LMD: Cluster-Independent Multiscale Marker Identification in Single-cell RNA-seq Data.

Identifying accurate cell markers in single-cell RNA-seq data is crucial for understanding cellular diversity and function. Localized Marker Detector (LMD) is a novel tool to identify "localized genes" - genes exclusively expressed in groups of highly similar cells - thereby characterizing cellular diversity in a multi-resolution and fine-grained manner. LMD constructs a cell-cell affinity graph, diffuses the gene expression value across the cell graph, and assigns a score to each gene based on its diffusion dynamics.

Immune dysfunction revealed by digital spatial profiling of immuno-oncology markers in progressive stages of renal cell carcinoma and in brain metastases.

Background: The tumor microenvironment (TME) contributes to cancer progression and treatment response to therapy, including in renal cell carcinoma (RCC). Prior profiling studies, including single-cell transcriptomics, often involve limited sample sizes and lack spatial orientation. The TME of RCC brain metastases, a major cause of morbidity, also remains largely uncharacterized.

Impact of healthcare worker shift scheduling on workforce preservation during the COVID-19 pandemic.

Reducing severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infections among healthcare workers is critical. We ran Monte Carlo simulations modeling the spread of SARS-CoV-2 in non-COVID-19 wards, and we found that longer nursing shifts and scheduling designs in which teams of nurses and doctors co-rotate no more frequently than every 3 days can lead to fewer infections.

A multicriteria approach for risk assessment of Covid-19 in urban district lockdown.

At the beginning of 2020, the spread of a new strand of Coronavirus named SARS-CoV-2 (COVID-19) raised the interest of the scientific community about the risk assessment related to the viral infection. The contagion became pandemic in few months forcing many Countries to declare lockdown status. In this context of quarantine, all commercial and productive activities are suspended, and many Countries are experiencing a serious crisis.

MET Expression in Primary and Metastatic Clear Cell Renal Cell Carcinoma: Implications of Correlative Biomarker Assessment to MET Pathway Inhibitors.

Aims: Inhibitors of the MET pathway hold promise in the treatment for metastatic kidney cancer. Assessment of predictive biomarkers may be necessary for appropriate patient selection. Understanding MET expression in metastases and the correlation to the primary site is important, as distant tissue is not always available.

Regulation of glutamine carrier proteins by RNF5 determines breast cancer response to ER stress-inducing chemotherapies.

Many tumor cells are fueled by altered metabolism and increased glutamine (Gln) dependence. We identify regulation of the L-glutamine carrier proteins SLC1A5 and SLC38A2 (SLC1A5/38A2) by the ubiquitin ligase RNF5. Paclitaxel-induced ER stress to breast cancer (BCa) cells promotes RNF5 association, ubiquitination, and degradation of SLC1A5/38A2.

Preanalytical variables and phosphoepitope expression in FFPE tissue: quantitative epitope assessment after variable cold ischemic time.

Individualized targeted therapies for cancer patients require accurate and reproducible assessment of biomarkers to be able to plan treatment accordingly. Recent studies have shown highly variable effects of preanalytical variables on gene expression profiling and protein levels of different tissue types. Several publications have described protein degradation of tissue samples as a direct result of delay of formalin fixation of the tissue.

PLEKHA5 as a Biomarker and Potential Mediator of Melanoma Brain Metastasis.

Purpose: Approximately 40% of patients with metastatic melanoma develop brain metastases. Our purpose was to identify genes aberrantly expressed in melanoma that might be associated with propensity for brain homing.

Experimental Design: We studied gene expression profiles in a cell line model of brain metastasis (cerebrotropic A375Br cells vs.

Interactions with RNA direct the Polycomb group protein SCML2 to chromatin where it represses target genes.

Polycomb repressive complex-1 (PRC1) is essential for the epigenetic regulation of gene expression. SCML2 is a mammalian homolog of Drosophila SCM, a Polycomb-group protein that associates with PRC1. In this study, we show that SCML2A, an SCML2 isoform tightly associated to chromatin, contributes to PRC1 localization and also directly enforces repression of certain Polycomb target genes.

