The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

Incidence and Risk Factors for Hepatocellular Carcinoma in Cirrhosis: The Multicenter Hepatocellular Carcinoma Early Detection Strategy (HEDS) Study.

BACKGROUND & AIMS: Worldwide, hepatocellular carcinoma (HCC) is a common malignancy. We aimed to prospectively determine the incidence and risk factors of HCC in a U.S. METHODS: The multicenter Hepatocellular Carcinoma Early Detection Strategy study of the National Institutes of Health prospectively enrolled patients with cirrhosis who underwent standard surveillance for HCC. Demographics, medical and family history, etiology of liver disease, and clinical features were evaluated for associations with HCC. RESULTS: Between April 10, 2013 and December 31, 2021, 1723 patients were enrolled and confirmed eligible. During median follow-up of 2.2 years (range, 0-8.7 years), there were 109 incident cases of HCC for an incidence rate of 2.4 per 100 person-years: 88 (81%) patients with very early/early Barcelona Clinic Liver Cancer stage (0, A), 20 (18%) intermediate stage (B), and 1 (1%) unknown stage. Risk factor analyses were restricted to 1325 patients, including 95 incident HCC, with at least 6 months of follow-up. The majority were men (53.2%), obese or severely obese (median body mass index, 30.2 kg/m2), and white (86.3%); 42.0% had history of hepatitis C virus infection, 20.7% had alcoholic liver disease, and 24.9% had nonalcoholic fatty liver disease. Fourteen risk factors for HCC were significant (P < .05) in univariate analyses, and a multivariate subset was selected using stepwise logistic regression. The multivariate subset contained gender (P < .001; male; odds ratio [OR], 2.47; 95% confidence interval [CI], 1.54-4.07), years with cirrhosis (P = .004; OR, 1.06; 95% CI, 1.02-1.1), family history of liver cancer (P = .02; yes; OR, 2.69; 95% CI, 1.11-5.86), age (per 5 years; P = .02; OR, 1.17; 95% CI, 1.03-1.33), obesity (P = .02; yes; OR, 1.7; 95% CI, 1.08-2.73), aspartate aminotransferase (log(1+AST); P = .06; OR, 1.54; 95% CI, 0.97-2.42), alpha-fetoprotein (log(1+AFP); P = .07; OR, 1.32; 95% CI, 0.97-1.77), and albumin (P = .10; OR, 0.7; 95% CI, 0.46-1.07). CONCLUSIONS: Thus far, this is the largest prospective and geographically diverse study of a U.S. cohort of patients with cirrhosis that validates known risk factors for HCC (gender, age, obesity, years with cirrhosis, family history of liver cancer, baseline AFP, albumin, and AST). The incidence of HCC was 2.4% per 100 person-years.

Chronic arsenic exposure induces malignant transformation of human HaCaT cells through both deterministic and stochastic changes in transcriptome expression.

Biological processes are inherently stochastic, i.e., are partially driven by hard to predict random probabilistic processes. Carcinogenesis is driven both by stochastic and deterministic (predictable non-random) changes. However, very few studies systematically examine the contribution of stochastic events leading to cancer development. In differential gene expression studies, the established data analysis paradigms incentivize expression changes that are uniformly different across the experimental versus control groups, introducing preferential inclusion of deterministic changes at the expense of stochastic processes that might also play a crucial role in the process of carcinogenesis. In this study, we applied simple computational techniques to quantify: (i) The impact of chronic arsenic (iAs) exposure as well as passaging time on stochastic gene expression and (ii) Which genes were expressed deterministically and which were expressed stochastically at each of the three stages of cancer development. Using biological coefficient of variation as an empirical measure of stochasticity we demonstrate that chronic iAs exposure consistently suppressed passaging related stochastic gene expression at multiple time points tested, selecting for a homogenous cell population that undergo transformation. Employing multiple balanced removal of outlier data, we show that chronic iAs exposure induced deterministic and stochastic changes in the expression of unique set of genes, that populate largely unique biological pathways. Together, our data unequivocally demonstrate that both deterministic and stochastic changes in transcriptome-wide expression are critical in driving biological processes, pathways and networks towards clonal selection, carcinogenesis, and tumor heterogeneity.

Study on the muscle transcriptome of two diverse Indian backyard poultry breeds acclimatized to different agro-ecological conditions.

