS

Among HIV infected patients, the EBV strain variant was mainly EBV-1, while EBV-2 had a higher viral load than EBV-1 (P = 0.001) and EBV-1/2 (P = 0.002). HIV infected patients had higher active virus replication. The EBV LMP-1 variants were mainly the China1 variant. HIV-infected patients had different nucleic acid positions of 30-bp deletion (del30) and had a higher incidence of high 33-bp tandem repeats (rep33) copies than non-HIV-infected patients. There was a difference in the mutations of EBV LMP-1 C-ter del30 and ins15 between HIV infected patients and the control group (P < 0.001).

CONCLUSION

In southeastern China, EBV in HIV-infected patients had higher active virus replication; EBV infection was mainly EBV-1, and EBV-2 infection has higher EBV virus load; hotspot mutations of LMP-1 C-ter were different between HIV-infected patients and non-HIV-infected patients.

TRIAL REGISTRATION

This study was approved by the ethics committee of the First Affiliated Hospital of Zhejiang University School of Medicine (Approval No. 2018764), and registered in Chinese Clinical Trial Registry on 3 June 2019 (ChiCTR, ChiCTR1900023600, http://www.chictr.org.cn/usercenter.aspx ).

Genome mosaic structure of two novel HIV-1 recombinant forms (CRF01_AE/B) in men who have sex with men in Hebei, China

BACKGROUND

Homosexual contact is the main route of human immunodeficiency virus type one (HIV-1) transmission in Cangzhou Prefecture, Hebei, China. Moreover, the number of circulating recombinant forms (CRFs) and unique recombinant forms (URFs) in this key population is ever increasing.

METHODS

In this study, we identified two novel URFs (hcz0017 and hcz0045) from two men who have sex with men (MSM) based in Cangzhou Prefecture. Phylogenetic and recombinant breakpoint analyses, based on the near full-length genomes (NFLGs) of the two novel URFs, showed that they originated from a recombination between HIV-1 CRF01_AE and subtype B.

RESULTS

HXB2 numbering revealed that the NFLGs of hcz0017 and hcz0045 each contained the following seven subregions: hcz0017: I_B (790-1,171 nt), II_{CRF01_AE} (1,172-2,022 nt), III_B (2,023-4,469 nt), IV_{CRF01_AE} (4,470-5,866 nt), V_B (5,867-7,462 nt), VI_{CRF01_AE} (7,463-8,379 nt), VII_B (8,380-9,411 nt); hcz0045: I_{CRF01_AE} (790-5,147 nt), II_B (5,148-5,614 nt), III_{CRF01_AE} (5,615-6,035 nt), IV_B (6,036-6,241 nt), V_{CRF01_AE} (6,242-7,325nt), VI_B (7,326-8,254 nt), VII_{CRF01_AE} (8,255-9,411 nt). Moreover, the two MSM from whom the novel URFs originated from were diagnosed as recently HIV-1-infected, suggesting that the high prevalence of HIV-1 among MSM was related to high-risk sexual activity such as unprotected anal sex and multiple sexual partners.

CONCLUSIONS

Our results highlight the need to continually monitor HIV-1 diversity in Hebei and its neighboring provinces to achieve a more effective control of HIV-1 spread within the MSM community.

Epidemiology and outcome of individuals with intraductal papillary neoplasms of the bile duct

BACKGROUND

Intraductal papillary neoplasm of the bile duct (IPNB) is a rare distinct subtype of precursor lesions of biliary carcinoma. IPNB is considered to originate from luminal biliary epithelial cells, typically displays mucin-hypersecretion or a papillary growth pattern, and results in cystic dilatation[1]. IPNB develops anywhere in the intrahepatic and extrahepatic biliary tracts, and can occur in various pathological stages from low-grade dysplasia to invasive carcinoma. IPNBs have similar phenotypic changes in the occurrence and development of all subtypes, and the prognosis is significantly better than that of traditional (non-papillary) cholangiocarcinoma.

AIM

To evaluate the clinicopathological features of IPNB to provide evidence-based guidance for treatment.

METHODS

Invasive IPNB, invasive intraductal papillary mucinous neoplasm of the pancreas (IPMN), and traditional cholangiocarcinoma data for affected individuals from 1975 to 2016 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Annual percentage changes (APCs) in the incidence and incidence-based (IB) mortality were calculated. We identified the independent predictors of overall survival (OS) and cancer-specific survival (CSS) in individuals with invasive IPNB.

RESULTS

The incidence and IB mortality of invasive IPNB showed sustained decreases, with an APC of -4.5% (95%CI: -5.1% to -3.8%) and -3.3% (95%CI: -4.1% to -2.6%) (P < 0.001), respectively. Similar decreases in incidence and IB mortality were seen for invasive IPMN but not for traditional cholangiocarcinoma. Both OS and CSS for invasive IPNB were better than for invasive IPMN and traditional cholangiocarcinoma. A total of 1635 individuals with invasive IPNB were included in our prognosis analysis. The most common tumor sites were the pancreaticobiliary ampulla (47.9%) and perihilar tract (36.7%), but the mucin-related subtype of invasive IPNB was the main type, intrahepatically (approximately 90%). In the univariate and multivariate Cox regression analysis, age, tumor site, grade and stage, subtype, surgery, and chemotherapy were associated with OS and CSS (P < 0.05).

CONCLUSION

Incidence and IB mortality of invasive IPNB trended steadily downward. The heterogeneity of IPNB comprises site and the tumor’s mucin-producing status.