NY-ESO-1 as a potential immunotherapeutic target in renal cell carcinoma.

Background: Novel immune therapies targeting tumor specific antigens are being developed. Our purpose was to determine expression of the cancer testes antigen NY-ESO-1 in renal cell carcinoma (RCC), as NY-ESO-1 targeting approaches, particularly adoptive cell therapy, have not been evaluated in this disease.

Methods: We employed tissue microarrays containing >300 unique RCC cases and adjacent benign renal tissue to determine NY-ESO-1 expression using a quantitative immunofluorescence method.

Oct-1 regulates IL-17 expression by directing interchromosomal associations in conjunction with CTCF in T cells.

Interchromosomal associations can regulate gene expression, but little is known about the molecular basis of such associations. In response to antigen stimulation, naive T cells can differentiate into Th1, Th2, and Th17 cells expressing IFN-γ, IL-4, and IL-17, respectively. We previously reported that in naive T cells, the IFN-γ locus is associated with the Th2 cytokine locus.

A tissue quality index: an intrinsic control for measurement of effects of preanalytical variables on FFPE tissue.

While efforts are made to improve tissue quality and control preanalytical variables, pathologists are often confronted with the challenge of molecular analysis of patient samples of unknown quality. Here we describe a first attempt to construct a tissue quality index (TQI) or an intrinsic control that would allow a global assessment of protein status based on quantitative measurement of a small number of selected, informative epitopes. Quantitative immunofluorescence (QIF) of a number of proteins was performed on a series of 93 breast cancer cases where levels of expression were assessed as a function of delayed time to formalin fixation.

Ranking and combining multiple predictors without labeled data.

In a broad range of classification and decision-making problems, one is given the advice or predictions of several classifiers, of unknown reliability, over multiple questions or queries. This scenario is different from the standard supervised setting, where each classifier's accuracy can be assessed using available labeled data, and raises two questions: Given only the predictions of several classifiers over a large set of unlabeled test data, is it possible to (i) reliably rank them and (ii) construct a metaclassifier more accurate than most classifiers in the ensemble? Here we present a spectral approach to address these questions. First, assuming conditional independence between classifiers, we show that the off-diagonal entries of their covariance matrix correspond to a rank-one matrix.

TrAp: a tree approach for fingerprinting subclonal tumor composition.

Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide only an overview of the aggregate of numerous cells. Computational approaches to de-mix a collective signal composed of the aberrations of a mixed cell population of a tumor sample into its individual components are not available.

Arpeggio: harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures.

Researchers generating new genome-wide data in an exploratory sequencing study can gain biological insights by comparing their data with well-annotated data sets possessing similar genomic patterns. Data compression techniques are needed for efficient comparisons of a new genomic experiment with large repositories of publicly available profiles. Furthermore, data representations that allow comparisons of genomic signals from different platforms and across species enhance our ability to leverage these large repositories.

Expression of drug targets in primary and matched metastatic renal cell carcinoma tumors.

Background: Targeted therapies in renal cell carcinoma can have different effects on primary and metastatic tumors. To pave the way for predictive biomarker development, we assessed differences in expression of targets of currently approved drugs in matched primary and metastatic specimens from 34 patients.

Methods: Four cores from each site were embedded in tissue microarray blocks.

Quantitative assessment of effect of preanalytic cold ischemic time on protein expression in breast cancer tissues.

Background: Companion diagnostic tests can depend on accurate measurement of protein expression in tissues. Preanalytic variables, especially cold ischemic time (time from tissue removal to fixation in formalin) can affect the measurement and may cause false-negative results. We examined 23 proteins, including four commonly used breast cancer biomarker proteins, to quantify their sensitivity to cold ischemia in breast cancer tissues.

Integrated analysis of tumor samples sheds light on tumor heterogeneity.