OBJECTIVE: Free-range (FR) poultry production systems are associated with quality products and improved welfare. All the 19 diverse chicken breeds of India have evolved under the FR system and are adapted to different agro-climatic conditions. It is vital to explore indigenous germplasm with modern genomic tools to have insights into genomic characteristics of production traits and adaptation. METHODS: In this study, breast tissue transcriptome profiles were generated and analyzed from four biological replicates of two indigenous backyard poultry breeds of India-Ankaleshwar, a breed of the mainland, and Nicobari, a breed adapted to islands. The read quality of sequences was checked by FASTQC and processed reads were aligned to the reference genome (bGalGal1). RESULTS: More than 94% mapping to the reference genome was observed for all samples. A total of 12,790 transcripts were common across both groups, while 657 were expressed only in Ankaleshwar and 169 in Nicobari. The highest expressed genes across both groups were associated mainly with muscle structure, contraction, and energy metabolism. The highly expressed genes identified in Ankaleshwar were involved in fatty acid catabolism and oxidative stress mitigation. Functional terms, pathways, and hub genes in Nicobari participated in muscle fiber growth, adipogenesis, and fatty acid anabolism. A key hub gene (RAC1) in Nicobari is a potential candidate affecting the laying rate in chickens. The qRT-PCR results also substantiate the RNA-seq results. CONCLUSION: The findings provide a precious molecular resource to advance understanding of the genetic basis of adaptation, meat quality, and egg production in backyard chickens.

Revelation of genes associated with energy generating metabolic pathways in the fighter type Aseel chicken of India through skeletal muscle transcriptome sequencing.

In this study, comparative analysis of skeletal muscle transcriptome was carried out for four biological replicates of Aseel, a fighter type breed and Punjab Brown, a meat type breed of India. The profusely expressed genes in both breeds were related to muscle contraction and motor activity. Differential expression analysis identified 961 up-regulated and 979 down-regulated genes in Aseel at a threshold of log2 fold change ≥ ±2.0 (padj<0.05). Significantly enriched KEGG pathways in Aseel included metabolic pathways and oxidative phosphorylation, with higher expression of genes associated with fatty acid beta-oxidation, formation of ATP by chemiosmotic coupling, response to oxidative stress, and muscle contraction. The highly connected hub genes identified through gene network analysis in the Aseel gamecocks were HNF4A, APOA2, APOB, APOC3, AMBP, and ACOT13, which are primarily associated with energy generating metabolic pathways. The up-regulated genes in Punjab Brown chicken were found to be related to muscle growth and differentiation. There was enrichment of pathways such as focal adhesion, insulin signaling pathway and ECM receptor interaction in these birds. The results presented in this study help to improve our understanding of the molecular mechanisms associated with fighting ability and muscle growth in Aseel and Punjab Brown chicken, respectively.

Genome-wide transcriptome profiling of CSF virus challenged monocyte-derived macrophages provides distinct insights into immune response of Landrace and indigenous Ghurrah pigs.

The present study was undertaken to characterize the distinct immune response in indigenous Ghurrah and exotic Landrace pigs by challenging monocyte-derived macrophages (MDMs) with CSF virus under in-vitro conditions and assessing the variations in the transcriptome profile at 48 h post-infection (hpi). RNA-sequencing was carried out in infected and non-infected MDMs of Ghurrah (n = 3) and Landrace (n = 3) piglets prior- as well as post-stimulation. MDMs of Ghurrah showed greater immune regulation in response to CSF infection with 518 significantly differentially expressed genes (DEG) in infected versus non-infected MDMs, as compared to only 31 DEGs in Landrace MDMs. In Landrace, the principal regulators of inflammation (IL1α, IL1ß and TNF) were upregulated in infected cells while in Ghurrah, these were downregulated. Overall, macrophages from indigenous Ghurrah showed more immunological dysregulation in response to virulent CSF virus infection as compared to the exotic Landrace pigs.

Different stages of microbial community during the anaerobic digestion of food waste.

