FTIR Spectroscopic Imaging Supports Urine Cytology for Classification of Low- and High-Grade Bladder Carcinoma

Bladder urothelial carcinoma (BC) is a common, recurrent, life-threatening, and unpredictable disease which is difficult to diagnose. These features make it one of the costliest malignancies. Although many possible diagnostic methods are available, molecular heterogeneity and difficulties in cytological or histological examination induce an urgent need to improve diagnostic techniques. Herein, we applied Fourier transform infrared spectroscopy in imaging mode (FTIR) to investigate patients’ cytology samples assigned to normal (N), low-grade (LG) and high-grade (HG) BC. With unsupervised hierarchical cluster analysis (UHCA) and hematoxylin-eosin (HE) staining, we observed a correlation between N cell types and morphology. High-glycogen superficial (umbrella) and low-glycogen piriform urothelial cells, both with normal morphology, were observed. Based on the spectra derived from UHCA, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed, indicating a variation of protein content between the patient groups. Moreover, BC spectral cytology identified a low number of high-glycogen cells for which a shift of the carbohydrate/phosphate bands was also observed. Despite high cellular heterogeneity, PLS-DA was able to classify the spectra obtained. The voided urine FTIR cytology is one of the options that might be helpful in BC diagnosis, as high sensitivity and specificity up to 97% were determined.

Genomic and Transcriptomic Profiling of Brain Metastases

Brain metastases (BM) are the most common brain tumors in adults occurring in up to 40% of all cancer patients. Multi-omics approaches allow for understanding molecular mechanisms and identification of markers with prognostic significance. In this study, we profile 130 BM using genomics and transcriptomics and correlate molecular characteristics to clinical parameters. The most common tumor origins for BM were lung (40%) followed by melanoma (21%) and breast (15%). Melanoma and lung BMs contained more deleterious mutations than other subtypes (p < 0.001). Mutational signatures suggested that the bulk of the mutations were gained before metastasis. A novel copy number event centered around the MCL1 gene was found in 75% of all samples, suggesting a broader role in promoting metastasis. Unsupervised hierarchical cluster analysis of transcriptional signatures available in 65 samples based on the hallmarks of cancer revealed four distinct clusters. Melanoma samples formed a distinctive cluster in comparison to other BM subtypes. Characteristics of molecular profiles did not correlate with survival. However, patients with self-identified black race or those who did not receive radiation correlated with poor survival. These data identify potential new drivers of brain metastatic progression. Our data also suggest further investigation of sociodemographic and clinical features is needed in BM cohorts.

Unsupervised Clustering Reveals Distinct Subtypes of Biliary Atresia Based on Immune Cell Types and Gene Expression

BackgroundBiliary atresia (BA) is a severe cholangiopathy of early infancy that destroys cholangiocytes, obstructs ductular pathways and if left untreated, culminates to liver cirrhosis. Mechanisms underlying the etiological heterogeneity remain elusive and few studies have attempted phenotyping BA. We applied machine learning to identify distinct subtypes of BA which correlate with the underlying pathogenesis.MethodsThe BA microarray dataset GSE46995 was downloaded from the Gene Expression Omnibus (GEO) database. Unsupervised hierarchical cluster analysis was performed to identify BA subtypes. Then, functional enrichment analysis was applied and hub genes identified to explore molecular mechanisms associated with each subtype. An independent dataset GSE15235 was used for validation process.ResultsBased on unsupervised cluster analysis, BA patients can be classified into three distinct subtypes: Autoimmune, Viral and Embryonic subtypes. Functional analysis of Subtype 1 correlated with Fc Gamma Receptor (FCGR) activation and hub gene FCGR2A, suggesting an autoimmune response targeting bile ducts. Subtype 2 was associated with immune receptor activity, cytokine receptor, signaling by interleukins, viral protein interaction, suggesting BA is associated with viral infection. Subtype 3 was associated with signaling and regulation of expression of Robo receptors and hub gene ITGB2, corresponding to embryonic BA. Moreover, Reactome pathway analysis showed Neutrophil degranulation pathway enrichment in all subtypes, suggesting it may result from an early insult that leads to biliary stasis.ConclusionsThe classification of BA into different subtypes improves our current understanding of the underlying pathogenesis of BA and provides new insights for future studies.