The heterogeneity of tumor samples is a major challenge in the analysis of high-throughput profiling of tumor biopsies and cell lines. The measured aggregate signals of multigenerational progenies often represent an average of several tumor subclones with varying genomic aberrations and different gene expression levels. The goal of the present study was to integrate copy number analyses from SNP-arrays and karyotyping, gene expression profiling, and pathway analyses to detect heterogeneity, identify driver mutations, and explore possible mechanisms of tumor evolution.

Close proximity to Igh is a contributing factor to AID-mediated translocations.

Class switch recombination (CSR) has the potential to generate genomic instability in B cells as activation-induced cytidine deaminase (AID), which mediates this process, is known to target many sites outside Igh. Nonetheless we do not fully understand what factors influence AID targeting genome-wide. Given that errors in CSR can lead to dangerous, oncogenic chromosomal translocations it is important to identify the elements that determine which genes are at risk of being "hit" and could be involved in aberrant rearrangements.

PCGF homologs, CBX proteins, and RYBP define functionally distinct PRC1 family complexes.

The heterogeneous nature of mammalian PRC1 complexes has hindered our understanding of their biological functions. Here, we present a comprehensive proteomic and genomic analysis that uncovered six major groups of PRC1 complexes, each containing a distinct PCGF subunit, a RING1A/B ubiquitin ligase, and a unique set of associated polypeptides. These PRC1 complexes differ in their genomic localization, and only a small subset colocalize with H3K27me3.

Picking ChIP-seq peak detectors for analyzing chromatin modification experiments.

Numerous algorithms have been developed to analyze ChIP-Seq data. However, the complexity of analyzing diverse patterns of ChIP-Seq signals, especially for epigenetic marks, still calls for the development of new algorithms and objective comparisons of existing methods. We developed Qeseq, an algorithm to detect regions of increased ChIP read density relative to background.

VDA, a method of choosing a better algorithm with fewer validations.

The multitude of bioinformatics algorithms designed for performing a particular computational task presents end-users with the problem of selecting the most appropriate computational tool for analyzing their biological data. The choice of the best available method is often based on expensive experimental validation of the results. We propose an approach to design validation sets for method comparison and performance assessment that are effective in terms of cost and discrimination power.

Inhibition of nonsense-mediated RNA decay by the tumor microenvironment promotes tumorigenesis.

While nonsense-mediated RNA decay (NMD) is an established mechanism to rapidly degrade select transcripts, the physiological regulation and biological significance of NMD are not well characterized. We previously demonstrated that NMD is inhibited in hypoxic cells. Here we show that the phosphorylation of the α subunit of eukaryotic initiation factor 2 (eIF2α) translation initiation factor by a variety of cellular stresses leads to the inhibition of NMD and that eIF2α phosphorylation and NMD inhibition occur in tumors.

Detecting copy number status and uncovering subclonal markers in heterogeneous tumor biopsies.

Background: Genomic aberrations can be used to determine cancer diagnosis and prognosis. Clinically relevant novel aberrations can be discovered using high-throughput assays such as Single Nucleotide Polymorphism (SNP) arrays and next-generation sequencing, which typically provide aggregate signals of many cells at once. However, heterogeneity of tumor subclones dramatically complicates the task of detecting aberrations.

Genome-wide remodeling of the epigenetic landscape during myogenic differentiation.

We have examined changes in the chromatin landscape during muscle differentiation by mapping the genome-wide location of ten key histone marks and transcription factors in mouse myoblasts and terminally differentiated myotubes, providing an exceptionally rich dataset that has enabled discovery of key epigenetic changes underlying myogenesis. Using this compendium, we focused on a well-known repressive mark, histone H3 lysine 27 trimethylation, and identified novel regulatory elements flanking the myogenin gene that function as a key differentiation-dependent switch during myogenesis. Next, we examined the role of Polycomb-mediated H3K27 methylation in gene repression by systematically ablating components of both PRC1 and PRC2 complexes.