Large-scale food waste (FW) disposal has resulted in severe environmental degradation and financial losses around the world. Although FW has a high biomass energy contents and a growing large number of national projects to recover energy from FW by anaerobic digestion (AD) are being developed. AD is a promising solution for FW management and energy generation when compared to typical disposal options including landfill disposal, incineration, and composting. AD of FW can be combined with an existing AD operation or linked to the manufacture of value-added products to reduce costs and increase income. AD is a metabolic process that requires four different types of microbes: hydrolyzers, acidogens, acetogens, and methanogens. Microbes use a variety of strategies to avoid difficult situations in the AD, such as competition for the same substrate between sulfate-reducing bacteria and methane-forming bacteria. An improved comprehension of the microbiology involved in the anaerobic digestion of FW will provide new insight into the circumstances needed to maximize this procedure, including its possibilities for use in co-digestion mechanisms. This paper reviewed the present scientific knowledge of microbial community during the AD and the connection between microbial diversity during the AD of FW.

Multicancer early detection test: Preclinical, translational, and clinical evidence-generation plan and provocative questions.

Minimally invasive molecular biomarkers have been applied to the early detection of multiple cancers in large scale case-control and cohort studies. These demonstrations of feasibility herald the potential for permanent transformation of current cancer screening paradigms. This commentary discusses the major opportunities and challenges facing the preclinical development and clinical validation of multicancer early detection test strategies. From a diverse set of early detection research perspectives, the authors recommend specific approaches and highlight important questions for future investigation.

Metabolomics-Driven Mining of Metabolite Resources: Applications and Prospects for Improving Vegetable Crops.

Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant's performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants.

Potentially toxic elements in groundwater of the upper Brahmaputra floodplains of Assam, India: water quality and health risk.

This paper presents the groundwater quality assessment of the upper Brahmaputra floodplains of Assam on a seasonal basis. A total of 88 samples were analyzed for the presence of potentially toxic elements in two seasons. In addition, an attempt is made to identify any possible associated health risks to the residents via the drinking water pathway. The study reveals the presence of various potentially toxic elements, in particular, manganese, iron, nickel, and fluoride concentration exceeding the drinking water specifications set by BIS and WHO drinking water standards. The degree of groundwater contamination was assessed using the Water Quality Index, Heavy metal Pollution Index, Heavy metal Evaluation Index, and Degree of Contamination. The spatial distribution maps of groundwater quality were prepared using geographical information system. The non-carcinogenic health risk was evaluated using hazard quotients and hazard index as per the United States Environmental Protection Agency methodology. The hazard quotient of fluoride and manganese have values > 1, which exceeds USEPA recommended benchmark. The health risk assessment identified that the risk was highest during the pre-monsoon season, and the child population is more vulnerable to non-carcinogenic risk than the adults. Findings of cancer risk identified that pre-monsoon groundwater samples from the Golaghat District pose the highest health risks in the upper Brahmaputra floodplains. The risk is highest in the southwest of the study area, followed by the south and then by the north.

Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project.

The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.

A Urine Exosome Gene Expression Panel Distinguishes between Indolent and Aggressive Prostate Cancers at Biopsy.

PURPOSE: Prostate cancer is predominantly indolent at diagnosis with a small fraction (15% to 25%) representing aggressive subtype (Gleason score 7-10), which is prone to metastatic progression. It is critical to explore noninvasive assays for the early detection of this aggressive subtype, when it still can be treated effectively. Additionally, there is an emerging need to develop markers that perform equally well across races, as racial differences in the prevalence and mortality of prostate cancer has become evident. MATERIALS AND METHODS: First catch, nondigital rectal examination urine specimens were collected from patients undergoing diagnostic biopsy. Total RNA was extracted from urinary exosomes and a quantitative expression assay protocol using droplet digital polymerase chain reaction was developed for detection of candidate genes in exosomal mRNAs from urine. Clinical performance for the gene expression assay was evaluated to predict high grade cancer (Gleason score 7-10) from low grade cancer (Gleason score 6) and cancer negative cases at biopsy. Assay performance was examined in combination with standard of care to determine improvement in model prediction. RESULTS: In a racially diverse patient cohort a 2-gene panel (PCA3, PCGEM1), in combination with standard of care variables, significantly improved the prediction of high grade cancer at diagnosis compared to standard of care variables alone (AUC 0.88 vs 0.80, respectively, p=0.016). Decision curve analysis showed that there is a benefit of adopting the gene panel for detection of high grade cancer compared to standard of care alone. CONCLUSIONS: This study highlights the potential for developing broadly applicable prostate cancer diagnostic biomarker panels for aggressive prostate cancer using our novel gene expression assay platform.