HLA-B52 allele in giant cell arteritis may indicate diffuse large-vessel vasculitis formation: a retrospective study

Background This study aimed to identify new characteristics of elderly onset large-vessel vasculitis (EOLVV) by focusing on human leucocyte antigen (HLA) genotype, polymyalgia rheumatica (PMR), and affected vascular lesions observed on positron emission tomography/computed tomography (PET/CT) imaging. Methods We retrospectively studied 65 consecutive Japanese patients with large-vessel vasculitis (LVV) who had extracranial vasculitis lesions and underwent PET/CT imaging. PET/CT images were assessed using the semi-quantitative PET visual score of each affected vessel, and the PET vascular activity score (PETVAS) and number of affected vessels were calculated. Subjects were subsequently grouped based on age at onset, superficial temporal artery (STA) involvement, and presence of PMR and compared each group according to HLA genotype. Unsupervised hierarchical cluster analysis was used to identify the patients with similar characteristics in terms of affected vascular lesions detected through PET/CT imaging. The clinical characteristics and PET/CT findings of the population newly identified in this study were examined. Results Twenty-seven patients with EOLVV did not meet the American College of Rheumatology 1990 criteria for giant cell arteritis (GCA) and Takayasu arteritis and were considered as unclassified EOLVV (UEOLVV). The unsupervised hierarchical cluster analysis revealed that UEOLVV with PMR and large-vessel GCA (LV-GCA) formed a cluster of LVV with GCA features (i.e., PMR and/or STA involvement) when restricted to patients who were HLA-B52-positive. Patients who were HLA-B52-positive with LVV and GCA features had similar clinical characteristics and patterns of affected vessels and presented with diffuse LVV lesions. HLA-B52-positive patients who had LVV with GCA features also presented with higher PETVAS, more affected vessels, and lower rates of biologics usage and relapse compared to HLA-B52-positive patients with TAK. Conclusions Patients who had UEOLVV with PMR had similar characteristics to patients with LV-GCA. Patients who were HLA-B52-positive and had LVV with GCA features presented with diffuse vascular lesions and may comprise a core population of Japanese patients with EOLVV. The findings of HLA-B52 positivity and diffusely affected vessels in patients with EOLVV can be considered as suspicious findings of LV-GCA.

Genetic instabilities as potential biomarkers for pregnancy-associated breast cancer.

e12559 Background: Pregnancy associated breast cancer (PABC), defined as breast cancer diagnosed during or within one year after pregnancy, occurs approximately once in every 3,000 pregnancies and accounts for up to 6.9% of all breast cancers in women ≤ 45 years. Compared to age-matched non-PABC patients, PABC is generally characterized by a particularly aggressive histopathologic profile (more ER-, PR- and HER2 negative tumors and tumors of higher grade) with a higher mortality rate. Whether these cancers arise before or during pregnancy, and whether their genetic profile differs from non-PABC tumors, is currently unknown. This study assesses the genetic background of PABC by detection of specific DNA copy number alterations (CNA). Methods: We assembled 29 triple-negative PABC patients from the Dutch nationwide pathology database (PALGA). From their formalin-fixed and paraffin embedded (FFPE) tumor tissue blocks, DNA was extracted. Multiplex Ligation-Dependent probe Amplification (MLPA) analysis was performed for detection of CNAs in 20 oncogenes and 2 tumor suppressor genes using the P078-D2 kit (MRC Holland). Individual gene copy number loss (MLPA ratio < 0.7), gain (ratio 1.3-2.0) and amplification (ratio > 2.0) was determined and unsupervised hierarchical cluster analysis was performed to identify differences in copy number (CN) patterns between PABC patients. Chi square statistics were used to interrogate associations with clinicopathologic characteristics. Log-Rank test was used to compare Kaplan Meier survival curves between CN subgroups. Results: Triple negative PABC tumors showed frequent copy number loss on chromosome 17q ( CPD, MED1, TOP2A, MAPT, PPM1D) and 8p ( ZNF703 and ADAM9), as well as frequent copy number gain/amplification of MYC (8q) and CCND1 (11q). Cluster analysis identified 2 clusters of PABC patients based on their tumor copy number patterns: a CN-neutral cluster and a CN-high cluster, the latter demonstrating significantly lower chromosome 17 copy numbers than the former (for PPM1D, ERBB2, CPD, MED1, TOP2A, CDC6 and MAPT). Patients with CN-neutral tumors more often showed lymph node metastases (p = 0.028), were of significantly higher stage (p = 0.031), and demonstrated a worse overall survival (p = 0.036) compared with PABC patients harboring CN-high tumors. Conclusions: We demonstrate different tumor CN patterns within a small group of triple negative PABC-patients, associated with distinct aggressiveness. This will form the basis for further in-depth genetic profiling within a larger Dutch PABC cohort, rendering insight in the disease progression and contributing to the development of more targeted and personalized treatments.