The national institutes of health's approach to address research gaps in pancreatitis, diabetes and early detection of pancreatic cancer.

PURPOSE OF REVIEW: Diseases of the pancreas are a broad spectrum of conditions resulting from metabolic, inflammatory, and neoplastic processes (pancreatitis, pancreatogenic diabetes, and pancreatic cancers). Pancreatic diseases cause significant morbidity, mortality, and cost. RECENT FINDINGS: Research progress in diseases of the exocrine pancreas (chronic pancreatitis [CP], pancreatogenic diabetes mellitus, and pancreatic cancer) has been hampered by the disorders' heterogeneity, the limitations of previous small cross-sectional studies, the inability to safely obtain pancreatic tissue for study, and the lack of structured epidemiology tools, genetic testing, and biomarker development. SUMMARY: Given the increasing incidence and prevalence of CP and its complications, high mortality rate, and associated healthcare cost, the National Institute of Diabetes and Digestive and Kidney Diseases and the National Cancer Institute funded the Consortium for the study of Chronic Pancreatitis, Diabetes and Pancreatic Cancer (CPDPC) to identify research gaps and foster multidisciplinary collaborations to better diagnose, characterize and manage CP and its sequelae and to understand the diabetes/pancreatic cancer association.The studies undertaken by the CPDPC are described in other articles in this journal's issue.

Decreased Tumoral Expression of Colon-Specific Water Channel Aquaporin 8 Is Associated With Reduced Overall Survival in Colon Adenocarcinoma.

BACKGROUND: Colon cancer survival is dependent on metastatic potential and treatment. Large RNA-sequencing data sets may assist in identifying colon cancer-specific biomarkers to improve patient outcomes. OBJECTIVE: This study aimed to identify a highly specific biomarker for overall survival in colon adenocarcinoma by using an RNA-sequencing data set. DESIGN: Raw RNA-sequencing and clinical data for patients with colon adenocarcinoma (n = 271) were downloaded from The Cancer Genome Atlas. A binomial regression model was used to calculate differential RNA expression between paired colon cancer and normal epithelium samples (n = 40). Highly differentially expressed RNAs were examined. SETTINGS: This study was conducted at the University of Louisville using data acquired by The Cancer Genome Atlas. PATIENTS: Patients from US accredited cancer centers between 1998 and 2013 were analyzed. MAIN OUTCOME MEASURES: The primary outcome measures were recurrence-free and overall survival. RESULTS: The median age was 66 years (147/271 men, 180/271 White patients). Thirty RNAs were differentially expressed in colon adenocarcinoma compared with paired normal epithelium, using a log-fold change cutoff of ±6. Using median expression as a cutoff, 4 RNAs were associated with worse overall survival: decreased ZG16 (log-rank = 0.023), aquaporin 8 (log-rank = 0.023), and SLC26A3 (log-rank = 0.098), and increased COL1A1 (log-rank = 0.105). On multivariable analysis, low aquaporin 8 expression (HR, 1.748; 95% CI, 1.016-3.008; p = 0.044) was a risk factor for worse overall survival. Our final aquaporin 8 model had an area under the curve of 0.85 for overall survival. On subgroup analysis, low aquaporin 8 was associated with worse overall survival in patients with high microsatellite instability and in patients with stage II disease. Low aquaporin 8 expression was associated with KRAS and BRAF mutations. Aquaporin 8 immunohistochemistry was optimized for clinical application. LIMITATIONS: This was a retrospective study. CONCLUSION: Aquaporin 8 is a water channel selectively expressed in normal colon tissue. Low aquaporin 8 expression is a risk factor for worse overall survival in patients who have colon cancer. Aquaporin 8 measurement may have a role as a colon-specific prognostic biomarker and help in patient risk stratification for increased surveillance. See Video Abstract at http://links.lww.com/DCR/B603. LA DISMINUCIN DE LA EXPRESIN TUMORAL DE LA ACUAPORINA DEL CANAL DE AGUA ESPECFICO DEL COLON SE ASOCIA CON UNA REDUCCIN DE LA SUPERVIVENCIA GENERAL EN EL ADENOCARCINOMA DE COLON: ANTECEDENTES:La supervivencia del cáncer de colon depende del potencial metastásico y del tratamiento. Grandes conjuntos de datos de secuenciación de ARN pueden ayudar a identificar biomarcadores específicos del cáncer de colon para mejorar los resultados de los pacientes.OBJETIVO:Identificar un biomarcador altamente específico para la supervivencia general en el adenocarcinoma de colon utilizando un conjunto de datos de secuenciación de ARN.DISEÑO:La secuenciación de ARN sin procesar y los datos clínicos para pacientes con adenocarcinoma de colon (n = 271) se descargaron de The Cancer Genome Atlas. Se utilizó un modelo de regresión binomial para calcular la expresión diferencial de ARN entre muestras de cáncer de colon emparejadas y muestras de epitelio normal (n = 40). Se examinaron los ARN expresados de forma altamente diferencial.ENTORNO CLINICO:Este estudio se realizó en la Universidad de Louisville utilizando datos adquiridos por The Cancer Genome Atlas.PACIENTES:Se analizaron pacientes de centros oncológicos acreditados en Estados Unidos entre 1998-2013.PRINCIPALES MEDIDAS DE VALORACION:Las principales medidas de valoración fueron la supervivencia general y libre de recurrencia.RESULTADOS:La mediana de edad fue de 66 años (147/271 hombres, 180/271 caucásicos). Treinta ARN se expresaron diferencialmente en el adenocarcinoma de colon en comparación con el epitelio normal emparejado, utilizando un límite de cambio logarítmico de ± 6. Utilizando la expresión mediana como punto de corte, cuatro ARN se asociaron con una peor supervivencia general: disminución de ZG16 (rango logarítmico = 0,023), acuaporina8 (rango logarítmico = 0,023) y SLC26A3 (rango logarítmico = 0,098) y aumento de COL1A1 (log -rango = 0,105). En el análisis multivariable, la baja expresión de acuaporina8 (HR = 1,748, IC del 95%: 1,016-3,008, p = 0,044) fue un factor de riesgo para una peor supervivencia global. Nuestro modelo de aquaporin8 final tuvo un AUC de 0,85 para la supervivencia global. En el análisis de subgrupos, la acuaporina8 baja se asoció con una peor supervivencia general en pacientes con MSI-H y en pacientes en estadio II. La baja expresión de acuaporina8 se asoció con mutaciones de KRAS y BRAF. La inmunohistoquímica de aquaporina8 se optimizó para su aplicación clínica.LIMITACIONES:Este fue un estudio retrospectivo.CONCLUSIÓN:La acuaporina8 es un canal de agua expresado selectivamente en el tejido normal del colon. La baja expresión de AQP8 es un factor de riesgo de peor supervivencia global en pacientes con cáncer de colon. La medición de aquaporina8 puede tener un papel como un biomarcador de pronóstico específico del colon y ayudar en la estratificación del riesgo del paciente para una mayor vigilancia. Consulte Video Resumen en http://links.lww.com/DCR/B603.

Dynamic alteration in miRNA and mRNA expression profiles at different stages of chronic arsenic exposure-induced carcinogenesis in a human cell culture model of skin cancer.

Chronic arsenic exposure causes skin cancer, although the underlying molecular mechanisms are not well defined. Altered microRNA and mRNA expression likely play a pivotal role in carcinogenesis. Changes in genome-wide differential expression of miRNA and mRNA at 3 strategic time points upon chronic sodium arsenite (As3+) exposure were investigated in a well-validated HaCaT cell line model of arsenic-induced cutaneous squamous cell carcinoma (cSCC). Quadruplicate independent HaCaT cell cultures were exposed to 0 or 100 nM As3+ for up to 28-weeks (wk). Cell growth was monitored throughout the course of exposure and epithelial-mesenchymal transition (EMT) was examined employing immunoblot. Differentially expressed miRNA and mRNA profiles were generated at 7, 19, and 28-wk by RNA-seq, followed by identification of differentially expressed mRNA targets of differentially expressed miRNAs through expression pairing at each time point. Pathway analyses were performed for total differentially expressed mRNAs and for the miRNA targeted mRNAs at each time point. RNA-seq predictions were validated by immunoblot of selected target proteins. While the As3+-exposed cells grew slower initially, growth was equal to that of unexposed cells by 19-wk (transformation initiation), and exposed cells subsequently grew faster than passage-matched unexposed cells. As3+-exposed cells had undergone EMT at 28-wk. Pathway analyses demonstrate dysregulation of carcinogenesis-related pathways and networks in a complex coordinated manner at each time point. Immunoblot data largely corroborate RNA-seq predictions in the endoplasmic reticulum stress (ER stress) pathway. This study provides a detailed molecular picture of changes occurring during the arsenic-induced transformation of human keratinocytes.