Early Phenotypes in Girls at Risk for PCOS Replicate Metabolic and Reproductive Subtypes: An Unsupervised Clustering Analysis

Both daughters of women with PCOS (PCOS-d) and overweight girls (OW-g) are proposed to be at increased risk of PCOS because they have peripubertal increases in testosterone (T) levels, a cardinal feature of PCOS. We are testing this hypothesis by performing longitudinal studies in these girls after menarche. In adult women with PCOS, we have recently identified reproductive and metabolic subtypes using unsupervised cluster analyses. These subtypes were associated with novel PCOS susceptibility genetic loci suggesting that the subtypes reflect biologically discrete entities. We performed similar analyses in our cohort of early postmenarchal PCOS-d and OW-g to test the hypothesis that these subtypes are present in girls at risk for PCOS. Fifteen PCOS-d and 10 OW-g aged 11-16 years and with postmenarchal age less than 2 years were studied. Mothers of PCOS-d fulfilled NIH criteria for PCOS, mothers of OW-g were reproductively normal with no history of irregular menses or clinical hyperandrogenism. OW-g had a BMI above the 85th percentile for age. There was no BMI inclusion criterion for PCOS-d; four PCOS-d had a BMI above the 85th percentile. The girls were of comparable age, post-menarchal age and BMI z score. A fasting morning blood sample was drawn for T, SHBG, DHEAS, glucose and insulin. Leuprolide 10 mcg/kg SC was administered. LH and FSH levels were measured at baseline, 30 min, and 60 min following leuprolide. Unsupervised hierarchical cluster analysis adjusted for age was performed on quantitative traits including BMI, T, fasting insulin, fasting glucose, DHEAS, SHBG, and LH and FSH. These are the same quantitative traits used for clustering in adult PCOS. The clustering revealed 2 distinct PCOS subtypes: a reproductive group (41%), characterized by higher SHBG levels, LH and FSH with relatively low BMI and insulin levels, and a metabolic group (41%), characterized by higher BMI and insulin levels and lower SHBG, LH, and FSH. Jaccard coefficients indicated cluster stability (0.70 reproductive, 0.69 metabolic). There was a significant difference in the distribution of the two subgroups in PCOS-d and OW-g: PCOS-d 60% reproductive, 13% metabolic, 27% indeterminate; OW-g 25% reproductive, 50% metabolic, 25% indeterminate (Chi Sq P=0.05). We found that early postmenarchal PCOS-d and OW-g demonstrate reproductive and metabolic subtypes similar to those identified in adult women with PCOS. The majority of PCOS-d had the reproductive subtype. These findings suggest that this subtype, which is characterized by disordered gonadotropin secretion, is an early harbinger of PCOS. Longitudinal studies are ongoing to test this hypothesis.

Refining the mutational spectrum and gene–phenotype correlates in pontocerebellar hypoplasia: results of a multicentric study

BackgroundPontocerebellar hypoplasias (PCH) comprise a group of genetically heterogeneous disorders characterised by concurrent hypoplasia of the pons and the cerebellum and variable clinical and imaging features. The current classification includes 13 subtypes, with ~20 known causative genes. Attempts have been made to delineate the phenotypic spectrum associated to specific PCH genes, yet clinical and neuroradiological features are not consistent across studies, making it difficult to define gene-specific outcomes.MethodsWe performed deep clinical and imaging phenotyping in 56 probands with a neuroradiological diagnosis of PCH, who underwent NGS-based panel sequencing of PCH genes and MLPA for CASK rearrangements. Next, we conducted a phenotype-based unsupervised hierarchical cluster analysis to investigate associations between genes and specific phenotypic clusters.ResultsA genetic diagnosis was obtained in 43 probands (77%). The most common causative gene was CASK, which accounted for nearly half cases (45%) and was mutated in females and occasionally in males. The European founder mutation p.Ala307Ser in TSEN54 and pathogenic variants in EXOSC3 accounted for 18% and 9% of cases, respectively. VLDLR, TOE1 and RARS2 were mutated in single patients. We were able to confirm only few previously reported associations, including jitteriness and clonus with TSEN54 and lower motor neuron signs with EXOSC3. When considering multiple features simultaneously, a clear association with a phenotypic cluster only emerged for EXOSC3.ConclusionCASK represents the major PCH causative gene in Italy. Phenotypic variability associated with the most common genetic causes of PCH is wider than previously thought, with marked overlap between CASK and TSEN54-associated disorders.