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions.

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts' opinion on the development and application of multiomic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, and prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular, and functional aberrations within the lesion and within individual cells. Single-cell proteomic data will be essential for the establishment of new tools with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included (i) The best way/s to analyze single-cells from fresh and preserved tissue; (ii) Detection and analysis of secreted molecules and from single cells, especially from a tissue slice; (iii) Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment; (iv) Multiomic integration of data to support and inform proteomic measurements; (v) Subcellular organelles-identifying abnormal structure, function, distribution, and location within individual premalignant and malignant cells; (vi) How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post-translational modifications (PTM); (vii) The depth of coverage measured concurrently using single-cell techniques; (viii) Quantitation - absolute or semiquantitative? (ix) Single methodology or multiplexed combinations? (x) Application of analytical methods for identification of biologically significant subsets; (xi) Data visualization of N-dimensional data sets; (xii) How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME); (xiii) Associations between intrinsic cellular processes and extrinsic stimuli; (xiv) How to predict cellular responses to stress-inducing stimuli; (xv) Identification of new markers for prediction of progression from precursor, benign, and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells; (xvi) Identification of new targets for immunoprevention or immunotherapy-identification of neoantigens and surfactome of individual cells within a lesion.

Management of congenital craniovertebral anomalies: a single-centre experience of 71 cases by an algorithmic approach.

STUDY DESIGN: Retrospective study. OBJECTIVE: Congenital craniovertebral (CV) anomalies include a wide variety of conditions involving basilar invagination (BI), atlantoaxial dislocation (AAD), bony congenital anomalies and Chiari malformation. The management of these disorders is more surgeon dependent rather than based on clear guidelines. This study aims to provide a step-by-step algorithmic approach to the management of congenital CV anomalies to achieve good CV alignment, neural recovery and long lasting stability. MATERIALS: The study retrospectively analyses 71 patients of congenital CV anomalies treated by our algorithmic approach. Clinical assessment was done with the help of Nurick's grading pre- and post-operatively. Radiological outcome was assessed by plain radiographs, and computed tomographic scan was done at 12-month follow-up. RESULTS: Mean age at presentation was 17.9 years (6-41 years). Mean Nurick score pre-operatively was 3.8 which was reduced to 1.3 at a mean follow-up of 13.6 months. Sixty-one patients had type I BI, 6 had type II BI, and 4 patients had os odontoideum. Most common symptom at presentation was weakness in limbs, neck pain and difficulty in walking. Patients of isolated AAD with os odontoideum required posterior atlantoaxial fixation and fusion only. Thirty-two patients of type I BI and 4 patients of type II BI required anterior release procedures prior to occipitocervical instrumentation. Bony fusion was achieved in 96% (68) cases with the help of autologous bone grafting. Three patients of occipitocervical fusion developed pseudoarthrosis. CONCLUSION: Our retrospective analysis demonstrates that the algorithm is effective in ensuring long lasting results in all types congenital CV anomalies.

Dioxin-like and non-dioxin-like PCBs differentially regulate the hepatic proteome and modify diet-induced nonalcoholic fatty liver disease severity.