Metabolomic Signature Discriminates Normal Human Cornea from Keratoconus—A Pilot GC/MS Study

The molecular etiology of keratoconus (KC), a pathological condition of the human cornea, remains unclear. The aim of this work was to perform profiling of metabolites and identification of features discriminating this pathology from the normal cornea. The combination of gas chromatography and mass spectrometry (GC/MS) techniques has been applied for profiling and identification of metabolites in corneal buttons from 6 healthy controls and 7 KC patients. An untargeted GC/MS-based approach allowed the detection of 377 compounds, including 46 identified unique metabolites, whose levels enabled the separation of compared groups of samples in unsupervised hierarchical cluster analysis. There were 13 identified metabolites whose levels differentiated between groups of samples. Downregulation of several carboxylic acids, fatty acids, and steroids was observed in KC when compared to the normal cornea. Metabolic pathways associated with compounds that discriminated both groups were involved in energy production, lipid metabolism, and amino acid metabolism. An observed signature may reflect cellular processes involved in the development of KC pathology, including oxidative stress and inflammation.

Yeast Smell Like What They Eat: Analysis of Volatile Organic Compounds of Malassezia furfur in Growth Media Supplemented with Different Lipids

Malassezia furfur is part of the human skin microbiota. Its volatile organic compounds (VOCs) possibly contribute to the characteristic odour in humans, as well as to microbiota interaction. The aim of this study was to investigate how the lipid composition of the liquid medium influences the production of VOCs. Growth was performed in four media: (1) mDixon, (2) oleic acid (OA), (3) oleic acid + palmitic acid (OA+PA), and (4) palmitic acid (PA). The profiles of the VOCs were characterized by HS-SPME/GC-MS in the exponential and stationary phases. A total number of 61 VOCs was found in M. furfur, among which alkanes, alcohols, ketones, and furanic compounds were the most abundant. Some compounds previously reported for Malassezia (γ-dodecalactone, 3-methylbutan-1-ol, and hexan-1-ol) were also found. Through our experiments, using univariate and multivariate unsupervised (Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA)) and supervised (Projection to Latent Structures Discriminant Analysis (PLS-DA)) statistical techniques, we have proven that each tested growth medium stimulates the production of a different volatiles profile in M. furfur. Carbon dioxide, hexan-1-ol, pentyl acetate, isomer5 of methyldecane, dimethyl sulphide, undec-5-ene, isomer2 of methylundecane, isomer1 of methyldecane, and 2-methyltetrahydrofuran were established as differentiating compounds among treatments by all the techniques. The significance of our findings deserves future research to investigate if certain volatile profiles could be related to the beneficial or pathogenic role of this yeast.

Early isolated V-lesion may not truly represent rejection of the kidney allograft

Intimal arteritis is known to be a negative prognostic factor for kidney allograft survival. Isolated v-lesion (IV) is defined as intimal arteritis with minimal tubulointerstitial inflammation (TI). Although the Banff classification assesses IV as T cell-mediated rejection (TCMR), clinical, and prognostic significance of early IV (early IV, eIV) with negative C4d and donor-specific antibodies (DSA) remains unclear. To help resolve if such eIV truly represents acute rejection, a molecular study was performed. The transcriptome of eIV (n=6), T cell-mediated vascular rejection with rich TI (T cell-mediated vascular rejection, TCMRV, n=4) and non-rejection histologic findings (n=8) was compared using microarrays. A total of 310 genes were identified to be deregulated in TCMRV compared with eIV. Gene enrichment analysis categorized deregulated genes to be associated primarily with T-cells associated biological processes involved in an innate and adaptive immune and inflammatory response. Comparison of deregulated gene lists between the study groups and controls showed only a 1.7% gene overlap. Unsupervised hierarchical cluster analysis revealed clear distinction of eIV from TCMRV and showed similarity with a control group. Up-regulation of immune response genes in TCMRV was validated using RT-qPCR in a different set of eIV (n=12) and TCMRV (n=8) samples. The transcriptome of early IV (< 1 month) with negative C4d and DSA is associated with a weak immune signature compared with TCMRV and shows similarity with normal findings. Such eIV may feature non-rejection origin and reflect an injury distinct from an alloimmune response. The present study supports use of molecular methods when interpreting kidney allograft biopsy findings.