Polychlorinated biphenyls (PCBs) are persistent organic pollutants associated with metabolic disruption and non-alcoholic fatty liver disease (NAFLD). Based on their ability to activate the aryl hydrocarbon receptor (AhR), PCBs are subdivided into two classes: dioxin-like (DL) and non-dioxin-like (NDL) PCBs. Previously, we demonstrated that NDL PCBs compromised the liver to promote more severe diet-induced NAFLD. Here, the hepatic effects and potential mechanisms (by untargeted liver proteomics) of DL PCBs, NDL PCBs or co-exposure to both in diet-induced NAFLD are investigated. Male C57Bl/6 mice were fed a 42% fat diet and exposed to vehicle control; Aroclor1260 (20 mg/kg, NDL PCB mixture); PCB126 (20 µg/kg, DL PCB congener); or a mixture of Aroclor1260 (20 mg/kg)+PCB126 (20 µg/kg) for 12 weeks. Each exposure was associated with a distinct hepatic proteome. Phenotypic and proteomic analyses revealed increased hepatic inflammation and phosphoprotein signaling disruption by Aroclor1260. PCB126 decreased hepatic inflammation and fibrosis at the molecular level; while altering cytoskeletal remodeling, metal homeostasis, and intermediary/xenobiotic metabolism. PCB126 attenuated Aroclor1260-induced hepatic inflammation but increased hepatic free fatty acids in the co-exposure group. Aroclor1260+PCB126 exposure was strongly associated with multiple epigenetic processes, and these could potentially explain the observed non-additive effects of the exposures on the hepatic proteome. Taken together, the results demonstrated that PCB exposures differentially regulated the hepatic proteome and the histologic severity of diet-induced NAFLD. Future research is warranted to determine the AhR-dependence of the observed effects including metal homeostasis and the epigenetic regulation of gene expression.

Carrier-Assisted Single-Tube Processing Approach for Targeted Proteomics Analysis of Low Numbers of Mammalian Cells.

Heterogeneity in composition is inherent in all cell populations, even those containing a single cell type. Single-cell proteomics characterization of cell heterogeneity is currently achieved by antibody-based technologies, which are limited by the availability of high-quality antibodies. Herein we report a simple, easily implemented, mass spectrometry (MS)-based targeted proteomics approach, termed cLC-SRM (carrier-assisted liquid chromatography coupled to selected reaction monitoring), for reliable multiplexed quantification of proteins in low numbers of mammalian cells. We combine a new single-tube digestion protocol to process low numbers of cells with minimal loss together with sensitive LC-SRM for protein quantification. This single-tube protocol builds upon trifluoroethanol digestion and further minimizes sample losses by tube pretreatment and the addition of carrier proteins. We also optimized the denaturing temperature and trypsin concentration to significantly improve digestion efficiency. cLC-SRM was demonstrated to have sufficient sensitivity for reproducible detection of most epidermal growth factor receptor (EGFR) pathway proteins expressed at levels ≥30 000 and ≥3000 copies per cell for 10 and 100 mammalian cells, respectively. Thus, cLC-SRM enables reliable quantification of low to moderately abundant proteins in less than 100 cells and could be broadly useful for multiplexed quantification of important proteins in small subpopulations of cells or in size-limited clinical samples. Further improvements of this method could eventually enable targeted single-cell proteomics when combined with either SRM or other emerging ultrasensitive MS detection.

Validation of a novel model for the early detection of hepatocellular carcinoma.

BACKGROUND: The biomarkers alpha-fetoprotein (AFP) and protein induced by vitamin K absence/antagonist-II (PIVKA-II) may be useful for detecting early-stage hepatocellular carcinoma (HCC). We evaluated the performance of AFP and PIVKA-II levels, alone and in combination with clinical factors, for the early detection of HCC. METHODS: In a case-control study, serum AFP and PIVKA-II were measured using the ARCHITECT immunoassay analyzer system in a cohort of 119 patients with HCC, 215 patients with non-malignant liver disease, and 34 healthy subjects. Five predictive models for detecting HCC were developed based on age, gender, AFP, and/or PIVKA-II levels; the best model was validated in an independent cohort of 416 patients with HCC and 412 control subjects with cirrhosis. RESULTS: In both cohorts, AFP and PIVKA-II concentrations were higher in patients with HCC compared to healthy controls and patients with non-malignant liver disease. The model that combined AFP and PIVKA-II, age, and gender had the highest AUC of 0.95 (0.95, 95% CI 0.93-0.98), with a sensitivity of 93% and a specificity of 84% in the development cohort, and an AUC of 0.87 (95% CI 0.85-0.90), sensitivity of 74%, and specificity of 85% in the validation cohort. When limiting the validation cohort to only early-stage HCC, the AUC was 0.85 (95% CI 0.81-0.88), sensitivity was 70%, and specificity was 86%. CONCLUSIONS: Compared to each biomarker alone, the combination of AFP and PIVKA-II with age and gender improved the accuracy of detecting HCC and differentiating HCC from non-malignant liver disease.